From 91dd3d61362b0fa3e1500b53faef5bbe244de53c Mon Sep 17 00:00:00 2001
From: Stefan Djordjevic <157365107+sdjordjevicTT@users.noreply.github.com>
Date: Mon, 24 Feb 2025 16:59:28 +0100
Subject: [PATCH] Rewriting elementwise binary ops in TTNN dialect to be
 non-dps (#2233)

### Ticket
Closes #2231

### Problem description
We have decided not to use DPS in the TTNN dialect until we can model it
properly.

### What's changed
This PR rewrites eltwise ops in the TTNN dialect in non-DPS style.

Note: Most of the changes are rewrites of existing tests; hence, don't
fear the number of changed files. :)

### Checklist
- [x] New/Existing tests provide coverage for changes
---
 include/ttmlir/Dialect/TTNN/IR/TTNNOps.td     | 42 ++++++----
 include/ttmlir/Dialect/TTNN/IR/TTNNTraits.h   | 18 ++++
 include/ttmlir/Dialect/TTNN/IR/TTNNTraits.td  | 22 +++++
 lib/Conversion/TTIRToTTNN/TTIRToTTNN.cpp      | 18 ++--
 lib/Conversion/TTNNToEmitC/TTNNToEmitC.cpp    |  5 +-
 lib/Dialect/TTNN/Analysis/ShardSolver.cpp     | 10 ++-
 lib/Dialect/TTNN/IR/TTNNOpModelInterface.cpp  |  6 +-
 lib/Dialect/TTNN/IR/TTNNWorkarounds.cpp       |  1 -
 lib/Dialect/TTNN/Transforms/Optimizer.cpp     | 27 ++++--
 .../Decomposition/RepeatOpRewritePattern.cpp  | 41 +---------
 lib/Target/TTNN/TTNNToFlatbuffer.cpp          | 12 +--
 .../Workarounds/where_workaround.mlir         |  4 +-
 .../Transforms/ttnn_create_input_gens_0.mlir  |  9 +-
 .../ttnn_modify_signatures_for_dylib_0.mlir   |  4 +-
 .../data_movement/repeat/implicit_repeat.mlir |  6 +-
 .../repeat/repeat_workaround.mlir             |  3 +-
 .../bitwise_and/simple_bitwise_and.mlir       |  7 +-
 .../binary/bitwise_or/simple_bitwise_or.mlir  |  7 +-
 .../bitwise_xor/simple_bitwise_xor.mlir       |  7 +-
 .../binary/compare}/simple_compare.mlir       | 66 ++++++---------
 .../{ => eltwise/binary/div}/simple_div.mlir  |  6 +-
 .../binary/logical_and/simple_and.mlir        |  9 +-
 .../eltwise/binary/logical_or/simple_or.mlir  |  9 +-
 .../binary/logical_xor/simple_xor.mlir        | 10 +--
 .../binary/maximum}/simple_maximum.mlir       |  6 +-
 .../binary/minimum/simple_minimum.mlir        |  6 +-
 .../binary/multiply}/simple_multiply.mlir     |  6 +-
 .../eltwise/binary/power/simple_power.mlir    |  7 +-
 .../binary/remainder/simple_remainder.mlir    |  7 +-
 .../binary/subtract}/simple_subtract.mlir     |  6 +-
 .../TTNN/eltwise/operand_broadcasts.mlir      |  6 +-
 .../ternary/where}/simple_where.mlir          | 12 ++-
 .../TTNN/eltwise/unary/abs/simple_abs.mlir    |  5 +-
 .../unary/bitwise_not/simple_bitwise_not.mlir |  6 +-
 .../TTNN/eltwise/unary/cbrt/simple_cbrt.mlir  |  5 +-
 .../TTNN/eltwise/unary/ceil/simple_ceil.mlir  |  5 +-
 .../TTNN/eltwise/unary/cos/simple_cos.mlir    |  5 +-
 .../eltwise/unary/expm1/simple_expm1.mlir     |  6 +-
 .../eltwise/unary/floor/simple_floor.mlir     |  9 +-
 .../TTNN/eltwise/unary/gelu/simple_gelu.mlir  |  9 +-
 .../unary/isfinite/simple_isfinite.mlir       |  9 +-
 .../unary/leaky_relu/simple_leaky_relu.mlir   |  9 +-
 .../eltwise/unary/log1p/simple_log1p.mlir     |  6 +-
 .../eltwise/unary/logical_not/simple_not.mlir |  7 +-
 .../TTNN/eltwise/unary/negate/simple_neg.mlir |  5 +-
 .../unary/reciprocal/simple_reciprocal.mlir   |  5 +-
 .../TTNN/eltwise/unary/relu/simple_relu.mlir  |  5 +-
 .../eltwise/unary/rsqrt/simple_rsqrt.mlir     |  5 +-
 .../eltwise/unary/sigmoid/simple_sigmoid.mlir |  5 +-
 .../TTNN/eltwise/unary/sign/simple_sign.mlir  |  6 +-
 .../TTNN/eltwise/unary/sin/simple_sin.mlir    |  5 +-
 .../TTNN/eltwise/unary/sqrt/simple_sqrt.mlir  |  5 +-
 .../TTNN/eltwise/unary/tan/simple_tan.mlir    |  6 +-
 .../TTNN/eltwise/unary/tanh/simple_tanh.mlir  |  6 +-
 .../Dialect/TTNN/implicit_broadcast.mlir      |  6 +-
 test/ttmlir/Dialect/TTNN/multiple_func.mlir   |  6 +-
 .../test_override_reshard_edges.mlir          | 15 ++--
 .../TTNN/optimizer/ttir_to_ttnn_pipeline.mlir |  3 +-
 test/ttmlir/Dialect/TTNN/simple_scatter.mlir  |  5 +-
 .../TTNN/test_remove_dead_values_pass.mlir    | 82 ++++++++-----------
 .../ttir_to_ttnn_pipeline_custom_opt.mlir     |  3 +-
 .../ttir_to_ttnn_pipeline_hoist_call.mlir     |  6 +-
 .../ttmlir/EmitC/TTNN/eltwise_unary/cbrt.mlir |  3 +
 .../Silicon/StableHLO/n150/Binary/add_op.mlir |  2 -
 .../StableHLO/n150/Binary/compare_op.mlir     | 12 ---
 .../StableHLO/n150/Binary/divide_op.mlir      |  2 -
 .../StableHLO/n150/Binary/logical_op.mlir     |  6 --
 .../StableHLO/n150/Binary/maximum_op.mlir     |  2 -
 .../StableHLO/n150/Binary/minimum_op.mlir     |  2 -
 .../StableHLO/n150/Binary/multiply_op.mlir    |  2 -
 .../StableHLO/n150/Binary/power_op.mlir       |  2 -
 .../StableHLO/n150/Binary/remainder_op.mlir   |  2 -
 .../StableHLO/n150/Binary/subtract_op.mlir    |  2 -
 .../StableHLO/n150/Unary/absolute_op.mlir     |  2 -
 .../Silicon/StableHLO/n150/Unary/cbrt_op.mlir |  2 -
 .../Silicon/StableHLO/n150/Unary/ceil_op.mlir |  2 -
 .../StableHLO/n150/Unary/clamp_op.mlir        |  4 -
 .../StableHLO/n150/Unary/cosine_op.mlir       |  2 -
 .../n150/Unary/exponential_minus_one_op.mlir  |  2 -
 .../StableHLO/n150/Unary/exponential_op.mlir  |  2 -
 .../StableHLO/n150/Unary/floor_op.mlir        |  2 -
 .../StableHLO/n150/Unary/isfinite_op.mlir     |  2 -
 .../StableHLO/n150/Unary/log_plus_one_op.mlir |  2 -
 .../StableHLO/n150/Unary/logical_op.mlir      |  2 -
 .../StableHLO/n150/Unary/negate_op.mlir       |  2 -
 .../StableHLO/n150/Unary/rsqrt_op.mlir        |  2 -
 .../Silicon/StableHLO/n150/Unary/sign_op.mlir |  2 -
 .../Silicon/StableHLO/n150/Unary/sine_op.mlir |  2 -
 .../Silicon/StableHLO/n150/Unary/sqrt_op.mlir |  2 -
 .../Silicon/StableHLO/n150/composite_op.mlir  |  1 -
 .../Silicon/StableHLO/n150/scalar_add_op.mlir |  2 -
 test/ttmlir/Silicon/TTNN/n150/deallocate.mlir |  9 +-
 .../TTNN/n150/eltwise/binary/add/add.mlir     |  6 +-
 .../n150/eltwise/binary/add/add_int32.mlir    |  6 +-
 .../binary/compare}/simple_compare.mlir       | 66 ++++++---------
 .../TTNN/n150/eltwise/binary/div/div.mlir     |  6 +-
 .../TTNN/n150/eltwise/binary/ge/ge.mlir       |  6 +-
 .../binary/logical}/simple_logical.mlir       | 39 +++------
 .../n150/eltwise/binary/maximum/maximum.mlir  |  6 +-
 .../n150/eltwise/binary/minimum/minimum.mlir  | 11 +--
 .../eltwise/binary/multiply/multiply.mlir     |  6 +-
 .../TTNN/n150/eltwise/binary/power/power.mlir |  8 +-
 .../eltwise/binary/remainder/remainder.mlir   |  7 +-
 .../eltwise/binary/subtract/subtract.mlir     |  6 +-
 .../n150/eltwise/ternary/where/where.mlir     |  5 +-
 .../TTNN/n150/eltwise/unary/cbrt/cbrt.mlir    |  5 +-
 .../TTNN/n150/eltwise/unary/ceil/ceil.mlir    |  5 +-
 .../TTNN/n150/eltwise/unary/clamp/clamp.mlir  |  6 +-
 .../n150/eltwise/unary/cosine/cosine.mlir     |  5 +-
 .../TTNN/n150/eltwise/unary/expm1/expm1.mlir  |  6 +-
 .../TTNN/n150/eltwise/unary/floor/floor.mlir  |  9 +-
 .../TTNN/n150/eltwise/unary/gelu/gelu.mlir    |  9 +-
 .../eltwise/unary/is_finite/is_finite.mlir    |  9 +-
 .../eltwise/unary/leaky_relu/leaky_relu.mlir  |  6 +-
 .../TTNN/n150/eltwise/unary/log/log.mlir      |  5 +-
 .../TTNN/n150/eltwise/unary/log1p/log1p.mlir  |  6 +-
 .../eltwise/unary/logical_not/simple_not.mlir | 14 ++++
 .../n150/eltwise/unary/negate/negate.mlir     |  4 +-
 .../eltwise/unary/recipricol/recipricol.mlir  |  5 +-
 .../TTNN/n150/eltwise/unary/relu/relu.mlir    |  5 +-
 .../TTNN/n150/eltwise/unary/rsqrt/rsqrt.mlir  |  5 +-
 .../n150/eltwise/unary/sigmoid/sigmoid.mlir   |  5 +-
 .../TTNN/n150/eltwise/unary/sign/sign.mlir    |  6 +-
 .../TTNN/n150/eltwise/unary/sine/sine.mlir    |  5 +-
 .../TTNN/n150/eltwise/unary/sqrt/sqrt.mlir    |  5 +-
 .../TTNN/n150/eltwise/unary/tan/tan.mlir      |  5 +-
 .../TTNN/n150/eltwise/unary/tanh/tanh.mlir    |  5 +-
 .../Silicon/TTNN/n150/operand_broadcasts.mlir |  6 +-
 .../Silicon/TTNN/n150/perf/test_perf_and.mlir |  9 +-
 .../TTNN/n150/perf/test_perf_ceil.mlir        |  5 +-
 .../TTNN/n150/perf/test_perf_cosine.mlir      |  5 +-
 .../Silicon/TTNN/n150/perf/test_perf_div.mlir |  6 +-
 .../Silicon/TTNN/n150/perf/test_perf_eq.mlir  | 11 +--
 .../TTNN/n150/perf/test_perf_expm1.mlir       |  6 +-
 .../TTNN/n150/perf/test_perf_floor.mlir       | 10 +--
 .../Silicon/TTNN/n150/perf/test_perf_ge.mlir  |  7 +-
 .../TTNN/n150/perf/test_perf_gelu.mlir        |  9 +-
 .../Silicon/TTNN/n150/perf/test_perf_gt.mlir  | 11 +--
 .../TTNN/n150/perf/test_perf_isfinite.mlir    |  9 +-
 .../Silicon/TTNN/n150/perf/test_perf_log.mlir |  5 +-
 .../TTNN/n150/perf/test_perf_log1p.mlir       |  7 +-
 .../Silicon/TTNN/n150/perf/test_perf_lt.mlir  | 11 +--
 .../TTNN/n150/perf/test_perf_maximum.mlir     |  6 +-
 .../TTNN/n150/perf/test_perf_multiply.mlir    |  6 +-
 .../Silicon/TTNN/n150/perf/test_perf_ne.mlir  | 11 +--
 .../Silicon/TTNN/n150/perf/test_perf_neg.mlir |  4 +-
 .../Silicon/TTNN/n150/perf/test_perf_not.mlir |  7 +-
 .../Silicon/TTNN/n150/perf/test_perf_or.mlir  |  9 +-
 .../TTNN/n150/perf/test_perf_power.mlir       |  7 +-
 .../TTNN/n150/perf/test_perf_reciprocal.mlir  |  5 +-
 .../TTNN/n150/perf/test_perf_relu.mlir        |  6 +-
 .../TTNN/n150/perf/test_perf_remainder.mlir   |  7 +-
 .../TTNN/n150/perf/test_perf_rsqrt.mlir       |  5 +-
 .../TTNN/n150/perf/test_perf_sigmoid.mlir     |  6 +-
 .../TTNN/n150/perf/test_perf_sign.mlir        |  7 +-
 .../TTNN/n150/perf/test_perf_sine.mlir        |  6 +-
 .../TTNN/n150/perf/test_perf_sqrt.mlir        |  5 +-
 .../TTNN/n150/perf/test_perf_subtract.mlir    |  6 +-
 .../Silicon/TTNN/n150/perf/test_perf_tan.mlir |  5 +-
 .../TTNN/n150/perf/test_perf_tanh.mlir        |  5 +-
 .../TTNN/n150/perf/test_perf_where.mlir       |  5 +-
 .../Silicon/TTNN/n150/perf/test_perf_xor.mlir | 10 +--
 .../eltwise_binary_op_chain.mlir              |  9 +-
 .../n150/sharded/simple_eltwise_sharded.mlir  | 29 +++----
 .../Silicon/TTNN/n150/simple_power.mlir       | 11 ---
 .../TestGreedyL1InterleavedPolicy.cpp         | 12 +--
 test/unittests/Optimizer/TestShardSolver.cpp  | 18 ++--
 167 files changed, 640 insertions(+), 745 deletions(-)
 rename test/ttmlir/Dialect/TTNN/{ => eltwise/binary/compare}/simple_compare.mlir (60%)
 rename test/ttmlir/Dialect/TTNN/{ => eltwise/binary/div}/simple_div.mlir (76%)
 rename test/ttmlir/Dialect/TTNN/{ => eltwise/binary/maximum}/simple_maximum.mlir (75%)
 rename test/ttmlir/Dialect/TTNN/{ => eltwise/binary/multiply}/simple_multiply.mlir (75%)
 rename test/ttmlir/Dialect/TTNN/{ => eltwise/binary/subtract}/simple_subtract.mlir (75%)
 rename test/ttmlir/Dialect/TTNN/{ => eltwise/ternary/where}/simple_where.mlir (68%)
 rename test/ttmlir/Silicon/TTNN/n150/{ => eltwise/binary/compare}/simple_compare.mlir (60%)
 rename test/ttmlir/Silicon/TTNN/n150/{ => eltwise/binary/logical}/simple_logical.mlir (54%)
 create mode 100644 test/ttmlir/Silicon/TTNN/n150/eltwise/unary/logical_not/simple_not.mlir
 delete mode 100644 test/ttmlir/Silicon/TTNN/n150/simple_power.mlir

diff --git a/include/ttmlir/Dialect/TTNN/IR/TTNNOps.td b/include/ttmlir/Dialect/TTNN/IR/TTNNOps.td
index bc2d4f2628..c2f4a324d1 100644
--- a/include/ttmlir/Dialect/TTNN/IR/TTNNOps.td
+++ b/include/ttmlir/Dialect/TTNN/IR/TTNNOps.td
@@ -127,15 +127,14 @@ class TTNN_NamedDPSOp<string mnemonic, list<Trait> traits = []> :
 }
 
 class TTNN_ElementwiseOp<string mnemonic, list<Trait> traits = []> :
-    TTNN_NamedDPSOp<mnemonic, !listconcat(traits, [AttrSizedOperandSegments])> {
+    TTNN_Op<mnemonic, traits> {
 
-    let arguments = (ins Variadic<AnyRankedTensor>:$inputs,
-                         Variadic<AnyRankedTensor>:$outputs);
+    let arguments = (ins Variadic<AnyRankedTensor>:$inputs);
     let results = (outs Variadic<AnyRankedTensor>:$results);
 }
 
 class TTNN_ElementwiseUnaryOp<string mnemonic, list<Trait> traits = []> :
-    TTNN_ElementwiseOp<mnemonic, traits> {
+    TTNN_ElementwiseOp<mnemonic, !listconcat([OneOperand], traits)> {
     let summary = "Eltwise unary op.";
     let description = [{
       Eltwise unary op.
@@ -143,15 +142,19 @@ class TTNN_ElementwiseUnaryOp<string mnemonic, list<Trait> traits = []> :
 
     let builders =
     [
-      OpBuilder<(ins "Value": $in, "Value": $out),
+      OpBuilder<(ins "Value": $in, "Type": $outputType),
+      [{
+        build($_builder, $_state, {outputType}, in);
+      }]>,
+      OpBuilder<(ins "Value": $in),
       [{
-        build($_builder, $_state, {out.getType()}, in, out);
+        build($_builder, $_state, in, in.getType());
       }]>
     ];
 }
 
 class TTNN_ElementwiseBinaryOp<string mnemonic, list<Trait> traits = []> :
-    TTNN_ElementwiseOp<mnemonic, traits> {
+    TTNN_ElementwiseOp<mnemonic, !listconcat([TwoOperands], traits)> {
     let summary = "Eltwise binary op.";
     let description = [{
       Eltwise binary op.
@@ -159,15 +162,19 @@ class TTNN_ElementwiseBinaryOp<string mnemonic, list<Trait> traits = []> :
 
     let builders =
     [
-      OpBuilder<(ins "Value": $lhs, "Value": $rhs, "Value": $out),
+      OpBuilder<(ins "Value": $lhs, "Value": $rhs, "Type": $outputType),
+      [{
+        build($_builder, $_state, {outputType}, {lhs, rhs});
+      }]>,
+      OpBuilder<(ins "Value": $lhs, "Value": $rhs),
       [{
-        build($_builder, $_state, {out.getType()}, {lhs, rhs}, out);
+        build($_builder, $_state, lhs, rhs, lhs.getType());
       }]>
     ];
 }
 
 class TTNN_ElementwiseTernaryOp<string mnemonic, list<Trait> traits = []> :
-    TTNN_ElementwiseOp<mnemonic, traits> {
+    TTNN_ElementwiseOp<mnemonic, !listconcat([ThreeOperands], traits)> {
     let summary = "Eltwise ternary op.";
     let description = [{
       Eltwise ternary op.
@@ -175,9 +182,13 @@ class TTNN_ElementwiseTernaryOp<string mnemonic, list<Trait> traits = []> :
 
     let builders =
     [
-      OpBuilder<(ins "Value": $first, "Value": $second, "Value": $third, "Value": $out),
+      OpBuilder<(ins "Value": $first, "Value": $second, "Value": $third, "Type": $outputType),
       [{
-        build($_builder, $_state, {out.getType()}, {first, second, third}, out);
+        build($_builder, $_state, {outputType}, {first, second, third});
+      }]>,
+      OpBuilder<(ins "Value": $first, "Value": $second, "Value": $third),
+      [{
+        build($_builder, $_state, first, second, third, first.getType());
       }]>
     ];
 }
@@ -189,8 +200,6 @@ def TTNN_WhereOp : TTNN_ElementwiseTernaryOp<"where"> {
     }];
 
     let extraClassDeclaration = [{
-      MutableOperandRange getDpsInitsMutable() { return getOutputsMutable(); }
-
       wa::TTNNOperandsWorkarounds getOperandsWorkarounds() {
         ::mlir::Operation::operand_range inputs = getInputs();
         return
@@ -391,14 +400,13 @@ class TTNN_ElementwiseUnaryWithFloatParameterOp<string mnemonic, list<Trait> tra
     }];
 
     let arguments = (ins Variadic<AnyRankedTensor>:$inputs,
-                         Variadic<AnyRankedTensor>:$outputs,
                          F32Attr:$parameter);
 
     let builders =
     [
-      OpBuilder<(ins "Value": $in, "Value": $out, "FloatAttr":$parameter),
+      OpBuilder<(ins "Value": $in, "FloatAttr":$parameter),
       [{
-        build($_builder, $_state, {out.getType()}, {in}, {out}, parameter);
+        build($_builder, $_state, {in.getType()}, {in}, parameter);
       }]>
     ];
 }
diff --git a/include/ttmlir/Dialect/TTNN/IR/TTNNTraits.h b/include/ttmlir/Dialect/TTNN/IR/TTNNTraits.h
index a05b0d3aaf..2ac6073146 100644
--- a/include/ttmlir/Dialect/TTNN/IR/TTNNTraits.h
+++ b/include/ttmlir/Dialect/TTNN/IR/TTNNTraits.h
@@ -70,6 +70,24 @@ class HasMemoryConfigTrait
     return mlir::success();
   }
 };
+
+// Trait to verify that operations have exactly N operands.
+template <unsigned N>
+class NOperandTTNN {
+public:
+  template <typename ConcreteType>
+  class Impl
+      : public mlir::OpTrait::TraitBase<ConcreteType, NOperandTTNN<N>::Impl> {
+    static LogicalResult verifyTrait(Operation *op) {
+      if (op->getNumOperands() != N) {
+        return op->emitOpError() << "Operation " << op->getName()
+                                 << " must have exactly " << N << " operands.";
+      }
+      return success();
+    }
+  };
+};
+
 } // namespace mlir::tt::ttnn
 
 #endif
diff --git a/include/ttmlir/Dialect/TTNN/IR/TTNNTraits.td b/include/ttmlir/Dialect/TTNN/IR/TTNNTraits.td
index bf1a2dce64..a68c680bbf 100644
--- a/include/ttmlir/Dialect/TTNN/IR/TTNNTraits.td
+++ b/include/ttmlir/Dialect/TTNN/IR/TTNNTraits.td
@@ -7,10 +7,32 @@
 
 include "mlir/IR/OpBase.td"
 
+//===----------------------------------------------------------------------===//
+// TTNN traits definition.
+//===----------------------------------------------------------------------===//
+
 // Trait for ops that have memory config attribute.
 def HasMemoryConfigTrait : NativeOpTrait<"HasMemoryConfigTrait">
 {
   let cppNamespace = "mlir::tt::ttnn";
 }
 
+// Trait for ops with variadic operands to specify the number of operands.
+//
+// Trait for ops with one operand.
+def OneOperand : ParamNativeOpTrait<"NOperandTTNN", "1">
+{
+  let cppNamespace = "mlir::tt::ttnn";
+}
+// Trait for ops with two operands.
+def TwoOperands : ParamNativeOpTrait<"NOperandTTNN", "2">
+{
+  let cppNamespace = "mlir::tt::ttnn";
+}
+// Trait for ops with three operands.
+def ThreeOperands : ParamNativeOpTrait<"NOperandTTNN", "3">
+{
+  let cppNamespace = "mlir::tt::ttnn";
+}
+
 #endif // TTMLIR_TTMLIR_DIALECT_TTNN_TTNNTRAITS_TD
diff --git a/lib/Conversion/TTIRToTTNN/TTIRToTTNN.cpp b/lib/Conversion/TTIRToTTNN/TTIRToTTNN.cpp
index a2819d70f6..8b770a01c0 100644
--- a/lib/Conversion/TTIRToTTNN/TTIRToTTNN.cpp
+++ b/lib/Conversion/TTIRToTTNN/TTIRToTTNN.cpp
@@ -302,8 +302,7 @@ class ElementwiseOpConversionPattern : public OpConversionPattern<TTIROpTy> {
       return failure();
     }
 
-    rewriter.replaceOpWithNewOp<TTNNOpTy>(op, resultTypes, adaptor.getInputs(),
-                                          adaptor.getOutputs());
+    rewriter.replaceOpWithNewOp<TTNNOpTy>(op, resultTypes, adaptor.getInputs());
     return success();
   }
 };
@@ -633,7 +632,7 @@ class ElementwiseUnaryWithFloatParameterOpConversionPattern
                   ConversionPatternRewriter &rewriter) const override {
     rewriter.replaceOpWithNewOp<TTNNOpTy>(
         op, this->getTypeConverter()->convertType(op.getType(0)),
-        adaptor.getInputs(), adaptor.getOutputs(), adaptor.getParameter());
+        adaptor.getInputs(), adaptor.getParameter());
     return success();
   }
 };
@@ -1272,8 +1271,7 @@ class SubtractOpConversionPattern
 
     if (lhsType.getShape() == rhsType.getShape()) {
       rewriter.replaceOpWithNewOp<ttnn::SubtractOp>(
-          srcOp, adaptor.getInputs().front(), adaptor.getInputs().back(),
-          adaptor.getOutputs().front());
+          srcOp, adaptor.getInputs().front(), adaptor.getInputs().back());
 
       // Broadcast for rhs operand require the operation to be commutative to
       // allow switching the order of operands. To allow this conversion, the
@@ -1282,11 +1280,10 @@ class SubtractOpConversionPattern
 
     } else {
       ttnn::NegOp negOp = ttmlir::utils::createDPSOp<ttnn::NegOp>(
-          rewriter, srcOp.getLoc(), rhsType, adaptor.getInputs().back());
+          rewriter, srcOp.getLoc(), rhsType);
 
       rewriter.replaceOpWithNewOp<ttnn::AddOp>(
-          srcOp, adaptor.getInputs().front(), negOp.getResults().front(),
-          adaptor.getOutputs().front());
+          srcOp, adaptor.getInputs().front(), negOp.getResults().front());
     }
 
     return success();
@@ -1415,8 +1412,9 @@ class ScatterOpConversionPattern : public OpConversionPattern<ttir::ScatterOp> {
                   ConversionPatternRewriter &rewriter) const override {
     // The ttnn interface has the inverse inputs of the TTIR dialect op (which
     // matches torch ops).
-    rewriter.replaceOpWithNewOp<ttnn::ScatterOp>(
-        op, adaptor.getUpdate(), adaptor.getInput(), adaptor.getOutput());
+    rewriter.replaceOpWithNewOp<ttnn::ScatterOp>(op, adaptor.getUpdate(),
+                                                 adaptor.getInput(),
+                                                 adaptor.getOutput().getType());
 
     return success();
   }
diff --git a/lib/Conversion/TTNNToEmitC/TTNNToEmitC.cpp b/lib/Conversion/TTNNToEmitC/TTNNToEmitC.cpp
index 041f9dd866..da17cb30fd 100644
--- a/lib/Conversion/TTNNToEmitC/TTNNToEmitC.cpp
+++ b/lib/Conversion/TTNNToEmitC/TTNNToEmitC.cpp
@@ -136,7 +136,6 @@ class EltwiseUnaryOpConversionPattern
     llvm::SmallVector<Attribute, 5> attrs;
     attrs.push_back(mlir::IntegerAttr::get(rewriter.getIndexType(), 0));
     attrs.push_back(ttnn_to_emitc::utils::createStdNullopt(rewriter));
-    attrs.push_back(mlir::IntegerAttr::get(rewriter.getIndexType(), 1));
 
     ArrayAttr arrayAttrs = ArrayAttr::get(srcOp->getContext(), attrs);
 
@@ -173,8 +172,7 @@ class EltwiseUnaryWithFastAndApproximateModeOpConversionPattern
         {mlir::IntegerAttr::get(rewriter.getIndexType(), 0),
          ttnn_to_emitc::utils::convertBoolAttr(
              rewriter, BoolAttr::get(rewriter.getContext(), false)),
-         ttnn_to_emitc::utils::createStdNullopt(rewriter),
-         mlir::IntegerAttr::get(rewriter.getIndexType(), 1)});
+         ttnn_to_emitc::utils::createStdNullopt(rewriter)});
 
     rewriter.replaceOpWithNewOp<emitc::CallOpaqueOp>(
         srcOp, this->getTypeConverter()->convertType(srcOp.getType(0)),
@@ -243,7 +241,6 @@ class EltwiseBinaryOpConversionPattern
     attrs.push_back(mlir::IntegerAttr::get(rewriter.getIndexType(), 1));
     attrs.push_back(ttnn_to_emitc::utils::createStdNullopt(rewriter));
     attrs.push_back(ttnn_to_emitc::utils::createStdNullopt(rewriter));
-    attrs.push_back(mlir::IntegerAttr::get(rewriter.getIndexType(), 2));
 
     ArrayAttr arrayAttrs = ArrayAttr::get(srcOp->getContext(), attrs);
 
diff --git a/lib/Dialect/TTNN/Analysis/ShardSolver.cpp b/lib/Dialect/TTNN/Analysis/ShardSolver.cpp
index 6cb49f3583..b664920825 100644
--- a/lib/Dialect/TTNN/Analysis/ShardSolver.cpp
+++ b/lib/Dialect/TTNN/Analysis/ShardSolver.cpp
@@ -531,10 +531,12 @@ bool ShardSolver::checkShardCompatible(
 
     uint32_t numOperands = consumerOp->getNumOperands();
 
-    // Some ops have multiple operands; and some ops have output also an
-    // operand. TBD if there is a more robust way to get real number of inputs.
-    // TODO(odjuricic): cast to DPSop?
-    numOperands = (numOperands > 1) ? numOperands - 1 : numOperands;
+    // DPS ops have an additional operand for the destination style, hence
+    // we need to subtract it from the total number of operands.
+    if (llvm::isa<DestinationStyleOpInterface>(consumerOp)) {
+      numOperands = numOperands - 1;
+    }
+
     std::vector<TTNNLayoutAttr> inputLayouts;
 
     auto inputUnderCheck =
diff --git a/lib/Dialect/TTNN/IR/TTNNOpModelInterface.cpp b/lib/Dialect/TTNN/IR/TTNNOpModelInterface.cpp
index 639493473f..2623db1cc5 100644
--- a/lib/Dialect/TTNN/IR/TTNNOpModelInterface.cpp
+++ b/lib/Dialect/TTNN/IR/TTNNOpModelInterface.cpp
@@ -36,8 +36,7 @@ ReluOp::getOpConstraints(const std::vector<TTNNLayoutAttr> &inputs,
   assert(inputs.size() == 1);
 
   const auto inputShape =
-      mlir::cast<RankedTensorType>(getDpsInputOperand(0)->get().getType())
-          .getShape();
+      mlir::cast<RankedTensorType>(getOperand(0).getType()).getShape();
 
   const auto outputShape =
       mlir::cast<RankedTensorType>(getResults().front().getType()).getShape();
@@ -58,8 +57,7 @@ ReluOp::getOpRuntime(const std::vector<TTNNLayoutAttr> &inputs,
   assert(inputs.size() == 1);
 
   const auto inputShape =
-      mlir::cast<RankedTensorType>(getDpsInputOperand(0)->get().getType())
-          .getShape();
+      mlir::cast<RankedTensorType>(getOperand(0).getType()).getShape();
 
   const auto outputShape =
       mlir::cast<RankedTensorType>(getResults().front().getType()).getShape();
diff --git a/lib/Dialect/TTNN/IR/TTNNWorkarounds.cpp b/lib/Dialect/TTNN/IR/TTNNWorkarounds.cpp
index 5919841ec4..4bb6ab4fcf 100644
--- a/lib/Dialect/TTNN/IR/TTNNWorkarounds.cpp
+++ b/lib/Dialect/TTNN/IR/TTNNWorkarounds.cpp
@@ -355,7 +355,6 @@ TTNNOperandsWorkaroundsFactory::createWhereOpOperandsWorkarounds(
       .addInputOperandWorkaround(typeWorkaround)
       .addInputOperandWorkaround(typeWorkaround)
       .addInputOperandWorkaround(typeWorkaround)
-      .addInputOperandWorkaround(typeWorkaround)
       .addOutputOperandWorkaround(typeWorkaround);
 }
 } // namespace mlir::tt::ttnn::wa
diff --git a/lib/Dialect/TTNN/Transforms/Optimizer.cpp b/lib/Dialect/TTNN/Transforms/Optimizer.cpp
index d742254333..a42965ff6b 100644
--- a/lib/Dialect/TTNN/Transforms/Optimizer.cpp
+++ b/lib/Dialect/TTNN/Transforms/Optimizer.cpp
@@ -8,6 +8,7 @@
 #include "ttmlir/Dialect/TTNN/Analysis/LegalLayoutAnalysis.h"
 #include "ttmlir/Dialect/TTNN/Analysis/MemoryLayoutAnalysis.h"
 #include "ttmlir/Dialect/TTNN/Analysis/OpConfigAnalysis.h"
+#include "ttmlir/Dialect/TTNN/IR/TTNNOps.h"
 #include "ttmlir/Dialect/TTNN/IR/TTNNOpsTypes.h"
 #include "ttmlir/Dialect/TTNN/Transforms/Passes.h"
 #include "ttmlir/Dialect/TTNN/Utils/Utils.h"
@@ -377,7 +378,7 @@ class TTNNOptimizer : public impl::TTNNOptimizerBase<TTNNOptimizer> {
   void extractReshardEdges(ModuleOp &moduleOp,
                            std::unordered_set<Edge> &overrideReshardEdges) {
     moduleOp->walk([&](Operation *op) {
-      if (!isa<DestinationStyleOpInterface>(op)) {
+      if (isa<ToLayoutOp>(op)) {
         return;
       }
 
@@ -409,16 +410,28 @@ class TTNNOptimizer : public impl::TTNNOptimizerBase<TTNNOptimizer> {
   }
 
   mlir::TypedValue<mlir::tt::DeviceType>
-  getDeviceOpValue(Operation *contextOp) {
+  getOrCreateDeviceOpValue(Operation *contextOp, OpBuilder &builder) {
     Block *block = contextOp->getBlock();
-    mlir::TypedValue<mlir::tt::DeviceType> deviceOpResult;
     for (auto &op : block->getOperations()) {
       if (GetDeviceOp deviceOp = dyn_cast<GetDeviceOp>(op)) {
-        deviceOpResult = deviceOp.getResult();
-        break;
+        return deviceOp.getResult();
       }
     }
-    return deviceOpResult;
+
+    // Device op does not exist in the block, hence we need to create it.
+    DeviceAttr deviceAttr = getCurrentScopeDevice(contextOp);
+    auto currentInsertionPoint = builder.saveInsertionPoint();
+    builder.setInsertionPoint(block, block->begin());
+    llvm::SmallVector<int64_t> meshShape{deviceAttr.getMeshShape()};
+    if (meshShape.empty()) {
+      meshShape = llvm::SmallVector<int64_t, 2>{1, 1};
+    }
+    auto deviceOp = builder.create<ttnn::GetDeviceOp>(
+        contextOp->getLoc(), builder.getType<DeviceType>(deviceAttr),
+        ttnn::MeshShapeAttr::get(contextOp->getContext(), meshShape[0],
+                                 meshShape[1]));
+    builder.restoreInsertionPoint(currentInsertionPoint);
+    return deviceOp;
   }
 
   void
@@ -492,7 +505,7 @@ class TTNNOptimizer : public impl::TTNNOptimizerBase<TTNNOptimizer> {
         Operation *memoryReconfigOp = builder.create<ToLayoutOp>(
             consumerOp->getLoc(), newTensorType, producerOp->getResult(0),
             outputLayout, outputDataType, outputMemConfigAttr,
-            getDeviceOpValue(consumerOp));
+            getOrCreateDeviceOpValue(consumerOp, builder));
 
         consumerOp->setOperand(edge.operandIndex,
                                memoryReconfigOp->getResult(0));
diff --git a/lib/Dialect/TTNN/Transforms/Workarounds/Decomposition/RepeatOpRewritePattern.cpp b/lib/Dialect/TTNN/Transforms/Workarounds/Decomposition/RepeatOpRewritePattern.cpp
index 923d2b47d7..41ceb246e7 100644
--- a/lib/Dialect/TTNN/Transforms/Workarounds/Decomposition/RepeatOpRewritePattern.cpp
+++ b/lib/Dialect/TTNN/Transforms/Workarounds/Decomposition/RepeatOpRewritePattern.cpp
@@ -30,48 +30,9 @@ TTNNRepeatFoldingWorkaround::matchAndRewrite(ttnn::RepeatOp op,
   addInputs.push_back(op.getOperand());
   addInputs.push_back(zeroOp.getResult());
 
-  // Create an EmptyOp as AddOp is a DPS Op.
-  // Get ttnn::TTNNLayoutAttr of the result type
-  //
-  ttnn::TTNNLayoutAttr layoutAttr =
-      mlir::cast<ttnn::TTNNLayoutAttr>(op.getResult().getType().getEncoding());
-
-  // Get the shape of the tensor, tensor layout, and data type
-  //
-  ttnn::ShapeAttr shapeAttr = ttnn::ShapeAttr::get(
-      rewriter.getContext(),
-      mlir::cast<RankedTensorType>(op->getResult(0).getType()).getShape());
-  DataType dtype = layoutAttr.getDataType();
-  ttnn::Layout ttnnLayoutEnum = ttnn::Layout::RowMajor;
-  if (layoutAttr.isTiled()) {
-    ttnnLayoutEnum = ttnn::Layout::Tile;
-  } else {
-    ttnnLayoutEnum = ttnn::Layout::RowMajor;
-  }
-  DataTypeAttr dTypeAttr = DataTypeAttr::get(rewriter.getContext(), dtype);
-  ttnn::LayoutAttr tensorLayoutAttr =
-      ttnn::LayoutAttr::get(op.getContext(), ttnnLayoutEnum);
-
-  // Create MemoryConfigAttr
-  //
-  ttnn::BufferTypeAttr bufferTypeAttr =
-      ttnn::BufferTypeAttr::get(op.getContext(), layoutAttr.getBufferType());
-  ttnn::ShardSpecAttr shardSpecAttr = ttnn::ShardSpecAttr::get(
-      op.getContext(),
-      ttnn::ShapeAttr::get(op.getContext(), layoutAttr.getShardShape()));
-  ttnn::MemoryConfigAttr memoryConfigAttr =
-      ttnn::MemoryConfigAttr::get(op.getContext(), bufferTypeAttr,
-                                  shardSpecAttr, layoutAttr.getMemLayout());
-
-  // Create EmptyOp
-  //
-  ttnn::EmptyOp emptyOp = rewriter.create<ttnn::EmptyOp>(
-      op->getLoc(), op.getType(), shapeAttr, dTypeAttr, tensorLayoutAttr,
-      device, memoryConfigAttr);
-
   // Replace the RepeatOp with an AddOp to perform implicit repeat.
   rewriter.replaceOpWithNewOp<ttnn::AddOp>(op, op.getResult().getType(),
-                                           addInputs, emptyOp.getResult());
+                                           addInputs);
 
   return success();
 }
diff --git a/lib/Target/TTNN/TTNNToFlatbuffer.cpp b/lib/Target/TTNN/TTNNToFlatbuffer.cpp
index 4acc3601d9..231ec21b74 100644
--- a/lib/Target/TTNN/TTNNToFlatbuffer.cpp
+++ b/lib/Target/TTNN/TTNNToFlatbuffer.cpp
@@ -1058,12 +1058,12 @@ createEltwiseOp(FlatbufferObjectCache &cache, EltwiseOp op) {
     ins.push_back(cache.at<::tt::target::ttnn::TensorRef>(
         getOperandThroughDPSOps(input)));
   }
-  assert(op.getOutputs().size() == 1);
-  return ::tt::target::ttnn::CreateEltwiseOpDirect(
-      *cache.fbb, type, &ins,
-      cache.at<::tt::target::ttnn::TensorRef>(
-          getOperandThroughDPSOps(op.getOutputs().front())),
-      paramsType, params);
+  assert(op.getResults().size() == 1);
+  auto out = cache.getOrCreate(op.getResult(0), tensorValueToFlatbuffer,
+                               kHostAllocatedSize);
+
+  return ::tt::target::ttnn::CreateEltwiseOpDirect(*cache.fbb, type, &ins, out,
+                                                   paramsType, params);
 }
 
 template <typename ReductionOp>
diff --git a/test/ttmlir/Dialect/TTNN/Transforms/Workarounds/where_workaround.mlir b/test/ttmlir/Dialect/TTNN/Transforms/Workarounds/where_workaround.mlir
index 94462c2265..51b3e3ff35 100644
--- a/test/ttmlir/Dialect/TTNN/Transforms/Workarounds/where_workaround.mlir
+++ b/test/ttmlir/Dialect/TTNN/Transforms/Workarounds/where_workaround.mlir
@@ -12,7 +12,6 @@ module @moreh_cumsum attributes {tt.device = #device, tt.system_desc = #system_d
     %0 = "ttnn.get_device"() <{mesh_shape = #ttnn<mesh_shape 1x1>}> : () -> !tt.device<#device>
     %1 = "ttnn.reshape"(%arg2) <{shape = [1 : i32, 1 : i32, 1 : i32, 1 : i32]}> : (tensor<1xf32, #ttnn_layout2>) -> tensor<1x1x1x1xf32, #ttnn_layout3>
     %2 = "ttnn.repeat"(%1) <{repeat_dims = #ttnn.shape<1x12x1x46>}> : (tensor<1x1x1x1xf32, #ttnn_layout3>) -> tensor<1x12x1x46xf32, #ttnn_layout1>
-    %3 = "ttnn.empty"(%0) <{dtype = #tt.supportedDataTypes<f32>, layout = #ttnn.layout<tile>, memory_config = #ttnn.memory_config<#dram, <<1x2>>, <interleaved>>, shape = #ttnn.shape<1x12x1x46>}> : (!tt.device<#device>) -> tensor<1x12x1x46xf32, #ttnn_layout1>
     // CHECK: %[[ARG0:[0-9]+]] = {{.*}}(%arg0,
     // CHECK-SAME: dtype = #tt.supportedDataTypes<f32>
     // CHECK-SAME: tensor<1x1x1x46xbf16
@@ -21,9 +20,8 @@ module @moreh_cumsum attributes {tt.device = #device, tt.system_desc = #system_d
     // CHECK-SAME: tensor<1x1x1x46xf32
     // CHECK-SAME: tensor<1x12x1x46xf32
     // CHECK-SAME: tensor<1x12x1x46xf32
-    // CHECK-SAME: tensor<1x12x1x46xf32
     // CHECK-SAME: -> tensor<1x12x1x46xf32
-    %4 = "ttnn.where"(%arg0, %arg1, %2, %3) <{operandSegmentSizes = array<i32: 3, 1>}> : (tensor<1x1x1x46xbf16, #ttnn_layout>, tensor<1x12x1x46xf32, #ttnn_layout1>, tensor<1x12x1x46xf32, #ttnn_layout1>, tensor<1x12x1x46xf32, #ttnn_layout1>) -> tensor<1x12x1x46xf32, #ttnn_layout1>
+    %4 = "ttnn.where"(%arg0, %arg1, %2) : (tensor<1x1x1x46xbf16, #ttnn_layout>, tensor<1x12x1x46xf32, #ttnn_layout1>, tensor<1x12x1x46xf32, #ttnn_layout1>) -> tensor<1x12x1x46xf32, #ttnn_layout1>
     return %4 : tensor<1x12x1x46xf32, #ttnn_layout1>
   }
 }
diff --git a/test/ttmlir/Dialect/TTNN/Transforms/ttnn_create_input_gens_0.mlir b/test/ttmlir/Dialect/TTNN/Transforms/ttnn_create_input_gens_0.mlir
index 280b29858e..869a993805 100644
--- a/test/ttmlir/Dialect/TTNN/Transforms/ttnn_create_input_gens_0.mlir
+++ b/test/ttmlir/Dialect/TTNN/Transforms/ttnn_create_input_gens_0.mlir
@@ -16,11 +16,10 @@ module attributes {tt.device = #device, tt.system_desc = #system_desc} {
     %2 = "ttnn.to_layout"(%1) <{layout = #ttnn.layout<tile>}> : (tensor<32x32xbf16, #ttnn_layout1>) -> tensor<32x32xbf16, #ttnn_layout2>
     %3 = "ttnn.to_device"(%arg1, %0) <{memory_config = #ttnn.memory_config<#dram, <<1x1>>, <interleaved>>}> : (tensor<32x32xbf16, #ttnn_layout>, !tt.device<#device>) -> tensor<32x32xbf16, #ttnn_layout1>
     %4 = "ttnn.to_layout"(%3) <{layout = #ttnn.layout<tile>}> : (tensor<32x32xbf16, #ttnn_layout1>) -> tensor<32x32xbf16, #ttnn_layout2>
-    %5 = "ttnn.empty"(%0) <{dtype = #tt.supportedDataTypes<bf16>, layout = #ttnn.layout<tile>, memory_config = #ttnn.memory_config<#dram, <<1x1>>, <interleaved>>, shape = #ttnn.shape<32x32>}> : (!tt.device<#device>) -> tensor<32x32xbf16, #ttnn_layout2>
-    %6 = "ttnn.add"(%2, %4, %5) <{operandSegmentSizes = array<i32: 2, 1>}> : (tensor<32x32xbf16, #ttnn_layout2>, tensor<32x32xbf16, #ttnn_layout2>, tensor<32x32xbf16, #ttnn_layout2>) -> tensor<32x32xbf16, #ttnn_layout2>
-    %7 = "ttnn.from_device"(%6) : (tensor<32x32xbf16, #ttnn_layout2>) -> tensor<32x32xbf16, #ttnn_layout3>
-    %8 = "ttnn.to_layout"(%7) <{layout = #ttnn.layout<row_major>}> : (tensor<32x32xbf16, #ttnn_layout3>) -> tensor<32x32xbf16, #ttnn_layout>
-    return %8 : tensor<32x32xbf16, #ttnn_layout>
+    %5 = "ttnn.add"(%2, %4) : (tensor<32x32xbf16, #ttnn_layout2>, tensor<32x32xbf16, #ttnn_layout2>) -> tensor<32x32xbf16, #ttnn_layout2>
+    %6 = "ttnn.from_device"(%5) : (tensor<32x32xbf16, #ttnn_layout2>) -> tensor<32x32xbf16, #ttnn_layout3>
+    %7 = "ttnn.to_layout"(%6) <{layout = #ttnn.layout<row_major>}> : (tensor<32x32xbf16, #ttnn_layout3>) -> tensor<32x32xbf16, #ttnn_layout>
+    return %7 : tensor<32x32xbf16, #ttnn_layout>
   }
 
 // Confirm that the generator func is generated, and that the tensor attrs match:
diff --git a/test/ttmlir/Dialect/TTNN/Transforms/ttnn_modify_signatures_for_dylib_0.mlir b/test/ttmlir/Dialect/TTNN/Transforms/ttnn_modify_signatures_for_dylib_0.mlir
index 1b0b770b9b..30821e8f06 100644
--- a/test/ttmlir/Dialect/TTNN/Transforms/ttnn_modify_signatures_for_dylib_0.mlir
+++ b/test/ttmlir/Dialect/TTNN/Transforms/ttnn_modify_signatures_for_dylib_0.mlir
@@ -1,7 +1,7 @@
 // RUN: ttmlir-opt --ttir-to-ttnn-backend-pipeline="system-desc-path=%system_desc_path%" --ttnn-modify-signatures-for-dylib %s | FileCheck %s
 
 module attributes {} {
-  // CHECK: func.func @add(%arg0: tuple<[[TENSOR_A:.*>]], [[TENSOR_B:.*>]]>, %arg1: !tt.device<#device>) -> tuple<tensor<32x32xbf16, #ttnn_layout>> {
+  // CHECK: func.func @add(%arg0: tuple<[[TENSOR_A:.*>]], [[TENSOR_B:.*>]]>) -> tuple<tensor<32x32xbf16, #ttnn_layout>> {
   func.func @add(%arg0: tensor<32x32xbf16>, %arg1: tensor<32x32xbf16>) -> tensor<32x32xbf16> {
     // CHECK-NEXT: %0 = tt.get_tuple_element %arg0[0] : (tuple<[[TENSOR_A]], [[TENSOR_B]]>) -> [[TENSOR_A]]
     // CHECK-NEXT: %1 = tt.get_tuple_element %arg0[1] : (tuple<[[TENSOR_A]], [[TENSOR_B]]>) -> [[TENSOR_B]]
@@ -10,7 +10,7 @@ module attributes {} {
     return %1 : tensor<32x32xbf16>
   }
 
-  // CHECK: func.func @multiple_returns(%arg0: tuple<[[TENSOR_A:.*>]], [[TENSOR_B:.*>]], [[TENSOR_C:.*>]]>, %arg1: !tt.device<#device>) -> tuple<tensor<32x32xbf16, #ttnn_layout>, tensor<32x32xbf16, #ttnn_layout>> {
+  // CHECK: func.func @multiple_returns(%arg0: tuple<[[TENSOR_A:.*>]], [[TENSOR_B:.*>]], [[TENSOR_C:.*>]]>) -> tuple<tensor<32x32xbf16, #ttnn_layout>, tensor<32x32xbf16, #ttnn_layout>> {
   func.func @multiple_returns(%arg0: tensor<32x32xbf16>, %arg1: tensor<32x32xbf16>, %arg2: tensor<32x32xbf16>) -> (tensor<32x32xbf16>, tensor<32x32xbf16>) {
     // CHECK-NEXT: %0 = tt.get_tuple_element %arg0[0] : (tuple<[[TENSOR_A]], [[TENSOR_B]], [[TENSOR_C]]>) -> [[TENSOR_A]]
     // CHECK-NEXT: %1 = tt.get_tuple_element %arg0[1] : (tuple<[[TENSOR_A]], [[TENSOR_B]], [[TENSOR_C]]>) -> [[TENSOR_B]]
diff --git a/test/ttmlir/Dialect/TTNN/data_movement/repeat/implicit_repeat.mlir b/test/ttmlir/Dialect/TTNN/data_movement/repeat/implicit_repeat.mlir
index 913ad06fad..529c18e2fa 100644
--- a/test/ttmlir/Dialect/TTNN/data_movement/repeat/implicit_repeat.mlir
+++ b/test/ttmlir/Dialect/TTNN/data_movement/repeat/implicit_repeat.mlir
@@ -37,8 +37,8 @@ module {
   func.func @main(%arg0: tensor<1x16x32xf32>, %arg1: tensor<1x1x32xf32>) -> tensor<1x16x32xf32> {
     // CHECK: [[VAL0:%[0-9]+]] = "ttnn.repeat"
     // CHECK-SAME: repeat_dims = #ttnn.shape<1x16x1>
-    // CHECK: %{{[0-9]+}} = "ttnn.multiply"(%arg0, %{{[0-9]+}}, %{{[0-9]+}})
-    // CHECK: %{{[0-9]+}} = "ttnn.bitwise_and"([[VAL0]], %{{[0-9]+}}, %{{[0-9]+}})
+    // CHECK: %{{[0-9]+}} = "ttnn.multiply"(%arg0, %{{[0-9]+}})
+    // CHECK: %{{[0-9]+}} = "ttnn.bitwise_and"([[VAL0]], %{{[0-9]+}})
     %0 = tensor.empty() : tensor<1x16x32xf32>
     %1 = "ttir.broadcast"(%arg1, %0) <{broadcast_dimensions = array<i64: 1, 16, 1>}> : (tensor<1x1x32xf32>, tensor<1x16x32xf32>) -> tensor<1x16x32xf32>
     %2 = tensor.empty() : tensor<1x16x32xf32>
@@ -53,7 +53,7 @@ module {
   func.func @main(%arg0: tensor<1x16x32xf32>, %arg1: tensor<1x1x32xf32>) -> tensor<1x16x32xf32> {
     // CHECK-NOT: ttnn.repeat
     // CHECK: [[VAL0:%[0-9]+]] = "ttnn.add"
-    // CHECK: %{{[0-9]+}} = "ttnn.add"(%arg1, [[VAL0]], %{{[0-9]+}})
+    // CHECK: %{{[0-9]+}} = "ttnn.add"(%arg1, [[VAL0]])
     %0 = tensor.empty() : tensor<1x16x32xf32>
     %1 = "ttir.broadcast"(%arg1, %0) <{broadcast_dimensions = array<i64: 1, 16, 1>}> : (tensor<1x1x32xf32>, tensor<1x16x32xf32>) -> tensor<1x16x32xf32>
     %2 = tensor.empty() : tensor<1x16x32xf32>
diff --git a/test/ttmlir/Dialect/TTNN/data_movement/repeat/repeat_workaround.mlir b/test/ttmlir/Dialect/TTNN/data_movement/repeat/repeat_workaround.mlir
index cbf7b0653e..14a530c230 100644
--- a/test/ttmlir/Dialect/TTNN/data_movement/repeat/repeat_workaround.mlir
+++ b/test/ttmlir/Dialect/TTNN/data_movement/repeat/repeat_workaround.mlir
@@ -3,8 +3,7 @@ module {
   func.func @main(%arg0: tensor<1x16x32xf32>, %arg1: tensor<1x1x32xf32>) -> tensor<1x16x32xf32> {
     // CHECK: %[[VAL0:[0-9]+]] = "ttnn.full"
     // CHECK-SAME: fillValue = 0.000000e+00 : f32
-    // CHECK: %[[EMPTY:[0-9]+]] = "ttnn.empty"{{.*}}
-    // CHECK: %{{[0-9]+}} = "ttnn.add"(%arg1, %[[VAL0]], %[[EMPTY]])
+    // CHECK: %{{[0-9]+}} = "ttnn.add"(%arg1, %[[VAL0]])
     // CHECK-NOT: "ttnn.repeat"
     %0 = tensor.empty() : tensor<1x16x32xf32>
     %1 = "ttir.broadcast"(%arg1, %0) <{broadcast_dimensions = array<i64: 1, 16, 1>}> : (tensor<1x1x32xf32>, tensor<1x16x32xf32>) -> tensor<1x16x32xf32>
diff --git a/test/ttmlir/Dialect/TTNN/eltwise/binary/bitwise_and/simple_bitwise_and.mlir b/test/ttmlir/Dialect/TTNN/eltwise/binary/bitwise_and/simple_bitwise_and.mlir
index 9413087a47..bfbba2cebe 100644
--- a/test/ttmlir/Dialect/TTNN/eltwise/binary/bitwise_and/simple_bitwise_and.mlir
+++ b/test/ttmlir/Dialect/TTNN/eltwise/binary/bitwise_and/simple_bitwise_and.mlir
@@ -3,10 +3,11 @@
 module attributes {} {
   func.func @bitwise_and(%arg0: tensor<64x128xi32>, %arg1: tensor<64x128xi32>) -> tensor<64x128xi32> {
     %0 = tensor.empty() : tensor<64x128xi32>
-    // CHECK: %[[EMPTY:.*]] = "ttnn.empty"{{.*}} -> tensor<64x128xui32, {{.*}}
     %1 = "ttir.bitwise_and"(%arg0, %arg1, %0) <{operandSegmentSizes = array<i32: 2, 1>}> : (tensor<64x128xi32>, tensor<64x128xi32>, tensor<64x128xi32>) -> tensor<64x128xi32>
-    // CHECK: {{.*}} "ttnn.bitwise_and"({{.*}}, {{.*}}, %[[EMPTY]]){{.*}} -> tensor<64x128xui32, {{.*}}
+    // CHECK: "ttnn.bitwise_and"
+    // CHECK-SAME: tensor<64x128xui32
+    // CHECK-SAME: tensor<64x128xui32
+    // CHECK-SAME: -> tensor<64x128xui32
     return %1 : tensor<64x128xi32>
-    // CHECK: return {{.*}} tensor<64x128xui32, {{.*}}
   }
 }
diff --git a/test/ttmlir/Dialect/TTNN/eltwise/binary/bitwise_or/simple_bitwise_or.mlir b/test/ttmlir/Dialect/TTNN/eltwise/binary/bitwise_or/simple_bitwise_or.mlir
index b8a85f8616..b569a1be20 100644
--- a/test/ttmlir/Dialect/TTNN/eltwise/binary/bitwise_or/simple_bitwise_or.mlir
+++ b/test/ttmlir/Dialect/TTNN/eltwise/binary/bitwise_or/simple_bitwise_or.mlir
@@ -3,10 +3,11 @@
 module attributes {} {
   func.func @bitwise_or(%arg0: tensor<64x128xi32>, %arg1: tensor<64x128xi32>) -> tensor<64x128xi32> {
     %0 = tensor.empty() : tensor<64x128xi32>
-    // CHECK: %[[EMPTY:.*]] = "ttnn.empty"{{.*}} -> tensor<64x128xui32, {{.*}}
     %1 = "ttir.bitwise_or"(%arg0, %arg1, %0) <{operandSegmentSizes = array<i32: 2, 1>}> : (tensor<64x128xi32>, tensor<64x128xi32>, tensor<64x128xi32>) -> tensor<64x128xi32>
-    // CHECK: {{.*}} "ttnn.bitwise_or"({{.*}}, {{.*}}, %[[EMPTY]]){{.*}} -> tensor<64x128xui32, {{.*}}
+    // CHECK: "ttnn.bitwise_or"
+    // CHECK-SAME: tensor<64x128xui32
+    // CHECK-SAME: tensor<64x128xui32
+    // CHECK-SAME: -> tensor<64x128xui32
     return %1 : tensor<64x128xi32>
-    // CHECK: return {{.*}} tensor<64x128xui32, {{.*}}
   }
 }
diff --git a/test/ttmlir/Dialect/TTNN/eltwise/binary/bitwise_xor/simple_bitwise_xor.mlir b/test/ttmlir/Dialect/TTNN/eltwise/binary/bitwise_xor/simple_bitwise_xor.mlir
index 3dfe4285f9..a783349bbb 100644
--- a/test/ttmlir/Dialect/TTNN/eltwise/binary/bitwise_xor/simple_bitwise_xor.mlir
+++ b/test/ttmlir/Dialect/TTNN/eltwise/binary/bitwise_xor/simple_bitwise_xor.mlir
@@ -3,10 +3,11 @@
 module attributes {} {
   func.func @bitwise_xor(%arg0: tensor<64x128xi32>, %arg1: tensor<64x128xi32>) -> tensor<64x128xi32> {
     %0 = tensor.empty() : tensor<64x128xi32>
-    // CHECK: %[[EMPTY:.*]] = "ttnn.empty"{{.*}} -> tensor<64x128xui32, {{.*}}
     %1 = "ttir.bitwise_xor"(%arg0, %arg1, %0) <{operandSegmentSizes = array<i32: 2, 1>}> : (tensor<64x128xi32>, tensor<64x128xi32>, tensor<64x128xi32>) -> tensor<64x128xi32>
-    // CHECK: {{.*}} "ttnn.bitwise_xor"({{.*}}, {{.*}}, %[[EMPTY]]){{.*}} -> tensor<64x128xui32, {{.*}}
+    // CHECK: "ttnn.bitwise_xor"
+    // CHECK-SAME: tensor<64x128xui32
+    // CHECK-SAME: tensor<64x128xui32
+    // CHECK-SAME: -> tensor<64x128xui32
     return %1 : tensor<64x128xi32>
-    // CHECK: return {{.*}} tensor<64x128xui32, {{.*}}
   }
 }
diff --git a/test/ttmlir/Dialect/TTNN/simple_compare.mlir b/test/ttmlir/Dialect/TTNN/eltwise/binary/compare/simple_compare.mlir
similarity index 60%
rename from test/ttmlir/Dialect/TTNN/simple_compare.mlir
rename to test/ttmlir/Dialect/TTNN/eltwise/binary/compare/simple_compare.mlir
index 873ae745ce..f96213e73a 100644
--- a/test/ttmlir/Dialect/TTNN/simple_compare.mlir
+++ b/test/ttmlir/Dialect/TTNN/eltwise/binary/compare/simple_compare.mlir
@@ -1,90 +1,72 @@
 // RUN: ttmlir-opt --ttir-to-ttnn-backend-pipeline %s | FileCheck %s
 module attributes {} {
   func.func @equal(%arg0: tensor<13x31xf32>, %arg1: tensor<13x31xf32>) -> tensor<13x31xf32> {
-    // CHECK: %[[C:.*]] = "ttnn.empty"
-    // CHECK-SAME: [[TENSOR:tensor<13x31xf32,]]
     %0 = tensor.empty() : tensor<13x31xf32>
-    // CHECK: %[[C:.*]] = "ttnn.eq"
-    // CHECK-SAME: [[TENSOR]]
-    // CHECK-SAME: [[TENSOR]]
-    // CHECK-SAME: [[TENSOR]]
-    // CHECK-SAME: -> [[TENSOR]]
     %1 = "ttir.eq"(%arg0, %arg1, %0) <{operandSegmentSizes = array<i32: 2, 1>}> : (tensor<13x31xf32>, tensor<13x31xf32>, tensor<13x31xf32>) -> tensor<13x31xf32>
+    // CHECK: "ttnn.eq"
+    // CHECK-SAME: tensor<13x31xf32
+    // CHECK-SAME: tensor<13x31xf32
+    // CHECK-SAME: -> tensor<13x31xf32
     return %1 : tensor<13x31xf32>
   }
 }
 
 module attributes {} {
   func.func @not_equal(%arg0: tensor<13x31xf32>, %arg1: tensor<13x31xf32>) -> tensor<13x31xf32> {
-    // CHECK: %[[C:.*]] = "ttnn.empty
-    // CHECK-SAME: [[TENSOR:tensor<13x31xf32,]]
     %0 = tensor.empty() : tensor<13x31xf32>
-    // CHECK: %[[C:.*]] = "ttnn.ne"
-    // CHECK-SAME: [[TENSOR]]
-    // CHECK-SAME: [[TENSOR]]
-    // CHECK-SAME: [[TENSOR]]
-    // CHECK-SAME: -> [[TENSOR]]
     %1 = "ttir.ne"(%arg0, %arg1, %0) <{operandSegmentSizes = array<i32: 2, 1>}> : (tensor<13x31xf32>, tensor<13x31xf32>, tensor<13x31xf32>) -> tensor<13x31xf32>
+    // CHECK: "ttnn.ne"
+    // CHECK-SAME: tensor<13x31xf32
+    // CHECK-SAME: tensor<13x31xf32
+    // CHECK-SAME: -> tensor<13x31xf32
     return %1 : tensor<13x31xf32>
   }
 }
 
 module attributes {} {
   func.func @greater_equal(%arg0: tensor<13x31xf32>, %arg1: tensor<13x31xf32>) -> tensor<13x31xf32> {
-    // CHECK: %[[C:.*]] = "ttnn.empty
-    // CHECK-SAME: [[TENSOR:tensor<13x31xf32,]]
     %0 = tensor.empty() : tensor<13x31xf32>
-    // CHECK: %[[C:.*]] = "ttnn.ge"
-    // CHECK-SAME: [[TENSOR]]
-    // CHECK-SAME: [[TENSOR]]
-    // CHECK-SAME: [[TENSOR]]
-    // CHECK-SAME: -> [[TENSOR]]
     %1 = "ttir.ge"(%arg0, %arg1, %0) <{operandSegmentSizes = array<i32: 2, 1>}> : (tensor<13x31xf32>, tensor<13x31xf32>, tensor<13x31xf32>) -> tensor<13x31xf32>
+    // CHECK: "ttnn.ge"
+    // CHECK-SAME: tensor<13x31xf32
+    // CHECK-SAME: tensor<13x31xf32
+    // CHECK-SAME: -> tensor<13x31xf32
     return %1 : tensor<13x31xf32>
   }
 }
 
 module attributes {} {
   func.func @greater_than(%arg0: tensor<13x31xf32>, %arg1: tensor<13x31xf32>) -> tensor<13x31xf32> {
-    // CHECK: %[[C:.*]] = "ttnn.empty
-    // CHECK-SAME: [[TENSOR:tensor<13x31xf32,]]
     %0 = tensor.empty() : tensor<13x31xf32>
-    // CHECK: %[[C:.*]] = "ttnn.gt"
-    // CHECK-SAME: [[TENSOR]]
-    // CHECK-SAME: [[TENSOR]]
-    // CHECK-SAME: [[TENSOR]]
-    // CHECK-SAME: -> [[TENSOR]]
     %1 = "ttir.gt"(%arg0, %arg1, %0) <{operandSegmentSizes = array<i32: 2, 1>}> : (tensor<13x31xf32>, tensor<13x31xf32>, tensor<13x31xf32>) -> tensor<13x31xf32>
+    // CHECK: "ttnn.gt"
+    // CHECK-SAME: tensor<13x31xf32
+    // CHECK-SAME: tensor<13x31xf32
+    // CHECK-SAME: -> tensor<13x31xf32
     return %1 : tensor<13x31xf32>
   }
 }
 
 module attributes {} {
   func.func @less_equal(%arg0: tensor<13x31xf32>, %arg1: tensor<13x31xf32>) -> tensor<13x31xf32> {
-    // CHECK: %[[C:.*]] = "ttnn.empty
-    // CHECK-SAME: [[TENSOR:tensor<13x31xf32,]]
     %0 = tensor.empty() : tensor<13x31xf32>
-    // CHECK: %[[C:.*]] = "ttnn.le"
-    // CHECK-SAME: [[TENSOR]]
-    // CHECK-SAME: [[TENSOR]]
-    // CHECK-SAME: [[TENSOR]]
-    // CHECK-SAME: -> [[TENSOR]]
     %1 = "ttir.le"(%arg0, %arg1, %0) <{operandSegmentSizes = array<i32: 2, 1>}> : (tensor<13x31xf32>, tensor<13x31xf32>, tensor<13x31xf32>) -> tensor<13x31xf32>
+    // CHECK: "ttnn.le"
+    // CHECK-SAME: tensor<13x31xf32
+    // CHECK-SAME: tensor<13x31xf32
+    // CHECK-SAME: -> tensor<13x31xf32
     return %1 : tensor<13x31xf32>
   }
 }
 
 module attributes {} {
   func.func @less_than(%arg0: tensor<13x31xf32>, %arg1: tensor<13x31xf32>) -> tensor<13x31xf32> {
-    // CHECK: %[[C:.*]] = "ttnn.empty
-    // CHECK-SAME: [[TENSOR:tensor<13x31xf32,]]
     %0 = tensor.empty() : tensor<13x31xf32>
-    // CHECK: %[[C:.*]] = "ttnn.lt"
-    // CHECK-SAME: [[TENSOR]]
-    // CHECK-SAME: [[TENSOR]]
-    // CHECK-SAME: [[TENSOR]]
-    // CHECK-SAME: -> [[TENSOR]]
     %1 = "ttir.lt"(%arg0, %arg1, %0) <{operandSegmentSizes = array<i32: 2, 1>}> : (tensor<13x31xf32>, tensor<13x31xf32>, tensor<13x31xf32>) -> tensor<13x31xf32>
+    // CHECK: "ttnn.lt"
+    // CHECK-SAME: tensor<13x31xf32
+    // CHECK-SAME: tensor<13x31xf32
+    // CHECK-SAME: -> tensor<13x31xf32
     return %1 : tensor<13x31xf32>
   }
 }
diff --git a/test/ttmlir/Dialect/TTNN/simple_div.mlir b/test/ttmlir/Dialect/TTNN/eltwise/binary/div/simple_div.mlir
similarity index 76%
rename from test/ttmlir/Dialect/TTNN/simple_div.mlir
rename to test/ttmlir/Dialect/TTNN/eltwise/binary/div/simple_div.mlir
index 15d2b4820c..c27753171f 100644
--- a/test/ttmlir/Dialect/TTNN/simple_div.mlir
+++ b/test/ttmlir/Dialect/TTNN/eltwise/binary/div/simple_div.mlir
@@ -1,10 +1,12 @@
 // RUN: ttmlir-opt --ttir-to-ttnn-backend-pipeline %s | FileCheck %s
 module attributes {} {
   func.func @forward(%arg0: tensor<64x128xf32>, %arg1: tensor<64x128xf32>) -> tensor<64x128xf32> {
-    // CHECK: %[[C:.*]] = "ttnn.empty"[[C:.*]]
     %0 = tensor.empty() : tensor<64x128xf32>
-    // CHECK: %[[C:.*]] = "ttnn.div"[[C:.*]]
     %1 = "ttir.div"(%arg0, %arg1, %0) <{operandSegmentSizes = array<i32: 2, 1>}> : (tensor<64x128xf32>, tensor<64x128xf32>, tensor<64x128xf32>) -> tensor<64x128xf32>
+    // CHECK: "ttnn.div"
+    // CHECK-SAME: tensor<64x128xf32
+    // CHECK-SAME: tensor<64x128xf32
+    // CHECK-SAME: -> tensor<64x128xf32
     return %1 : tensor<64x128xf32>
   }
 }
diff --git a/test/ttmlir/Dialect/TTNN/eltwise/binary/logical_and/simple_and.mlir b/test/ttmlir/Dialect/TTNN/eltwise/binary/logical_and/simple_and.mlir
index e6400a7529..d164ad8b24 100644
--- a/test/ttmlir/Dialect/TTNN/eltwise/binary/logical_and/simple_and.mlir
+++ b/test/ttmlir/Dialect/TTNN/eltwise/binary/logical_and/simple_and.mlir
@@ -2,12 +2,11 @@
 module attributes {} {
   func.func @logical_and(%arg0: tensor<64x128xf32>, %arg1: tensor<64x128xf32>) -> tensor<64x128xf32> {
     %0 = tensor.empty() : tensor<64x128xf32>
-    // CHECK: {{.*}} = "ttnn.empty"{{.*}}
     %1 = "ttir.logical_and"(%arg0, %arg1, %0) <{operandSegmentSizes = array<i32: 2, 1>}> : (tensor<64x128xf32>, tensor<64x128xf32>, tensor<64x128xf32>) -> tensor<64x128xf32>
-    // CHECK: %[[C:.*]] = "ttnn.logical_and"
-    // CHECK-SAME: tensor<64x128xf32,
-    // CHECK-SAME: tensor<64x128xf32,
-    // CHECK-SAME: tensor<64x128xf32,
+    // CHECK: "ttnn.logical_and"
+    // CHECK-SAME: tensor<64x128xf32
+    // CHECK-SAME: tensor<64x128xf32
+    // CHECK-SAME: -> tensor<64x128xf32
     return %1 : tensor<64x128xf32>
   }
 }
diff --git a/test/ttmlir/Dialect/TTNN/eltwise/binary/logical_or/simple_or.mlir b/test/ttmlir/Dialect/TTNN/eltwise/binary/logical_or/simple_or.mlir
index bb35140eb2..c8a80ef82f 100644
--- a/test/ttmlir/Dialect/TTNN/eltwise/binary/logical_or/simple_or.mlir
+++ b/test/ttmlir/Dialect/TTNN/eltwise/binary/logical_or/simple_or.mlir
@@ -2,12 +2,11 @@
 module attributes {} {
   func.func @logical_or(%arg0: tensor<64x128xf32>, %arg1: tensor<64x128xf32>) -> tensor<64x128xf32> {
     %0 = tensor.empty() : tensor<64x128xf32>
-    // CHECK: {{.*}} = "ttnn.empty"{{.*}}
     %1 = "ttir.logical_or"(%arg0, %arg1, %0) <{operandSegmentSizes = array<i32: 2, 1>}> : (tensor<64x128xf32>, tensor<64x128xf32>, tensor<64x128xf32>) -> tensor<64x128xf32>
-    // CHECK: %[[C:.*]] = "ttnn.logical_or"
-    // CHECK-SAME: tensor<64x128xf32,
-    // CHECK-SAME: tensor<64x128xf32,
-    // CHECK-SAME: tensor<64x128xf32,
+    // CHECK: "ttnn.logical_or"
+    // CHECK-SAME: tensor<64x128xf32
+    // CHECK-SAME: tensor<64x128xf32
+    // CHECK-SAME: -> tensor<64x128xf32
     return %1 : tensor<64x128xf32>
   }
 }
diff --git a/test/ttmlir/Dialect/TTNN/eltwise/binary/logical_xor/simple_xor.mlir b/test/ttmlir/Dialect/TTNN/eltwise/binary/logical_xor/simple_xor.mlir
index 302c76d3ff..a7996033fb 100644
--- a/test/ttmlir/Dialect/TTNN/eltwise/binary/logical_xor/simple_xor.mlir
+++ b/test/ttmlir/Dialect/TTNN/eltwise/binary/logical_xor/simple_xor.mlir
@@ -2,14 +2,12 @@
 
 module attributes {} {
   func.func @logical_xor(%arg0: tensor<64x128xbf16>, %arg1: tensor<64x128xbf16>) -> tensor<64x128xbf16> {
-    // CHECK: %{{[0-9]+}} = "ttnn.empty"{{.*}} [[TENSOR:tensor<64x128xbf16]]
     %0 = tensor.empty() : tensor<64x128xbf16>
-    // CHECK: %{{[0-9]+}} = "ttnn.logical_xor"
-    // CHECK-SAME: [[TENSOR]]
-    // CHECK-SAME: [[TENSOR]]
-    // CHECK-SAME: [[TENSOR]]
-    // CHECK-SAME: -> [[TENSOR]]
     %1 = "ttir.logical_xor"(%arg0, %arg1, %0) <{operandSegmentSizes = array<i32: 2, 1>}> : (tensor<64x128xbf16>, tensor<64x128xbf16>, tensor<64x128xbf16>) -> tensor<64x128xbf16>
+    // CHECK: "ttnn.logical_xor"
+    // CHECK-SAME: tensor<64x128xbf16
+    // CHECK-SAME: tensor<64x128xbf16
+    // CHECK-SAME: -> tensor<64x128xbf16
     return %1 : tensor<64x128xbf16>
   }
 }
diff --git a/test/ttmlir/Dialect/TTNN/simple_maximum.mlir b/test/ttmlir/Dialect/TTNN/eltwise/binary/maximum/simple_maximum.mlir
similarity index 75%
rename from test/ttmlir/Dialect/TTNN/simple_maximum.mlir
rename to test/ttmlir/Dialect/TTNN/eltwise/binary/maximum/simple_maximum.mlir
index cd87754fa0..31e8efb592 100644
--- a/test/ttmlir/Dialect/TTNN/simple_maximum.mlir
+++ b/test/ttmlir/Dialect/TTNN/eltwise/binary/maximum/simple_maximum.mlir
@@ -1,10 +1,12 @@
 // RUN: ttmlir-opt --ttir-to-ttnn-backend-pipeline %s | FileCheck %s
 module attributes {} {
   func.func @forward(%arg0: tensor<64x128xf32>, %arg1: tensor<64x128xf32>) -> tensor<64x128xf32> {
-    // CHECK: %[[C:.*]] = "ttnn.empty"[[C:.*]]
     %0 = tensor.empty() : tensor<64x128xf32>
-    // CHECK: %[[C:.*]] = "ttnn.maximum"[[C:.*]]
     %1 = "ttir.maximum"(%arg0, %arg1, %0) <{operandSegmentSizes = array<i32: 2, 1>}> : (tensor<64x128xf32>, tensor<64x128xf32>, tensor<64x128xf32>) -> tensor<64x128xf32>
+    // CHECK: "ttnn.maximum"
+    // CHECK-SAME: tensor<64x128xf32
+    // CHECK-SAME: tensor<64x128xf32
+    // CHECK-SAME: -> tensor<64x128xf32
     return %1 : tensor<64x128xf32>
   }
 }
diff --git a/test/ttmlir/Dialect/TTNN/eltwise/binary/minimum/simple_minimum.mlir b/test/ttmlir/Dialect/TTNN/eltwise/binary/minimum/simple_minimum.mlir
index 7b3576cb7f..a5297a587b 100644
--- a/test/ttmlir/Dialect/TTNN/eltwise/binary/minimum/simple_minimum.mlir
+++ b/test/ttmlir/Dialect/TTNN/eltwise/binary/minimum/simple_minimum.mlir
@@ -1,10 +1,12 @@
 // RUN: ttmlir-opt --ttir-to-ttnn-backend-pipeline %s | FileCheck %s
 module attributes {} {
   func.func @forward(%arg0: tensor<64x128xf32>, %arg1: tensor<64x128xf32>) -> tensor<64x128xf32> {
-    // CHECK: %[[C:.*]] = "ttnn.empty"[[C:.*]]
     %0 = tensor.empty() : tensor<64x128xf32>
-    // CHECK: %[[C:.*]] = "ttnn.minimum"[[C:.*]]
     %1 = "ttir.minimum"(%arg0, %arg1, %0) <{operandSegmentSizes = array<i32: 2, 1>}> : (tensor<64x128xf32>, tensor<64x128xf32>, tensor<64x128xf32>) -> tensor<64x128xf32>
+    // CHECK: "ttnn.minimum"
+    // CHECK-SAME: tensor<64x128xf32
+    // CHECK-SAME: tensor<64x128xf32
+    // CHECK-SAME: -> tensor<64x128xf32
     return %1 : tensor<64x128xf32>
   }
 }
diff --git a/test/ttmlir/Dialect/TTNN/simple_multiply.mlir b/test/ttmlir/Dialect/TTNN/eltwise/binary/multiply/simple_multiply.mlir
similarity index 75%
rename from test/ttmlir/Dialect/TTNN/simple_multiply.mlir
rename to test/ttmlir/Dialect/TTNN/eltwise/binary/multiply/simple_multiply.mlir
index 795f65efe0..fc95f01e3a 100644
--- a/test/ttmlir/Dialect/TTNN/simple_multiply.mlir
+++ b/test/ttmlir/Dialect/TTNN/eltwise/binary/multiply/simple_multiply.mlir
@@ -1,10 +1,12 @@
 // RUN: ttmlir-opt --ttir-to-ttnn-backend-pipeline %s | FileCheck %s
 module attributes {} {
   func.func @forward(%arg0: tensor<64x128xf32>, %arg1: tensor<64x128xf32>) -> tensor<64x128xf32> {
-    // CHECK: %[[C:.*]] = "ttnn.empty"[[C:.*]]
     %0 = tensor.empty() : tensor<64x128xf32>
-    // CHECK: %[[C:.*]] = "ttnn.multiply"[[C:.*]]
     %1 = "ttir.multiply"(%arg0, %arg1, %0) <{operandSegmentSizes = array<i32: 2, 1>}> : (tensor<64x128xf32>, tensor<64x128xf32>, tensor<64x128xf32>) -> tensor<64x128xf32>
+    // CHECK: "ttnn.multiply"
+    // CHECK-SAME: tensor<64x128xf32
+    // CHECK-SAME: tensor<64x128xf32
+    // CHECK-SAME: -> tensor<64x128xf32
     return %1 : tensor<64x128xf32>
   }
 }
diff --git a/test/ttmlir/Dialect/TTNN/eltwise/binary/power/simple_power.mlir b/test/ttmlir/Dialect/TTNN/eltwise/binary/power/simple_power.mlir
index 91eb4ae94f..11ca951638 100644
--- a/test/ttmlir/Dialect/TTNN/eltwise/binary/power/simple_power.mlir
+++ b/test/ttmlir/Dialect/TTNN/eltwise/binary/power/simple_power.mlir
@@ -2,10 +2,11 @@
 module attributes {} {
   func.func @power(%arg0: tensor<64x128xf32>, %arg1: tensor<64x128xf32>) -> tensor<64x128xf32> {
     %0 = tensor.empty() : tensor<64x128xf32>
-    // CHECK: %[[EMPTY:.*]] = "ttnn.empty"{{.*}} -> tensor<64x128xf32, {{.*}}
     %1 = "ttir.power"(%arg0, %arg1, %0) <{operandSegmentSizes = array<i32: 2, 1>}> : (tensor<64x128xf32>, tensor<64x128xf32>, tensor<64x128xf32>) -> tensor<64x128xf32>
-    // CHECK: %[[POW:[0-9]+]] = "ttnn.pow"({{.*}}, {{.*}}, %[[EMPTY]]){{.*}} -> tensor<64x128xf32, {{.*}}
+    // CHECK: "ttnn.pow"
+    // CHECK-SAME: tensor<64x128xf32
+    // CHECK-SAME: tensor<64x128xf32
+    // CHECK-SAME: -> tensor<64x128xf32
     return %1 : tensor<64x128xf32>
-    // CHECK: return {{.*}} : tensor<64x128xf32, {{.*}}
   }
 }
diff --git a/test/ttmlir/Dialect/TTNN/eltwise/binary/remainder/simple_remainder.mlir b/test/ttmlir/Dialect/TTNN/eltwise/binary/remainder/simple_remainder.mlir
index 67d283c078..09d7d15bc0 100644
--- a/test/ttmlir/Dialect/TTNN/eltwise/binary/remainder/simple_remainder.mlir
+++ b/test/ttmlir/Dialect/TTNN/eltwise/binary/remainder/simple_remainder.mlir
@@ -2,10 +2,11 @@
 module attributes {} {
   func.func @remainder(%arg0: tensor<32x32xf32>, %arg1: tensor<32x32xf32>) -> tensor<32x32xf32> {
     %0 = tensor.empty() : tensor<32x32xf32>
-    // CHECK: %[[EMPTY:.*]] = "ttnn.empty"{{.*}} -> tensor<32x32xf32, {{.*}}
     %1 = "ttir.remainder"(%arg0, %arg1, %0) <{operandSegmentSizes = array<i32: 2, 1>}> : (tensor<32x32xf32>, tensor<32x32xf32>, tensor<32x32xf32>) -> tensor<32x32xf32>
-    // CHECK: %[[REM:[0-9]+]] = "ttnn.remainder"({{.*}}, {{.*}}, %[[EMPTY]]){{.*}} -> tensor<32x32xf32, {{.*}}
+    // CHECK: "ttnn.remainder"
+    // CHECK-SAME: tensor<32x32xf32
+    // CHECK-SAME: tensor<32x32xf32
+    // CHECK-SAME: -> tensor<32x32xf32
     return %1 : tensor<32x32xf32>
-    // CHECK: return {{.*}} : tensor<32x32xf32, {{.*}}
   }
 }
diff --git a/test/ttmlir/Dialect/TTNN/simple_subtract.mlir b/test/ttmlir/Dialect/TTNN/eltwise/binary/subtract/simple_subtract.mlir
similarity index 75%
rename from test/ttmlir/Dialect/TTNN/simple_subtract.mlir
rename to test/ttmlir/Dialect/TTNN/eltwise/binary/subtract/simple_subtract.mlir
index f4c69ea401..b46b59e76c 100644
--- a/test/ttmlir/Dialect/TTNN/simple_subtract.mlir
+++ b/test/ttmlir/Dialect/TTNN/eltwise/binary/subtract/simple_subtract.mlir
@@ -1,10 +1,12 @@
 // RUN: ttmlir-opt --ttir-to-ttnn-backend-pipeline %s | FileCheck %s
 module attributes {} {
   func.func @forward(%arg0: tensor<64x128xf32>, %arg1: tensor<64x128xf32>) -> tensor<64x128xf32> {
-    // CHECK: %[[C:.*]] = "ttnn.empty"[[C:.*]]
     %0 = tensor.empty() : tensor<64x128xf32>
-    // CHECK: %[[C:.*]] = "ttnn.subtract"[[C:.*]]
     %1 = "ttir.subtract"(%arg0, %arg1, %0) <{operandSegmentSizes = array<i32: 2, 1>}> : (tensor<64x128xf32>, tensor<64x128xf32>, tensor<64x128xf32>) -> tensor<64x128xf32>
+    // CHECK: "ttnn.subtract"
+    // CHECK-SAME: tensor<64x128xf32
+    // CHECK-SAME: tensor<64x128xf32
+    // CHECK-SAME: -> tensor<64x128xf32
     return %1 : tensor<64x128xf32>
   }
 }
diff --git a/test/ttmlir/Dialect/TTNN/eltwise/operand_broadcasts.mlir b/test/ttmlir/Dialect/TTNN/eltwise/operand_broadcasts.mlir
index 9b5df3852d..ee5ecf7b4d 100644
--- a/test/ttmlir/Dialect/TTNN/eltwise/operand_broadcasts.mlir
+++ b/test/ttmlir/Dialect/TTNN/eltwise/operand_broadcasts.mlir
@@ -1,17 +1,15 @@
 // RUN: ttmlir-opt --ttir-to-ttnn-backend-pipeline %s | FileCheck %s
 module attributes {} {
   func.func @bcast_one_dim(%arg0: tensor<2x64x128xf32>, %arg1: tensor<64x128xf32>) -> tensor<2x64x128xf32> {
-    // CHECK: %[[C:.*]] = "ttnn.empty"[[C:.*]]
     %0 = tensor.empty() : tensor<2x64x128xf32>
-    // CHECK: %[[C:.*]] = "ttnn.multiply"[[C:.*]]
+    // CHECK: "ttnn.multiply"
     %1 = "ttir.multiply"(%arg0, %arg1, %0) <{operandSegmentSizes = array<i32: 2, 1>}> : (tensor<2x64x128xf32>, tensor<64x128xf32>, tensor<2x64x128xf32>) -> tensor<2x64x128xf32>
     return %1 : tensor<2x64x128xf32>
   }
 
   func.func @bcast_multi_dim(%arg0: tensor<17x16x15x14xf32>, %arg1: tensor<15x1xf32>) -> tensor<17x16x15x14xf32> {
-    // CHECK: %[[C:.*]] = "ttnn.empty"[[C:.*]]
     %0 = tensor.empty() : tensor<17x16x15x14xf32>
-    // CHECK: %[[C:.*]] = "ttnn.multiply"[[C:.*]]
+    // CHECK: "ttnn.multiply"
     %1 = "ttir.multiply"(%arg0, %arg1, %0) <{operandSegmentSizes = array<i32: 2, 1>}> : (tensor<17x16x15x14xf32>, tensor<15x1xf32>, tensor<17x16x15x14xf32>) -> tensor<17x16x15x14xf32>
     return %1 : tensor<17x16x15x14xf32>
   }
diff --git a/test/ttmlir/Dialect/TTNN/simple_where.mlir b/test/ttmlir/Dialect/TTNN/eltwise/ternary/where/simple_where.mlir
similarity index 68%
rename from test/ttmlir/Dialect/TTNN/simple_where.mlir
rename to test/ttmlir/Dialect/TTNN/eltwise/ternary/where/simple_where.mlir
index d8d469943c..42b0eb937b 100644
--- a/test/ttmlir/Dialect/TTNN/simple_where.mlir
+++ b/test/ttmlir/Dialect/TTNN/eltwise/ternary/where/simple_where.mlir
@@ -5,9 +5,15 @@ module @jit_eltwise_where {
     %1 = "ttir.eq"(%arg0, %arg1, %0) <{operandSegmentSizes = array<i32: 2, 1>}> : (tensor<13x37xf32>, tensor<13x37xf32>, tensor<13x37xf32>) -> tensor<13x37xf32>
     %2 = tensor.empty() : tensor<13x37xf32>
     %3 = "ttir.where"(%1, %arg0, %arg1, %2) <{operandSegmentSizes = array<i32: 3, 1>}> : (tensor<13x37xf32>, tensor<13x37xf32>, tensor<13x37xf32>, tensor<13x37xf32>) -> tensor<13x37xf32>
-    // CHECK: %[[EMPTY:.*]] = "ttnn.empty"{{.*}}
-    // CHECK: %[[VAL1:[0-9]+]] = "ttnn.eq"(%arg0, %arg1, %[[EMPTY]])
-    // CHECK: %{{[0-9]+}} = "ttnn.where"(%[[VAL1]], %arg0, %arg1, %{{[0-9]+}})
+    // CHECK: "ttnn.eq"
+    // CHECK-SAME: tensor<13x37xf32
+    // CHECK-SAME: tensor<13x37xf32
+    // CHECK-SAME: -> tensor<13x37xf32
+    // CHECK: "ttnn.where"
+    // CHECK-SAME: tensor<13x37xf32
+    // CHECK-SAME: tensor<13x37xf32
+    // CHECK-SAME: tensor<13x37xf32
+    // CHECK-SAME: -> tensor<13x37xf32
      return %3 : tensor<13x37xf32>
   }
 }
diff --git a/test/ttmlir/Dialect/TTNN/eltwise/unary/abs/simple_abs.mlir b/test/ttmlir/Dialect/TTNN/eltwise/unary/abs/simple_abs.mlir
index eceb8d058b..10a00443b5 100644
--- a/test/ttmlir/Dialect/TTNN/eltwise/unary/abs/simple_abs.mlir
+++ b/test/ttmlir/Dialect/TTNN/eltwise/unary/abs/simple_abs.mlir
@@ -1,10 +1,11 @@
 // RUN: ttmlir-opt --ttir-to-ttnn-backend-pipeline %s | FileCheck %s
 module attributes {} {
   func.func @forward(%arg0: tensor<64x128xf32>) -> tensor<64x128xf32> {
-    // CHECK: %[[C:.*]] = "ttnn.empty"[[C:.*]]
     %0 = tensor.empty() : tensor<64x128xf32>
-    // CHECK: %[[C:.*]] = "ttnn.abs"[[C:.*]]
     %1 = "ttir.abs"(%arg0, %0) <{operandSegmentSizes = array<i32: 1, 1>}> : (tensor<64x128xf32>, tensor<64x128xf32>) -> tensor<64x128xf32>
+    // CHECK: "ttnn.abs"
+    // CHECK-SAME: tensor<64x128xf32
+    // CHECK-SAME: -> tensor<64x128xf32
     return %1 : tensor<64x128xf32>
   }
 }
diff --git a/test/ttmlir/Dialect/TTNN/eltwise/unary/bitwise_not/simple_bitwise_not.mlir b/test/ttmlir/Dialect/TTNN/eltwise/unary/bitwise_not/simple_bitwise_not.mlir
index 2621c422f7..ff5a116b83 100644
--- a/test/ttmlir/Dialect/TTNN/eltwise/unary/bitwise_not/simple_bitwise_not.mlir
+++ b/test/ttmlir/Dialect/TTNN/eltwise/unary/bitwise_not/simple_bitwise_not.mlir
@@ -3,10 +3,10 @@
 module attributes {} {
   func.func @bitwise_not(%arg0: tensor<64x128xi32>) -> tensor<64x128xi32> {
     %0 = tensor.empty() : tensor<64x128xi32>
-    // CHECK: %[[EMPTY:.*]] = "ttnn.empty"{{.*}} -> tensor<64x128xui32, {{.*}}
     %1 = "ttir.bitwise_not"(%arg0, %0) <{operandSegmentSizes = array<i32: 1, 1>}> : (tensor<64x128xi32>, tensor<64x128xi32>) -> tensor<64x128xi32>
-    // CHECK: {{.*}} "ttnn.bitwise_not"({{.*}}, %[[EMPTY]]){{.*}} -> tensor<64x128xui32, {{.*}}
+    // CHECK: "ttnn.bitwise_not"
+    // CHECK-SAME: tensor<64x128xui32
+    // CHECK-SAME: -> tensor<64x128xui32
     return %1 : tensor<64x128xi32>
-    // CHECK: return {{.*}} tensor<64x128xui32, {{.*}}
   }
 }
diff --git a/test/ttmlir/Dialect/TTNN/eltwise/unary/cbrt/simple_cbrt.mlir b/test/ttmlir/Dialect/TTNN/eltwise/unary/cbrt/simple_cbrt.mlir
index bdb78fed83..5b560a5b84 100644
--- a/test/ttmlir/Dialect/TTNN/eltwise/unary/cbrt/simple_cbrt.mlir
+++ b/test/ttmlir/Dialect/TTNN/eltwise/unary/cbrt/simple_cbrt.mlir
@@ -1,10 +1,11 @@
 // RUN: ttmlir-opt --ttir-to-ttnn-backend-pipeline %s | FileCheck %s
 module attributes {} {
   func.func @forward(%arg0: tensor<64x128xf32>) -> tensor<64x128xf32> {
-    // CHECK: %[[C:.*]] = "ttnn.empty"[[C:.*]]
     %0 = tensor.empty() : tensor<64x128xf32>
-    // CHECK: %[[C:.*]] = "ttnn.cbrt"[[C:.*]]
     %1 = "ttir.cbrt"(%arg0, %0) <{operandSegmentSizes = array<i32: 1, 1>}> : (tensor<64x128xf32>, tensor<64x128xf32>) -> tensor<64x128xf32>
+    // CHECK: "ttnn.cbrt"
+    // CHECK-SAME: tensor<64x128xf32
+    // CHECK-SAME: -> tensor<64x128xf32
     return %1 : tensor<64x128xf32>
   }
 }
diff --git a/test/ttmlir/Dialect/TTNN/eltwise/unary/ceil/simple_ceil.mlir b/test/ttmlir/Dialect/TTNN/eltwise/unary/ceil/simple_ceil.mlir
index d0250d5cd8..46f4677d76 100644
--- a/test/ttmlir/Dialect/TTNN/eltwise/unary/ceil/simple_ceil.mlir
+++ b/test/ttmlir/Dialect/TTNN/eltwise/unary/ceil/simple_ceil.mlir
@@ -1,10 +1,11 @@
 // RUN: ttmlir-opt --ttir-to-ttnn-backend-pipeline %s | FileCheck %s
 module attributes {} {
   func.func @forward(%arg0: tensor<64x128xf32>) -> tensor<64x128xf32> {
-    // CHECK: %[[C:.*]] = "ttnn.empty"[[C:.*]]
     %0 = tensor.empty() : tensor<64x128xf32>
-    // CHECK: %[[C:.*]] = "ttnn.ceil"[[C:.*]]
     %1 = "ttir.ceil"(%arg0, %0) <{operandSegmentSizes = array<i32: 1, 1>}> : (tensor<64x128xf32>, tensor<64x128xf32>) -> tensor<64x128xf32>
+    // CHECK: "ttnn.ceil"
+    // CHECK-SAME: tensor<64x128xf32
+    // CHECK-SAME: -> tensor<64x128xf32
     return %1 : tensor<64x128xf32>
   }
 }
diff --git a/test/ttmlir/Dialect/TTNN/eltwise/unary/cos/simple_cos.mlir b/test/ttmlir/Dialect/TTNN/eltwise/unary/cos/simple_cos.mlir
index e990aa59c1..4d652d21aa 100644
--- a/test/ttmlir/Dialect/TTNN/eltwise/unary/cos/simple_cos.mlir
+++ b/test/ttmlir/Dialect/TTNN/eltwise/unary/cos/simple_cos.mlir
@@ -1,10 +1,11 @@
 // RUN: ttmlir-opt --ttir-to-ttnn-backend-pipeline %s | FileCheck %s
 module attributes {} {
   func.func @forward(%arg0: tensor<64x128xf32>) -> tensor<64x128xf32> {
-    // CHECK: %[[C:.*]] = "ttnn.empty"[[C:.*]]
     %0 = tensor.empty() : tensor<64x128xf32>
-    // CHECK: %[[C:.*]] = "ttnn.cos"[[C:.*]]
     %1 = "ttir.cos"(%arg0, %0) <{operandSegmentSizes = array<i32: 1, 1>}> : (tensor<64x128xf32>, tensor<64x128xf32>) -> tensor<64x128xf32>
+    // CHECK: "ttnn.cos"
+    // CHECK-SAME: tensor<64x128xf32
+    // CHECK-SAME: -> tensor<64x128xf32
     return %1 : tensor<64x128xf32>
   }
 }
diff --git a/test/ttmlir/Dialect/TTNN/eltwise/unary/expm1/simple_expm1.mlir b/test/ttmlir/Dialect/TTNN/eltwise/unary/expm1/simple_expm1.mlir
index a8228fe9c0..faaec5bc7f 100644
--- a/test/ttmlir/Dialect/TTNN/eltwise/unary/expm1/simple_expm1.mlir
+++ b/test/ttmlir/Dialect/TTNN/eltwise/unary/expm1/simple_expm1.mlir
@@ -2,10 +2,10 @@
 module attributes {} {
   func.func @forward(%arg0: tensor<64x128xf32>) -> tensor<64x128xf32> {
     %0 = tensor.empty() : tensor<64x128xf32>
-    // CHECK: [[VAL0:%[0-9]+]] = "ttnn.empty"(%{{[0-9]+}}) <{dtype = {{.*}}, layout = {{.*}}, memory_config = {{.*}}, <{{.*}}>>, shape = #ttnn.shape<[[TENSOR_SHAPE:[0-9]+x[0-9]+]]>}>
     %1 = "ttir.expm1"(%arg0, %0) <{operandSegmentSizes = array<i32: 1, 1>}> : (tensor<64x128xf32>, tensor<64x128xf32>) -> tensor<64x128xf32>
-    // CHECK: %{{[0-9]+}} = "ttnn.expm1"(%arg0, [[VAL0]]) <{operandSegmentSizes = array<i32: 1, 1>}> : (tensor<[[TENSOR_SHAPE]]x{{.*}}, {{.*}}>, tensor<[[TENSOR_SHAPE]]x{{.*}}, {{.*}}) -> tensor<[[TENSOR_SHAPE]]x{{.*}}, {{.*}}>
+    // CHECK:"ttnn.expm1"
+    // CHECK-SAME: tensor<64x128xf32
+    // CHECK-SAME: -> tensor<64x128xf32
     return %1 : tensor<64x128xf32>
-    // CHECK: return %{{[0-9]+}} : tensor<[[TENSOR_SHAPE]]xf32, {{.*}}>
   }
 }
diff --git a/test/ttmlir/Dialect/TTNN/eltwise/unary/floor/simple_floor.mlir b/test/ttmlir/Dialect/TTNN/eltwise/unary/floor/simple_floor.mlir
index fd418fbda5..842277ad4c 100644
--- a/test/ttmlir/Dialect/TTNN/eltwise/unary/floor/simple_floor.mlir
+++ b/test/ttmlir/Dialect/TTNN/eltwise/unary/floor/simple_floor.mlir
@@ -1,14 +1,11 @@
 // RUN: ttmlir-opt --ttir-to-ttnn-backend-pipeline %s | FileCheck %s
 module attributes {} {
   func.func @floor(%arg0: tensor<64x128xf32>) -> tensor<64x128xf32> {
-    // CHECK: %{{[0-9]+}} = "ttnn.empty"
-    // CHECK-SAME: [[TENSOR:tensor<64x128xf32,]]
     %0 = tensor.empty() : tensor<64x128xf32>
-    // CHECK: %{{[0-9]+}} = "ttnn.floor"
-    // CHECK-SAME: [[TENSOR]]
-    // CHECK-SAME: [[TENSOR]]
-    // CHECK-SAME: -> [[TENSOR]]
     %1 = "ttir.floor"(%arg0, %0) <{operandSegmentSizes = array<i32: 1, 1>}> : (tensor<64x128xf32>, tensor<64x128xf32>) -> tensor<64x128xf32>
+    // CHECK: "ttnn.floor"
+    // CHECK-SAME: tensor<64x128xf32
+    // CHECK-SAME: -> tensor<64x128xf32
     return %1 : tensor<64x128xf32>
   }
 }
diff --git a/test/ttmlir/Dialect/TTNN/eltwise/unary/gelu/simple_gelu.mlir b/test/ttmlir/Dialect/TTNN/eltwise/unary/gelu/simple_gelu.mlir
index 1cec49a356..5f429016e6 100644
--- a/test/ttmlir/Dialect/TTNN/eltwise/unary/gelu/simple_gelu.mlir
+++ b/test/ttmlir/Dialect/TTNN/eltwise/unary/gelu/simple_gelu.mlir
@@ -1,14 +1,11 @@
 // RUN: ttmlir-opt --ttir-to-ttnn-backend-pipeline %s | FileCheck %s
 module attributes {} {
   func.func @forward(%arg0: tensor<64x128xf32>) -> tensor<64x128xf32> {
-  // CHECK: "ttnn.empty"
-  // CHECK-SAME: tensor<64x128xf32,
   %0 = tensor.empty() : tensor<64x128xf32>
-  // CHECK: "ttnn.gelu"
-  // CHECK-SAME: tensor<64x128xf32,
-  // CHECK-SAME: tensor<64x128xf32,
-  // CHECK-SAME: tensor<64x128xf32,
     %1 = "ttir.gelu"(%arg0, %0) <{operandSegmentSizes = array<i32: 1, 1>}> : (tensor<64x128xf32>, tensor<64x128xf32>) -> tensor<64x128xf32>
+    // CHECK: "ttnn.gelu"
+    // CHECK-SAME: tensor<64x128xf32
+    // CHECK-SAME: -> tensor<64x128xf32
     return %1 : tensor<64x128xf32>
   }
 }
diff --git a/test/ttmlir/Dialect/TTNN/eltwise/unary/isfinite/simple_isfinite.mlir b/test/ttmlir/Dialect/TTNN/eltwise/unary/isfinite/simple_isfinite.mlir
index 7745adf067..4e93126e1e 100644
--- a/test/ttmlir/Dialect/TTNN/eltwise/unary/isfinite/simple_isfinite.mlir
+++ b/test/ttmlir/Dialect/TTNN/eltwise/unary/isfinite/simple_isfinite.mlir
@@ -1,14 +1,11 @@
 // RUN: ttmlir-opt --ttir-to-ttnn-backend-pipeline %s | FileCheck %s
 module attributes {} {
   func.func @is_finite(%arg0: tensor<64x128xbf16>) -> tensor<64x128xbf16> {
-    // CHECK: %[[C:.*]] = "ttnn.empty"
-    // CHECK-SAME: [[TENSOR:tensor<64x128xbf16,]]
     %0 = tensor.empty() : tensor<64x128xbf16>
-    // CHECK: %[[C:.*]] = "ttnn.isfinite"
-    // CHECK-SAME: tensor<64x128xbf16,
-    // CHECK-SAME: [[TENSOR]]
-    // CHECK-SAME: -> [[TENSOR]]
     %1 = "ttir.isfinite"(%arg0, %0) <{operandSegmentSizes = array<i32: 1, 1>}> : (tensor<64x128xbf16>, tensor<64x128xbf16>) -> tensor<64x128xbf16>
+    // CHECK: "ttnn.isfinite"
+    // CHECK-SAME: tensor<64x128xbf16
+    // CHECK-SAME: -> tensor<64x128xbf16
     return %1 : tensor<64x128xbf16>
   }
 }
diff --git a/test/ttmlir/Dialect/TTNN/eltwise/unary/leaky_relu/simple_leaky_relu.mlir b/test/ttmlir/Dialect/TTNN/eltwise/unary/leaky_relu/simple_leaky_relu.mlir
index 93dbb03f0f..78555ed49e 100644
--- a/test/ttmlir/Dialect/TTNN/eltwise/unary/leaky_relu/simple_leaky_relu.mlir
+++ b/test/ttmlir/Dialect/TTNN/eltwise/unary/leaky_relu/simple_leaky_relu.mlir
@@ -1,14 +1,11 @@
 // RUN: ttmlir-opt --ttir-to-ttnn-backend-pipeline %s | FileCheck %s
 module attributes {} {
   func.func @leaky_relu(%arg0: tensor<64x128xf32>) -> tensor<64x128xf32> {
-    // CHECK: %[[C:.*]] = "ttnn.empty"
-    // CHECK-SAME: [[TENSOR:tensor<64x128xf32,]]
     %0 = tensor.empty() : tensor<64x128xf32>
-    // CHECK: %[[C:.*]] = "ttnn.leaky_relu"
-    // CHECK-SAME: tensor<64x128xf32,
-    // CHECK-SAME: [[TENSOR]]
-    // CHECK-SAME: -> [[TENSOR]]
     %1 = "ttir.leaky_relu"(%arg0, %0) <{parameter = 0.01 : f32, operandSegmentSizes = array<i32: 1, 1>}> : (tensor<64x128xf32>, tensor<64x128xf32>) -> tensor<64x128xf32>
+    // CHECK: "ttnn.leaky_relu"
+    // CHECK-SAME: (tensor<64x128xf32
+    // CHECK-SAME: -> tensor<64x128xf32
     return %1 : tensor<64x128xf32>
   }
 }
diff --git a/test/ttmlir/Dialect/TTNN/eltwise/unary/log1p/simple_log1p.mlir b/test/ttmlir/Dialect/TTNN/eltwise/unary/log1p/simple_log1p.mlir
index 7d6ca51f3a..25e72c1b4f 100644
--- a/test/ttmlir/Dialect/TTNN/eltwise/unary/log1p/simple_log1p.mlir
+++ b/test/ttmlir/Dialect/TTNN/eltwise/unary/log1p/simple_log1p.mlir
@@ -2,10 +2,10 @@
 module attributes {} {
   func.func @forward(%arg0: tensor<64x128xf32>) -> tensor<64x128xf32> {
     %0 = tensor.empty() : tensor<64x128xf32>
-    // CHECK: [[VAL0:%[0-9]+]] = "ttnn.empty"(%{{[0-9]+}}) <{dtype = {{.*}}, layout = {{.*}}, memory_config = {{.*}}, <{{.*}}>>, shape = #ttnn.shape<[[TENSOR_SHAPE:[0-9]+x[0-9]+]]>}>
     %1 = "ttir.log1p"(%arg0, %0) <{operandSegmentSizes = array<i32: 1, 1>}> : (tensor<64x128xf32>, tensor<64x128xf32>) -> tensor<64x128xf32>
-    // CHECK: %{{[0-9]+}} = "ttnn.log1p"(%arg0, [[VAL0]]) <{operandSegmentSizes = array<i32: 1, 1>}> : (tensor<[[TENSOR_SHAPE]]x{{.*}}, {{.*}}>, tensor<[[TENSOR_SHAPE]]x{{.*}}, {{.*}}) -> tensor<[[TENSOR_SHAPE]]x{{.*}}, {{.*}}>
+    // CHECK: "ttnn.log1p"
+    // CHECK-SAME: tensor<64x128xf32
+    // CHECK-SAME: -> tensor<64x128xf32
     return %1 : tensor<64x128xf32>
-    // CHECK: return %{{[0-9]+}} : tensor<[[TENSOR_SHAPE]]xf32, {{.*}}>
   }
 }
diff --git a/test/ttmlir/Dialect/TTNN/eltwise/unary/logical_not/simple_not.mlir b/test/ttmlir/Dialect/TTNN/eltwise/unary/logical_not/simple_not.mlir
index a80dffca88..d48ee5f659 100644
--- a/test/ttmlir/Dialect/TTNN/eltwise/unary/logical_not/simple_not.mlir
+++ b/test/ttmlir/Dialect/TTNN/eltwise/unary/logical_not/simple_not.mlir
@@ -2,11 +2,10 @@
 module attributes {} {
   func.func @logical_not(%arg0: tensor<64x128xf32>) -> tensor<64x128xf32> {
     %0 = tensor.empty() : tensor<64x128xf32>
-    // CHECK: {{.*}} = "ttnn.empty"{{.*}}
     %1 = "ttir.logical_not"(%arg0, %0) <{operandSegmentSizes = array<i32: 1, 1>}> : (tensor<64x128xf32>, tensor<64x128xf32>) -> tensor<64x128xf32>
-    // CHECK: %[[C:.*]] = "ttnn.logical_not"
-    // CHECK-SAME: tensor<64x128xf32,
-    // CHECK-SAME: tensor<64x128xf32,
+    // CHECK: "ttnn.logical_not"
+    // CHECK-SAME: tensor<64x128xf32
+    // CHECK-SAME: -> tensor<64x128xf32
     return %1 : tensor<64x128xf32>
   }
 }
diff --git a/test/ttmlir/Dialect/TTNN/eltwise/unary/negate/simple_neg.mlir b/test/ttmlir/Dialect/TTNN/eltwise/unary/negate/simple_neg.mlir
index aa63ee6e52..bafe10faaf 100644
--- a/test/ttmlir/Dialect/TTNN/eltwise/unary/negate/simple_neg.mlir
+++ b/test/ttmlir/Dialect/TTNN/eltwise/unary/negate/simple_neg.mlir
@@ -1,10 +1,11 @@
 // RUN: ttmlir-opt --ttir-to-ttnn-backend-pipeline %s | FileCheck %s
 module attributes {} {
   func.func @forward(%arg0: tensor<64x128xf32>) -> tensor<64x128xf32> {
-    // CHECK: %[[C:.*]] = "ttnn.empty"[[C:.*]]
     %0 = tensor.empty() : tensor<64x128xf32>
-    // CHECK: %[[C:.*]] = "ttnn.neg"[[C:.*]]
     %1 = "ttir.neg"(%arg0, %0) <{operandSegmentSizes = array<i32: 1, 1>}> : (tensor<64x128xf32>, tensor<64x128xf32>) -> tensor<64x128xf32>
+    // CHECK: "ttnn.neg"
+    // CHECK-SAME: tensor<64x128xf32
+    // CHECK-SAME: -> tensor<64x128xf32
     return %1 : tensor<64x128xf32>
   }
 }
diff --git a/test/ttmlir/Dialect/TTNN/eltwise/unary/reciprocal/simple_reciprocal.mlir b/test/ttmlir/Dialect/TTNN/eltwise/unary/reciprocal/simple_reciprocal.mlir
index fd98ade3ef..132963829f 100644
--- a/test/ttmlir/Dialect/TTNN/eltwise/unary/reciprocal/simple_reciprocal.mlir
+++ b/test/ttmlir/Dialect/TTNN/eltwise/unary/reciprocal/simple_reciprocal.mlir
@@ -1,10 +1,11 @@
 // RUN: ttmlir-opt --ttir-to-ttnn-backend-pipeline %s | FileCheck %s
 module attributes {} {
   func.func @forward(%arg0: tensor<64x128xf32>) -> tensor<64x128xf32> {
-    // CHECK: %[[C:.*]] = "ttnn.empty"[[C:.*]]
     %0 = tensor.empty() : tensor<64x128xf32>
-    // CHECK: %[[C:.*]] = "ttnn.reciprocal"[[C:.*]]
     %1 = "ttir.reciprocal"(%arg0, %0) <{operandSegmentSizes = array<i32: 1, 1>}> : (tensor<64x128xf32>, tensor<64x128xf32>) -> tensor<64x128xf32>
+    // CHECK: "ttnn.reciprocal"
+    // CHECK-SAME: (tensor<64x128xf32
+    // CHECK-SAME: -> tensor<64x128xf32
     return %1 : tensor<64x128xf32>
   }
 }
diff --git a/test/ttmlir/Dialect/TTNN/eltwise/unary/relu/simple_relu.mlir b/test/ttmlir/Dialect/TTNN/eltwise/unary/relu/simple_relu.mlir
index 7666df7a1c..72e4d3605b 100644
--- a/test/ttmlir/Dialect/TTNN/eltwise/unary/relu/simple_relu.mlir
+++ b/test/ttmlir/Dialect/TTNN/eltwise/unary/relu/simple_relu.mlir
@@ -1,10 +1,11 @@
 // RUN: ttmlir-opt --ttir-to-ttnn-backend-pipeline %s | FileCheck %s
 module attributes {} {
   func.func @forward(%arg0: tensor<64x128xf32>) -> tensor<64x128xf32> {
-    // CHECK: "ttnn.empty"
     %0 = tensor.empty() : tensor<64x128xf32>
-    // CHECK: "ttnn.relu"
     %1 = "ttir.relu"(%arg0, %0) <{operandSegmentSizes = array<i32: 1, 1>}> : (tensor<64x128xf32>, tensor<64x128xf32>) -> tensor<64x128xf32>
+    // CHECK: "ttnn.relu"
+    // CHECK-SAME: (tensor<64x128xf32
+    // CHECK-SAME: -> tensor<64x128xf32
     return %1 : tensor<64x128xf32>
   }
 }
diff --git a/test/ttmlir/Dialect/TTNN/eltwise/unary/rsqrt/simple_rsqrt.mlir b/test/ttmlir/Dialect/TTNN/eltwise/unary/rsqrt/simple_rsqrt.mlir
index b7a339d229..89a2b0e6d5 100644
--- a/test/ttmlir/Dialect/TTNN/eltwise/unary/rsqrt/simple_rsqrt.mlir
+++ b/test/ttmlir/Dialect/TTNN/eltwise/unary/rsqrt/simple_rsqrt.mlir
@@ -1,10 +1,11 @@
 // RUN: ttmlir-opt --ttir-to-ttnn-backend-pipeline %s | FileCheck %s
 module attributes {} {
   func.func @forward(%arg0: tensor<64x128xf32>) -> tensor<64x128xf32> {
-    // CHECK: %[[C:.*]] = "ttnn.empty"[[C:.*]]
     %0 = tensor.empty() : tensor<64x128xf32>
-    // CHECK: %[[C:.*]] = "ttnn.rsqrt"[[C:.*]]
     %1 = "ttir.rsqrt"(%arg0, %0) <{operandSegmentSizes = array<i32: 1, 1>}> : (tensor<64x128xf32>, tensor<64x128xf32>) -> tensor<64x128xf32>
+    // CHECK: "ttnn.rsqrt"
+    // CHECK-SAME: tensor<64x128xf32
+    // CHECK-SAME: -> tensor<64x128xf32
     return %1 : tensor<64x128xf32>
   }
 }
diff --git a/test/ttmlir/Dialect/TTNN/eltwise/unary/sigmoid/simple_sigmoid.mlir b/test/ttmlir/Dialect/TTNN/eltwise/unary/sigmoid/simple_sigmoid.mlir
index d3762db91b..a7520dd2e1 100644
--- a/test/ttmlir/Dialect/TTNN/eltwise/unary/sigmoid/simple_sigmoid.mlir
+++ b/test/ttmlir/Dialect/TTNN/eltwise/unary/sigmoid/simple_sigmoid.mlir
@@ -1,10 +1,11 @@
 // RUN: ttmlir-opt --ttir-to-ttnn-backend-pipeline %s | FileCheck %s
 module attributes {} {
   func.func @forward(%arg0: tensor<64x128xf32>) -> tensor<64x128xf32> {
-    // CHECK: %[[C:.*]] = "ttnn.empty"[[C:.*]]
     %0 = tensor.empty() : tensor<64x128xf32>
-    // CHECK: %[[C:.*]] = "ttnn.sigmoid"[[C:.*]]
     %1 = "ttir.sigmoid"(%arg0, %0) <{operandSegmentSizes = array<i32: 1, 1>}> : (tensor<64x128xf32>, tensor<64x128xf32>) -> tensor<64x128xf32>
+    // CHECK: "ttnn.sigmoid"
+    // CHECK-SAME: tensor<64x128xf32
+    // CHECK-SAME: -> tensor<64x128xf32
     return %1 : tensor<64x128xf32>
   }
 }
diff --git a/test/ttmlir/Dialect/TTNN/eltwise/unary/sign/simple_sign.mlir b/test/ttmlir/Dialect/TTNN/eltwise/unary/sign/simple_sign.mlir
index ccc3b82a84..1209bbf22e 100644
--- a/test/ttmlir/Dialect/TTNN/eltwise/unary/sign/simple_sign.mlir
+++ b/test/ttmlir/Dialect/TTNN/eltwise/unary/sign/simple_sign.mlir
@@ -2,10 +2,10 @@
 module attributes {} {
   func.func @forward(%arg0: tensor<64x128xf32>) -> tensor<64x128xf32> {
     %0 = tensor.empty() : tensor<64x128xf32>
-    // CHECK: [[VAL0:%[0-9]+]] = "ttnn.empty"(%{{[0-9]+}}) <{dtype = {{.*}}, layout = {{.*}}, memory_config = {{.*}}, <{{.*}}>>, shape = #ttnn.shape<[[TENSOR_SHAPE:[0-9]+x[0-9]+]]>}>
     %1 = "ttir.sign"(%arg0, %0) <{operandSegmentSizes = array<i32: 1, 1>}> : (tensor<64x128xf32>, tensor<64x128xf32>) -> tensor<64x128xf32>
-    // CHECK: %{{[0-9]+}} = "ttnn.sign"(%arg0, [[VAL0]]) <{operandSegmentSizes = array<i32: 1, 1>}> : (tensor<[[TENSOR_SHAPE]]x{{.*}}, {{.*}}>, tensor<[[TENSOR_SHAPE]]x{{.*}}, {{.*}}) -> tensor<[[TENSOR_SHAPE]]x{{.*}}, {{.*}}>
+    // CHECK: "ttnn.sign"
+    // CHECK-SAME: tensor<64x128xf32
+    // CHECK-SAME: -> tensor<64x128xf32
     return %1 : tensor<64x128xf32>
-    // CHECK: return %{{[0-9]+}} : tensor<[[TENSOR_SHAPE]]xf32, {{.*}}>
   }
 }
diff --git a/test/ttmlir/Dialect/TTNN/eltwise/unary/sin/simple_sin.mlir b/test/ttmlir/Dialect/TTNN/eltwise/unary/sin/simple_sin.mlir
index a1ebaa368b..a65f328676 100644
--- a/test/ttmlir/Dialect/TTNN/eltwise/unary/sin/simple_sin.mlir
+++ b/test/ttmlir/Dialect/TTNN/eltwise/unary/sin/simple_sin.mlir
@@ -1,10 +1,11 @@
 // RUN: ttmlir-opt --ttir-to-ttnn-backend-pipeline %s | FileCheck %s
 module attributes {} {
   func.func @forward(%arg0: tensor<64x128xf32>) -> tensor<64x128xf32> {
-    // CHECK: %[[C:.*]] = "ttnn.empty"[[C:.*]]
     %0 = tensor.empty() : tensor<64x128xf32>
-    // CHECK: %[[C:.*]] = "ttnn.sin"[[C:.*]]
     %1 = "ttir.sin"(%arg0, %0) <{operandSegmentSizes = array<i32: 1, 1>}> : (tensor<64x128xf32>, tensor<64x128xf32>) -> tensor<64x128xf32>
+    // CHECK: "ttnn.sin"
+    // CHECK-SAME: tensor<64x128xf32
+    // CHECK-SAME: -> tensor<64x128xf32
     return %1 : tensor<64x128xf32>
   }
 }
diff --git a/test/ttmlir/Dialect/TTNN/eltwise/unary/sqrt/simple_sqrt.mlir b/test/ttmlir/Dialect/TTNN/eltwise/unary/sqrt/simple_sqrt.mlir
index bd468bd8ee..bd5bcad78d 100644
--- a/test/ttmlir/Dialect/TTNN/eltwise/unary/sqrt/simple_sqrt.mlir
+++ b/test/ttmlir/Dialect/TTNN/eltwise/unary/sqrt/simple_sqrt.mlir
@@ -1,10 +1,11 @@
 // RUN: ttmlir-opt --ttir-to-ttnn-backend-pipeline %s | FileCheck %s
 module attributes {} {
   func.func @forward(%arg0: tensor<64x128xf32>) -> tensor<64x128xf32> {
-    // CHECK: %[[C:.*]] = "ttnn.empty"[[C:.*]]
     %0 = tensor.empty() : tensor<64x128xf32>
-    // CHECK: %[[C:.*]] = "ttnn.sqrt"[[C:.*]]
     %1 = "ttir.sqrt"(%arg0, %0) <{operandSegmentSizes = array<i32: 1, 1>}> : (tensor<64x128xf32>, tensor<64x128xf32>) -> tensor<64x128xf32>
+    // CHECK: "ttnn.sqrt"
+    // CHECK-SAME: tensor<64x128xf32
+    // CHECK-SAME: -> tensor<64x128xf32
     return %1 : tensor<64x128xf32>
   }
 }
diff --git a/test/ttmlir/Dialect/TTNN/eltwise/unary/tan/simple_tan.mlir b/test/ttmlir/Dialect/TTNN/eltwise/unary/tan/simple_tan.mlir
index 987d459aba..29279b22f2 100644
--- a/test/ttmlir/Dialect/TTNN/eltwise/unary/tan/simple_tan.mlir
+++ b/test/ttmlir/Dialect/TTNN/eltwise/unary/tan/simple_tan.mlir
@@ -2,10 +2,10 @@
 module attributes {} {
   func.func @forward(%arg0: tensor<64x128xf32>) -> tensor<64x128xf32> {
     %0 = tensor.empty() : tensor<64x128xf32>
-    // CHECK: [[VAL0:%[0-9]+]] = "ttnn.empty"(%{{[0-9]+}}) <{dtype = {{.*}}, layout = {{.*}}, memory_config = {{.*}}, <{{.*}}>>, shape = #ttnn.shape<[[TENSOR_SHAPE:[0-9]+x[0-9]+]]>}>
     %1 = "ttir.tan"(%arg0, %0) <{operandSegmentSizes = array<i32: 1, 1>}> : (tensor<64x128xf32>, tensor<64x128xf32>) -> tensor<64x128xf32>
-    // CHECK: %{{[0-9]+}} = "ttnn.tan"(%arg0, [[VAL0]]) <{operandSegmentSizes = array<i32: 1, 1>}> : (tensor<[[TENSOR_SHAPE]]x{{.*}}, {{.*}}>, tensor<[[TENSOR_SHAPE]]x{{.*}}, {{.*}}) -> tensor<[[TENSOR_SHAPE]]x{{.*}}, {{.*}}>
+    // CHECK: "ttnn.tan"
+    // CHECK-SAME: tensor<64x128xf32
+    // CHECK-SAME: -> tensor<64x128xf32
     return %1 : tensor<64x128xf32>
-    // CHECK: return %{{[0-9]+}} : tensor<[[TENSOR_SHAPE]]xf32, {{.*}}>
   }
 }
diff --git a/test/ttmlir/Dialect/TTNN/eltwise/unary/tanh/simple_tanh.mlir b/test/ttmlir/Dialect/TTNN/eltwise/unary/tanh/simple_tanh.mlir
index 62618ae829..720be63225 100644
--- a/test/ttmlir/Dialect/TTNN/eltwise/unary/tanh/simple_tanh.mlir
+++ b/test/ttmlir/Dialect/TTNN/eltwise/unary/tanh/simple_tanh.mlir
@@ -2,10 +2,10 @@
 module attributes {} {
   func.func @forward(%arg0: tensor<64x128xf32>) -> tensor<64x128xf32> {
     %0 = tensor.empty() : tensor<64x128xf32>
-    // CHECK: [[VAL0:%[0-9]+]] = "ttnn.empty"(%{{[0-9]+}}) <{dtype = {{.*}}, layout = {{.*}}, memory_config = {{.*}}, <{{.*}}>>, shape = #ttnn.shape<[[TENSOR_SHAPE:[0-9]+x[0-9]+]]>}>
     %1 = "ttir.tanh"(%arg0, %0) <{operandSegmentSizes = array<i32: 1, 1>}> : (tensor<64x128xf32>, tensor<64x128xf32>) -> tensor<64x128xf32>
-    // CHECK: %{{[0-9]+}} = "ttnn.tanh"(%arg0, [[VAL0]]) <{operandSegmentSizes = array<i32: 1, 1>}> : (tensor<[[TENSOR_SHAPE]]x{{.*}}, {{.*}}>, tensor<[[TENSOR_SHAPE]]x{{.*}}, {{.*}}) -> tensor<[[TENSOR_SHAPE]]x{{.*}}, {{.*}}>
+    // CHECK: "ttnn.tanh"
+    // CHECK-SAME: tensor<64x128xf32
+    // CHECK-SAME: -> tensor<64x128xf32
     return %1 : tensor<64x128xf32>
-    // CHECK: return %{{[0-9]+}} : tensor<[[TENSOR_SHAPE]]xf32, {{.*}}>
   }
 }
diff --git a/test/ttmlir/Dialect/TTNN/implicit_broadcast.mlir b/test/ttmlir/Dialect/TTNN/implicit_broadcast.mlir
index 5be11a6484..1fcabc2b73 100644
--- a/test/ttmlir/Dialect/TTNN/implicit_broadcast.mlir
+++ b/test/ttmlir/Dialect/TTNN/implicit_broadcast.mlir
@@ -37,8 +37,8 @@ module {
   func.func @main(%arg0: tensor<1x16x32xf32>, %arg1: tensor<1x1x32xf32>) -> tensor<1x16x32xf32> {
     // CHECK: [[VAL0:%[0-9]+]] = "ttnn.repeat"
     // CHECK-SAME: repeat_dims = #ttnn.shape<1x16x1>
-    // CHECK: %{{[0-9]+}} = "ttnn.multiply"(%arg0, %{{[0-9]+}}, %{{[0-9]+}})
-    // CHECK: %{{[0-9]+}} = "ttnn.bitwise_and"([[VAL0]], %{{[0-9]+}}, %{{[0-9]+}})
+    // CHECK: %{{[0-9]+}} = "ttnn.multiply"(%arg0, %{{[0-9]+}})
+    // CHECK: %{{[0-9]+}} = "ttnn.bitwise_and"([[VAL0]], %{{[0-9]+}})
     %0 = tensor.empty() : tensor<1x16x32xf32>
     %1 = "ttir.broadcast"(%arg1, %0) <{broadcast_dimensions = array<i64: 1, 16, 1>}> : (tensor<1x1x32xf32>, tensor<1x16x32xf32>) -> tensor<1x16x32xf32>
     %2 = tensor.empty() : tensor<1x16x32xf32>
@@ -53,7 +53,7 @@ module {
   func.func @main(%arg0: tensor<1x16x32xf32>, %arg1: tensor<1x1x32xf32>) -> tensor<1x16x32xf32> {
     // CHECK-NOT: ttnn.repeat
     // CHECK: [[VAL0:%[0-9]+]] = "ttnn.add"
-    // CHECK: %{{[0-9]+}} = "ttnn.add"(%arg1, [[VAL0]], %{{[0-9]+}})
+    // CHECK: %{{[0-9]+}} = "ttnn.add"(%arg1, [[VAL0]])
     %0 = tensor.empty() : tensor<1x16x32xf32>
     %1 = "ttir.broadcast"(%arg1, %0) <{broadcast_dimensions = array<i64: 1, 16, 1>}> : (tensor<1x1x32xf32>, tensor<1x16x32xf32>) -> tensor<1x16x32xf32>
     %2 = tensor.empty() : tensor<1x16x32xf32>
diff --git a/test/ttmlir/Dialect/TTNN/multiple_func.mlir b/test/ttmlir/Dialect/TTNN/multiple_func.mlir
index 3961fac038..006827b138 100644
--- a/test/ttmlir/Dialect/TTNN/multiple_func.mlir
+++ b/test/ttmlir/Dialect/TTNN/multiple_func.mlir
@@ -1,10 +1,12 @@
 // RUN: ttmlir-opt --ttir-to-ttnn-backend-pipeline %s | FileCheck %s
 module attributes {} {
   func.func @main(%arg0: tensor<64x128xf32>, %arg1: tensor<64x128xf32>) -> tensor<64x128xf32> {
-    // CHECK: %[[C:.*]] = "ttnn.empty"[[C:.*]]
     %0 = tensor.empty() : tensor<64x128xf32>
-    // CHECK: %[[C:.*]] = "ttnn.multiply"[[C:.*]]
     %1 = call @do_mult(%arg0, %arg1, %0) : (tensor<64x128xf32>, tensor<64x128xf32>, tensor<64x128xf32>) -> tensor<64x128xf32>
+    // CHECK: "ttnn.multiply"
+    // CHECK-SAME: tensor<64x128xf32
+    // CHECK-SAME: tensor<64x128xf32
+    // CHECK-SAME: -> tensor<64x128xf32
     return %1 : tensor<64x128xf32>
   }
 
diff --git a/test/ttmlir/Dialect/TTNN/optimizer/test_override_reshard_edges.mlir b/test/ttmlir/Dialect/TTNN/optimizer/test_override_reshard_edges.mlir
index 4a375fa6e3..e5e41bef16 100644
--- a/test/ttmlir/Dialect/TTNN/optimizer/test_override_reshard_edges.mlir
+++ b/test/ttmlir/Dialect/TTNN/optimizer/test_override_reshard_edges.mlir
@@ -12,17 +12,14 @@ module attributes {tt.device = #device} {
     %0 = "ttnn.get_device"() <{mesh_shape = #ttnn<mesh_shape 1x1>}> : () -> !tt.device<#device>
     %1 = "ttnn.to_layout"(%arg0, %0) <{dtype = #tt.supportedDataTypes<f32>, layout = #ttnn.layout<tile>, memory_config = #ttnn.memory_config<<dram>, <<32x32>>, <interleaved>>}> : (tensor<1x32x32xf32, #ttnn_layout>, !tt.device<#device>) -> tensor<1x32x32xf32, #ttnn_layout1>
     %2 = "ttnn.to_layout"(%arg1, %0) <{dtype = #tt.supportedDataTypes<f32>, layout = #ttnn.layout<tile>, memory_config = #ttnn.memory_config<<dram>, <<32x32>>, <interleaved>>}> : (tensor<1x32x32xf32, #ttnn_layout>, !tt.device<#device>) -> tensor<1x32x32xf32, #ttnn_layout1>
-    %3 = "ttnn.empty"(%0) <{dtype = #tt.supportedDataTypes<f32>, layout = #ttnn.layout<row_major>, memory_config = #ttnn.memory_config<<dram>, <<32x32>>, <interleaved>>, shape = #ttnn.shape<1x32x32>}> : (!tt.device<#device>) -> tensor<1x32x32xf32, #ttnn_layout1> loc(#loc1)
     // CHECK: %[[C:.*]] = "ttnn.add"{{.*}} -> tensor<1x32x32xf32, #[[LAYOUT_1]]>
-    %4 = "ttnn.add"(%1, %2, %3) <{operandSegmentSizes = array<i32: 2, 1>}> : (tensor<1x32x32xf32, #ttnn_layout1>, tensor<1x32x32xf32, #ttnn_layout1>, tensor<1x32x32xf32, #ttnn_layout1>) -> tensor<1x32x32xf32, #ttnn_layout1> loc(#loc1)
-    %5 = "ttnn.to_layout"(%arg0, %0) <{dtype = #tt.supportedDataTypes<f32>, layout = #ttnn.layout<tile>, memory_config = #ttnn.memory_config<<dram>, <<32x32>>, <interleaved>>}> : (tensor<1x32x32xf32, #ttnn_layout>, !tt.device<#device>) -> tensor<1x32x32xf32, #ttnn_layout1>
-    %6 = "ttnn.empty"(%0) <{dtype = #tt.supportedDataTypes<f32>, layout = #ttnn.layout<row_major>, memory_config = #ttnn.memory_config<<dram>, <<32x32>>, <interleaved>>, shape = #ttnn.shape<1x32x32>}> : (!tt.device<#device>) -> tensor<1x32x32xf32, #ttnn_layout1> loc(#loc2)
+    %3 = "ttnn.add"(%1, %2) : (tensor<1x32x32xf32, #ttnn_layout1>, tensor<1x32x32xf32, #ttnn_layout1>) -> tensor<1x32x32xf32, #ttnn_layout1> loc(#loc1)
+    %4 = "ttnn.to_layout"(%arg0, %0) <{dtype = #tt.supportedDataTypes<f32>, layout = #ttnn.layout<tile>, memory_config = #ttnn.memory_config<<dram>, <<32x32>>, <interleaved>>}> : (tensor<1x32x32xf32, #ttnn_layout>, !tt.device<#device>) -> tensor<1x32x32xf32, #ttnn_layout1>
     // CHECK: %{{.*}} = "ttnn.to_layout"(%[[C]], %0) {{.*}} -> tensor<1x32x32xf32, #[[LAYOUT_2]]>
-    %7 = "ttnn.add"(%4, %6, %6) <{operandSegmentSizes = array<i32: 2, 1>}> : (tensor<1x32x32xf32, #ttnn_layout1>, tensor<1x32x32xf32, #ttnn_layout1>, tensor<1x32x32xf32, #ttnn_layout1>) -> tensor<1x32x32xf32, #ttnn_layout1> loc(#loc2)
-    %8 = "ttnn.empty"(%0) <{dtype = #tt.supportedDataTypes<f32>, layout = #ttnn.layout<row_major>, memory_config = #ttnn.memory_config<<dram>, <<32x32>>, <interleaved>>, shape = #ttnn.shape<1x32x32>}> : (!tt.device<#device>) -> tensor<1x32x32xf32, #ttnn_layout1> loc(#loc3)
-    %9 = "ttnn.relu"(%7, %8) <{operandSegmentSizes = array<i32: 1, 1>}> : (tensor<1x32x32xf32, #ttnn_layout1>, tensor<1x32x32xf32, #ttnn_layout1>) -> tensor<1x32x32xf32, #ttnn_layout1> loc(#loc3)
-    %10 = "ttnn.to_layout"(%9) <{dtype = #tt.supportedDataTypes<f32>, layout = #ttnn.layout<row_major>, memory_config = #ttnn.memory_config<<system_memory>, <<32x32>>>}> : (tensor<1x32x32xf32, #ttnn_layout1>) -> tensor<1x32x32xf32, #ttnn_layout>
-    return %10 : tensor<1x32x32xf32, #ttnn_layout>
+    %5 = "ttnn.add"(%3, %3) : (tensor<1x32x32xf32, #ttnn_layout1>, tensor<1x32x32xf32, #ttnn_layout1>) -> tensor<1x32x32xf32, #ttnn_layout1> loc(#loc2)
+    %6 = "ttnn.relu"(%5) : (tensor<1x32x32xf32, #ttnn_layout1>) -> tensor<1x32x32xf32, #ttnn_layout1> loc(#loc3)
+    %7 = "ttnn.to_layout"(%6) <{dtype = #tt.supportedDataTypes<f32>, layout = #ttnn.layout<row_major>, memory_config = #ttnn.memory_config<<system_memory>, <<32x32>>>}> : (tensor<1x32x32xf32, #ttnn_layout1>) -> tensor<1x32x32xf32, #ttnn_layout>
+    return %7 : tensor<1x32x32xf32, #ttnn_layout>
   }
 }
 #loc1 = loc("add_1_2")
diff --git a/test/ttmlir/Dialect/TTNN/optimizer/ttir_to_ttnn_pipeline.mlir b/test/ttmlir/Dialect/TTNN/optimizer/ttir_to_ttnn_pipeline.mlir
index 5d924a9195..03be014790 100644
--- a/test/ttmlir/Dialect/TTNN/optimizer/ttir_to_ttnn_pipeline.mlir
+++ b/test/ttmlir/Dialect/TTNN/optimizer/ttir_to_ttnn_pipeline.mlir
@@ -1,10 +1,9 @@
 // RUN: ttmlir-opt --ttir-to-ttnn-backend-pipeline="enable-optimizer=true" %s | FileCheck %s
 module attributes {} {
   func.func @forward(%arg0: tensor<64x128xf32>, %arg1: tensor<64x128xf32>) -> tensor<64x128xf32> {
-    // CHECK: %{{.*}} = "ttnn.empty"{{.*}}
     %0 = tensor.empty() : tensor<64x128xf32>
-    // CHECK: %{{.*}} = "ttnn.multiply"{{.*}}
     %1 = "ttir.multiply"(%arg0, %arg1, %0) <{operandSegmentSizes = array<i32: 2, 1>}> : (tensor<64x128xf32>, tensor<64x128xf32>, tensor<64x128xf32>) -> tensor<64x128xf32>
+    // CHECK: "ttnn.multiply"
     return %1 : tensor<64x128xf32>
   }
 }
diff --git a/test/ttmlir/Dialect/TTNN/simple_scatter.mlir b/test/ttmlir/Dialect/TTNN/simple_scatter.mlir
index 43c87b89a2..e72e41aa33 100644
--- a/test/ttmlir/Dialect/TTNN/simple_scatter.mlir
+++ b/test/ttmlir/Dialect/TTNN/simple_scatter.mlir
@@ -3,13 +3,12 @@ module attributes {} {
   func.func @forward(%arg0: tensor<1x3x320x320xf32>, %arg1: tensor<1x3x32x32xf32>) -> tensor<1x3x320x320xf32> {
     %0 = tensor.empty() : tensor<1x3x320x320xf32>
     %1 = tensor.empty() : tensor<1x1xi32>
-    // CHECK: [[VAL0:%[0-9]+]] = "ttnn.empty"(%{{[0-9]+}}) <{dtype = {{.*}}, layout = {{.*}}, memory_config = {{.*}}, shape = #ttnn.shape<[[TENSOR_SHAPE0:[0-9]+x[0-9]+x[0-9]+x[0-9]+]]>}> : (!tt.device<#device>) -> tensor<[[TENSOR_SHAPE1:[0-9]+x[0-9]+x[0-9]+x[0-9]+xf[0-9]+]], {{.*}}>
     %2 = "ttir.scatter"(%arg0, %1, %arg1, %0) <{index_vector_dim = 1 : i32, indices_are_sorted = false, input_batching_dims = array<i32>, inserted_window_dims = array<i32: 0>, scatter_dims_to_operand_dims = array<i32: 0>, scatter_indices_batching_dims = array<i32>, unique_indices = false, update_window_dims = array<i32: 1, 2, 3>}> ({
     ^bb0(%arg3: tensor<1xf32>, %arg4: tensor<1xf32>):
       "ttir.yield"(%arg4) : (tensor<1xf32>) -> ()
     }) : (tensor<1x3x320x320xf32>, tensor<1x1xi32>, tensor<1x3x32x32xf32>, tensor<1x3x320x320xf32>) -> tensor<1x3x320x320xf32>
-    // CHECK: %{{[0-9]+}} = "ttnn.scatter"(%arg1, %arg0, %1) <{operandSegmentSizes = array<i32: 2, 1>}> : (tensor<1x3x32x32xf32, {{.*}}>, tensor<[[TENSOR_SHAPE1]], {{.*}}>, tensor<[[TENSOR_SHAPE1]], {{.*}}>) -> tensor<[[TENSOR_SHAPE1]], {{.*}}>
+    // CHECK: %{{[0-9]+}} = "ttnn.scatter"(%arg1, %arg0) : (tensor<1x3x32x32xf32, {{.*}}>, tensor<1x3x320x320xf32, {{.*}}>) -> tensor<1x3x320x320xf32, {{.*}}>
     return %2 : tensor<1x3x320x320xf32>
-    // CHECK: return %{{[0-9]+}} : tensor<[[TENSOR_SHAPE1]], {{.*}}>
+    // CHECK: return %{{[0-9]+}} : tensor<1x3x320x320xf32, {{.*}}>
   }
 }
diff --git a/test/ttmlir/Dialect/TTNN/test_remove_dead_values_pass.mlir b/test/ttmlir/Dialect/TTNN/test_remove_dead_values_pass.mlir
index 632b1f59a0..67b21bc8bb 100644
--- a/test/ttmlir/Dialect/TTNN/test_remove_dead_values_pass.mlir
+++ b/test/ttmlir/Dialect/TTNN/test_remove_dead_values_pass.mlir
@@ -15,61 +15,51 @@ module attributes {tt.device = #device, tt.system_desc = #system_desc} {
     %3 = "ttnn.to_layout"(%arg1) <{layout = #ttnn.layout<tile>}> : (tensor<64x128xf32, #ttnn_layout>) -> tensor<64x128xf32, #ttnn_layout1>
     %4 = "ttnn.to_device"(%3, %0) <{memory_config = #ttnn.memory_config<#dram, <<2x4>>, <interleaved>>}> : (tensor<64x128xf32, #ttnn_layout1>, !tt.device<#device>) -> tensor<64x128xf32, #ttnn_layout1>
     "ttnn.deallocate"(%3) <{force = false}> : (tensor<64x128xf32, #ttnn_layout1>) -> ()
-    %5 = "ttnn.empty"(%0) <{dtype = #tt.supportedDataTypes<f32>, layout = #ttnn.layout<row_major>, memory_config = #ttnn.memory_config<#dram, <<64x128>>, <interleaved>>, shape = #ttnn.shape<64x128>}> : (!tt.device<#device>) -> tensor<64x128xf32, #ttnn_layout2>
-    // CHECK: %[[C:.*]] = "ttnn.multiply"[[C:.*]]
-    %6 = "ttnn.multiply"(%2, %4, %5) <{operandSegmentSizes = array<i32: 2, 1>}> : (tensor<64x128xf32, #ttnn_layout1>, tensor<64x128xf32, #ttnn_layout1>, tensor<64x128xf32, #ttnn_layout2>) -> tensor<64x128xf32, #ttnn_layout2>
+    // CHECK: "ttnn.multiply"
+    %5 = "ttnn.multiply"(%2, %4) : (tensor<64x128xf32, #ttnn_layout1>, tensor<64x128xf32, #ttnn_layout1>) -> tensor<64x128xf32, #ttnn_layout2>
     "ttnn.deallocate"(%4) <{force = false}> : (tensor<64x128xf32, #ttnn_layout1>) -> ()
     "ttnn.deallocate"(%2) <{force = false}> : (tensor<64x128xf32, #ttnn_layout1>) -> ()
-    %7 = "ttnn.to_layout"(%arg0) <{layout = #ttnn.layout<tile>}> : (tensor<64x128xf32, #ttnn_layout>) -> tensor<64x128xf32, #ttnn_layout1>
-    %8 = "ttnn.to_device"(%7, %0) <{memory_config = #ttnn.memory_config<#dram, <<2x4>>, <interleaved>>}> : (tensor<64x128xf32, #ttnn_layout1>, !tt.device<#device>) -> tensor<64x128xf32, #ttnn_layout1>
-    "ttnn.deallocate"(%7) <{force = false}> : (tensor<64x128xf32, #ttnn_layout1>) -> ()
-    %9 = "ttnn.to_layout"(%arg1) <{layout = #ttnn.layout<tile>}> : (tensor<64x128xf32, #ttnn_layout>) -> tensor<64x128xf32, #ttnn_layout1>
-    %10 = "ttnn.to_device"(%9, %0) <{memory_config = #ttnn.memory_config<#dram, <<2x4>>, <interleaved>>}> : (tensor<64x128xf32, #ttnn_layout1>, !tt.device<#device>) -> tensor<64x128xf32, #ttnn_layout1>
-    "ttnn.deallocate"(%9) <{force = false}> : (tensor<64x128xf32, #ttnn_layout1>) -> ()
-    %11 = "ttnn.empty"(%0) <{dtype = #tt.supportedDataTypes<f32>, layout = #ttnn.layout<row_major>, memory_config = #ttnn.memory_config<#dram, <<64x128>>, <interleaved>>, shape = #ttnn.shape<64x128>}> : (!tt.device<#device>) -> tensor<64x128xf32, #ttnn_layout2>
-    // CHECK-NOT: %[[C:.*]] = "ttnn.add"[[C:.*]]
-    %12 = "ttnn.add"(%8, %10, %11) <{operandSegmentSizes = array<i32: 2, 1>}> : (tensor<64x128xf32, #ttnn_layout1>, tensor<64x128xf32, #ttnn_layout1>, tensor<64x128xf32, #ttnn_layout2>) -> tensor<64x128xf32, #ttnn_layout2>
-    "ttnn.deallocate"(%11) <{force = false}> : (tensor<64x128xf32, #ttnn_layout2>) -> ()
-    "ttnn.deallocate"(%10) <{force = false}> : (tensor<64x128xf32, #ttnn_layout1>) -> ()
+    %6 = "ttnn.to_layout"(%arg0) <{layout = #ttnn.layout<tile>}> : (tensor<64x128xf32, #ttnn_layout>) -> tensor<64x128xf32, #ttnn_layout1>
+    %7 = "ttnn.to_device"(%6, %0) <{memory_config = #ttnn.memory_config<#dram, <<2x4>>, <interleaved>>}> : (tensor<64x128xf32, #ttnn_layout1>, !tt.device<#device>) -> tensor<64x128xf32, #ttnn_layout1>
+    "ttnn.deallocate"(%6) <{force = false}> : (tensor<64x128xf32, #ttnn_layout1>) -> ()
+    %8 = "ttnn.to_layout"(%arg1) <{layout = #ttnn.layout<tile>}> : (tensor<64x128xf32, #ttnn_layout>) -> tensor<64x128xf32, #ttnn_layout1>
+    %9 = "ttnn.to_device"(%8, %0) <{memory_config = #ttnn.memory_config<#dram, <<2x4>>, <interleaved>>}> : (tensor<64x128xf32, #ttnn_layout1>, !tt.device<#device>) -> tensor<64x128xf32, #ttnn_layout1>
     "ttnn.deallocate"(%8) <{force = false}> : (tensor<64x128xf32, #ttnn_layout1>) -> ()
-    %13 = "ttnn.to_layout"(%arg0) <{layout = #ttnn.layout<tile>}> : (tensor<64x128xf32, #ttnn_layout>) -> tensor<64x128xf32, #ttnn_layout1>
+    // CHECK-NOT: "ttnn.add"
+    %10 = "ttnn.add"(%7, %9) : (tensor<64x128xf32, #ttnn_layout1>, tensor<64x128xf32, #ttnn_layout1>) -> tensor<64x128xf32, #ttnn_layout2>
+    "ttnn.deallocate"(%9) <{force = false}> : (tensor<64x128xf32, #ttnn_layout1>) -> ()
+    "ttnn.deallocate"(%7) <{force = false}> : (tensor<64x128xf32, #ttnn_layout1>) -> ()
+    %11 = "ttnn.to_layout"(%arg0) <{layout = #ttnn.layout<tile>}> : (tensor<64x128xf32, #ttnn_layout>) -> tensor<64x128xf32, #ttnn_layout1>
+    %12 = "ttnn.to_device"(%11, %0) <{memory_config = #ttnn.memory_config<#dram, <<2x4>>, <interleaved>>}> : (tensor<64x128xf32, #ttnn_layout1>, !tt.device<#device>) -> tensor<64x128xf32, #ttnn_layout1>
+    "ttnn.deallocate"(%11) <{force = false}> : (tensor<64x128xf32, #ttnn_layout1>) -> ()
+    %13 = "ttnn.to_layout"(%arg1) <{layout = #ttnn.layout<tile>}> : (tensor<64x128xf32, #ttnn_layout>) -> tensor<64x128xf32, #ttnn_layout1>
     %14 = "ttnn.to_device"(%13, %0) <{memory_config = #ttnn.memory_config<#dram, <<2x4>>, <interleaved>>}> : (tensor<64x128xf32, #ttnn_layout1>, !tt.device<#device>) -> tensor<64x128xf32, #ttnn_layout1>
     "ttnn.deallocate"(%13) <{force = false}> : (tensor<64x128xf32, #ttnn_layout1>) -> ()
-    %15 = "ttnn.to_layout"(%arg1) <{layout = #ttnn.layout<tile>}> : (tensor<64x128xf32, #ttnn_layout>) -> tensor<64x128xf32, #ttnn_layout1>
-    %16 = "ttnn.to_device"(%15, %0) <{memory_config = #ttnn.memory_config<#dram, <<2x4>>, <interleaved>>}> : (tensor<64x128xf32, #ttnn_layout1>, !tt.device<#device>) -> tensor<64x128xf32, #ttnn_layout1>
-    "ttnn.deallocate"(%15) <{force = false}> : (tensor<64x128xf32, #ttnn_layout1>) -> ()
-    %17 = "ttnn.empty"(%0) <{dtype = #tt.supportedDataTypes<f32>, layout = #ttnn.layout<row_major>, memory_config = #ttnn.memory_config<#dram, <<64x128>>, <interleaved>>, shape = #ttnn.shape<64x128>}> : (!tt.device<#device>) -> tensor<64x128xf32, #ttnn_layout2>
-    // CHECK-NOT: %[[C:.*]] = "ttnn.subtract"[[C:.*]]
-    %18 = "ttnn.subtract"(%14, %16, %17) <{operandSegmentSizes = array<i32: 2, 1>}> : (tensor<64x128xf32, #ttnn_layout1>, tensor<64x128xf32, #ttnn_layout1>, tensor<64x128xf32, #ttnn_layout2>) -> tensor<64x128xf32, #ttnn_layout2>
-    "ttnn.deallocate"(%17) <{force = false}> : (tensor<64x128xf32, #ttnn_layout2>) -> ()
-    "ttnn.deallocate"(%16) <{force = false}> : (tensor<64x128xf32, #ttnn_layout1>) -> ()
+    // CHECK-NOT: "ttnn.subtract"
+    %15 = "ttnn.subtract"(%12, %14) : (tensor<64x128xf32, #ttnn_layout1>, tensor<64x128xf32, #ttnn_layout1>) -> tensor<64x128xf32, #ttnn_layout2>
     "ttnn.deallocate"(%14) <{force = false}> : (tensor<64x128xf32, #ttnn_layout1>) -> ()
-    %19 = "ttnn.to_layout"(%arg0) <{layout = #ttnn.layout<tile>}> : (tensor<64x128xf32, #ttnn_layout>) -> tensor<64x128xf32, #ttnn_layout1>
-    %20 = "ttnn.to_device"(%19, %0) <{memory_config = #ttnn.memory_config<#dram, <<2x4>>, <interleaved>>}> : (tensor<64x128xf32, #ttnn_layout1>, !tt.device<#device>) -> tensor<64x128xf32, #ttnn_layout1>
+    "ttnn.deallocate"(%12) <{force = false}> : (tensor<64x128xf32, #ttnn_layout1>) -> ()
+    %16 = "ttnn.to_layout"(%arg0) <{layout = #ttnn.layout<tile>}> : (tensor<64x128xf32, #ttnn_layout>) -> tensor<64x128xf32, #ttnn_layout1>
+    %17 = "ttnn.to_device"(%16, %0) <{memory_config = #ttnn.memory_config<#dram, <<2x4>>, <interleaved>>}> : (tensor<64x128xf32, #ttnn_layout1>, !tt.device<#device>) -> tensor<64x128xf32, #ttnn_layout1>
+    "ttnn.deallocate"(%16) <{force = false}> : (tensor<64x128xf32, #ttnn_layout1>) -> ()
+    %18 = "ttnn.to_layout"(%arg1) <{layout = #ttnn.layout<tile>}> : (tensor<64x128xf32, #ttnn_layout>) -> tensor<64x128xf32, #ttnn_layout1>
+    %19 = "ttnn.to_device"(%18, %0) <{memory_config = #ttnn.memory_config<#dram, <<2x4>>, <interleaved>>}> : (tensor<64x128xf32, #ttnn_layout1>, !tt.device<#device>) -> tensor<64x128xf32, #ttnn_layout1>
+    "ttnn.deallocate"(%18) <{force = false}> : (tensor<64x128xf32, #ttnn_layout1>) -> ()
+    // CHECK-NOT: "ttnn.div"
+    %20 = "ttnn.div"(%17, %19) : (tensor<64x128xf32, #ttnn_layout1>, tensor<64x128xf32, #ttnn_layout1>) -> tensor<64x128xf32, #ttnn_layout2>
     "ttnn.deallocate"(%19) <{force = false}> : (tensor<64x128xf32, #ttnn_layout1>) -> ()
-    %21 = "ttnn.to_layout"(%arg1) <{layout = #ttnn.layout<tile>}> : (tensor<64x128xf32, #ttnn_layout>) -> tensor<64x128xf32, #ttnn_layout1>
+    "ttnn.deallocate"(%17) <{force = false}> : (tensor<64x128xf32, #ttnn_layout1>) -> ()
+    %21 = "ttnn.to_layout"(%arg0) <{layout = #ttnn.layout<tile>}> : (tensor<64x128xf32, #ttnn_layout>) -> tensor<64x128xf32, #ttnn_layout1>
     %22 = "ttnn.to_device"(%21, %0) <{memory_config = #ttnn.memory_config<#dram, <<2x4>>, <interleaved>>}> : (tensor<64x128xf32, #ttnn_layout1>, !tt.device<#device>) -> tensor<64x128xf32, #ttnn_layout1>
     "ttnn.deallocate"(%21) <{force = false}> : (tensor<64x128xf32, #ttnn_layout1>) -> ()
-    %23 = "ttnn.empty"(%0) <{dtype = #tt.supportedDataTypes<f32>, layout = #ttnn.layout<row_major>, memory_config = #ttnn.memory_config<#dram, <<64x128>>, <interleaved>>, shape = #ttnn.shape<64x128>}> : (!tt.device<#device>) -> tensor<64x128xf32, #ttnn_layout2>
-    // CHECK-NOT: %[[C:.*]] = "ttnn.div"[[C:.*]]
-    %24 = "ttnn.div"(%20, %22, %23) <{operandSegmentSizes = array<i32: 2, 1>}> : (tensor<64x128xf32, #ttnn_layout1>, tensor<64x128xf32, #ttnn_layout1>, tensor<64x128xf32, #ttnn_layout2>) -> tensor<64x128xf32, #ttnn_layout2>
-    "ttnn.deallocate"(%23) <{force = false}> : (tensor<64x128xf32, #ttnn_layout2>) -> ()
+    %23 = "ttnn.to_layout"(%arg1) <{layout = #ttnn.layout<tile>}> : (tensor<64x128xf32, #ttnn_layout>) -> tensor<64x128xf32, #ttnn_layout1>
+    %24 = "ttnn.to_device"(%23, %0) <{memory_config = #ttnn.memory_config<#dram, <<2x4>>, <interleaved>>}> : (tensor<64x128xf32, #ttnn_layout1>, !tt.device<#device>) -> tensor<64x128xf32, #ttnn_layout1>
+    "ttnn.deallocate"(%23) <{force = false}> : (tensor<64x128xf32, #ttnn_layout1>) -> ()
+    // CHECK-NOT: "ttnn.eq"
+    %25 = "ttnn.eq"(%22, %24) : (tensor<64x128xf32, #ttnn_layout1>, tensor<64x128xf32, #ttnn_layout1>) -> tensor<64x128xf32, #ttnn_layout2>
+    "ttnn.deallocate"(%24) <{force = false}> : (tensor<64x128xf32, #ttnn_layout1>) -> ()
     "ttnn.deallocate"(%22) <{force = false}> : (tensor<64x128xf32, #ttnn_layout1>) -> ()
-    "ttnn.deallocate"(%20) <{force = false}> : (tensor<64x128xf32, #ttnn_layout1>) -> ()
-    %25 = "ttnn.to_layout"(%arg0) <{layout = #ttnn.layout<tile>}> : (tensor<64x128xf32, #ttnn_layout>) -> tensor<64x128xf32, #ttnn_layout1>
-    %26 = "ttnn.to_device"(%25, %0) <{memory_config = #ttnn.memory_config<#dram, <<2x4>>, <interleaved>>}> : (tensor<64x128xf32, #ttnn_layout1>, !tt.device<#device>) -> tensor<64x128xf32, #ttnn_layout1>
-    "ttnn.deallocate"(%25) <{force = false}> : (tensor<64x128xf32, #ttnn_layout1>) -> ()
-    %27 = "ttnn.to_layout"(%arg1) <{layout = #ttnn.layout<tile>}> : (tensor<64x128xf32, #ttnn_layout>) -> tensor<64x128xf32, #ttnn_layout1>
-    %28 = "ttnn.to_device"(%27, %0) <{memory_config = #ttnn.memory_config<#dram, <<2x4>>, <interleaved>>}> : (tensor<64x128xf32, #ttnn_layout1>, !tt.device<#device>) -> tensor<64x128xf32, #ttnn_layout1>
-    "ttnn.deallocate"(%27) <{force = false}> : (tensor<64x128xf32, #ttnn_layout1>) -> ()
-    %29 = "ttnn.empty"(%0) <{dtype = #tt.supportedDataTypes<f32>, layout = #ttnn.layout<row_major>, memory_config = #ttnn.memory_config<#dram, <<64x128>>, <interleaved>>, shape = #ttnn.shape<64x128>}> : (!tt.device<#device>) -> tensor<64x128xf32, #ttnn_layout2>
-    // CHECK-NOT: %[[C:.*]] = "ttnn.eq"[[C:.*]]
-    %30 = "ttnn.eq"(%26, %28, %29) <{operandSegmentSizes = array<i32: 2, 1>}> : (tensor<64x128xf32, #ttnn_layout1>, tensor<64x128xf32, #ttnn_layout1>, tensor<64x128xf32, #ttnn_layout2>) -> tensor<64x128xf32, #ttnn_layout2>
-    "ttnn.deallocate"(%29) <{force = false}> : (tensor<64x128xf32, #ttnn_layout2>) -> ()
-    "ttnn.deallocate"(%28) <{force = false}> : (tensor<64x128xf32, #ttnn_layout1>) -> ()
-    "ttnn.deallocate"(%26) <{force = false}> : (tensor<64x128xf32, #ttnn_layout1>) -> ()
-    %31 = "ttnn.from_device"(%6) : (tensor<64x128xf32, #ttnn_layout2>) -> tensor<64x128xf32, #ttnn_layout>
-    "ttnn.deallocate"(%5) <{force = false}> : (tensor<64x128xf32, #ttnn_layout2>) -> ()
-    return %31 : tensor<64x128xf32, #ttnn_layout>
+    %26 = "ttnn.from_device"(%5) : (tensor<64x128xf32, #ttnn_layout2>) -> tensor<64x128xf32, #ttnn_layout>
+    return %26 : tensor<64x128xf32, #ttnn_layout>
   }
 }
diff --git a/test/ttmlir/Dialect/TTNN/ttir_to_ttnn_pipeline_custom_opt.mlir b/test/ttmlir/Dialect/TTNN/ttir_to_ttnn_pipeline_custom_opt.mlir
index 63d263365c..0ebfa2625e 100644
--- a/test/ttmlir/Dialect/TTNN/ttir_to_ttnn_pipeline_custom_opt.mlir
+++ b/test/ttmlir/Dialect/TTNN/ttir_to_ttnn_pipeline_custom_opt.mlir
@@ -2,9 +2,8 @@
 module attributes {} {
   func.func @forward(%arg0: tensor<64x128xf32>, %arg1: tensor<64x128xf32>) -> tensor<64x128xf32> {
     // CHECK: #[[LAYOUT_1:.*]] = #ttnn.ttnn_layout<(d0, d1) -> (d0, d1), <1x1>, memref<2x4x!tt.tile<32x32, f32>, #dram>, <interleaved>>
-    // CHECK: %[[C:.*]] = "ttnn.empty"[[C:.*]]
     %0 = tensor.empty() : tensor<64x128xf32>
-    // CHECK: %[[C:.*]] = "ttnn.multiply"[[C:.*]] -> tensor<64x128xf32, #[[LAYOUT_1:.*]]>
+    // CHECK: %{{.*}} = "ttnn.multiply"{{.*}} -> tensor<64x128xf32, #[[LAYOUT_1:.*]]>
     %1 = "ttir.multiply"(%arg0, %arg1, %0) <{operandSegmentSizes = array<i32: 2, 1>}> : (tensor<64x128xf32>, tensor<64x128xf32>, tensor<64x128xf32>) -> tensor<64x128xf32>
     return %1 : tensor<64x128xf32>
   }
diff --git a/test/ttmlir/Dialect/TTNN/ttir_to_ttnn_pipeline_hoist_call.mlir b/test/ttmlir/Dialect/TTNN/ttir_to_ttnn_pipeline_hoist_call.mlir
index 0eeabfbf3a..ae704bc8bf 100644
--- a/test/ttmlir/Dialect/TTNN/ttir_to_ttnn_pipeline_hoist_call.mlir
+++ b/test/ttmlir/Dialect/TTNN/ttir_to_ttnn_pipeline_hoist_call.mlir
@@ -3,9 +3,8 @@ module attributes {} {
     // CHECK-DAG: #{{.*}} = #ttnn.ttnn_layout<(d0, d1) -> (d0, d1), <1x1>, memref<64x128xf32, #system_memory>>
     // CHECK-DAG: #{{.*}} = #ttnn.ttnn_layout<(d0, d1) -> (d0, d1), <1x1>, memref<2x4x!tt.tile<32x32, f32>, #dram>, <interleaved>>
   func.func @forward(%arg0: tensor<64x128xf32>, %arg1: tensor<64x128xf32>) -> tensor<64x128xf32> {
-    // CHECK: %{{.*}} = "ttnn.empty"(%{{.*}})
     %0 = tensor.empty() : tensor<64x128xf32>
-    // CHECK: %{{.*}} = "ttnn.multiply"(%{{.*}}, %{{.*}}, %{{.*}})
+    // CHECK: %{{.*}} = "ttnn.multiply"(%{{.*}}, %{{.*}})
     %1 = "ttir.multiply"(%arg0, %arg1, %0) <{operandSegmentSizes = array<i32: 2, 1>}> : (tensor<64x128xf32>, tensor<64x128xf32>, tensor<64x128xf32>) -> tensor<64x128xf32>
     // CHECK: %{{.*}} = "ttnn.ones"
     %2 = "ttir.ones"() <{shape = array<i32:64, 128>}> : () -> tensor<64x128xf32>
@@ -15,13 +14,12 @@ module attributes {} {
     // CHECK: %{{.*}} = "ttnn.zeros"
     %4 = "ttir.zeros"() <{shape = array<i32:64, 128>}> : () -> tensor<64x128xf32>
     %5 = call @hoisted_func_decl(%arg0, %3, %4) {ttir.hoisted_call} : (tensor<64x128xf32>, tensor<64x128xf32>, tensor<64x128xf32>) -> tensor<64x128xf32>
-    // CHECK: %{{.*}} = "ttnn.empty"(%{{.*}})
     %6 = tensor.empty() : tensor<64x128xf32>
     // CHECK: %{{.*}} = "ttnn.to_layout"(%{{.*}}) <{layout = #ttnn.layout<{{.*}}>}> : (tensor<[[DIMS:.*]], #{{.*}}>) -> tensor<[[DIMS]], #{{.*}}>
     // CHECK: %{{.*}} = "ttnn.to_device"(%{{.*}}, %{{.*}}) <{memory_config = {{.*}}}> : (tensor<[[DIMS:.*]], #{{.*}}>, !tt.device<#{{.*}}>) -> tensor<[[DIMS]], #{{.*}}>
     // CHECK: %{{.*}} = "ttnn.to_layout"(%{{.*}}) <{layout = #ttnn.layout<{{.*}}>}> : (tensor<[[DIMS:.*]], #{{.*}}>) -> tensor<[[DIMS]], #{{.*}}>
     // CHECK: %{{.*}} = "ttnn.to_device"(%{{.*}}, %{{.*}}) <{memory_config = {{.*}}}> : (tensor<[[DIMS:.*]], #{{.*}}>, !tt.device<#{{.*}}>) -> tensor<[[DIMS]], #{{.*}}>
-    // CHECK: %{{.*}} = "ttnn.multiply"(%{{.*}}, %{{.*}}, %{{.*}})
+    // CHECK: %{{.*}} = "ttnn.multiply"(%{{.*}}, %{{.*}})
     %7 = "ttir.multiply"(%3, %5, %6) <{operandSegmentSizes = array<i32: 2, 1>}> : (tensor<64x128xf32>, tensor<64x128xf32>, tensor<64x128xf32>) -> tensor<64x128xf32>
     return %7 : tensor<64x128xf32>
   }
diff --git a/test/ttmlir/EmitC/TTNN/eltwise_unary/cbrt.mlir b/test/ttmlir/EmitC/TTNN/eltwise_unary/cbrt.mlir
index 4ad4d1b5fb..052b8f921d 100644
--- a/test/ttmlir/EmitC/TTNN/eltwise_unary/cbrt.mlir
+++ b/test/ttmlir/EmitC/TTNN/eltwise_unary/cbrt.mlir
@@ -2,6 +2,9 @@
 // RUN: ttmlir-translate --ttnn-to-flatbuffer %t.mlir > %basename_t.ttnn
 // RUN: ttmlir-opt --ttnn-modify-signatures-for-dylib --convert-ttnn-to-emitc %t.mlir > %t2.mlir
 // RUN: ttmlir-translate --mlir-to-cpp %t2.mlir > %basename_t.cpp
+// UNSUPPORTED: true
+// There is an issue where this test fails when it is run as a part of the group of tests. It passes when run individually.
+// Related issue: https://github.com/tenstorrent/tt-mlir/issues/2261
 
 func.func @cbrt(%arg0: tensor<64x128xf32>) -> tensor<64x128xf32> {
   %0 = tensor.empty() : tensor<64x128xf32>
diff --git a/test/ttmlir/Silicon/StableHLO/n150/Binary/add_op.mlir b/test/ttmlir/Silicon/StableHLO/n150/Binary/add_op.mlir
index e6524689c5..1efbc30b8f 100644
--- a/test/ttmlir/Silicon/StableHLO/n150/Binary/add_op.mlir
+++ b/test/ttmlir/Silicon/StableHLO/n150/Binary/add_op.mlir
@@ -9,11 +9,9 @@
 module @jit_eltwise_add attributes {} {
   func.func public @test_add(%arg0: tensor<64x128xf32>, %arg1: tensor<64x128xf32>) -> tensor<64x128xf32> {
     // CHECK-LABEL: func.func public @test_add
-    // CHECK: ttnn.empty
     // CHECK: ttnn.add
     // CHECK-SAME: tensor<64x128xf32,
     // CHECK-SAME: tensor<64x128xf32,
-    // CHECK-SAME: tensor<64x128xf32,
     // CHECK-SAME: -> tensor<64x128xf32,
     %0 = stablehlo.add %arg0, %arg1 : tensor<64x128xf32>
     return %0 : tensor<64x128xf32>
diff --git a/test/ttmlir/Silicon/StableHLO/n150/Binary/compare_op.mlir b/test/ttmlir/Silicon/StableHLO/n150/Binary/compare_op.mlir
index 4ba35b125b..83e4b1527d 100644
--- a/test/ttmlir/Silicon/StableHLO/n150/Binary/compare_op.mlir
+++ b/test/ttmlir/Silicon/StableHLO/n150/Binary/compare_op.mlir
@@ -9,11 +9,9 @@
 module @jit_eltwise_compare attributes {} {
   func.func public @test_eq(%arg0: tensor<64x128xf32>, %arg1: tensor<64x128xf32>) -> tensor<64x128xi1> {
     // CHECK-LABEL: func.func public @test_eq
-    // CHECK: ttnn.empty
     // CHECK: ttnn.eq
     // CHECK-SAME: tensor<64x128xf32,
     // CHECK-SAME: tensor<64x128xf32,
-    // CHECK-SAME: tensor<64x128xbf16,
     // CHECK-SAME: -> tensor<64x128xbf16,
     %0 = stablehlo.compare  EQ, %arg0, %arg1 : (tensor<64x128xf32>, tensor<64x128xf32>) -> tensor<64x128xi1>
     return %0 : tensor<64x128xi1>
@@ -21,11 +19,9 @@ module @jit_eltwise_compare attributes {} {
 
   func.func public @test_ne(%arg0: tensor<64x128xf32>, %arg1: tensor<64x128xf32>) -> tensor<64x128xi1> {
     // CHECK-LABEL: func.func public @test_ne
-    // CHECK: ttnn.empty
     // CHECK: ttnn.ne
     // CHECK-SAME: tensor<64x128xf32,
     // CHECK-SAME: tensor<64x128xf32,
-    // CHECK-SAME: tensor<64x128xbf16,
     // CHECK-SAME: -> tensor<64x128xbf16,
     %0 = stablehlo.compare  NE, %arg0, %arg1 : (tensor<64x128xf32>, tensor<64x128xf32>) -> tensor<64x128xi1>
     return %0 : tensor<64x128xi1>
@@ -33,11 +29,9 @@ module @jit_eltwise_compare attributes {} {
 
   func.func public @test_ge(%arg0: tensor<64x128xf32>, %arg1: tensor<64x128xf32>) -> tensor<64x128xi1> {
     // CHECK-LABEL: func.func public @test_ge
-    // CHECK: ttnn.empty
     // CHECK: ttnn.ge
     // CHECK-SAME: tensor<64x128xf32,
     // CHECK-SAME: tensor<64x128xf32,
-    // CHECK-SAME: tensor<64x128xbf16,
     // CHECK-SAME: -> tensor<64x128xbf16,
     %0 = stablehlo.compare  GE, %arg0, %arg1 : (tensor<64x128xf32>, tensor<64x128xf32>) -> tensor<64x128xi1>
     return %0 : tensor<64x128xi1>
@@ -45,11 +39,9 @@ module @jit_eltwise_compare attributes {} {
 
   func.func public @test_gt(%arg0: tensor<64x128xf32>, %arg1: tensor<64x128xf32>) -> tensor<64x128xi1> {
     // CHECK-LABEL: func.func public @test_gt
-    // CHECK: ttnn.empty
     // CHECK: ttnn.gt
     // CHECK-SAME: tensor<64x128xf32,
     // CHECK-SAME: tensor<64x128xf32,
-    // CHECK-SAME: tensor<64x128xbf16,
     // CHECK-SAME: -> tensor<64x128xbf16,
     %0 = stablehlo.compare  GT, %arg0, %arg1 : (tensor<64x128xf32>, tensor<64x128xf32>) -> tensor<64x128xi1>
     return %0 : tensor<64x128xi1>
@@ -57,11 +49,9 @@ module @jit_eltwise_compare attributes {} {
 
   func.func public @test_le(%arg0: tensor<64x128xf32>, %arg1: tensor<64x128xf32>) -> tensor<64x128xi1> {
     // CHECK-LABEL: func.func public @test_le
-    // CHECK: ttnn.empty
     // CHECK: ttnn.le
     // CHECK-SAME: tensor<64x128xf32,
     // CHECK-SAME: tensor<64x128xf32,
-    // CHECK-SAME: tensor<64x128xbf16,
     // CHECK-SAME: -> tensor<64x128xbf16,
     %0 = stablehlo.compare  LE, %arg0, %arg1 : (tensor<64x128xf32>, tensor<64x128xf32>) -> tensor<64x128xi1>
     return %0 : tensor<64x128xi1>
@@ -69,11 +59,9 @@ module @jit_eltwise_compare attributes {} {
 
   func.func public @test_lt(%arg0: tensor<64x128xf32>, %arg1: tensor<64x128xf32>) -> tensor<64x128xi1> {
     // CHECK-LABEL: func.func public @test_lt
-    // CHECK: ttnn.empty
     // CHECK: ttnn.lt
     // CHECK-SAME: tensor<64x128xf32,
     // CHECK-SAME: tensor<64x128xf32,
-    // CHECK-SAME: tensor<64x128xbf16,
     // CHECK-SAME: -> tensor<64x128xbf16,
     %0 = stablehlo.compare  LT, %arg0, %arg1 : (tensor<64x128xf32>, tensor<64x128xf32>) -> tensor<64x128xi1>
     return %0 : tensor<64x128xi1>
diff --git a/test/ttmlir/Silicon/StableHLO/n150/Binary/divide_op.mlir b/test/ttmlir/Silicon/StableHLO/n150/Binary/divide_op.mlir
index 6d27885e69..a59add950d 100644
--- a/test/ttmlir/Silicon/StableHLO/n150/Binary/divide_op.mlir
+++ b/test/ttmlir/Silicon/StableHLO/n150/Binary/divide_op.mlir
@@ -9,11 +9,9 @@
 module @jit_eltwise_divice attributes {} {
   func.func public @test_divide(%arg0: tensor<64x128xf32>, %arg1: tensor<64x128xf32>) -> tensor<64x128xf32> {
     // CHECK-LABEL: func.func public @test_divide
-    // CHECK: ttnn.empty
     // CHECK: ttnn.div
     // CHECK-SAME: tensor<64x128xf32,
     // CHECK-SAME: tensor<64x128xf32,
-    // CHECK-SAME: tensor<64x128xf32,
     // CHECK-SAME: -> tensor<64x128xf32,
     %0 = stablehlo.divide %arg0, %arg1 : tensor<64x128xf32>
     return %0 : tensor<64x128xf32>
diff --git a/test/ttmlir/Silicon/StableHLO/n150/Binary/logical_op.mlir b/test/ttmlir/Silicon/StableHLO/n150/Binary/logical_op.mlir
index dcfc073f95..f625862c49 100644
--- a/test/ttmlir/Silicon/StableHLO/n150/Binary/logical_op.mlir
+++ b/test/ttmlir/Silicon/StableHLO/n150/Binary/logical_op.mlir
@@ -9,11 +9,9 @@
 module @jit_eltwise_compare attributes {} {
   func.func public @logical_and(%arg0: tensor<64x128xi1>, %arg1: tensor<64x128xi1>) -> tensor<64x128xi1> {
     // CHECK-LABEL: func.func public @logical_and
-    // CHECK: ttnn.empty
     // CHECK: ttnn.logical_and
     // CHECK-SAME: tensor<64x128xbf16,
     // CHECK-SAME: tensor<64x128xbf16,
-    // CHECK-SAME: tensor<64x128xbf16,
     // CHECK-SAME: -> tensor<64x128xbf16,
     %0 = stablehlo.and  %arg0, %arg1 : tensor<64x128xi1>
     return %0 : tensor<64x128xi1>
@@ -21,11 +19,9 @@ module @jit_eltwise_compare attributes {} {
 
   func.func public @logical_or(%arg0: tensor<64x128xi1>, %arg1: tensor<64x128xi1>) -> tensor<64x128xi1> {
     // CHECK-LABEL: func.func public @logical_or
-    // CHECK: ttnn.empty
     // CHECK: ttnn.logical_or
     // CHECK-SAME: tensor<64x128xbf16,
     // CHECK-SAME: tensor<64x128xbf16,
-    // CHECK-SAME: tensor<64x128xbf16,
     // CHECK-SAME: -> tensor<64x128xbf16,
     %0 = stablehlo.or  %arg0, %arg1 : tensor<64x128xi1>
     return %0 : tensor<64x128xi1>
@@ -33,11 +29,9 @@ module @jit_eltwise_compare attributes {} {
 
   func.func public @logical_xor(%arg0: tensor<64x128xi1>, %arg1: tensor<64x128xi1>) -> tensor<64x128xi1> {
     // CHECK-LABEL: func.func public @logical_xor
-    // CHECK: ttnn.empty
     // CHECK: ttnn.logical_xor
     // CHECK-SAME: tensor<64x128xbf16,
     // CHECK-SAME: tensor<64x128xbf16,
-    // CHECK-SAME: tensor<64x128xbf16,
     // CHECK-SAME: -> tensor<64x128xbf16,
     %0 = stablehlo.xor  %arg0, %arg1 : tensor<64x128xi1>
     return %0 : tensor<64x128xi1>
diff --git a/test/ttmlir/Silicon/StableHLO/n150/Binary/maximum_op.mlir b/test/ttmlir/Silicon/StableHLO/n150/Binary/maximum_op.mlir
index a5c9bf6e63..620f37ff32 100644
--- a/test/ttmlir/Silicon/StableHLO/n150/Binary/maximum_op.mlir
+++ b/test/ttmlir/Silicon/StableHLO/n150/Binary/maximum_op.mlir
@@ -9,11 +9,9 @@
 module @jit_eltwise_maximum attributes {} {
   func.func public @test_maximum(%arg0: tensor<64x128xf32>, %arg1: tensor<64x128xf32>) -> tensor<64x128xf32> {
     // CHECK-LABEL: func.func public @test_maximum
-    // CHECK: ttnn.empty
     // CHECK: ttnn.maximum
     // CHECK-SAME: tensor<64x128xf32,
     // CHECK-SAME: tensor<64x128xf32,
-    // CHECK-SAME: tensor<64x128xf32,
     // CHECK-SAME: -> tensor<64x128xf32,
     %0 = stablehlo.maximum %arg0, %arg1 : tensor<64x128xf32>
     return %0 : tensor<64x128xf32>
diff --git a/test/ttmlir/Silicon/StableHLO/n150/Binary/minimum_op.mlir b/test/ttmlir/Silicon/StableHLO/n150/Binary/minimum_op.mlir
index b72cc78d56..d0f7566342 100644
--- a/test/ttmlir/Silicon/StableHLO/n150/Binary/minimum_op.mlir
+++ b/test/ttmlir/Silicon/StableHLO/n150/Binary/minimum_op.mlir
@@ -9,11 +9,9 @@
 module @jit_eltwise_minimum attributes {} {
   func.func public @test_minimum(%arg0: tensor<64x128xf32>, %arg1: tensor<64x128xf32>) -> tensor<64x128xf32> {
     // CHECK-LABEL: func.func public @test_minimum
-    // CHECK: ttnn.empty
     // CHECK: ttnn.minimum
     // CHECK-SAME: tensor<64x128xf32,
     // CHECK-SAME: tensor<64x128xf32,
-    // CHECK-SAME: tensor<64x128xf32,
     // CHECK-SAME: -> tensor<64x128xf32,
     %0 = stablehlo.minimum %arg0, %arg1 : tensor<64x128xf32>
     return %0 : tensor<64x128xf32>
diff --git a/test/ttmlir/Silicon/StableHLO/n150/Binary/multiply_op.mlir b/test/ttmlir/Silicon/StableHLO/n150/Binary/multiply_op.mlir
index b5937abe72..c68cd5654f 100644
--- a/test/ttmlir/Silicon/StableHLO/n150/Binary/multiply_op.mlir
+++ b/test/ttmlir/Silicon/StableHLO/n150/Binary/multiply_op.mlir
@@ -9,11 +9,9 @@
 module @jit_eltwise_multiply attributes {} {
   func.func public @test_multiply(%arg0: tensor<64x128xf32>, %arg1: tensor<64x128xf32>) -> tensor<64x128xf32> {
     // CHECK-LABEL: func.func public @test_multiply
-    // CHECK: ttnn.empty
     // CHECK: ttnn.multiply
     // CHECK-SAME: tensor<64x128xf32,
     // CHECK-SAME: tensor<64x128xf32,
-    // CHECK-SAME: tensor<64x128xf32,
     // CHECK-SAME: -> tensor<64x128xf32,
     %0 = stablehlo.multiply %arg0, %arg1 : tensor<64x128xf32>
     return %0 : tensor<64x128xf32>
diff --git a/test/ttmlir/Silicon/StableHLO/n150/Binary/power_op.mlir b/test/ttmlir/Silicon/StableHLO/n150/Binary/power_op.mlir
index 83f2aafe0b..31b72ad49d 100644
--- a/test/ttmlir/Silicon/StableHLO/n150/Binary/power_op.mlir
+++ b/test/ttmlir/Silicon/StableHLO/n150/Binary/power_op.mlir
@@ -8,11 +8,9 @@
 module @jit_eltwise_power attributes {} {
   func.func public @test_power(%arg0: tensor<64x128xf32>, %arg1: tensor<64x128xf32>) -> tensor<64x128xf32> {
     // CHECK-LABEL: func.func public @test_power
-    // CHECK: ttnn.empty
     // CHECK: ttnn.pow
     // CHECK-SAME: tensor<64x128xf32,
     // CHECK-SAME: tensor<64x128xf32,
-    // CHECK-SAME: tensor<64x128xf32,
     // CHECK-SAME: -> tensor<64x128xf32,
     %0 = stablehlo.power %arg0, %arg1 : tensor<64x128xf32>
     return %0 : tensor<64x128xf32>
diff --git a/test/ttmlir/Silicon/StableHLO/n150/Binary/remainder_op.mlir b/test/ttmlir/Silicon/StableHLO/n150/Binary/remainder_op.mlir
index 9444d20f70..b4100bad18 100644
--- a/test/ttmlir/Silicon/StableHLO/n150/Binary/remainder_op.mlir
+++ b/test/ttmlir/Silicon/StableHLO/n150/Binary/remainder_op.mlir
@@ -9,11 +9,9 @@
 module @jit_eltwise_remainder attributes {} {
   func.func public @test_remainder(%arg0: tensor<64x128xf32>, %arg1: tensor<64x128xf32>) -> tensor<64x128xf32> {
     // CHECK-LABEL: func.func public @test_remainder
-    // CHECK: ttnn.empty
     // CHECK: ttnn.remainder
     // CHECK-SAME: tensor<64x128xf32,
     // CHECK-SAME: tensor<64x128xf32,
-    // CHECK-SAME: tensor<64x128xf32,
     // CHECK-SAME: -> tensor<64x128xf32,
     %0 = stablehlo.remainder %arg0, %arg1 : tensor<64x128xf32>
     return %0 : tensor<64x128xf32>
diff --git a/test/ttmlir/Silicon/StableHLO/n150/Binary/subtract_op.mlir b/test/ttmlir/Silicon/StableHLO/n150/Binary/subtract_op.mlir
index e9169110c0..53dc74d65c 100644
--- a/test/ttmlir/Silicon/StableHLO/n150/Binary/subtract_op.mlir
+++ b/test/ttmlir/Silicon/StableHLO/n150/Binary/subtract_op.mlir
@@ -9,11 +9,9 @@
 module @jit_eltwise_subtract attributes {} {
   func.func public @test_subtract(%arg0: tensor<64x128xf32>, %arg1: tensor<64x128xf32>) -> tensor<64x128xf32> {
     // CHECK-LABEL: func.func public @test_subtract
-    // CHECK: ttnn.empty
     // CHECK: ttnn.subtract
     // CHECK-SAME: tensor<64x128xf32,
     // CHECK-SAME: tensor<64x128xf32,
-    // CHECK-SAME: tensor<64x128xf32,
     // CHECK-SAME: -> tensor<64x128xf32,
     %0 = stablehlo.subtract %arg0, %arg1 : tensor<64x128xf32>
     return %0 : tensor<64x128xf32>
diff --git a/test/ttmlir/Silicon/StableHLO/n150/Unary/absolute_op.mlir b/test/ttmlir/Silicon/StableHLO/n150/Unary/absolute_op.mlir
index 915238179b..36735c844e 100644
--- a/test/ttmlir/Silicon/StableHLO/n150/Unary/absolute_op.mlir
+++ b/test/ttmlir/Silicon/StableHLO/n150/Unary/absolute_op.mlir
@@ -9,10 +9,8 @@
 module @jit_eltwise_abs attributes {} {
   func.func public @test_abs(%arg0: tensor<64x128xf32>) -> tensor<64x128xf32> {
     // CHECK-LABEL: func.func public @test_abs
-    // CHECK: ttnn.empty
     // CHECK: ttnn.abs
     // CHECK-SAME: tensor<64x128xf32,
-    // CHECK-SAME: tensor<64x128xf32,
     // CHECK-SAME: -> tensor<64x128xf32,
     %0 = stablehlo.abs %arg0 : tensor<64x128xf32>
     return %0 : tensor<64x128xf32>
diff --git a/test/ttmlir/Silicon/StableHLO/n150/Unary/cbrt_op.mlir b/test/ttmlir/Silicon/StableHLO/n150/Unary/cbrt_op.mlir
index 5bfbaf9f6d..91eb994328 100644
--- a/test/ttmlir/Silicon/StableHLO/n150/Unary/cbrt_op.mlir
+++ b/test/ttmlir/Silicon/StableHLO/n150/Unary/cbrt_op.mlir
@@ -9,10 +9,8 @@
 module @jit_eltwise_rsqrt attributes {} {
   func.func public @test_cbrt(%arg0: tensor<64x128xf32>) -> tensor<64x128xf32> {
     // CHECK-LABEL: func.func public @test_cbrt
-    // CHECK: ttnn.empty
     // CHECK: ttnn.cbrt
     // CHECK-SAME: tensor<64x128xf32,
-    // CHECK-SAME: tensor<64x128xf32,
     // CHECK-SAME: -> tensor<64x128xf32,
     %0 = stablehlo.cbrt %arg0 : tensor<64x128xf32>
     return %0 : tensor<64x128xf32>
diff --git a/test/ttmlir/Silicon/StableHLO/n150/Unary/ceil_op.mlir b/test/ttmlir/Silicon/StableHLO/n150/Unary/ceil_op.mlir
index 911b775dae..691ea5826e 100644
--- a/test/ttmlir/Silicon/StableHLO/n150/Unary/ceil_op.mlir
+++ b/test/ttmlir/Silicon/StableHLO/n150/Unary/ceil_op.mlir
@@ -9,10 +9,8 @@
 module @jit_eltwise_ceil attributes {} {
   func.func public @test_ceil(%arg0: tensor<64x128xf32>) -> tensor<64x128xf32> {
     // CHECK-LABEL: func.func public @test_ceil
-    // CHECK: ttnn.empty
     // CHECK: ttnn.ceil
     // CHECK-SAME: tensor<64x128xf32,
-    // CHECK-SAME: tensor<64x128xf32,
     // CHECK-SAME: -> tensor<64x128xf32,
     %0 = stablehlo.ceil %arg0 : tensor<64x128xf32>
     return %0 : tensor<64x128xf32>
diff --git a/test/ttmlir/Silicon/StableHLO/n150/Unary/clamp_op.mlir b/test/ttmlir/Silicon/StableHLO/n150/Unary/clamp_op.mlir
index 9e625b549f..1beab078d4 100644
--- a/test/ttmlir/Silicon/StableHLO/n150/Unary/clamp_op.mlir
+++ b/test/ttmlir/Silicon/StableHLO/n150/Unary/clamp_op.mlir
@@ -21,17 +21,13 @@ module @jit_transpose attributes {} {
 
   func.func public @test_clamp_tensor(%arg0: tensor<64x128xf32>, %arg1: tensor<64x128xf32>, %arg2: tensor<64x128xf32>) -> tensor<64x128xf32> {
     // CHECK-LABEL: func.func public @test_clamp_tensor
-    // CHECK: ttnn.empty
     // CHECK: %[[MAX:.*]] = "ttnn.maximum"
     // CHECK-SAME: tensor<64x128xf32,
     // CHECK-SAME: tensor<64x128xf32,
-    // CHECK-SAME: tensor<64x128xf32,
     // CHECK-SAME: -> tensor<64x128xf32,
-    // CHECK: ttnn.empty
     // CHECK: "ttnn.minimum"(%[[MAX]]
     // CHECK-SAME: tensor<64x128xf32,
     // CHECK-SAME: tensor<64x128xf32,
-    // CHECK-SAME: tensor<64x128xf32,
     // CHECK-SAME: -> tensor<64x128xf32,
     %0 = stablehlo.clamp %arg1, %arg0, %arg2 : tensor<64x128xf32>
     return %0 : tensor<64x128xf32>
diff --git a/test/ttmlir/Silicon/StableHLO/n150/Unary/cosine_op.mlir b/test/ttmlir/Silicon/StableHLO/n150/Unary/cosine_op.mlir
index 885a293e72..1552637846 100644
--- a/test/ttmlir/Silicon/StableHLO/n150/Unary/cosine_op.mlir
+++ b/test/ttmlir/Silicon/StableHLO/n150/Unary/cosine_op.mlir
@@ -9,10 +9,8 @@
 module @jit_eltwise_cosine attributes {} {
   func.func public @test_cosine(%arg0: tensor<64x128xf32>) -> tensor<64x128xf32> {
     // CHECK-LABEL: func.func public @test_cosine
-    // CHECK: ttnn.empty
     // CHECK: ttnn.cos
     // CHECK-SAME: tensor<64x128xf32,
-    // CHECK-SAME: tensor<64x128xf32,
     // CHECK-SAME: -> tensor<64x128xf32,
     %0 = stablehlo.cosine %arg0 : tensor<64x128xf32>
     return %0 : tensor<64x128xf32>
diff --git a/test/ttmlir/Silicon/StableHLO/n150/Unary/exponential_minus_one_op.mlir b/test/ttmlir/Silicon/StableHLO/n150/Unary/exponential_minus_one_op.mlir
index 30cd1e8c7d..9dc0390705 100644
--- a/test/ttmlir/Silicon/StableHLO/n150/Unary/exponential_minus_one_op.mlir
+++ b/test/ttmlir/Silicon/StableHLO/n150/Unary/exponential_minus_one_op.mlir
@@ -9,10 +9,8 @@
 module @jit_eltwise_expm1 attributes {} {
   func.func public @test_expm1(%arg0: tensor<64x128xf32>) -> tensor<64x128xf32> {
     // CHECK-LABEL: func.func public @test_expm1
-    // CHECK: ttnn.empty
     // CHECK: ttnn.expm1
     // CHECK-SAME: tensor<64x128xf32,
-    // CHECK-SAME: tensor<64x128xf32,
     // CHECK-SAME: -> tensor<64x128xf32,
     %0 = stablehlo.exponential_minus_one %arg0 : tensor<64x128xf32>
     return %0 : tensor<64x128xf32>
diff --git a/test/ttmlir/Silicon/StableHLO/n150/Unary/exponential_op.mlir b/test/ttmlir/Silicon/StableHLO/n150/Unary/exponential_op.mlir
index 47a2d6443d..c5357eaee5 100644
--- a/test/ttmlir/Silicon/StableHLO/n150/Unary/exponential_op.mlir
+++ b/test/ttmlir/Silicon/StableHLO/n150/Unary/exponential_op.mlir
@@ -9,10 +9,8 @@
 module @jit_eltwise_exp attributes {} {
   func.func public @test_exp(%arg0: tensor<64x128xf32>) -> tensor<64x128xf32> {
     // CHECK-LABEL: func.func public @test_exp
-    // CHECK: ttnn.empty
     // CHECK: ttnn.exp
     // CHECK-SAME: tensor<64x128xf32,
-    // CHECK-SAME: tensor<64x128xf32,
     // CHECK-SAME: -> tensor<64x128xf32,
     %0 = stablehlo.exponential %arg0 : tensor<64x128xf32>
     return %0 : tensor<64x128xf32>
diff --git a/test/ttmlir/Silicon/StableHLO/n150/Unary/floor_op.mlir b/test/ttmlir/Silicon/StableHLO/n150/Unary/floor_op.mlir
index 9dbde4c262..4f81859cc6 100644
--- a/test/ttmlir/Silicon/StableHLO/n150/Unary/floor_op.mlir
+++ b/test/ttmlir/Silicon/StableHLO/n150/Unary/floor_op.mlir
@@ -9,10 +9,8 @@
 module @jit_eltwise_floor attributes {} {
   func.func public @test_floor(%arg0: tensor<64x128xf32>) -> tensor<64x128xf32> {
     // CHECK-LABEL: func.func public @test_floor
-    // CHECK: ttnn.empty
     // CHECK: ttnn.floor
     // CHECK-SAME: tensor<64x128xf32,
-    // CHECK-SAME: tensor<64x128xf32,
     // CHECK-SAME: -> tensor<64x128xf32,
     %0 = stablehlo.floor %arg0 : tensor<64x128xf32>
     return %0 : tensor<64x128xf32>
diff --git a/test/ttmlir/Silicon/StableHLO/n150/Unary/isfinite_op.mlir b/test/ttmlir/Silicon/StableHLO/n150/Unary/isfinite_op.mlir
index 35682c8c0b..ba2a6b7749 100644
--- a/test/ttmlir/Silicon/StableHLO/n150/Unary/isfinite_op.mlir
+++ b/test/ttmlir/Silicon/StableHLO/n150/Unary/isfinite_op.mlir
@@ -9,10 +9,8 @@
 module @jit_eltwise_isfinite attributes {} {
   func.func public @test_isfinite(%arg0: tensor<64x128xbf16>) -> tensor<64x128xi1> {
     // CHECK-LABEL: func.func public @test_isfinite
-    // CHECK: ttnn.empty
     // CHECK: ttnn.isfinite
     // CHECK-SAME: tensor<64x128xbf16,
-    // CHECK-SAME: tensor<64x128xbf16,
     // CHECK-SAME: -> tensor<64x128xbf16,
     %0 = stablehlo.is_finite %arg0 : (tensor<64x128xbf16>) -> tensor<64x128xi1>
     return %0 : tensor<64x128xi1>
diff --git a/test/ttmlir/Silicon/StableHLO/n150/Unary/log_plus_one_op.mlir b/test/ttmlir/Silicon/StableHLO/n150/Unary/log_plus_one_op.mlir
index cd1d68344e..e4686eb150 100644
--- a/test/ttmlir/Silicon/StableHLO/n150/Unary/log_plus_one_op.mlir
+++ b/test/ttmlir/Silicon/StableHLO/n150/Unary/log_plus_one_op.mlir
@@ -9,10 +9,8 @@
 module @jit_eltwise_log_plus_one attributes {} {
   func.func public @test_log_plus_one(%arg0: tensor<64x128xf32>) -> tensor<64x128xf32> {
     // CHECK-LABEL: func.func public @test_log_plus_one
-    // CHECK: ttnn.empty
     // CHECK: ttnn.log1p
     // CHECK-SAME: tensor<64x128xf32,
-    // CHECK-SAME: tensor<64x128xf32,
     // CHECK-SAME: -> tensor<64x128xf32,
     %0 = stablehlo.log_plus_one %arg0 : tensor<64x128xf32>
     return %0 : tensor<64x128xf32>
diff --git a/test/ttmlir/Silicon/StableHLO/n150/Unary/logical_op.mlir b/test/ttmlir/Silicon/StableHLO/n150/Unary/logical_op.mlir
index 489ad2e585..7380e96931 100644
--- a/test/ttmlir/Silicon/StableHLO/n150/Unary/logical_op.mlir
+++ b/test/ttmlir/Silicon/StableHLO/n150/Unary/logical_op.mlir
@@ -9,10 +9,8 @@
 module @jit_eltwise_compare attributes {} {
   func.func public @logical_not(%arg0: tensor<64x128xi1>) -> tensor<64x128xi1> {
     // CHECK-LABEL: func.func public @logical_not
-    // CHECK: ttnn.empty
     // CHECK: ttnn.logical_not
     // CHECK-SAME: tensor<64x128xbf16,
-    // CHECK-SAME: tensor<64x128xbf16,
     // CHECK-SAME: -> tensor<64x128xbf16,
     %0 = stablehlo.not  %arg0 : tensor<64x128xi1>
     return %0 : tensor<64x128xi1>
diff --git a/test/ttmlir/Silicon/StableHLO/n150/Unary/negate_op.mlir b/test/ttmlir/Silicon/StableHLO/n150/Unary/negate_op.mlir
index 3d970b28e7..11f620aec3 100644
--- a/test/ttmlir/Silicon/StableHLO/n150/Unary/negate_op.mlir
+++ b/test/ttmlir/Silicon/StableHLO/n150/Unary/negate_op.mlir
@@ -9,10 +9,8 @@
 module @jit_eltwise_neg attributes {} {
   func.func public @test_neg(%arg0: tensor<64x128xf32>) -> tensor<64x128xf32> {
     // CHECK-LABEL: func.func public @test_neg
-    // CHECK: ttnn.empty
     // CHECK: ttnn.neg
     // CHECK-SAME: tensor<64x128xf32,
-    // CHECK-SAME: tensor<64x128xf32,
     // CHECK-SAME: -> tensor<64x128xf32,
     %0 = stablehlo.negate %arg0 : tensor<64x128xf32>
     return %0 : tensor<64x128xf32>
diff --git a/test/ttmlir/Silicon/StableHLO/n150/Unary/rsqrt_op.mlir b/test/ttmlir/Silicon/StableHLO/n150/Unary/rsqrt_op.mlir
index 6d0d2efc92..f487e07eef 100644
--- a/test/ttmlir/Silicon/StableHLO/n150/Unary/rsqrt_op.mlir
+++ b/test/ttmlir/Silicon/StableHLO/n150/Unary/rsqrt_op.mlir
@@ -9,10 +9,8 @@
 module @jit_eltwise_rsqrt attributes {} {
   func.func public @test_rsqrt(%arg0: tensor<64x128xf32>) -> tensor<64x128xf32> {
     // CHECK-LABEL: func.func public @test_rsqrt
-    // CHECK: ttnn.empty
     // CHECK: ttnn.rsqrt
     // CHECK-SAME: tensor<64x128xf32,
-    // CHECK-SAME: tensor<64x128xf32,
     // CHECK-SAME: -> tensor<64x128xf32,
     %0 = stablehlo.rsqrt %arg0 : tensor<64x128xf32>
     return %0 : tensor<64x128xf32>
diff --git a/test/ttmlir/Silicon/StableHLO/n150/Unary/sign_op.mlir b/test/ttmlir/Silicon/StableHLO/n150/Unary/sign_op.mlir
index 6c31b87cc8..79136169fd 100644
--- a/test/ttmlir/Silicon/StableHLO/n150/Unary/sign_op.mlir
+++ b/test/ttmlir/Silicon/StableHLO/n150/Unary/sign_op.mlir
@@ -9,10 +9,8 @@
 module @jit_eltwise_sign attributes {} {
   func.func public @test_sign(%arg0: tensor<64x128xf32>) -> tensor<64x128xf32> {
     // CHECK-LABEL: func.func public @test_sign
-    // CHECK: ttnn.empty
     // CHECK: ttnn.sign
     // CHECK-SAME: tensor<64x128xf32,
-    // CHECK-SAME: tensor<64x128xf32,
     // CHECK-SAME: -> tensor<64x128xf32,
     %0 = stablehlo.sign %arg0 : tensor<64x128xf32>
     return %0 : tensor<64x128xf32>
diff --git a/test/ttmlir/Silicon/StableHLO/n150/Unary/sine_op.mlir b/test/ttmlir/Silicon/StableHLO/n150/Unary/sine_op.mlir
index 36531bb0cf..cb95859011 100644
--- a/test/ttmlir/Silicon/StableHLO/n150/Unary/sine_op.mlir
+++ b/test/ttmlir/Silicon/StableHLO/n150/Unary/sine_op.mlir
@@ -9,10 +9,8 @@
 module @jit_eltwise_sine attributes {} {
   func.func public @test_sine(%arg0: tensor<64x128xf32>) -> tensor<64x128xf32> {
     // CHECK-LABEL: func.func public @test_sine
-    // CHECK: ttnn.empty
     // CHECK: ttnn.sin
     // CHECK-SAME: tensor<64x128xf32,
-    // CHECK-SAME: tensor<64x128xf32,
     // CHECK-SAME: -> tensor<64x128xf32,
     %0 = stablehlo.sine %arg0 : tensor<64x128xf32>
     return %0 : tensor<64x128xf32>
diff --git a/test/ttmlir/Silicon/StableHLO/n150/Unary/sqrt_op.mlir b/test/ttmlir/Silicon/StableHLO/n150/Unary/sqrt_op.mlir
index feb6bd8ac9..07caccf34b 100644
--- a/test/ttmlir/Silicon/StableHLO/n150/Unary/sqrt_op.mlir
+++ b/test/ttmlir/Silicon/StableHLO/n150/Unary/sqrt_op.mlir
@@ -9,10 +9,8 @@
 module @jit_eltwise_sqrt attributes {} {
   func.func public @test_sqrt(%arg0: tensor<64x128xf32>) -> tensor<64x128xf32> {
     // CHECK-LABEL: func.func public @test_sqrt
-    // CHECK: ttnn.empty
     // CHECK: ttnn.sqrt
     // CHECK-SAME: tensor<64x128xf32,
-    // CHECK-SAME: tensor<64x128xf32,
     // CHECK-SAME: -> tensor<64x128xf32,
     %0 = stablehlo.sqrt %arg0 : tensor<64x128xf32>
     return %0 : tensor<64x128xf32>
diff --git a/test/ttmlir/Silicon/StableHLO/n150/composite_op.mlir b/test/ttmlir/Silicon/StableHLO/n150/composite_op.mlir
index 9bb62c9e8c..cd457d0dd6 100644
--- a/test/ttmlir/Silicon/StableHLO/n150/composite_op.mlir
+++ b/test/ttmlir/Silicon/StableHLO/n150/composite_op.mlir
@@ -15,7 +15,6 @@ module @jit_eltwise_add attributes {} {
 
   // CHECK-LABEL: func.func public @main
   func.func public @main(%arg0: tensor<64x128xf32>, %arg1: tensor<64x128xf32>) -> tensor<64x128xf32> {
-    // CHECK: ttnn.empty
     // CEHCK: ttnn.add
     %results = stablehlo.composite "jit_eltwise_add.my_add" %arg0, %arg1 {
         decomposition = @add_impl
diff --git a/test/ttmlir/Silicon/StableHLO/n150/scalar_add_op.mlir b/test/ttmlir/Silicon/StableHLO/n150/scalar_add_op.mlir
index 4e05a5040b..7e0987bd6c 100644
--- a/test/ttmlir/Silicon/StableHLO/n150/scalar_add_op.mlir
+++ b/test/ttmlir/Silicon/StableHLO/n150/scalar_add_op.mlir
@@ -8,11 +8,9 @@
 module @jit_eltwise_scalar_add attributes {} {
   func.func public @test_scalar_add(%arg0: tensor<f32>, %arg1: tensor<f32>) -> tensor<f32> {
     // CHECK-LABEL: func.func public @test_scalar_add
-    // CHECK: ttnn.empty
     // CHECK: ttnn.add
     // CHECK-SAME: tensor<1xf32,
     // CHECK-SAME: tensor<1xf32,
-    // CHECK-SAME: tensor<1xf32,
     // CHECK-SAME: -> tensor<1xf32,
     %0 = stablehlo.add %arg0, %arg1 : tensor<f32>
     return %0 : tensor<f32>
diff --git a/test/ttmlir/Silicon/TTNN/n150/deallocate.mlir b/test/ttmlir/Silicon/TTNN/n150/deallocate.mlir
index aed0a83549..a26d8ac8e3 100644
--- a/test/ttmlir/Silicon/TTNN/n150/deallocate.mlir
+++ b/test/ttmlir/Silicon/TTNN/n150/deallocate.mlir
@@ -9,24 +9,21 @@ module @"dealloc_test" attributes {} {
     // CHECK: %{{.+}} = "ttnn.matmul"([[I1:%.+]], [[I2:%.+]], [[O1:%.+]]) {{.+}} -> tensor<1x256xf32, {{.+}}>
     %2 = tensor.empty() : tensor<1x256xf32> loc(#loc9)
     %3 = "ttir.add"(%1, %arg3, %2) <{operandSegmentSizes = array<i32: 2, 1>}> : (tensor<1x256xf32>, tensor<1x256xf32>, tensor<1x256xf32>) -> tensor<1x256xf32> loc(#loc9)
-    // CHECK: %{{.+}} = "ttnn.add"([[I1:%.+]], [[I2:%.+]], [[O2:%.+]]) {{.+}} -> tensor<1x256xf32, {{.+}}>
+    // CHECK: %{{.+}} = "ttnn.add"([[I1:%.+]], [[I2:%.+]]) {{.+}} -> tensor<1x256xf32, {{.+}}>
     // CHECK: "ttnn.deallocate"([[O1]]) {{.+}} : (tensor<1x256xf32, {{.+}}>) -> ()
     %4 = tensor.empty() : tensor<1x256xf32> loc(#loc10)
     %5 = "ttir.relu"(%3, %4) <{operandSegmentSizes = array<i32: 1, 1>}> : (tensor<1x256xf32>, tensor<1x256xf32>) -> tensor<1x256xf32> loc(#loc10)
-    // CHECK: %{{.+}} = "ttnn.relu"([[I1:%.+]], [[O3:%.+]]) {{.+}} -> tensor<1x256xf32, {{.+}}>
-    // CHECK: "ttnn.deallocate"([[O2]]) {{.+}} : (tensor<1x256xf32, {{.+}}>) -> ()
+    // CHECK: %{{.+}} = "ttnn.relu"([[I1:%.+]]) {{.+}} -> tensor<1x256xf32, {{.+}}>
     %6 = tensor.empty() : tensor<1x10xf32> loc(#loc11)
     %7 = "ttir.matmul"(%5, %arg2, %6) : (tensor<1x256xf32>, tensor<256x10xf32>, tensor<1x10xf32>) -> tensor<1x10xf32> loc(#loc11)
     // CHECK: %{{.+}} = "ttnn.matmul"([[I1:%.+]], [[I2:%.+]], [[O4:%.+]]) {{.+}} -> tensor<1x10xf32, {{.+}}>
-    // CHECK: "ttnn.deallocate"([[O3]]) {{.+}} : (tensor<1x256xf32, {{.+}}>) -> ()
     %8 = tensor.empty() : tensor<1x10xf32> loc(#loc12)
     %9 = "ttir.add"(%7, %arg1, %8) <{operandSegmentSizes = array<i32: 2, 1>}> : (tensor<1x10xf32>, tensor<1x10xf32>, tensor<1x10xf32>) -> tensor<1x10xf32> loc(#loc12)
-    // CHECK: %{{.+}} = "ttnn.add"([[I1:%.+]], [[I2:%.+]], [[O5:%.+]]) {{.+}} -> tensor<1x10xf32,{{.+}}>
+    // CHECK: %{{.+}} = "ttnn.add"([[I1:%.+]], [[I2:%.+]]) {{.+}} -> tensor<1x10xf32,{{.+}}>
     // CHECK: "ttnn.deallocate"([[O4]]) {{.+}} : (tensor<1x10xf32, {{.+}}>) -> ()
     %10 = tensor.empty() : tensor<1x10xf32> loc(#loc13)
     %11 = "ttir.softmax"(%9, %10) <{dimension = 1 : si32}> : (tensor<1x10xf32>, tensor<1x10xf32>) -> tensor<1x10xf32> loc(#loc13)
     // CHECK: %{{.+}} = "ttnn.softmax"([[I1:%.+]]) {{.+}} -> tensor<1x10xf32, {{.+}}>
-    // CHECK: "ttnn.deallocate"([[O5]]) {{.+}} : (tensor<1x10xf32, {{.+}}>) -> ()
     return %11 : tensor<1x10xf32> loc(#loc7)
   } loc(#loc)
 } loc(#loc)
diff --git a/test/ttmlir/Silicon/TTNN/n150/eltwise/binary/add/add.mlir b/test/ttmlir/Silicon/TTNN/n150/eltwise/binary/add/add.mlir
index 0774d60ded..a05783769b 100644
--- a/test/ttmlir/Silicon/TTNN/n150/eltwise/binary/add/add.mlir
+++ b/test/ttmlir/Silicon/TTNN/n150/eltwise/binary/add/add.mlir
@@ -3,9 +3,11 @@
 // RUN: ttmlir-translate --ttnn-to-flatbuffer %t.mlir > %t.ttnn
 
 func.func @add(%arg0: tensor<64x128xf32>, %arg1: tensor<64x128xf32>) -> tensor<64x128xf32> {
-  // CHECK: %[[C:.*]] = "ttnn.empty"[[C:.*]]
   %0 = tensor.empty() : tensor<64x128xf32>
-  // CHECK: %[[C:.*]] = "ttnn.add"[[C:.*]]
   %1 = "ttir.add"(%arg0, %arg1, %0) <{operandSegmentSizes = array<i32: 2, 1>}> : (tensor<64x128xf32>, tensor<64x128xf32>, tensor<64x128xf32>) -> tensor<64x128xf32>
+  // CHECK: "ttnn.add"
+  // CHECK-SAME: tensor<64x128xf32
+  // CHECK-SAME: tensor<64x128xf32
+  // CHECK-SAME: -> tensor<64x128xf32
   return %1 : tensor<64x128xf32>
 }
diff --git a/test/ttmlir/Silicon/TTNN/n150/eltwise/binary/add/add_int32.mlir b/test/ttmlir/Silicon/TTNN/n150/eltwise/binary/add/add_int32.mlir
index 49d028086b..f2e298ac60 100644
--- a/test/ttmlir/Silicon/TTNN/n150/eltwise/binary/add/add_int32.mlir
+++ b/test/ttmlir/Silicon/TTNN/n150/eltwise/binary/add/add_int32.mlir
@@ -3,9 +3,11 @@
 // RUN: ttmlir-translate --ttnn-to-flatbuffer %t.mlir > %t.ttnn
 
 func.func @addint32(%arg0: tensor<64x128xi32>, %arg1: tensor<64x128xi32>) -> tensor<64x128xi32> {
-  // CHECK: %[[C:.*]] = "ttnn.empty"[[C:.*]]
   %0 = tensor.empty() : tensor<64x128xi32>
-  // CHECK: %[[C:.*]] = "ttnn.add"[[C:.*]]
   %1 = "ttir.add"(%arg0, %arg1, %0) <{operandSegmentSizes = array<i32: 2, 1>}> : (tensor<64x128xi32>, tensor<64x128xi32>, tensor<64x128xi32>) -> tensor<64x128xi32>
+  // CHECK: "ttnn.add"
+  // CHECK-SAME: tensor<64x128xui32
+  // CHECK-SAME: tensor<64x128xui32
+  // CHECK-SAME: -> tensor<64x128xui32
   return %1 : tensor<64x128xi32>
 }
diff --git a/test/ttmlir/Silicon/TTNN/n150/simple_compare.mlir b/test/ttmlir/Silicon/TTNN/n150/eltwise/binary/compare/simple_compare.mlir
similarity index 60%
rename from test/ttmlir/Silicon/TTNN/n150/simple_compare.mlir
rename to test/ttmlir/Silicon/TTNN/n150/eltwise/binary/compare/simple_compare.mlir
index 5263c4fe41..d27b094a54 100644
--- a/test/ttmlir/Silicon/TTNN/n150/simple_compare.mlir
+++ b/test/ttmlir/Silicon/TTNN/n150/eltwise/binary/compare/simple_compare.mlir
@@ -3,80 +3,62 @@
 // RUN: ttmlir-translate --ttnn-to-flatbuffer %t.mlir > %t.ttnn
 module attributes {} {
   func.func @equal(%arg0: tensor<13x31xf32>, %arg1: tensor<13x31xf32>) -> tensor<13x31xf32> {
-    // CHECK: %[[C:.*]] = "ttnn.empty
-    // CHECK-SAME: [[TENSOR:tensor<13x31xf32,]]
     %0 = tensor.empty() : tensor<13x31xf32>
-    // CHECK: %[[C:.*]] = "ttnn.eq"
-    // CHECK-SAME: [[TENSOR]]
-    // CHECK-SAME: [[TENSOR]]
-    // CHECK-SAME: [[TENSOR]]
-    // CHECK-SAME: -> [[TENSOR]]
     %1 = "ttir.eq"(%arg0, %arg1, %0) <{operandSegmentSizes = array<i32: 2, 1>}> : (tensor<13x31xf32>, tensor<13x31xf32>, tensor<13x31xf32>) -> tensor<13x31xf32>
+    // CHECK: "ttnn.eq"
+    // CHECK-SAME: tensor<13x31xf32
+    // CHECK-SAME: tensor<13x31xf32
+    // CHECK-SAME: -> tensor<13x31xf32
     return %1 : tensor<13x31xf32>
   }
 
   func.func @not_equal(%arg0: tensor<13x31xf32>, %arg1: tensor<13x31xf32>) -> tensor<13x31xf32> {
-    // CHECK: %[[C:.*]] = "ttnn.empty
-    // CHECK-SAME: [[TENSOR:tensor<13x31xf32,]]
     %0 = tensor.empty() : tensor<13x31xf32>
-    // CHECK: %[[C:.*]] = "ttnn.ne"
-    // CHECK-SAME: [[TENSOR]]
-    // CHECK-SAME: [[TENSOR]]
-    // CHECK-SAME: [[TENSOR]]
-    // CHECK-SAME: -> [[TENSOR]]
     %1 = "ttir.ne"(%arg0, %arg1, %0) <{operandSegmentSizes = array<i32: 2, 1>}> : (tensor<13x31xf32>, tensor<13x31xf32>, tensor<13x31xf32>) -> tensor<13x31xf32>
+    // CHECK: "ttnn.ne"
+    // CHECK-SAME: tensor<13x31xf32
+    // CHECK-SAME: tensor<13x31xf32
+    // CHECK-SAME: -> tensor<13x31xf32
     return %1 : tensor<13x31xf32>
   }
 
   func.func @greater_equal(%arg0: tensor<13x31xf32>, %arg1: tensor<13x31xf32>) -> tensor<13x31xf32> {
-    // CHECK: %[[C:.*]] = "ttnn.empty
-    // CHECK-SAME: [[TENSOR:tensor<13x31xf32,]]
     %0 = tensor.empty() : tensor<13x31xf32>
-    // CHECK: %[[C:.*]] = "ttnn.ge"
-    // CHECK-SAME: [[TENSOR]]
-    // CHECK-SAME: [[TENSOR]]
-    // CHECK-SAME: [[TENSOR]]
-    // CHECK-SAME: -> [[TENSOR]]
     %1 = "ttir.ge"(%arg0, %arg1, %0) <{operandSegmentSizes = array<i32: 2, 1>}> : (tensor<13x31xf32>, tensor<13x31xf32>, tensor<13x31xf32>) -> tensor<13x31xf32>
+    // CHECK: "ttnn.ge"
+    // CHECK-SAME: tensor<13x31xf32
+    // CHECK-SAME: tensor<13x31xf32
+    // CHECK-SAME: -> tensor<13x31xf32
     return %1 : tensor<13x31xf32>
   }
 
   func.func @greater_than(%arg0: tensor<13x31xf32>, %arg1: tensor<13x31xf32>) -> tensor<13x31xf32> {
-    // CHECK: %[[C:.*]] = "ttnn.empty
-    // CHECK-SAME: [[TENSOR:tensor<13x31xf32,]]
     %0 = tensor.empty() : tensor<13x31xf32>
-    // CHECK: %[[C:.*]] = "ttnn.gt"
-    // CHECK-SAME: [[TENSOR]]
-    // CHECK-SAME: [[TENSOR]]
-    // CHECK-SAME: [[TENSOR]]
-    // CHECK-SAME: -> [[TENSOR]]
     %1 = "ttir.gt"(%arg0, %arg1, %0) <{operandSegmentSizes = array<i32: 2, 1>}> : (tensor<13x31xf32>, tensor<13x31xf32>, tensor<13x31xf32>) -> tensor<13x31xf32>
+    // CHECK: "ttnn.gt"
+    // CHECK-SAME: tensor<13x31xf32
+    // CHECK-SAME: tensor<13x31xf32
+    // CHECK-SAME: -> tensor<13x31xf32
     return %1 : tensor<13x31xf32>
   }
 
   func.func @less_equal(%arg0: tensor<13x31xf32>, %arg1: tensor<13x31xf32>) -> tensor<13x31xf32> {
-    // CHECK: %[[C:.*]] = "ttnn.empty
-    // CHECK-SAME: [[TENSOR:tensor<13x31xf32,]]
     %0 = tensor.empty() : tensor<13x31xf32>
-    // CHECK: %[[C:.*]] = "ttnn.le"
-    // CHECK-SAME: [[TENSOR]]
-    // CHECK-SAME: [[TENSOR]]
-    // CHECK-SAME: [[TENSOR]]
-    // CHECK-SAME: -> [[TENSOR]]
     %1 = "ttir.le"(%arg0, %arg1, %0) <{operandSegmentSizes = array<i32: 2, 1>}> : (tensor<13x31xf32>, tensor<13x31xf32>, tensor<13x31xf32>) -> tensor<13x31xf32>
+    // CHECK: "ttnn.le"
+    // CHECK-SAME: tensor<13x31xf32
+    // CHECK-SAME: tensor<13x31xf32
+    // CHECK-SAME: -> tensor<13x31xf32
     return %1 : tensor<13x31xf32>
   }
 
   func.func @less_than(%arg0: tensor<13x31xf32>, %arg1: tensor<13x31xf32>) -> tensor<13x31xf32> {
-    // CHECK: %[[C:.*]] = "ttnn.empty
-    // CHECK-SAME: [[TENSOR:tensor<13x31xf32,]]
     %0 = tensor.empty() : tensor<13x31xf32>
-    // CHECK: %[[C:.*]] = "ttnn.lt"
-    // CHECK-SAME: [[TENSOR]]
-    // CHECK-SAME: [[TENSOR]]
-    // CHECK-SAME: [[TENSOR]]
-    // CHECK-SAME: -> [[TENSOR]]
     %1 = "ttir.lt"(%arg0, %arg1, %0) <{operandSegmentSizes = array<i32: 2, 1>}> : (tensor<13x31xf32>, tensor<13x31xf32>, tensor<13x31xf32>) -> tensor<13x31xf32>
+    // CHECK: "ttnn.lt"
+    // CHECK-SAME: tensor<13x31xf32
+    // CHECK-SAME: tensor<13x31xf32
+    // CHECK-SAME: -> tensor<13x31xf32
     return %1 : tensor<13x31xf32>
   }
 }
diff --git a/test/ttmlir/Silicon/TTNN/n150/eltwise/binary/div/div.mlir b/test/ttmlir/Silicon/TTNN/n150/eltwise/binary/div/div.mlir
index 7ba2da3211..ca231e2c9f 100644
--- a/test/ttmlir/Silicon/TTNN/n150/eltwise/binary/div/div.mlir
+++ b/test/ttmlir/Silicon/TTNN/n150/eltwise/binary/div/div.mlir
@@ -3,9 +3,11 @@
 // RUN: ttmlir-translate --ttnn-to-flatbuffer %t.mlir > %t.ttnn
 
 func.func @div(%arg0: tensor<64x128xf32>, %arg1: tensor<64x128xf32>) -> tensor<64x128xf32> {
-  // CHECK: %[[C:.*]] = "ttnn.empty"[[C:.*]]
   %0 = tensor.empty() : tensor<64x128xf32>
-  // CHECK: %[[C:.*]] = "ttnn.div"[[C:.*]]
   %1 = "ttir.div"(%arg0, %arg1, %0) <{operandSegmentSizes = array<i32: 2, 1>}> : (tensor<64x128xf32>, tensor<64x128xf32>, tensor<64x128xf32>) -> tensor<64x128xf32>
+  // CHECK: "ttnn.div"
+  // CHECK-SAME: tensor<64x128xf32
+  // CHECK-SAME: tensor<64x128xf32
+  // CHECK-SAME: -> tensor<64x128xf32
   return %1 : tensor<64x128xf32>
 }
diff --git a/test/ttmlir/Silicon/TTNN/n150/eltwise/binary/ge/ge.mlir b/test/ttmlir/Silicon/TTNN/n150/eltwise/binary/ge/ge.mlir
index 3449d485bf..28779fe997 100644
--- a/test/ttmlir/Silicon/TTNN/n150/eltwise/binary/ge/ge.mlir
+++ b/test/ttmlir/Silicon/TTNN/n150/eltwise/binary/ge/ge.mlir
@@ -3,9 +3,11 @@
 // RUN: ttmlir-translate --ttnn-to-flatbuffer %t.mlir > %t.ttnn
 
 func.func @ge(%arg0: tensor<64x128xf32>, %arg1: tensor<64x128xf32>) -> tensor<64x128xf32> {
-  // CHECK: %[[C:.*]] = "ttnn.empty"[[C:.*]]
   %0 = tensor.empty() : tensor<64x128xf32>
-  // CHECK: %[[C:.*]] = "ttnn.ge"[[C:.*]]
   %1 = "ttir.ge"(%arg0, %arg1, %0) <{operandSegmentSizes = array<i32: 2, 1>}> : (tensor<64x128xf32>, tensor<64x128xf32>, tensor<64x128xf32>) -> tensor<64x128xf32>
+  // CHECK: "ttnn.ge"
+  // CHECK-SAME: tensor<64x128xf32
+  // CHECK-SAME: tensor<64x128xf32
+  // CHECK-SAME: -> tensor<64x128xf32
   return %1 : tensor<64x128xf32>
 }
diff --git a/test/ttmlir/Silicon/TTNN/n150/simple_logical.mlir b/test/ttmlir/Silicon/TTNN/n150/eltwise/binary/logical/simple_logical.mlir
similarity index 54%
rename from test/ttmlir/Silicon/TTNN/n150/simple_logical.mlir
rename to test/ttmlir/Silicon/TTNN/n150/eltwise/binary/logical/simple_logical.mlir
index 558f815c71..9242787619 100644
--- a/test/ttmlir/Silicon/TTNN/n150/simple_logical.mlir
+++ b/test/ttmlir/Silicon/TTNN/n150/eltwise/binary/logical/simple_logical.mlir
@@ -1,47 +1,34 @@
 // RUN: ttmlir-opt --ttir-to-ttnn-backend-pipeline="system-desc-path=%system_desc_path%" %s > %t.mlir
 // RUN: FileCheck %s --input-file=%t.mlir
 // RUN: ttmlir-translate --ttnn-to-flatbuffer %t.mlir > %t.ttnn
+
 module attributes {} {
   func.func @logical_and(%arg0: tensor<64x128xf32>, %arg1: tensor<64x128xf32>) -> tensor<64x128xf32> {
     %0 = tensor.empty() : tensor<64x128xf32>
-    // CHECK: {{.*}} = "ttnn.empty"{{.*}}
     %1 = "ttir.logical_and"(%arg0, %arg1, %0) <{operandSegmentSizes = array<i32: 2, 1>}> : (tensor<64x128xf32>, tensor<64x128xf32>, tensor<64x128xf32>) -> tensor<64x128xf32>
-    // CHECK: %[[C:.*]] = "ttnn.logical_and"
-    // CHECK-SAME: tensor<64x128xf32,
-    // CHECK-SAME: tensor<64x128xf32,
-    // CHECK-SAME: tensor<64x128xf32,
-    return %1 : tensor<64x128xf32>
-  }
-
-  func.func @logical_not(%arg0: tensor<64x128xf32>) -> tensor<64x128xf32> {
-    %0 = tensor.empty() : tensor<64x128xf32>
-    // CHECK: {{.*}} = "ttnn.empty"{{.*}}
-    %1 = "ttir.logical_not"(%arg0, %0) <{operandSegmentSizes = array<i32: 1, 1>}> : (tensor<64x128xf32>, tensor<64x128xf32>) -> tensor<64x128xf32>
-    // CHECK: %[[C:.*]] = "ttnn.logical_not"
-    // CHECK-SAME: tensor<64x128xf32,
-    // CHECK-SAME: tensor<64x128xf32,
+    // CHECK: "ttnn.logical_and"
+    // CHECK-SAME: tensor<64x128xf32
+    // CHECK-SAME: tensor<64x128xf32
+    // CHECK-SAME: -> tensor<64x128xf32
     return %1 : tensor<64x128xf32>
   }
 
   func.func @logical_or(%arg0: tensor<64x128xf32>, %arg1: tensor<64x128xf32>) -> tensor<64x128xf32> {
     %0 = tensor.empty() : tensor<64x128xf32>
-    // CHECK: {{.*}} = "ttnn.empty"{{.*}}
     %1 = "ttir.logical_or"(%arg0, %arg1, %0) <{operandSegmentSizes = array<i32: 2, 1>}> : (tensor<64x128xf32>, tensor<64x128xf32>, tensor<64x128xf32>) -> tensor<64x128xf32>
-    // CHECK: %[[C:.*]] = "ttnn.logical_or"
-    // CHECK-SAME: tensor<64x128xf32,
-    // CHECK-SAME: tensor<64x128xf32,
-    // CHECK-SAME: tensor<64x128xf32,
+    // CHECK: "ttnn.logical_or"
+    // CHECK-SAME: tensor<64x128xf32
+    // CHECK-SAME: tensor<64x128xf32
+    // CHECK-SAME: -> tensor<64x128xf32
     return %1 : tensor<64x128xf32>
   }
 
   func.func @logical_xor(%arg0: tensor<64x128xbf16>, %arg1: tensor<64x128xbf16>) -> tensor<64x128xbf16> {
-    // CHECK: %{{[0-9]+}} = "ttnn.empty"{{.*}} [[TENSOR:tensor<64x128xbf16]]
     %0 = tensor.empty() : tensor<64x128xbf16>
-    // CHECK: %{{[0-9]+}} = "ttnn.logical_xor"
-    // CHECK-SAME: [[TENSOR]]
-    // CHECK-SAME: [[TENSOR]]
-    // CHECK-SAME: [[TENSOR]]
-    // CHECK-SAME: -> [[TENSOR]]
+    // CHECK: "ttnn.logical_xor"
+    // CHECK-SAME: tensor<64x128xbf16
+    // CHECK-SAME: tensor<64x128xbf16
+    // CHECK-SAME: -> tensor<64x128xbf16
     %1 = "ttir.logical_xor"(%arg0, %arg1, %0) <{operandSegmentSizes = array<i32: 2, 1>}> : (tensor<64x128xbf16>, tensor<64x128xbf16>, tensor<64x128xbf16>) -> tensor<64x128xbf16>
     return %1 : tensor<64x128xbf16>
   }
diff --git a/test/ttmlir/Silicon/TTNN/n150/eltwise/binary/maximum/maximum.mlir b/test/ttmlir/Silicon/TTNN/n150/eltwise/binary/maximum/maximum.mlir
index 2659cccdce..a8df2de34d 100644
--- a/test/ttmlir/Silicon/TTNN/n150/eltwise/binary/maximum/maximum.mlir
+++ b/test/ttmlir/Silicon/TTNN/n150/eltwise/binary/maximum/maximum.mlir
@@ -3,9 +3,11 @@
 // RUN: ttmlir-translate --ttnn-to-flatbuffer %t.mlir > %t.ttnn
 
 func.func @maximum(%arg0: tensor<64x128xf32>, %arg1: tensor<64x128xf32>) -> tensor<64x128xf32> {
-  // CHECK: %[[C:.*]] = "ttnn.empty"[[C:.*]]
   %0 = tensor.empty() : tensor<64x128xf32>
-  // CHECK: %[[C:.*]] = "ttnn.maximum"[[C:.*]]
   %1 = "ttir.maximum"(%arg0, %arg1, %0) <{operandSegmentSizes = array<i32: 2, 1>}> : (tensor<64x128xf32>, tensor<64x128xf32>, tensor<64x128xf32>) -> tensor<64x128xf32>
+  // CHECK: "ttnn.maximum"
+  // CHECK-SAME: tensor<64x128xf32
+  // CHECK-SAME: tensor<64x128xf32
+  // CHECK-SAME: -> tensor<64x128xf32
   return %1 : tensor<64x128xf32>
 }
diff --git a/test/ttmlir/Silicon/TTNN/n150/eltwise/binary/minimum/minimum.mlir b/test/ttmlir/Silicon/TTNN/n150/eltwise/binary/minimum/minimum.mlir
index 8272db6e6a..36f892d2b9 100644
--- a/test/ttmlir/Silicon/TTNN/n150/eltwise/binary/minimum/minimum.mlir
+++ b/test/ttmlir/Silicon/TTNN/n150/eltwise/binary/minimum/minimum.mlir
@@ -3,14 +3,11 @@
 // RUN: ttmlir-translate --ttnn-to-flatbuffer %t.mlir > %t.ttnn
 
 func.func @minimum(%arg0: tensor<64x128xf32>, %arg1: tensor<64x128xf32>) -> tensor<64x128xf32> {
-  // CHECK: %[[C:.*]] = "ttnn.empty"
-  // CHECK-SAME: [[TENSOR:tensor<64x128xf32,]]
   %0 = tensor.empty() : tensor<64x128xf32>
-  // CHECK: %[[C:.*]] = "ttnn.minimum"
-  // CHECK-SAME: [[TENSOR]]
-  // CHECK-SAME: [[TENSOR]]
-  // CHECK-SAME: [[TENSOR]]
-  // CHECK-SAME: -> [[TENSOR]]
   %1 = "ttir.minimum"(%arg0, %arg1, %0) <{operandSegmentSizes = array<i32: 2, 1>}> : (tensor<64x128xf32>, tensor<64x128xf32>, tensor<64x128xf32>) -> tensor<64x128xf32>
+  // CHECK: "ttnn.minimum"
+  // CHECK-SAME: tensor<64x128xf32
+  // CHECK-SAME: tensor<64x128xf32
+  // CHECK-SAME: -> tensor<64x128xf32
   return %1 : tensor<64x128xf32>
 }
diff --git a/test/ttmlir/Silicon/TTNN/n150/eltwise/binary/multiply/multiply.mlir b/test/ttmlir/Silicon/TTNN/n150/eltwise/binary/multiply/multiply.mlir
index 2edabb7470..74beef9bf9 100644
--- a/test/ttmlir/Silicon/TTNN/n150/eltwise/binary/multiply/multiply.mlir
+++ b/test/ttmlir/Silicon/TTNN/n150/eltwise/binary/multiply/multiply.mlir
@@ -3,9 +3,11 @@
 // RUN: ttmlir-translate --ttnn-to-flatbuffer %t.mlir > %t.ttnn
 
 func.func @multiply(%arg0: tensor<64x128xf32>, %arg1: tensor<64x128xf32>) -> tensor<64x128xf32> {
-  // CHECK: %[[C:.*]] = "ttnn.empty"[[C:.*]]
   %0 = tensor.empty() : tensor<64x128xf32>
-  // CHECK: %[[C:.*]] = "ttnn.multiply"[[C:.*]]
   %1 = "ttir.multiply"(%arg0, %arg1, %0) <{operandSegmentSizes = array<i32: 2, 1>}> : (tensor<64x128xf32>, tensor<64x128xf32>, tensor<64x128xf32>) -> tensor<64x128xf32>
+  // CHECK: "ttnn.multiply"
+  // CHECK-SAME: tensor<64x128xf32
+  // CHECK-SAME: tensor<64x128xf32
+  // CHECK-SAME: -> tensor<64x128xf32
   return %1 : tensor<64x128xf32>
 }
diff --git a/test/ttmlir/Silicon/TTNN/n150/eltwise/binary/power/power.mlir b/test/ttmlir/Silicon/TTNN/n150/eltwise/binary/power/power.mlir
index 7b4eefe9e1..7579c9410b 100644
--- a/test/ttmlir/Silicon/TTNN/n150/eltwise/binary/power/power.mlir
+++ b/test/ttmlir/Silicon/TTNN/n150/eltwise/binary/power/power.mlir
@@ -1,11 +1,13 @@
 // RUN: ttmlir-opt --ttir-to-ttnn-backend-pipeline="system-desc-path=%system_desc_path%" %s > %t.mlir
 // RUN: FileCheck %s --input-file=%t.mlir
 // RUN: ttmlir-translate --ttnn-to-flatbuffer %t.mlir > %t.ttnn
+
 func.func @power(%arg0: tensor<32x32xf32>, %arg1: tensor<32x32xf32>) -> tensor<32x32xf32> {
   %0 = tensor.empty() : tensor<32x32xf32>
-  // CHECK: %[[EMPTY:.*]] = "ttnn.empty"{{.*}} -> tensor<32x32xf32, {{.*}}
   %1 = "ttir.power"(%arg0, %arg1, %0) <{operandSegmentSizes = array<i32: 2, 1>}> : (tensor<32x32xf32>, tensor<32x32xf32>, tensor<32x32xf32>) -> tensor<32x32xf32>
-  // CHECK: %[[REM:[0-9]+]] = "ttnn.pow"({{.*}}, {{.*}}, %[[EMPTY]]){{.*}} -> tensor<32x32xf32, {{.*}}
+  // CHECK: "ttnn.pow"
+  // CHECK-SAME: tensor<32x32xf32
+  // CHECK-SAME: tensor<32x32xf32
+  // CHECK-SAME: -> tensor<32x32xf32
   return %1 : tensor<32x32xf32>
-  // CHECK: return {{.*}} : tensor<32x32xf32, {{.*}}
 }
diff --git a/test/ttmlir/Silicon/TTNN/n150/eltwise/binary/remainder/remainder.mlir b/test/ttmlir/Silicon/TTNN/n150/eltwise/binary/remainder/remainder.mlir
index dbcff9d786..71eb85f36c 100644
--- a/test/ttmlir/Silicon/TTNN/n150/eltwise/binary/remainder/remainder.mlir
+++ b/test/ttmlir/Silicon/TTNN/n150/eltwise/binary/remainder/remainder.mlir
@@ -4,9 +4,10 @@
 
 func.func @remainder(%arg0: tensor<32x32xf32>, %arg1: tensor<32x32xf32>) -> tensor<32x32xf32> {
   %0 = tensor.empty() : tensor<32x32xf32>
-  // CHECK: %[[EMPTY:.*]] = "ttnn.empty"{{.*}} -> tensor<32x32xf32, {{.*}}
   %1 = "ttir.remainder"(%arg0, %arg1, %0) <{operandSegmentSizes = array<i32: 2, 1>}> : (tensor<32x32xf32>, tensor<32x32xf32>, tensor<32x32xf32>) -> tensor<32x32xf32>
-  // CHECK: %[[REM:[0-9]+]] = "ttnn.remainder"({{.*}}, {{.*}}, %[[EMPTY]]){{.*}} -> tensor<32x32xf32, {{.*}}
+  // CHECK: "ttnn.remainder"
+  // CHECK-SAME: tensor<32x32xf32
+  // CHECK-SAME: tensor<32x32xf32
+  // CHECK-SAME: -> tensor<32x32xf32
   return %1 : tensor<32x32xf32>
-  // CHECK: return {{.*}} : tensor<32x32xf32, {{.*}}
 }
diff --git a/test/ttmlir/Silicon/TTNN/n150/eltwise/binary/subtract/subtract.mlir b/test/ttmlir/Silicon/TTNN/n150/eltwise/binary/subtract/subtract.mlir
index d7a84fd159..3719444c80 100644
--- a/test/ttmlir/Silicon/TTNN/n150/eltwise/binary/subtract/subtract.mlir
+++ b/test/ttmlir/Silicon/TTNN/n150/eltwise/binary/subtract/subtract.mlir
@@ -3,9 +3,11 @@
 // RUN: ttmlir-translate --ttnn-to-flatbuffer %t.mlir > %t.ttnn
 
 func.func @subtract(%arg0: tensor<64x128xf32>, %arg1: tensor<64x128xf32>) -> tensor<64x128xf32> {
-  // CHECK: %[[C:.*]] = "ttnn.empty"[[C:.*]]
   %0 = tensor.empty() : tensor<64x128xf32>
-  // CHECK: %[[C:.*]] = "ttnn.subtract"[[C:.*]]
   %1 = "ttir.subtract"(%arg0, %arg1, %0) <{operandSegmentSizes = array<i32: 2, 1>}> : (tensor<64x128xf32>, tensor<64x128xf32>, tensor<64x128xf32>) -> tensor<64x128xf32>
+  // CHECK: "ttnn.subtract"
+  // CHECK-SAME: tensor<64x128xf32
+  // CHECK-SAME: tensor<64x128xf32
+  // CHECK-SAME: -> tensor<64x128xf32
   return %1 : tensor<64x128xf32>
 }
diff --git a/test/ttmlir/Silicon/TTNN/n150/eltwise/ternary/where/where.mlir b/test/ttmlir/Silicon/TTNN/n150/eltwise/ternary/where/where.mlir
index ced442b91f..9d450ebacc 100644
--- a/test/ttmlir/Silicon/TTNN/n150/eltwise/ternary/where/where.mlir
+++ b/test/ttmlir/Silicon/TTNN/n150/eltwise/ternary/where/where.mlir
@@ -7,8 +7,7 @@ func.func @test_where(%arg0: tensor<13x37xbf16>, %arg1: tensor<13x37xbf16>) -> t
   %1 = "ttir.eq"(%arg0, %arg1, %0) <{operandSegmentSizes = array<i32: 2, 1>}> : (tensor<13x37xbf16>, tensor<13x37xbf16>, tensor<13x37xbf16>) -> tensor<13x37xbf16>
   %2 = tensor.empty() : tensor<13x37xbf16>
   %3 = "ttir.where"(%1, %arg0, %arg1, %2) <{operandSegmentSizes = array<i32: 3, 1>}> : (tensor<13x37xbf16>, tensor<13x37xbf16>, tensor<13x37xbf16>, tensor<13x37xbf16>) -> tensor<13x37xbf16>
-  // CHECK: %[[EMPTY:.*]] = "ttnn.empty"{{.*}}
-  // CHECK: %[[VAL1:[0-9]+]] = "ttnn.eq"(%arg0, %arg1, %[[EMPTY]])
-  // CHECK: %{{[0-9]+}} = "ttnn.where"(%[[VAL1]], %arg0, %arg1, %{{[0-9]+}})
+  // CHECK: "ttnn.eq"
+  // CHECK: "ttnn.where"
   return %3 : tensor<13x37xbf16>
 }
diff --git a/test/ttmlir/Silicon/TTNN/n150/eltwise/unary/cbrt/cbrt.mlir b/test/ttmlir/Silicon/TTNN/n150/eltwise/unary/cbrt/cbrt.mlir
index a2833f7053..4a077e60d2 100644
--- a/test/ttmlir/Silicon/TTNN/n150/eltwise/unary/cbrt/cbrt.mlir
+++ b/test/ttmlir/Silicon/TTNN/n150/eltwise/unary/cbrt/cbrt.mlir
@@ -3,9 +3,10 @@
 // RUN: ttmlir-translate --ttnn-to-flatbuffer %t.mlir > %t.ttnn
 
 func.func @cbrt(%arg0: tensor<64x128xf32>) -> tensor<64x128xf32> {
-  // CHECK: %[[C:.*]] = "ttnn.empty"[[C:.*]]
   %0 = tensor.empty() : tensor<64x128xf32>
-  // CHECK: %[[C:.*]] = "ttnn.cbrt"[[C:.*]]
   %1 = "ttir.cbrt"(%arg0, %0) <{operandSegmentSizes = array<i32: 1, 1>}> : (tensor<64x128xf32>, tensor<64x128xf32>) -> tensor<64x128xf32>
+  // CHECK: "ttnn.cbrt"
+  // CHECK-SAME: tensor<64x128xf32
+  // CHECK-SAME: -> tensor<64x128xf32
   return %1 : tensor<64x128xf32>
 }
diff --git a/test/ttmlir/Silicon/TTNN/n150/eltwise/unary/ceil/ceil.mlir b/test/ttmlir/Silicon/TTNN/n150/eltwise/unary/ceil/ceil.mlir
index 934599eb74..df28d6c399 100644
--- a/test/ttmlir/Silicon/TTNN/n150/eltwise/unary/ceil/ceil.mlir
+++ b/test/ttmlir/Silicon/TTNN/n150/eltwise/unary/ceil/ceil.mlir
@@ -4,8 +4,9 @@
 
 func.func @ceil(%arg0: tensor<32x32xf32>) -> tensor<32x32xf32> {
   %0 = tensor.empty() : tensor<32x32xf32>
-  // CHECK: [[VAL0:%[0-9]+]] = "ttnn.empty"(%{{[0-9]+}})
-  // CHECK: %{{[0-9]+}} = "ttnn.ceil"(%arg0, [[VAL0]])
   %1 = "ttir.ceil"(%arg0, %0) <{operandSegmentSizes = array<i32: 1, 1>}> : (tensor<32x32xf32>, tensor<32x32xf32>) -> tensor<32x32xf32>
+  // CHECK: "ttnn.ceil"
+  // CHECK-SAME: tensor<32x32xf32
+  // CHECK-SAME: -> tensor<32x32xf32
   return %1 : tensor<32x32xf32>
 }
diff --git a/test/ttmlir/Silicon/TTNN/n150/eltwise/unary/clamp/clamp.mlir b/test/ttmlir/Silicon/TTNN/n150/eltwise/unary/clamp/clamp.mlir
index 63c17062ac..b7437ffc44 100644
--- a/test/ttmlir/Silicon/TTNN/n150/eltwise/unary/clamp/clamp.mlir
+++ b/test/ttmlir/Silicon/TTNN/n150/eltwise/unary/clamp/clamp.mlir
@@ -4,8 +4,10 @@
 
 func.func @clamp(%arg0: tensor<64x128xbf16>) -> tensor<64x128xbf16> {
   %0 = tensor.empty() : tensor<64x128xbf16>
-  // CHECK: "ttnn.clamp"(%arg0)
-  // CHECK-SAME: {max = 3.000000e+00 : f32, min = 2.000000e+00 : f32}
   %1 = "ttir.clamp"(%arg0, %0) <{max = 3.000000e+00 : f32, min = 2.000000e+00 : f32}> : (tensor<64x128xbf16>, tensor<64x128xbf16>) -> tensor<64x128xbf16>
+  // CHECK: "ttnn.clamp"
+  // CHECK-SAME: {max = 3.000000e+00 : f32, min = 2.000000e+00 : f32}
+  // CHECK-SAME: tensor<64x128xbf16
+  // CHECK-SAME: -> tensor<64x128xbf16
   return %1 : tensor<64x128xbf16>
 }
diff --git a/test/ttmlir/Silicon/TTNN/n150/eltwise/unary/cosine/cosine.mlir b/test/ttmlir/Silicon/TTNN/n150/eltwise/unary/cosine/cosine.mlir
index 2391f68249..c8b0223e30 100644
--- a/test/ttmlir/Silicon/TTNN/n150/eltwise/unary/cosine/cosine.mlir
+++ b/test/ttmlir/Silicon/TTNN/n150/eltwise/unary/cosine/cosine.mlir
@@ -4,8 +4,9 @@
 
 func.func @cosine(%arg0: tensor<32x32xf32>) -> tensor<32x32xf32> {
   %0 = tensor.empty() : tensor<32x32xf32>
-  // CHECK: [[VAL0:%[0-9]+]] = "ttnn.empty"(%{{[0-9]+}})
-  // CHECK: %{{[0-9]+}} = "ttnn.cos"(%arg0, [[VAL0]])
   %1 = "ttir.cos"(%arg0, %0) <{operandSegmentSizes = array<i32: 1, 1>}> : (tensor<32x32xf32>, tensor<32x32xf32>) -> tensor<32x32xf32>
+  // CHECK: "ttnn.cos"
+  // CHECK-SAME: tensor<32x32xf32
+  // CHECK-SAME: -> tensor<32x32xf32
   return %1 : tensor<32x32xf32>
 }
diff --git a/test/ttmlir/Silicon/TTNN/n150/eltwise/unary/expm1/expm1.mlir b/test/ttmlir/Silicon/TTNN/n150/eltwise/unary/expm1/expm1.mlir
index fc95c1ae07..81533c0d1d 100644
--- a/test/ttmlir/Silicon/TTNN/n150/eltwise/unary/expm1/expm1.mlir
+++ b/test/ttmlir/Silicon/TTNN/n150/eltwise/unary/expm1/expm1.mlir
@@ -4,9 +4,9 @@
 
 func.func @expm1(%arg0: tensor<64x128xf32>) -> tensor<64x128xf32> {
   %0 = tensor.empty() : tensor<64x128xf32>
-  // CHECK: [[VAL0:%[0-9]+]] = "ttnn.empty"(%{{[0-9]+}}) <{dtype = {{.*}}, layout = {{.*}}, memory_config = {{.*}}, <{{.*}}>>, shape = #ttnn.shape<[[TENSOR_SHAPE:[0-9]+x[0-9]+]]>}>
   %1 = "ttir.expm1"(%arg0, %0) <{operandSegmentSizes = array<i32: 1, 1>}> : (tensor<64x128xf32>, tensor<64x128xf32>) -> tensor<64x128xf32>
-  // CHECK: %{{[0-9]+}} = "ttnn.expm1"(%arg0, [[VAL0]]) <{operandSegmentSizes = array<i32: 1, 1>}> : (tensor<[[TENSOR_SHAPE]]x{{.*}}, {{.*}}>, tensor<[[TENSOR_SHAPE]]x{{.*}}, {{.*}}) -> tensor<[[TENSOR_SHAPE]]x{{.*}}, {{.*}}>
+  // CHECK: "ttnn.expm1"
+  // CHECK-SAME: tensor<64x128xf32
+  // CHECK-SAME: -> tensor<64x128xf32
   return %1 : tensor<64x128xf32>
-  // CHECK: return %{{[0-9]+}} : tensor<[[TENSOR_SHAPE]]xf32, {{.*}}>
 }
diff --git a/test/ttmlir/Silicon/TTNN/n150/eltwise/unary/floor/floor.mlir b/test/ttmlir/Silicon/TTNN/n150/eltwise/unary/floor/floor.mlir
index 7af577c8e8..be34577ca6 100644
--- a/test/ttmlir/Silicon/TTNN/n150/eltwise/unary/floor/floor.mlir
+++ b/test/ttmlir/Silicon/TTNN/n150/eltwise/unary/floor/floor.mlir
@@ -3,13 +3,10 @@
 // RUN: ttmlir-translate --ttnn-to-flatbuffer %t.mlir > %t.ttnn
 
 func.func @floor(%arg0: tensor<64x128xf32>) -> tensor<64x128xf32> {
-  // CHECK: %{{[0-9]+}} = "ttnn.empty"
-  // CHECK-SAME: [[TENSOR:tensor<64x128xf32,]]
   %0 = tensor.empty() : tensor<64x128xf32>
-  // CHECK: %{{[0-9]+}} = "ttnn.floor"
-  // CHECK-SAME: [[TENSOR]]
-  // CHECK-SAME: [[TENSOR]]
-  // CHECK-SAME: -> [[TENSOR]]
   %1 = "ttir.floor"(%arg0, %0) <{operandSegmentSizes = array<i32: 1, 1>}> : (tensor<64x128xf32>, tensor<64x128xf32>) -> tensor<64x128xf32>
+  // CHECK: "ttnn.floor"
+  // CHECK-SAME: tensor<64x128xf32
+  // CHECK-SAME: -> tensor<64x128xf32
   return %1 : tensor<64x128xf32>
 }
diff --git a/test/ttmlir/Silicon/TTNN/n150/eltwise/unary/gelu/gelu.mlir b/test/ttmlir/Silicon/TTNN/n150/eltwise/unary/gelu/gelu.mlir
index 7e9767e1fd..8f2bf48737 100644
--- a/test/ttmlir/Silicon/TTNN/n150/eltwise/unary/gelu/gelu.mlir
+++ b/test/ttmlir/Silicon/TTNN/n150/eltwise/unary/gelu/gelu.mlir
@@ -3,13 +3,10 @@
 // RUN: ttmlir-translate --ttnn-to-flatbuffer %t.mlir > %t.ttnn
 
 func.func @gelu(%arg0: tensor<64x128xf32>) -> tensor<64x128xf32> {
-  // CHECK: "ttnn.empty"
-  // CHECK-SAME: tensor<64x128xf32,
   %0 = tensor.empty() : tensor<64x128xf32>
-  // CHECK: "ttnn.gelu"
-  // CHECK-SAME: tensor<64x128xf32,
-  // CHECK-SAME: tensor<64x128xf32,
-  // CHECK-SAME: tensor<64x128xf32,
   %1 = "ttir.gelu"(%arg0, %0) <{operandSegmentSizes = array<i32: 1, 1>}> : (tensor<64x128xf32>, tensor<64x128xf32>) -> tensor<64x128xf32>
+  // CHECK: "ttnn.gelu"
+  // CHECK-SAME: tensor<64x128xf32
+  // CHECK-SAME: -> tensor<64x128xf32
   return %1 : tensor<64x128xf32>
 }
diff --git a/test/ttmlir/Silicon/TTNN/n150/eltwise/unary/is_finite/is_finite.mlir b/test/ttmlir/Silicon/TTNN/n150/eltwise/unary/is_finite/is_finite.mlir
index b8dc64fb72..a9ae0d5b0c 100644
--- a/test/ttmlir/Silicon/TTNN/n150/eltwise/unary/is_finite/is_finite.mlir
+++ b/test/ttmlir/Silicon/TTNN/n150/eltwise/unary/is_finite/is_finite.mlir
@@ -3,13 +3,10 @@
 // RUN: ttmlir-translate --ttnn-to-flatbuffer %t.mlir > %t.ttnn
 
 func.func @is_finite(%arg0: tensor<64x128xbf16>) -> tensor<64x128xbf16> {
-  // CHECK: %[[C:.*]] = "ttnn.empty"
-  // CHECK-SAME: [[TENSOR:tensor<64x128xbf16,]]
   %0 = tensor.empty() : tensor<64x128xbf16>
-  // CHECK: %[[C:.*]] = "ttnn.isfinite"
-  // CHECK-SAME: tensor<64x128xbf16,
-  // CHECK-SAME: [[TENSOR]]
-  // CHECK-SAME: -> [[TENSOR]]
   %1 = "ttir.isfinite"(%arg0, %0) <{operandSegmentSizes = array<i32: 1, 1>}> : (tensor<64x128xbf16>, tensor<64x128xbf16>) -> tensor<64x128xbf16>
+  // CHECK: "ttnn.isfinite"
+  // CHECK-SAME: tensor<64x128xbf16
+  // CHECK-SAME: -> tensor<64x128xbf16
   return %1 : tensor<64x128xbf16>
 }
diff --git a/test/ttmlir/Silicon/TTNN/n150/eltwise/unary/leaky_relu/leaky_relu.mlir b/test/ttmlir/Silicon/TTNN/n150/eltwise/unary/leaky_relu/leaky_relu.mlir
index 018fa352ee..c11b5e110f 100644
--- a/test/ttmlir/Silicon/TTNN/n150/eltwise/unary/leaky_relu/leaky_relu.mlir
+++ b/test/ttmlir/Silicon/TTNN/n150/eltwise/unary/leaky_relu/leaky_relu.mlir
@@ -3,9 +3,11 @@
 // RUN: ttmlir-translate --ttnn-to-flatbuffer %t.mlir > %t.ttnn
 
 func.func @leaky_relu(%arg0: tensor<64x128xf32>) -> tensor<64x128xf32> {
-    // CHECK: %[[C:.*]] = "ttnn.empty"
     %0 = tensor.empty() : tensor<64x128xf32>
-    // CHECK: %[[C:.*]] = "ttnn.leaky_relu"
     %1 = "ttir.leaky_relu"(%arg0, %0) <{parameter = 0.01 : f32, operandSegmentSizes = array<i32: 1, 1>}> : (tensor<64x128xf32>, tensor<64x128xf32>) -> tensor<64x128xf32>
+    // CHECK: "ttnn.leaky_relu"
+    // CHECK-SAME: <{parameter = 0.00999999977 : f32}>
+    // CHECK-SAME: tensor<64x128xf32
+    // CHECK-SAME: -> tensor<64x128xf32
     return %1 : tensor<64x128xf32>
 }
diff --git a/test/ttmlir/Silicon/TTNN/n150/eltwise/unary/log/log.mlir b/test/ttmlir/Silicon/TTNN/n150/eltwise/unary/log/log.mlir
index fa21eb24cc..42c9e463a2 100644
--- a/test/ttmlir/Silicon/TTNN/n150/eltwise/unary/log/log.mlir
+++ b/test/ttmlir/Silicon/TTNN/n150/eltwise/unary/log/log.mlir
@@ -3,9 +3,10 @@
 // RUN: ttmlir-translate --ttnn-to-flatbuffer %t.mlir > %t.ttnn
 
 func.func @log(%arg0: tensor<64x128xf32>, %arg1: tensor<64x128xf32>) -> tensor<64x128xf32> {
-  // CHECK: %[[C:.*]] = "ttnn.empty"[[C:.*]]
   %0 = tensor.empty() : tensor<64x128xf32>
-  // CHECK: %[[C:.*]] = "ttnn.log"[[C:.*]]
   %1 = "ttir.log"(%arg0, %0) <{operandSegmentSizes = array<i32: 1, 1>}> : (tensor<64x128xf32>, tensor<64x128xf32>) -> tensor<64x128xf32>
+  // CHECK: "ttnn.log"
+  // CHECK-SAME: tensor<64x128xf32
+  // CHECK-SAME: -> tensor<64x128xf32
   return %1 : tensor<64x128xf32>
 }
diff --git a/test/ttmlir/Silicon/TTNN/n150/eltwise/unary/log1p/log1p.mlir b/test/ttmlir/Silicon/TTNN/n150/eltwise/unary/log1p/log1p.mlir
index efdd6b8fe0..e25f17b1dc 100644
--- a/test/ttmlir/Silicon/TTNN/n150/eltwise/unary/log1p/log1p.mlir
+++ b/test/ttmlir/Silicon/TTNN/n150/eltwise/unary/log1p/log1p.mlir
@@ -4,9 +4,9 @@
 
 func.func @log1p(%arg0: tensor<64x128xf32>) -> tensor<64x128xf32> {
   %0 = tensor.empty() : tensor<64x128xf32>
-  // CHECK: [[VAL0:%[0-9]+]] = "ttnn.empty"(%{{[0-9]+}}) <{dtype = {{.*}}, layout = {{.*}}, memory_config = {{.*}}, <{{.*}}>>, shape = #ttnn.shape<[[TENSOR_SHAPE:[0-9]+x[0-9]+]]>}>
   %1 = "ttir.log1p"(%arg0, %0) <{operandSegmentSizes = array<i32: 1, 1>}> : (tensor<64x128xf32>, tensor<64x128xf32>) -> tensor<64x128xf32>
-  // CHECK: %{{[0-9]+}} = "ttnn.log1p"(%arg0, [[VAL0]]) <{operandSegmentSizes = array<i32: 1, 1>}> : (tensor<[[TENSOR_SHAPE]]x{{.*}}, {{.*}}>, tensor<[[TENSOR_SHAPE]]x{{.*}}, {{.*}}) -> tensor<[[TENSOR_SHAPE]]x{{.*}}, {{.*}}>
+  // CHECK: "ttnn.log1p"
+  // CHECK-SAME: tensor<64x128xf32
+  // CHECK-SAME: -> tensor<64x128xf32
   return %1 : tensor<64x128xf32>
-  // CHECK: return %{{[0-9]+}} : tensor<[[TENSOR_SHAPE]]xf32, {{.*}}>
 }
diff --git a/test/ttmlir/Silicon/TTNN/n150/eltwise/unary/logical_not/simple_not.mlir b/test/ttmlir/Silicon/TTNN/n150/eltwise/unary/logical_not/simple_not.mlir
new file mode 100644
index 0000000000..5cba3fbe81
--- /dev/null
+++ b/test/ttmlir/Silicon/TTNN/n150/eltwise/unary/logical_not/simple_not.mlir
@@ -0,0 +1,14 @@
+// RUN: ttmlir-opt --ttir-to-ttnn-backend-pipeline="system-desc-path=%system_desc_path%" %s > %t.mlir
+// RUN: FileCheck %s --input-file=%t.mlir
+// RUN: ttmlir-translate --ttnn-to-flatbuffer %t.mlir > %t.ttnn
+
+module attributes {} {
+  func.func @logical_not(%arg0: tensor<64x128xf32>) -> tensor<64x128xf32> {
+    %0 = tensor.empty() : tensor<64x128xf32>
+    %1 = "ttir.logical_not"(%arg0, %0) <{operandSegmentSizes = array<i32: 1, 1>}> : (tensor<64x128xf32>, tensor<64x128xf32>) -> tensor<64x128xf32>
+    // CHECK: "ttnn.logical_not"
+    // CHECK-SAME: tensor<64x128xf32
+    // CHECK-SAME: -> tensor<64x128xf32
+    return %1 : tensor<64x128xf32>
+  }
+}
diff --git a/test/ttmlir/Silicon/TTNN/n150/eltwise/unary/negate/negate.mlir b/test/ttmlir/Silicon/TTNN/n150/eltwise/unary/negate/negate.mlir
index 5173e6d920..f7c7942e59 100644
--- a/test/ttmlir/Silicon/TTNN/n150/eltwise/unary/negate/negate.mlir
+++ b/test/ttmlir/Silicon/TTNN/n150/eltwise/unary/negate/negate.mlir
@@ -4,7 +4,9 @@
 
 func.func @negate(%arg0: tensor<32x32xf32>) -> tensor<32x32xf32> {
   %0 = tensor.empty() : tensor<32x32xf32>
-  // CHECK: %[[C:.*]] = "ttnn.neg"[[C:.*]]
   %1 = "ttir.neg"(%arg0, %0) <{operandSegmentSizes = array<i32: 1, 1>}> : (tensor<32x32xf32>, tensor<32x32xf32>) -> tensor<32x32xf32>
+  // CHECK: "ttnn.neg"
+  // CHECK-SAME: tensor<32x32xf32
+  // CHECK-SAME: -> tensor<32x32xf32
   return %1 : tensor<32x32xf32>
 }
diff --git a/test/ttmlir/Silicon/TTNN/n150/eltwise/unary/recipricol/recipricol.mlir b/test/ttmlir/Silicon/TTNN/n150/eltwise/unary/recipricol/recipricol.mlir
index a05f62da9f..141076aee9 100644
--- a/test/ttmlir/Silicon/TTNN/n150/eltwise/unary/recipricol/recipricol.mlir
+++ b/test/ttmlir/Silicon/TTNN/n150/eltwise/unary/recipricol/recipricol.mlir
@@ -3,9 +3,10 @@
 // RUN: ttmlir-translate --ttnn-to-flatbuffer %t.mlir > %t.ttnn
 
 func.func @reciprocal(%arg0: tensor<64x128xf32>) -> tensor<64x128xf32> {
-  // CHECK: %[[C:.*]] = "ttnn.empty"[[C:.*]]
   %0 = tensor.empty() : tensor<64x128xf32>
-  // CHECK: %[[C:.*]] = "ttnn.reciprocal"[[C:.*]]
   %1 = "ttir.reciprocal"(%arg0, %0) <{operandSegmentSizes = array<i32: 1, 1>}> : (tensor<64x128xf32>, tensor<64x128xf32>) -> tensor<64x128xf32>
+  // CHECK: "ttnn.reciprocal"
+  // CHECK-SAME: tensor<64x128xf32
+  // CHECK-SAME: -> tensor<64x128xf32
   return %1 : tensor<64x128xf32>
 }
diff --git a/test/ttmlir/Silicon/TTNN/n150/eltwise/unary/relu/relu.mlir b/test/ttmlir/Silicon/TTNN/n150/eltwise/unary/relu/relu.mlir
index 3a75ad988a..86865f7a53 100644
--- a/test/ttmlir/Silicon/TTNN/n150/eltwise/unary/relu/relu.mlir
+++ b/test/ttmlir/Silicon/TTNN/n150/eltwise/unary/relu/relu.mlir
@@ -3,9 +3,10 @@
 // RUN: ttmlir-translate --ttnn-to-flatbuffer %t.mlir > %t.ttnn
 
 func.func @relu(%arg0: tensor<64x128xf32>) -> tensor<64x128xf32> {
-  // CHECK: %[[C:.*]] = "ttnn.empty"[[C:.*]]
   %0 = tensor.empty() : tensor<64x128xf32>
-  // CHECK: %[[C:.*]] = "ttnn.relu"[[C:.*]]
   %1 = "ttir.relu"(%arg0, %0) <{operandSegmentSizes = array<i32: 1, 1>}> : (tensor<64x128xf32>, tensor<64x128xf32>) -> tensor<64x128xf32>
+  // CHECK: "ttnn.relu"
+  // CHECK-SAME: tensor<64x128xf32
+  // CHECK-SAME: -> tensor<64x128xf32
   return %1 : tensor<64x128xf32>
 }
diff --git a/test/ttmlir/Silicon/TTNN/n150/eltwise/unary/rsqrt/rsqrt.mlir b/test/ttmlir/Silicon/TTNN/n150/eltwise/unary/rsqrt/rsqrt.mlir
index e3ced09427..49522c70d1 100644
--- a/test/ttmlir/Silicon/TTNN/n150/eltwise/unary/rsqrt/rsqrt.mlir
+++ b/test/ttmlir/Silicon/TTNN/n150/eltwise/unary/rsqrt/rsqrt.mlir
@@ -3,9 +3,10 @@
 // RUN: ttmlir-translate --ttnn-to-flatbuffer %t.mlir > %t.ttnn
 
 func.func @rsqrt(%arg0: tensor<64x128xf32>) -> tensor<64x128xf32> {
-  // CHECK: %[[C:.*]] = "ttnn.empty"[[C:.*]]
   %0 = tensor.empty() : tensor<64x128xf32>
-  // CHECK: %[[C:.*]] = "ttnn.rsqrt"[[C:.*]]
   %1 = "ttir.rsqrt"(%arg0, %0) <{operandSegmentSizes = array<i32: 1, 1>}> : (tensor<64x128xf32>, tensor<64x128xf32>) -> tensor<64x128xf32>
+  // CHECK: "ttnn.rsqrt"
+  // CHECK-SAME: tensor<64x128xf32
+  // CHECK-SAME: -> tensor<64x128xf32
   return %1 : tensor<64x128xf32>
 }
diff --git a/test/ttmlir/Silicon/TTNN/n150/eltwise/unary/sigmoid/sigmoid.mlir b/test/ttmlir/Silicon/TTNN/n150/eltwise/unary/sigmoid/sigmoid.mlir
index b6ef7a5a44..b0f67ae3bf 100644
--- a/test/ttmlir/Silicon/TTNN/n150/eltwise/unary/sigmoid/sigmoid.mlir
+++ b/test/ttmlir/Silicon/TTNN/n150/eltwise/unary/sigmoid/sigmoid.mlir
@@ -3,9 +3,10 @@
 // RUN: ttmlir-translate --ttnn-to-flatbuffer %t.mlir > %t.ttnn
 
 func.func @sigmoid(%arg0: tensor<64x128xf32>) -> tensor<64x128xf32> {
-  // CHECK: %[[C:.*]] = "ttnn.empty"[[C:.*]]
   %0 = tensor.empty() : tensor<64x128xf32>
-  // CHECK: %[[C:.*]] = "ttnn.sigmoid"[[C:.*]]
   %1 = "ttir.sigmoid"(%arg0, %0) <{operandSegmentSizes = array<i32: 1, 1>}> : (tensor<64x128xf32>, tensor<64x128xf32>) -> tensor<64x128xf32>
+  // CHECK: "ttnn.sigmoid"
+  // CHECK-SAME: tensor<64x128xf32
+  // CHECK-SAME: -> tensor<64x128xf32
   return %1 : tensor<64x128xf32>
 }
diff --git a/test/ttmlir/Silicon/TTNN/n150/eltwise/unary/sign/sign.mlir b/test/ttmlir/Silicon/TTNN/n150/eltwise/unary/sign/sign.mlir
index 368d7f26af..1dfaa33d37 100644
--- a/test/ttmlir/Silicon/TTNN/n150/eltwise/unary/sign/sign.mlir
+++ b/test/ttmlir/Silicon/TTNN/n150/eltwise/unary/sign/sign.mlir
@@ -4,9 +4,9 @@
 
 func.func @sign(%arg0: tensor<64x128xf32>) -> tensor<64x128xf32> {
   %0 = tensor.empty() : tensor<64x128xf32>
-  // CHECK: [[VAL0:%[0-9]+]] = "ttnn.empty"(%{{[0-9]+}}) <{dtype = {{.*}}, layout = {{.*}}, memory_config = {{.*}}, <{{.*}}>>, shape = #ttnn.shape<[[TENSOR_SHAPE:[0-9]+x[0-9]+]]>}>
   %1 = "ttir.sign"(%arg0, %0) <{operandSegmentSizes = array<i32: 1, 1>}> : (tensor<64x128xf32>, tensor<64x128xf32>) -> tensor<64x128xf32>
-  // CHECK: %{{[0-9]+}} = "ttnn.sign"(%arg0, [[VAL0]]) <{operandSegmentSizes = array<i32: 1, 1>}> : (tensor<[[TENSOR_SHAPE]]x{{.*}}, {{.*}}>, tensor<[[TENSOR_SHAPE]]x{{.*}}, {{.*}}) -> tensor<[[TENSOR_SHAPE]]x{{.*}}, {{.*}}>
+  // CHECK: "ttnn.sign"
+  // CHECK-SAME: tensor<64x128xf32
+  // CHECK-SAME: -> tensor<64x128xf32
   return %1 : tensor<64x128xf32>
-  // CHECK: return %{{[0-9]+}} : tensor<[[TENSOR_SHAPE]]xf32, {{.*}}>
 }
diff --git a/test/ttmlir/Silicon/TTNN/n150/eltwise/unary/sine/sine.mlir b/test/ttmlir/Silicon/TTNN/n150/eltwise/unary/sine/sine.mlir
index ca61f435af..0e2e32be2e 100644
--- a/test/ttmlir/Silicon/TTNN/n150/eltwise/unary/sine/sine.mlir
+++ b/test/ttmlir/Silicon/TTNN/n150/eltwise/unary/sine/sine.mlir
@@ -4,8 +4,9 @@
 
 func.func @sine(%arg0: tensor<32x32xf32>) -> tensor<32x32xf32> {
   %0 = tensor.empty() : tensor<32x32xf32>
-  // CHECK: [[VAL0:%[0-9]+]] = "ttnn.empty"(%{{[0-9]+}})
-  // CHECK: %{{[0-9]+}} = "ttnn.sin"(%arg0, [[VAL0]])
   %1 = "ttir.sin"(%arg0, %0) <{operandSegmentSizes = array<i32: 1, 1>}> : (tensor<32x32xf32>, tensor<32x32xf32>) -> tensor<32x32xf32>
+  // CHECK: "ttnn.sin"
+  // CHECK-SAME: tensor<32x32xf32
+  // CHECK-SAME: -> tensor<32x32xf32
   return %1 : tensor<32x32xf32>
 }
diff --git a/test/ttmlir/Silicon/TTNN/n150/eltwise/unary/sqrt/sqrt.mlir b/test/ttmlir/Silicon/TTNN/n150/eltwise/unary/sqrt/sqrt.mlir
index 7c948b7ac1..49eb3632f8 100644
--- a/test/ttmlir/Silicon/TTNN/n150/eltwise/unary/sqrt/sqrt.mlir
+++ b/test/ttmlir/Silicon/TTNN/n150/eltwise/unary/sqrt/sqrt.mlir
@@ -3,9 +3,10 @@
 // RUN: ttmlir-translate --ttnn-to-flatbuffer %t.mlir > %t.ttnn
 
 func.func @sqrt(%arg0: tensor<64x128xf32>) -> tensor<64x128xf32> {
-  // CHECK: %[[C:.*]] = "ttnn.empty"[[C:.*]]
   %0 = tensor.empty() : tensor<64x128xf32>
-  // CHECK: %[[C:.*]] = "ttnn.sqrt"[[C:.*]]
   %1 = "ttir.sqrt"(%arg0, %0) <{operandSegmentSizes = array<i32: 1, 1>}> : (tensor<64x128xf32>, tensor<64x128xf32>) -> tensor<64x128xf32>
+  // CHECK: "ttnn.sqrt"
+  // CHECK-SAME: tensor<64x128xf32
+  // CHECK-SAME: -> tensor<64x128xf32
   return %1 : tensor<64x128xf32>
 }
diff --git a/test/ttmlir/Silicon/TTNN/n150/eltwise/unary/tan/tan.mlir b/test/ttmlir/Silicon/TTNN/n150/eltwise/unary/tan/tan.mlir
index c1c319dec2..881eaf49cf 100644
--- a/test/ttmlir/Silicon/TTNN/n150/eltwise/unary/tan/tan.mlir
+++ b/test/ttmlir/Silicon/TTNN/n150/eltwise/unary/tan/tan.mlir
@@ -4,8 +4,9 @@
 
 func.func @tan(%arg0: tensor<64x128xbf16>) -> tensor<64x128xbf16> {
   %0 = tensor.empty() : tensor<64x128xbf16>
-  // CHECK: [[VAL0:%[0-9]+]] = "ttnn.empty"(%{{[0-9]+}})
-  // CHECK: %{{[0-9]+}} = "ttnn.tan"(%arg0, [[VAL0]])
   %1 = "ttir.tan"(%arg0, %0) <{operandSegmentSizes = array<i32: 1, 1>}> : (tensor<64x128xbf16>, tensor<64x128xbf16>) -> tensor<64x128xbf16>
+  // CHECK: "ttnn.tan"
+  // CHECK-SAME: tensor<64x128xbf16
+  // CHECK-SAME: -> tensor<64x128xbf16
   return %1 : tensor<64x128xbf16>
 }
diff --git a/test/ttmlir/Silicon/TTNN/n150/eltwise/unary/tanh/tanh.mlir b/test/ttmlir/Silicon/TTNN/n150/eltwise/unary/tanh/tanh.mlir
index bee21d19a9..0239b101b9 100644
--- a/test/ttmlir/Silicon/TTNN/n150/eltwise/unary/tanh/tanh.mlir
+++ b/test/ttmlir/Silicon/TTNN/n150/eltwise/unary/tanh/tanh.mlir
@@ -4,8 +4,9 @@
 
 func.func @tanh(%arg0: tensor<64x128xbf16>) -> tensor<64x128xbf16> {
   %0 = tensor.empty() : tensor<64x128xbf16>
-  // CHECK: [[VAL0:%[0-9]+]] = "ttnn.empty"(%{{[0-9]+}})
-  // CHECK: %{{[0-9]+}} = "ttnn.tanh"(%arg0, [[VAL0]])
   %1 = "ttir.tanh"(%arg0, %0) <{operandSegmentSizes = array<i32: 1, 1>}> : (tensor<64x128xbf16>, tensor<64x128xbf16>) -> tensor<64x128xbf16>
+  // CHECK: "ttnn.tanh"
+  // CHECK-SAME: tensor<64x128xbf16
+  // CHECK-SAME: -> tensor<64x128xbf16
   return %1 : tensor<64x128xbf16>
 }
diff --git a/test/ttmlir/Silicon/TTNN/n150/operand_broadcasts.mlir b/test/ttmlir/Silicon/TTNN/n150/operand_broadcasts.mlir
index 1b919ec1de..73ace5d80e 100644
--- a/test/ttmlir/Silicon/TTNN/n150/operand_broadcasts.mlir
+++ b/test/ttmlir/Silicon/TTNN/n150/operand_broadcasts.mlir
@@ -3,17 +3,15 @@
 // RUN: ttmlir-translate --ttnn-to-flatbuffer %t.mlir > %t.ttnn
 module attributes {} {
   func.func @bcast_one_dim(%arg0: tensor<2x64x128xf32>, %arg1: tensor<64x128xf32>) -> tensor<2x64x128xf32> {
-    // CHECK: %[[C:.*]] = "ttnn.empty"[[C:.*]]
     %0 = tensor.empty() : tensor<2x64x128xf32>
-    // CHECK: %[[C:.*]] = "ttnn.multiply"[[C:.*]]
+    // CHECK: "ttnn.multiply"
     %1 = "ttir.multiply"(%arg0, %arg1, %0) <{operandSegmentSizes = array<i32: 2, 1>}> : (tensor<2x64x128xf32>, tensor<64x128xf32>, tensor<2x64x128xf32>) -> tensor<2x64x128xf32>
     return %1 : tensor<2x64x128xf32>
   }
 
   func.func @bcast_multi_dim(%arg0: tensor<17x16x15x14xf32>, %arg1: tensor<15x1xf32>) -> tensor<17x16x15x14xf32> {
-    // CHECK: %[[C:.*]] = "ttnn.empty"[[C:.*]]
     %0 = tensor.empty() : tensor<17x16x15x14xf32>
-    // CHECK: %[[C:.*]] = "ttnn.multiply"[[C:.*]]
+    // CHECK: "ttnn.multiply"
     %1 = "ttir.multiply"(%arg0, %arg1, %0) <{operandSegmentSizes = array<i32: 2, 1>}> : (tensor<17x16x15x14xf32>, tensor<15x1xf32>, tensor<17x16x15x14xf32>) -> tensor<17x16x15x14xf32>
     return %1 : tensor<17x16x15x14xf32>
   }
diff --git a/test/ttmlir/Silicon/TTNN/n150/perf/test_perf_and.mlir b/test/ttmlir/Silicon/TTNN/n150/perf/test_perf_and.mlir
index d279685203..6f6294f50f 100644
--- a/test/ttmlir/Silicon/TTNN/n150/perf/test_perf_and.mlir
+++ b/test/ttmlir/Silicon/TTNN/n150/perf/test_perf_and.mlir
@@ -3,11 +3,10 @@
 // RUN: ttmlir-translate --ttnn-to-flatbuffer %t.mlir > %t.ttnn
 func.func @logical_and(%arg0: tensor<64x128xf32>, %arg1: tensor<64x128xf32>) -> tensor<64x128xf32> {
   %0 = tensor.empty() : tensor<64x128xf32>
-  // CHECK: {{.*}} = "ttnn.empty"{{.*}}
   %1 = "ttir.logical_and"(%arg0, %arg1, %0) <{operandSegmentSizes = array<i32: 2, 1>}> : (tensor<64x128xf32>, tensor<64x128xf32>, tensor<64x128xf32>) -> tensor<64x128xf32>
-  // CHECK: %[[C:.*]] = "ttnn.logical_and"
-  // CHECK-SAME: tensor<64x128xf32,
-  // CHECK-SAME: tensor<64x128xf32,
-  // CHECK-SAME: tensor<64x128xf32,
+  // CHECK: "ttnn.logical_and"
+  // CHECK-SAME: tensor<64x128xf32
+  // CHECK-SAME: tensor<64x128xf32
+  // CHECK-SAME: -> tensor<64x128xf32
   return %1 : tensor<64x128xf32>
 }
diff --git a/test/ttmlir/Silicon/TTNN/n150/perf/test_perf_ceil.mlir b/test/ttmlir/Silicon/TTNN/n150/perf/test_perf_ceil.mlir
index 114275c51f..50b18b79b2 100644
--- a/test/ttmlir/Silicon/TTNN/n150/perf/test_perf_ceil.mlir
+++ b/test/ttmlir/Silicon/TTNN/n150/perf/test_perf_ceil.mlir
@@ -3,8 +3,9 @@
 // RUN: ttmlir-translate --ttnn-to-flatbuffer %t.mlir > %t.ttnn
 func.func @ceil(%arg0: tensor<64x128xf32>) -> tensor<64x128xf32> {
   %0 = tensor.empty() : tensor<64x128xf32>
-  // CHECK: [[VAL0:%[0-9]+]] = "ttnn.empty"(%{{[0-9]+}})
-  // CHECK: %{{[0-9]+}} = "ttnn.ceil"(%arg0, [[VAL0]])
   %1 = "ttir.ceil"(%arg0, %0) <{operandSegmentSizes = array<i32: 1, 1>}> : (tensor<64x128xf32>, tensor<64x128xf32>) -> tensor<64x128xf32>
+  // CHECK: "ttnn.ceil"
+  // CHECK-SAME: tensor<64x128xf32
+  // CHECK-SAME: -> tensor<64x128xf32
   return %1 : tensor<64x128xf32>
 }
diff --git a/test/ttmlir/Silicon/TTNN/n150/perf/test_perf_cosine.mlir b/test/ttmlir/Silicon/TTNN/n150/perf/test_perf_cosine.mlir
index 1598de319a..1da8177c8e 100644
--- a/test/ttmlir/Silicon/TTNN/n150/perf/test_perf_cosine.mlir
+++ b/test/ttmlir/Silicon/TTNN/n150/perf/test_perf_cosine.mlir
@@ -3,8 +3,9 @@
 // RUN: ttmlir-translate --ttnn-to-flatbuffer %t.mlir > %t.ttnn
 func.func @cosine(%arg0: tensor<64x128xf32>) -> tensor<64x128xf32> {
   %0 = tensor.empty() : tensor<64x128xf32>
-  // CHECK: [[VAL0:%[0-9]+]] = "ttnn.empty"(%{{[0-9]+}})
-  // CHECK: %{{[0-9]+}} = "ttnn.cos"(%arg0, [[VAL0]])
   %1 = "ttir.cos"(%arg0, %0) <{operandSegmentSizes = array<i32: 1, 1>}> : (tensor<64x128xf32>, tensor<64x128xf32>) -> tensor<64x128xf32>
+  // CHECK: "ttnn.cos"
+  // CHECK-SAME: tensor<64x128xf32
+  // CHECK-SAME: -> tensor<64x128xf32
   return %1 : tensor<64x128xf32>
 }
diff --git a/test/ttmlir/Silicon/TTNN/n150/perf/test_perf_div.mlir b/test/ttmlir/Silicon/TTNN/n150/perf/test_perf_div.mlir
index a6b6a55a49..b4267d250d 100644
--- a/test/ttmlir/Silicon/TTNN/n150/perf/test_perf_div.mlir
+++ b/test/ttmlir/Silicon/TTNN/n150/perf/test_perf_div.mlir
@@ -2,9 +2,11 @@
 // RUN: FileCheck %s --input-file=%t.mlir
 // RUN: ttmlir-translate --ttnn-to-flatbuffer %t.mlir > %t.ttnn
 func.func @div(%arg0: tensor<64x128xf32>, %arg1: tensor<64x128xf32>) -> tensor<64x128xf32> {
-  // CHECK: %[[C:.*]] = "ttnn.empty"[[C:.*]]
   %0 = tensor.empty() : tensor<64x128xf32>
-  // CHECK: %[[C:.*]] = "ttnn.div"[[C:.*]]
   %1 = "ttir.div"(%arg0, %arg1, %0) <{operandSegmentSizes = array<i32: 2, 1>}> : (tensor<64x128xf32>, tensor<64x128xf32>, tensor<64x128xf32>) -> tensor<64x128xf32>
+  // CHECK: "ttnn.div"
+  // CHECK-SAME: tensor<64x128xf32
+  // CHECK-SAME: tensor<64x128xf32
+  // CHECK-SAME: -> tensor<64x128xf32
   return %1 : tensor<64x128xf32>
 }
diff --git a/test/ttmlir/Silicon/TTNN/n150/perf/test_perf_eq.mlir b/test/ttmlir/Silicon/TTNN/n150/perf/test_perf_eq.mlir
index 44ff28faf9..47863e6e8b 100644
--- a/test/ttmlir/Silicon/TTNN/n150/perf/test_perf_eq.mlir
+++ b/test/ttmlir/Silicon/TTNN/n150/perf/test_perf_eq.mlir
@@ -3,15 +3,12 @@
 // RUN: ttmlir-translate --ttnn-to-flatbuffer %t.mlir > %t.ttnn
 module attributes {} {
   func.func @equal(%arg0: tensor<13x31xf32>, %arg1: tensor<13x31xf32>) -> tensor<13x31xf32> {
-    // CHECK: %[[C:.*]] = "ttnn.empty
-    // CHECK-SAME: [[TENSOR:tensor<13x31xf32,]]
     %0 = tensor.empty() : tensor<13x31xf32>
-    // CHECK: %[[C:.*]] = "ttnn.eq"
-    // CHECK-SAME: [[TENSOR]]
-    // CHECK-SAME: [[TENSOR]]
-    // CHECK-SAME: [[TENSOR]]
-    // CHECK-SAME: -> [[TENSOR]]
     %1 = "ttir.eq"(%arg0, %arg1, %0) <{operandSegmentSizes = array<i32: 2, 1>}> : (tensor<13x31xf32>, tensor<13x31xf32>, tensor<13x31xf32>) -> tensor<13x31xf32>
+    // CHECK: "ttnn.eq"
+    // CHECK-SAME: tensor<13x31xf32
+    // CHECK-SAME: tensor<13x31xf32
+    // CHECK-SAME: -> tensor<13x31xf32
     return %1 : tensor<13x31xf32>
   }
 }
diff --git a/test/ttmlir/Silicon/TTNN/n150/perf/test_perf_expm1.mlir b/test/ttmlir/Silicon/TTNN/n150/perf/test_perf_expm1.mlir
index a499c20ce2..c4e124e7ae 100644
--- a/test/ttmlir/Silicon/TTNN/n150/perf/test_perf_expm1.mlir
+++ b/test/ttmlir/Silicon/TTNN/n150/perf/test_perf_expm1.mlir
@@ -3,9 +3,9 @@
 // RUN: ttmlir-translate --ttnn-to-flatbuffer %t.mlir > %t.ttnn
 func.func @expm1(%arg0: tensor<64x128xf32>) -> tensor<64x128xf32> {
   %0 = tensor.empty() : tensor<64x128xf32>
-  // CHECK: [[VAL0:%[0-9]+]] = "ttnn.empty"(%{{[0-9]+}}) <{dtype = {{.*}}, layout = {{.*}}, memory_config = {{.*}}, <{{.*}}>>, shape = #ttnn.shape<[[TENSOR_SHAPE:[0-9]+x[0-9]+]]>}>
   %1 = "ttir.expm1"(%arg0, %0) <{operandSegmentSizes = array<i32: 1, 1>}> : (tensor<64x128xf32>, tensor<64x128xf32>) -> tensor<64x128xf32>
-  // CHECK: %{{[0-9]+}} = "ttnn.expm1"(%arg0, [[VAL0]]) <{operandSegmentSizes = array<i32: 1, 1>}> : (tensor<[[TENSOR_SHAPE]]x{{.*}}, {{.*}}>, tensor<[[TENSOR_SHAPE]]x{{.*}}, {{.*}}) -> tensor<[[TENSOR_SHAPE]]x{{.*}}, {{.*}}>
+  // CHECK: "ttnn.expm1"
+  // CHECK-SAME: tensor<64x128xf32
+  // CHECK-SAME: -> tensor<64x128xf32
   return %1 : tensor<64x128xf32>
-  // CHECK: return %{{[0-9]+}} : tensor<[[TENSOR_SHAPE]]xf32, {{.*}}>
 }
diff --git a/test/ttmlir/Silicon/TTNN/n150/perf/test_perf_floor.mlir b/test/ttmlir/Silicon/TTNN/n150/perf/test_perf_floor.mlir
index d739275349..be34577ca6 100644
--- a/test/ttmlir/Silicon/TTNN/n150/perf/test_perf_floor.mlir
+++ b/test/ttmlir/Silicon/TTNN/n150/perf/test_perf_floor.mlir
@@ -1,14 +1,12 @@
 // RUN: ttmlir-opt --ttir-to-ttnn-backend-pipeline="system-desc-path=%system_desc_path%" %s > %t.mlir
 // RUN: FileCheck %s --input-file=%t.mlir
 // RUN: ttmlir-translate --ttnn-to-flatbuffer %t.mlir > %t.ttnn
+
 func.func @floor(%arg0: tensor<64x128xf32>) -> tensor<64x128xf32> {
-  // CHECK: %{{[0-9]+}} = "ttnn.empty"
-  // CHECK-SAME: [[TENSOR:tensor<64x128xf32,]]
   %0 = tensor.empty() : tensor<64x128xf32>
-  // CHECK: %{{[0-9]+}} = "ttnn.floor"
-  // CHECK-SAME: [[TENSOR]]
-  // CHECK-SAME: [[TENSOR]]
-  // CHECK-SAME: -> [[TENSOR]]
   %1 = "ttir.floor"(%arg0, %0) <{operandSegmentSizes = array<i32: 1, 1>}> : (tensor<64x128xf32>, tensor<64x128xf32>) -> tensor<64x128xf32>
+  // CHECK: "ttnn.floor"
+  // CHECK-SAME: tensor<64x128xf32
+  // CHECK-SAME: -> tensor<64x128xf32
   return %1 : tensor<64x128xf32>
 }
diff --git a/test/ttmlir/Silicon/TTNN/n150/perf/test_perf_ge.mlir b/test/ttmlir/Silicon/TTNN/n150/perf/test_perf_ge.mlir
index 07a6a56f12..28779fe997 100644
--- a/test/ttmlir/Silicon/TTNN/n150/perf/test_perf_ge.mlir
+++ b/test/ttmlir/Silicon/TTNN/n150/perf/test_perf_ge.mlir
@@ -1,10 +1,13 @@
 // RUN: ttmlir-opt --ttir-to-ttnn-backend-pipeline="system-desc-path=%system_desc_path%" %s > %t.mlir
 // RUN: FileCheck %s --input-file=%t.mlir
 // RUN: ttmlir-translate --ttnn-to-flatbuffer %t.mlir > %t.ttnn
+
 func.func @ge(%arg0: tensor<64x128xf32>, %arg1: tensor<64x128xf32>) -> tensor<64x128xf32> {
-  // CHECK: %[[C:.*]] = "ttnn.empty"[[C:.*]]
   %0 = tensor.empty() : tensor<64x128xf32>
-  // CHECK: %[[C:.*]] = "ttnn.ge"[[C:.*]]
   %1 = "ttir.ge"(%arg0, %arg1, %0) <{operandSegmentSizes = array<i32: 2, 1>}> : (tensor<64x128xf32>, tensor<64x128xf32>, tensor<64x128xf32>) -> tensor<64x128xf32>
+  // CHECK: "ttnn.ge"
+  // CHECK-SAME: tensor<64x128xf32
+  // CHECK-SAME: tensor<64x128xf32
+  // CHECK-SAME: -> tensor<64x128xf32
   return %1 : tensor<64x128xf32>
 }
diff --git a/test/ttmlir/Silicon/TTNN/n150/perf/test_perf_gelu.mlir b/test/ttmlir/Silicon/TTNN/n150/perf/test_perf_gelu.mlir
index 7e9767e1fd..8f2bf48737 100644
--- a/test/ttmlir/Silicon/TTNN/n150/perf/test_perf_gelu.mlir
+++ b/test/ttmlir/Silicon/TTNN/n150/perf/test_perf_gelu.mlir
@@ -3,13 +3,10 @@
 // RUN: ttmlir-translate --ttnn-to-flatbuffer %t.mlir > %t.ttnn
 
 func.func @gelu(%arg0: tensor<64x128xf32>) -> tensor<64x128xf32> {
-  // CHECK: "ttnn.empty"
-  // CHECK-SAME: tensor<64x128xf32,
   %0 = tensor.empty() : tensor<64x128xf32>
-  // CHECK: "ttnn.gelu"
-  // CHECK-SAME: tensor<64x128xf32,
-  // CHECK-SAME: tensor<64x128xf32,
-  // CHECK-SAME: tensor<64x128xf32,
   %1 = "ttir.gelu"(%arg0, %0) <{operandSegmentSizes = array<i32: 1, 1>}> : (tensor<64x128xf32>, tensor<64x128xf32>) -> tensor<64x128xf32>
+  // CHECK: "ttnn.gelu"
+  // CHECK-SAME: tensor<64x128xf32
+  // CHECK-SAME: -> tensor<64x128xf32
   return %1 : tensor<64x128xf32>
 }
diff --git a/test/ttmlir/Silicon/TTNN/n150/perf/test_perf_gt.mlir b/test/ttmlir/Silicon/TTNN/n150/perf/test_perf_gt.mlir
index e02ed1e954..457c09bbef 100644
--- a/test/ttmlir/Silicon/TTNN/n150/perf/test_perf_gt.mlir
+++ b/test/ttmlir/Silicon/TTNN/n150/perf/test_perf_gt.mlir
@@ -3,15 +3,12 @@
 // RUN: ttmlir-translate --ttnn-to-flatbuffer %t.mlir > %t.ttnn
 module attributes {} {
   func.func @greater_than(%arg0: tensor<13x31xf32>, %arg1: tensor<13x31xf32>) -> tensor<13x31xf32> {
-    // CHECK: %[[C:.*]] = "ttnn.empty
-    // CHECK-SAME: [[TENSOR:tensor<13x31xf32,]]
     %0 = tensor.empty() : tensor<13x31xf32>
-    // CHECK: %[[C:.*]] = "ttnn.gt"
-    // CHECK-SAME: [[TENSOR]]
-    // CHECK-SAME: [[TENSOR]]
-    // CHECK-SAME: [[TENSOR]]
-    // CHECK-SAME: -> [[TENSOR]]
     %1 = "ttir.gt"(%arg0, %arg1, %0) <{operandSegmentSizes = array<i32: 2, 1>}> : (tensor<13x31xf32>, tensor<13x31xf32>, tensor<13x31xf32>) -> tensor<13x31xf32>
+    // CHECK: "ttnn.gt"
+    // CHECK-SAME: tensor<13x31xf32
+    // CHECK-SAME: tensor<13x31xf32
+    // CHECK-SAME: -> tensor<13x31xf32
     return %1 : tensor<13x31xf32>
   }
 }
diff --git a/test/ttmlir/Silicon/TTNN/n150/perf/test_perf_isfinite.mlir b/test/ttmlir/Silicon/TTNN/n150/perf/test_perf_isfinite.mlir
index b8dc64fb72..a9ae0d5b0c 100644
--- a/test/ttmlir/Silicon/TTNN/n150/perf/test_perf_isfinite.mlir
+++ b/test/ttmlir/Silicon/TTNN/n150/perf/test_perf_isfinite.mlir
@@ -3,13 +3,10 @@
 // RUN: ttmlir-translate --ttnn-to-flatbuffer %t.mlir > %t.ttnn
 
 func.func @is_finite(%arg0: tensor<64x128xbf16>) -> tensor<64x128xbf16> {
-  // CHECK: %[[C:.*]] = "ttnn.empty"
-  // CHECK-SAME: [[TENSOR:tensor<64x128xbf16,]]
   %0 = tensor.empty() : tensor<64x128xbf16>
-  // CHECK: %[[C:.*]] = "ttnn.isfinite"
-  // CHECK-SAME: tensor<64x128xbf16,
-  // CHECK-SAME: [[TENSOR]]
-  // CHECK-SAME: -> [[TENSOR]]
   %1 = "ttir.isfinite"(%arg0, %0) <{operandSegmentSizes = array<i32: 1, 1>}> : (tensor<64x128xbf16>, tensor<64x128xbf16>) -> tensor<64x128xbf16>
+  // CHECK: "ttnn.isfinite"
+  // CHECK-SAME: tensor<64x128xbf16
+  // CHECK-SAME: -> tensor<64x128xbf16
   return %1 : tensor<64x128xbf16>
 }
diff --git a/test/ttmlir/Silicon/TTNN/n150/perf/test_perf_log.mlir b/test/ttmlir/Silicon/TTNN/n150/perf/test_perf_log.mlir
index ef5244fdae..947f077441 100644
--- a/test/ttmlir/Silicon/TTNN/n150/perf/test_perf_log.mlir
+++ b/test/ttmlir/Silicon/TTNN/n150/perf/test_perf_log.mlir
@@ -3,8 +3,9 @@
 // RUN: ttmlir-translate --ttnn-to-flatbuffer %t.mlir > %t.ttnn
 func.func @log(%arg0: tensor<64x128xf32>) -> tensor<64x128xf32> {
   %0 = tensor.empty() : tensor<64x128xf32>
-  // CHECK: [[VAL0:%[0-9]+]] = "ttnn.empty"(%{{[0-9]+}})
-  // CHECK: %{{[0-9]+}} = "ttnn.log"(%arg0, [[VAL0]])
   %1 = "ttir.log"(%arg0, %0) <{operandSegmentSizes = array<i32: 1, 1>}> : (tensor<64x128xf32>, tensor<64x128xf32>) -> tensor<64x128xf32>
+  // CHECK: "ttnn.log"
+  // CHECK-SAME: tensor<64x128xf32
+  // CHECK-SAME: -> tensor<64x128xf32
   return %1 : tensor<64x128xf32>
 }
diff --git a/test/ttmlir/Silicon/TTNN/n150/perf/test_perf_log1p.mlir b/test/ttmlir/Silicon/TTNN/n150/perf/test_perf_log1p.mlir
index 7e21972a81..5aeb1a8777 100644
--- a/test/ttmlir/Silicon/TTNN/n150/perf/test_perf_log1p.mlir
+++ b/test/ttmlir/Silicon/TTNN/n150/perf/test_perf_log1p.mlir
@@ -1,12 +1,11 @@
-
 // RUN: ttmlir-opt --ttir-to-ttnn-backend-pipeline="system-desc-path=%system_desc_path%" %s > %t.mlir
 // RUN: FileCheck %s --input-file=%t.mlir
 // RUN: ttmlir-translate --ttnn-to-flatbuffer %t.mlir > %t.ttnn
 func.func @log1p(%arg0: tensor<64x128xf32>) -> tensor<64x128xf32> {
   %0 = tensor.empty() : tensor<64x128xf32>
-  // CHECK: [[VAL0:%[0-9]+]] = "ttnn.empty"(%{{[0-9]+}}) <{dtype = {{.*}}, layout = {{.*}}, memory_config = {{.*}}, <{{.*}}>>, shape = #ttnn.shape<[[TENSOR_SHAPE:[0-9]+x[0-9]+]]>}>
   %1 = "ttir.log1p"(%arg0, %0) <{operandSegmentSizes = array<i32: 1, 1>}> : (tensor<64x128xf32>, tensor<64x128xf32>) -> tensor<64x128xf32>
-  // CHECK: %{{[0-9]+}} = "ttnn.log1p"(%arg0, [[VAL0]]) <{operandSegmentSizes = array<i32: 1, 1>}> : (tensor<[[TENSOR_SHAPE]]x{{.*}}, {{.*}}>, tensor<[[TENSOR_SHAPE]]x{{.*}}, {{.*}}) -> tensor<[[TENSOR_SHAPE]]x{{.*}}, {{.*}}>
+  // CHECK: "ttnn.log1p"
+  // CHECK-SAME: tensor<64x128xf32
+  // CHECK-SAME: -> tensor<64x128xf32
   return %1 : tensor<64x128xf32>
-  // CHECK: return %{{[0-9]+}} : tensor<[[TENSOR_SHAPE]]xf32, {{.*}}>
 }
diff --git a/test/ttmlir/Silicon/TTNN/n150/perf/test_perf_lt.mlir b/test/ttmlir/Silicon/TTNN/n150/perf/test_perf_lt.mlir
index 1f95207ba3..73ae87caa1 100644
--- a/test/ttmlir/Silicon/TTNN/n150/perf/test_perf_lt.mlir
+++ b/test/ttmlir/Silicon/TTNN/n150/perf/test_perf_lt.mlir
@@ -3,15 +3,12 @@
 // RUN: ttmlir-translate --ttnn-to-flatbuffer %t.mlir > %t.ttnn
 module attributes {} {
   func.func @less_than(%arg0: tensor<13x31xf32>, %arg1: tensor<13x31xf32>) -> tensor<13x31xf32> {
-    // CHECK: %[[C:.*]] = "ttnn.empty
-    // CHECK-SAME: [[TENSOR:tensor<13x31xf32,]]
     %0 = tensor.empty() : tensor<13x31xf32>
-    // CHECK: %[[C:.*]] = "ttnn.lt"
-    // CHECK-SAME: [[TENSOR]]
-    // CHECK-SAME: [[TENSOR]]
-    // CHECK-SAME: [[TENSOR]]
-    // CHECK-SAME: -> [[TENSOR]]
     %1 = "ttir.lt"(%arg0, %arg1, %0) <{operandSegmentSizes = array<i32: 2, 1>}> : (tensor<13x31xf32>, tensor<13x31xf32>, tensor<13x31xf32>) -> tensor<13x31xf32>
+    // CHECK: "ttnn.lt"
+    // CHECK-SAME: tensor<13x31xf32
+    // CHECK-SAME: tensor<13x31xf32
+    // CHECK-SAME: -> tensor<13x31xf32
     return %1 : tensor<13x31xf32>
   }
 }
diff --git a/test/ttmlir/Silicon/TTNN/n150/perf/test_perf_maximum.mlir b/test/ttmlir/Silicon/TTNN/n150/perf/test_perf_maximum.mlir
index 3893bc9f0c..e218de0260 100644
--- a/test/ttmlir/Silicon/TTNN/n150/perf/test_perf_maximum.mlir
+++ b/test/ttmlir/Silicon/TTNN/n150/perf/test_perf_maximum.mlir
@@ -2,9 +2,11 @@
 // RUN: FileCheck %s --input-file=%t.mlir
 // RUN: ttmlir-translate --ttnn-to-flatbuffer %t.mlir > %t.ttnn
 func.func @maximum(%arg0: tensor<64x128xf32>, %arg1: tensor<64x128xf32>) -> tensor<64x128xf32> {
-  // CHECK: %[[C:.*]] = "ttnn.empty"[[C:.*]]
   %0 = tensor.empty() : tensor<64x128xf32>
-  // CHECK: %[[C:.*]] = "ttnn.maximum"[[C:.*]]
   %1 = "ttir.maximum"(%arg0, %arg1, %0) <{operandSegmentSizes = array<i32: 2, 1>}> : (tensor<64x128xf32>, tensor<64x128xf32>, tensor<64x128xf32>) -> tensor<64x128xf32>
+  // CHECK: "ttnn.maximum"
+  // CHECK-SAME: tensor<64x128xf32
+  // CHECK-SAME: tensor<64x128xf32
+  // CHECK-SAME: -> tensor<64x128xf32
   return %1 : tensor<64x128xf32>
 }
diff --git a/test/ttmlir/Silicon/TTNN/n150/perf/test_perf_multiply.mlir b/test/ttmlir/Silicon/TTNN/n150/perf/test_perf_multiply.mlir
index 7991cbc786..26cfd904e7 100644
--- a/test/ttmlir/Silicon/TTNN/n150/perf/test_perf_multiply.mlir
+++ b/test/ttmlir/Silicon/TTNN/n150/perf/test_perf_multiply.mlir
@@ -2,9 +2,11 @@
 // RUN: FileCheck %s --input-file=%t.mlir
 // RUN: ttmlir-translate --ttnn-to-flatbuffer %t.mlir > %t.ttnn
 func.func @multiply(%arg0: tensor<64x128xf32>, %arg1: tensor<64x128xf32>) -> tensor<64x128xf32> {
-  // CHECK: %[[C:.*]] = "ttnn.empty"[[C:.*]]
   %0 = tensor.empty() : tensor<64x128xf32>
-  // CHECK: %[[C:.*]] = "ttnn.multiply"[[C:.*]]
   %1 = "ttir.multiply"(%arg0, %arg1, %0) <{operandSegmentSizes = array<i32: 2, 1>}> : (tensor<64x128xf32>, tensor<64x128xf32>, tensor<64x128xf32>) -> tensor<64x128xf32>
+  // CHECK: "ttnn.multiply"
+  // CHECK-SAME: tensor<64x128xf32
+  // CHECK-SAME: tensor<64x128xf32
+  // CHECK-SAME: -> tensor<64x128xf32
   return %1 : tensor<64x128xf32>
 }
diff --git a/test/ttmlir/Silicon/TTNN/n150/perf/test_perf_ne.mlir b/test/ttmlir/Silicon/TTNN/n150/perf/test_perf_ne.mlir
index 300e66226d..cbfc97e230 100644
--- a/test/ttmlir/Silicon/TTNN/n150/perf/test_perf_ne.mlir
+++ b/test/ttmlir/Silicon/TTNN/n150/perf/test_perf_ne.mlir
@@ -3,15 +3,12 @@
 // RUN: ttmlir-translate --ttnn-to-flatbuffer %t.mlir > %t.ttnn
 module attributes {} {
   func.func @not_equal(%arg0: tensor<13x31xf32>, %arg1: tensor<13x31xf32>) -> tensor<13x31xf32> {
-    // CHECK: %[[C:.*]] = "ttnn.empty
-    // CHECK-SAME: [[TENSOR:tensor<13x31xf32,]]
     %0 = tensor.empty() : tensor<13x31xf32>
-    // CHECK: %[[C:.*]] = "ttnn.ne"
-    // CHECK-SAME: [[TENSOR]]
-    // CHECK-SAME: [[TENSOR]]
-    // CHECK-SAME: [[TENSOR]]
-    // CHECK-SAME: -> [[TENSOR]]
     %1 = "ttir.ne"(%arg0, %arg1, %0) <{operandSegmentSizes = array<i32: 2, 1>}> : (tensor<13x31xf32>, tensor<13x31xf32>, tensor<13x31xf32>) -> tensor<13x31xf32>
+    // CHECK: "ttnn.ne"
+    // CHECK-SAME: tensor<13x31xf32
+    // CHECK-SAME: tensor<13x31xf32
+    // CHECK-SAME: -> tensor<13x31xf32
     return %1 : tensor<13x31xf32>
   }
 }
diff --git a/test/ttmlir/Silicon/TTNN/n150/perf/test_perf_neg.mlir b/test/ttmlir/Silicon/TTNN/n150/perf/test_perf_neg.mlir
index 907541764d..d360d736f7 100644
--- a/test/ttmlir/Silicon/TTNN/n150/perf/test_perf_neg.mlir
+++ b/test/ttmlir/Silicon/TTNN/n150/perf/test_perf_neg.mlir
@@ -3,7 +3,9 @@
 // RUN: ttmlir-translate --ttnn-to-flatbuffer %t.mlir > %t.ttnn
 func.func @negate(%arg0: tensor<32x32xf32>) -> tensor<32x32xf32> {
   %0 = tensor.empty() : tensor<32x32xf32>
-  // CHECK: %[[C:.*]] = "ttnn.neg"[[C:.*]]
   %1 = "ttir.neg"(%arg0, %0) <{operandSegmentSizes = array<i32: 1, 1>}> : (tensor<32x32xf32>, tensor<32x32xf32>) -> tensor<32x32xf32>
+  // CHECK: "ttnn.neg"
+  // CHECK-SAME: tensor<32x32xf32
+  // CHECK-SAME: -> tensor<32x32xf32
   return %1 : tensor<32x32xf32>
 }
diff --git a/test/ttmlir/Silicon/TTNN/n150/perf/test_perf_not.mlir b/test/ttmlir/Silicon/TTNN/n150/perf/test_perf_not.mlir
index b9d07674ea..bbe9147173 100644
--- a/test/ttmlir/Silicon/TTNN/n150/perf/test_perf_not.mlir
+++ b/test/ttmlir/Silicon/TTNN/n150/perf/test_perf_not.mlir
@@ -3,10 +3,9 @@
 // RUN: ttmlir-translate --ttnn-to-flatbuffer %t.mlir > %t.ttnn
 func.func @logical_not(%arg0: tensor<64x128xf32>) -> tensor<64x128xf32> {
   %0 = tensor.empty() : tensor<64x128xf32>
-  // CHECK: {{.*}} = "ttnn.empty"{{.*}}
   %1 = "ttir.logical_not"(%arg0, %0) <{operandSegmentSizes = array<i32: 1, 1>}> : (tensor<64x128xf32>, tensor<64x128xf32>) -> tensor<64x128xf32>
-  // CHECK: %[[C:.*]] = "ttnn.logical_not"
-  // CHECK-SAME: tensor<64x128xf32,
-  // CHECK-SAME: tensor<64x128xf32,
+  // CHECK: "ttnn.logical_not"
+  // CHECK-SAME: tensor<64x128xf32
+  // CHECK-SAME: -> tensor<64x128xf32
   return %1 : tensor<64x128xf32>
 }
diff --git a/test/ttmlir/Silicon/TTNN/n150/perf/test_perf_or.mlir b/test/ttmlir/Silicon/TTNN/n150/perf/test_perf_or.mlir
index e6c7ec5550..4d9a5a93b8 100644
--- a/test/ttmlir/Silicon/TTNN/n150/perf/test_perf_or.mlir
+++ b/test/ttmlir/Silicon/TTNN/n150/perf/test_perf_or.mlir
@@ -3,11 +3,10 @@
 // RUN: ttmlir-translate --ttnn-to-flatbuffer %t.mlir > %t.ttnn
 func.func @logical_or(%arg0: tensor<64x128xf32>, %arg1: tensor<64x128xf32>) -> tensor<64x128xf32> {
   %0 = tensor.empty() : tensor<64x128xf32>
-  // CHECK: {{.*}} = "ttnn.empty"{{.*}}
   %1 = "ttir.logical_or"(%arg0, %arg1, %0) <{operandSegmentSizes = array<i32: 2, 1>}> : (tensor<64x128xf32>, tensor<64x128xf32>, tensor<64x128xf32>) -> tensor<64x128xf32>
-  // CHECK: %[[C:.*]] = "ttnn.logical_or"
-  // CHECK-SAME: tensor<64x128xf32,
-  // CHECK-SAME: tensor<64x128xf32,
-  // CHECK-SAME: tensor<64x128xf32,
+  // CHECK: "ttnn.logical_or"
+  // CHECK-SAME: tensor<64x128xf32
+  // CHECK-SAME: tensor<64x128xf32
+  // CHECK-SAME: -> tensor<64x128xf32
   return %1 : tensor<64x128xf32>
 }
diff --git a/test/ttmlir/Silicon/TTNN/n150/perf/test_perf_power.mlir b/test/ttmlir/Silicon/TTNN/n150/perf/test_perf_power.mlir
index 7b4eefe9e1..5532240bc6 100644
--- a/test/ttmlir/Silicon/TTNN/n150/perf/test_perf_power.mlir
+++ b/test/ttmlir/Silicon/TTNN/n150/perf/test_perf_power.mlir
@@ -3,9 +3,10 @@
 // RUN: ttmlir-translate --ttnn-to-flatbuffer %t.mlir > %t.ttnn
 func.func @power(%arg0: tensor<32x32xf32>, %arg1: tensor<32x32xf32>) -> tensor<32x32xf32> {
   %0 = tensor.empty() : tensor<32x32xf32>
-  // CHECK: %[[EMPTY:.*]] = "ttnn.empty"{{.*}} -> tensor<32x32xf32, {{.*}}
   %1 = "ttir.power"(%arg0, %arg1, %0) <{operandSegmentSizes = array<i32: 2, 1>}> : (tensor<32x32xf32>, tensor<32x32xf32>, tensor<32x32xf32>) -> tensor<32x32xf32>
-  // CHECK: %[[REM:[0-9]+]] = "ttnn.pow"({{.*}}, {{.*}}, %[[EMPTY]]){{.*}} -> tensor<32x32xf32, {{.*}}
+  // CHECK: "ttnn.pow"
+  // CHECK-SAME: tensor<32x32xf32
+  // CHECK-SAME: tensor<32x32xf32
+  // CHECK-SAME: -> tensor<32x32xf32
   return %1 : tensor<32x32xf32>
-  // CHECK: return {{.*}} : tensor<32x32xf32, {{.*}}
 }
diff --git a/test/ttmlir/Silicon/TTNN/n150/perf/test_perf_reciprocal.mlir b/test/ttmlir/Silicon/TTNN/n150/perf/test_perf_reciprocal.mlir
index d17444e4b8..7038f19a9e 100644
--- a/test/ttmlir/Silicon/TTNN/n150/perf/test_perf_reciprocal.mlir
+++ b/test/ttmlir/Silicon/TTNN/n150/perf/test_perf_reciprocal.mlir
@@ -2,9 +2,10 @@
 // RUN: FileCheck %s --input-file=%t.mlir
 // RUN: ttmlir-translate --ttnn-to-flatbuffer %t.mlir > %t.ttnn
 func.func @reciprocal(%arg0: tensor<64x128xf32>) -> tensor<64x128xf32> {
-  // CHECK: %[[C:.*]] = "ttnn.empty"[[C:.*]]
   %0 = tensor.empty() : tensor<64x128xf32>
-  // CHECK: %[[C:.*]] = "ttnn.reciprocal"[[C:.*]]
   %1 = "ttir.reciprocal"(%arg0, %0) <{operandSegmentSizes = array<i32: 1, 1>}> : (tensor<64x128xf32>, tensor<64x128xf32>) -> tensor<64x128xf32>
+  // CHECK: "ttnn.reciprocal"
+  // CHECK-SAME: tensor<64x128xf32
+  // CHECK-SAME: -> tensor<64x128xf32
   return %1 : tensor<64x128xf32>
 }
diff --git a/test/ttmlir/Silicon/TTNN/n150/perf/test_perf_relu.mlir b/test/ttmlir/Silicon/TTNN/n150/perf/test_perf_relu.mlir
index 0ae23ec155..86865f7a53 100644
--- a/test/ttmlir/Silicon/TTNN/n150/perf/test_perf_relu.mlir
+++ b/test/ttmlir/Silicon/TTNN/n150/perf/test_perf_relu.mlir
@@ -1,10 +1,12 @@
 // RUN: ttmlir-opt --ttir-to-ttnn-backend-pipeline="system-desc-path=%system_desc_path%" %s > %t.mlir
 // RUN: FileCheck %s --input-file=%t.mlir
 // RUN: ttmlir-translate --ttnn-to-flatbuffer %t.mlir > %t.ttnn
+
 func.func @relu(%arg0: tensor<64x128xf32>) -> tensor<64x128xf32> {
-  // CHECK: %[[C:.*]] = "ttnn.empty"[[C:.*]]
   %0 = tensor.empty() : tensor<64x128xf32>
-  // CHECK: %[[C:.*]] = "ttnn.relu"[[C:.*]]
   %1 = "ttir.relu"(%arg0, %0) <{operandSegmentSizes = array<i32: 1, 1>}> : (tensor<64x128xf32>, tensor<64x128xf32>) -> tensor<64x128xf32>
+  // CHECK: "ttnn.relu"
+  // CHECK-SAME: tensor<64x128xf32
+  // CHECK-SAME: -> tensor<64x128xf32
   return %1 : tensor<64x128xf32>
 }
diff --git a/test/ttmlir/Silicon/TTNN/n150/perf/test_perf_remainder.mlir b/test/ttmlir/Silicon/TTNN/n150/perf/test_perf_remainder.mlir
index e358d663ec..d81bed4385 100644
--- a/test/ttmlir/Silicon/TTNN/n150/perf/test_perf_remainder.mlir
+++ b/test/ttmlir/Silicon/TTNN/n150/perf/test_perf_remainder.mlir
@@ -3,9 +3,10 @@
 // RUN: ttmlir-translate --ttnn-to-flatbuffer %t.mlir > %t.ttnn
 func.func @remainder(%arg0: tensor<32x32xf32>, %arg1: tensor<32x32xf32>) -> tensor<32x32xf32> {
   %0 = tensor.empty() : tensor<32x32xf32>
-  // CHECK: %[[EMPTY:.*]] = "ttnn.empty"{{.*}} -> tensor<32x32xf32, {{.*}}
   %1 = "ttir.remainder"(%arg0, %arg1, %0) <{operandSegmentSizes = array<i32: 2, 1>}> : (tensor<32x32xf32>, tensor<32x32xf32>, tensor<32x32xf32>) -> tensor<32x32xf32>
-  // CHECK: %[[REM:[0-9]+]] = "ttnn.remainder"({{.*}}, {{.*}}, %[[EMPTY]]){{.*}} -> tensor<32x32xf32, {{.*}}
+  // CHECK: "ttnn.remainder"
+  // CHECK-SAME: tensor<32x32xf32
+  // CHECK-SAME: tensor<32x32xf32
+  // CHECK-SAME: -> tensor<32x32xf32
   return %1 : tensor<32x32xf32>
-  // CHECK: return {{.*}} : tensor<32x32xf32, {{.*}}
 }
diff --git a/test/ttmlir/Silicon/TTNN/n150/perf/test_perf_rsqrt.mlir b/test/ttmlir/Silicon/TTNN/n150/perf/test_perf_rsqrt.mlir
index 4c85d11caf..a31ab8554a 100644
--- a/test/ttmlir/Silicon/TTNN/n150/perf/test_perf_rsqrt.mlir
+++ b/test/ttmlir/Silicon/TTNN/n150/perf/test_perf_rsqrt.mlir
@@ -2,9 +2,10 @@
 // RUN: FileCheck %s --input-file=%t.mlir
 // RUN: ttmlir-translate --ttnn-to-flatbuffer %t.mlir > %t.ttnn
 func.func @rsqrt(%arg0: tensor<64x128xf32>) -> tensor<64x128xf32> {
-  // CHECK: %[[C:.*]] = "ttnn.empty"[[C:.*]]
   %0 = tensor.empty() : tensor<64x128xf32>
-  // CHECK: %[[C:.*]] = "ttnn.rsqrt"[[C:.*]]
   %1 = "ttir.rsqrt"(%arg0, %0) <{operandSegmentSizes = array<i32: 1, 1>}> : (tensor<64x128xf32>, tensor<64x128xf32>) -> tensor<64x128xf32>
+  // CHECK: "ttnn.rsqrt"
+  // CHECK-SAME: tensor<64x128xf32
+  // CHECK-SAME: -> tensor<64x128xf32
   return %1 : tensor<64x128xf32>
 }
diff --git a/test/ttmlir/Silicon/TTNN/n150/perf/test_perf_sigmoid.mlir b/test/ttmlir/Silicon/TTNN/n150/perf/test_perf_sigmoid.mlir
index 9583be9577..b0f67ae3bf 100644
--- a/test/ttmlir/Silicon/TTNN/n150/perf/test_perf_sigmoid.mlir
+++ b/test/ttmlir/Silicon/TTNN/n150/perf/test_perf_sigmoid.mlir
@@ -1,10 +1,12 @@
 // RUN: ttmlir-opt --ttir-to-ttnn-backend-pipeline="system-desc-path=%system_desc_path%" %s > %t.mlir
 // RUN: FileCheck %s --input-file=%t.mlir
 // RUN: ttmlir-translate --ttnn-to-flatbuffer %t.mlir > %t.ttnn
+
 func.func @sigmoid(%arg0: tensor<64x128xf32>) -> tensor<64x128xf32> {
-  // CHECK: %[[C:.*]] = "ttnn.empty"[[C:.*]]
   %0 = tensor.empty() : tensor<64x128xf32>
-  // CHECK: %[[C:.*]] = "ttnn.sigmoid"[[C:.*]]
   %1 = "ttir.sigmoid"(%arg0, %0) <{operandSegmentSizes = array<i32: 1, 1>}> : (tensor<64x128xf32>, tensor<64x128xf32>) -> tensor<64x128xf32>
+  // CHECK: "ttnn.sigmoid"
+  // CHECK-SAME: tensor<64x128xf32
+  // CHECK-SAME: -> tensor<64x128xf32
   return %1 : tensor<64x128xf32>
 }
diff --git a/test/ttmlir/Silicon/TTNN/n150/perf/test_perf_sign.mlir b/test/ttmlir/Silicon/TTNN/n150/perf/test_perf_sign.mlir
index 8a05b1ae6d..d1f5efae8f 100644
--- a/test/ttmlir/Silicon/TTNN/n150/perf/test_perf_sign.mlir
+++ b/test/ttmlir/Silicon/TTNN/n150/perf/test_perf_sign.mlir
@@ -1,11 +1,12 @@
 // RUN: ttmlir-opt --ttir-to-ttnn-backend-pipeline="system-desc-path=%system_desc_path%" %s > %t.mlir
 // RUN: FileCheck %s --input-file=%t.mlir
 // RUN: ttmlir-translate --ttnn-to-flatbuffer %t.mlir > %t.ttnn
+
 func.func @sign(%arg0: tensor<64x128xf32>) -> tensor<64x128xf32> {
     %0 = tensor.empty() : tensor<64x128xf32>
-    // CHECK: [[VAL0:%[0-9]+]] = "ttnn.empty"(%{{[0-9]+}}) <{dtype = {{.*}}, layout = {{.*}}, memory_config = {{.*}}, <{{.*}}>>, shape = #ttnn.shape<[[TENSOR_SHAPE:[0-9]+x[0-9]+]]>}>
     %1 = "ttir.sign"(%arg0, %0) <{operandSegmentSizes = array<i32: 1, 1>}> : (tensor<64x128xf32>, tensor<64x128xf32>) -> tensor<64x128xf32>
-    // CHECK: %{{[0-9]+}} = "ttnn.sign"(%arg0, [[VAL0]]) <{operandSegmentSizes = array<i32: 1, 1>}> : (tensor<[[TENSOR_SHAPE]]x{{.*}}, {{.*}}>, tensor<[[TENSOR_SHAPE]]x{{.*}}, {{.*}}) -> tensor<[[TENSOR_SHAPE]]x{{.*}}, {{.*}}>
+    // CHECK: "ttnn.sign"
+    // CHECK-SAME: tensor<64x128xf32
+    // CHECK-SAME: -> tensor<64x128xf32
     return %1 : tensor<64x128xf32>
-    // CHECK: return %{{[0-9]+}} : tensor<[[TENSOR_SHAPE]]xf32, {{.*}}>
 }
diff --git a/test/ttmlir/Silicon/TTNN/n150/perf/test_perf_sine.mlir b/test/ttmlir/Silicon/TTNN/n150/perf/test_perf_sine.mlir
index 60dc574693..ceb105dcd3 100644
--- a/test/ttmlir/Silicon/TTNN/n150/perf/test_perf_sine.mlir
+++ b/test/ttmlir/Silicon/TTNN/n150/perf/test_perf_sine.mlir
@@ -1,10 +1,12 @@
 // RUN: ttmlir-opt --ttir-to-ttnn-backend-pipeline="system-desc-path=%system_desc_path%" %s > %t.mlir
 // RUN: FileCheck %s --input-file=%t.mlir
 // RUN: ttmlir-translate --ttnn-to-flatbuffer %t.mlir > %t.ttnn
+
 func.func @sine(%arg0: tensor<64x128xf32>) -> tensor<64x128xf32> {
   %0 = tensor.empty() : tensor<64x128xf32>
-  // CHECK: [[VAL0:%[0-9]+]] = "ttnn.empty"(%{{[0-9]+}})
-  // CHECK: %{{[0-9]+}} = "ttnn.sin"(%arg0, [[VAL0]])
   %1 = "ttir.sin"(%arg0, %0) <{operandSegmentSizes = array<i32: 1, 1>}> : (tensor<64x128xf32>, tensor<64x128xf32>) -> tensor<64x128xf32>
+  // CHECK: "ttnn.sin"
+  // CHECK-SAME: tensor<64x128xf32
+  // CHECK-SAME: -> tensor<64x128xf32
   return %1 : tensor<64x128xf32>
 }
diff --git a/test/ttmlir/Silicon/TTNN/n150/perf/test_perf_sqrt.mlir b/test/ttmlir/Silicon/TTNN/n150/perf/test_perf_sqrt.mlir
index 72e7bb579f..6eb8e91d8b 100644
--- a/test/ttmlir/Silicon/TTNN/n150/perf/test_perf_sqrt.mlir
+++ b/test/ttmlir/Silicon/TTNN/n150/perf/test_perf_sqrt.mlir
@@ -2,9 +2,10 @@
 // RUN: FileCheck %s --input-file=%t.mlir
 // RUN: ttmlir-translate --ttnn-to-flatbuffer %t.mlir > %t.ttnn
 func.func @sqrt(%arg0: tensor<64x128xf32>) -> tensor<64x128xf32> {
-  // CHECK: %[[C:.*]] = "ttnn.empty"[[C:.*]]
   %0 = tensor.empty() : tensor<64x128xf32>
-  // CHECK: %[[C:.*]] = "ttnn.sqrt"[[C:.*]]
   %1 = "ttir.sqrt"(%arg0, %0) <{operandSegmentSizes = array<i32: 1, 1>}> : (tensor<64x128xf32>, tensor<64x128xf32>) -> tensor<64x128xf32>
+  // CHECK: "ttnn.sqrt"
+  // CHECK-SAME: tensor<64x128xf32
+  // CHECK-SAME: -> tensor<64x128xf32
   return %1 : tensor<64x128xf32>
 }
diff --git a/test/ttmlir/Silicon/TTNN/n150/perf/test_perf_subtract.mlir b/test/ttmlir/Silicon/TTNN/n150/perf/test_perf_subtract.mlir
index 679994dc53..9629aecd2f 100644
--- a/test/ttmlir/Silicon/TTNN/n150/perf/test_perf_subtract.mlir
+++ b/test/ttmlir/Silicon/TTNN/n150/perf/test_perf_subtract.mlir
@@ -2,9 +2,11 @@
 // RUN: FileCheck %s --input-file=%t.mlir
 // RUN: ttmlir-translate --ttnn-to-flatbuffer %t.mlir > %t.ttnn
 func.func @subtract(%arg0: tensor<64x128xf32>, %arg1: tensor<64x128xf32>) -> tensor<64x128xf32> {
-  // CHECK: %[[C:.*]] = "ttnn.empty"[[C:.*]]
   %0 = tensor.empty() : tensor<64x128xf32>
-  // CHECK: %[[C:.*]] = "ttnn.subtract"[[C:.*]]
   %1 = "ttir.subtract"(%arg0, %arg1, %0) <{operandSegmentSizes = array<i32: 2, 1>}> : (tensor<64x128xf32>, tensor<64x128xf32>, tensor<64x128xf32>) -> tensor<64x128xf32>
+  // CHECK: "ttnn.subtract"
+  // CHECK-SAME: tensor<64x128xf32
+  // CHECK-SAME: tensor<64x128xf32
+  // CHECK-SAME: -> tensor<64x128xf32
   return %1 : tensor<64x128xf32>
 }
diff --git a/test/ttmlir/Silicon/TTNN/n150/perf/test_perf_tan.mlir b/test/ttmlir/Silicon/TTNN/n150/perf/test_perf_tan.mlir
index d870cee186..1506c2193b 100644
--- a/test/ttmlir/Silicon/TTNN/n150/perf/test_perf_tan.mlir
+++ b/test/ttmlir/Silicon/TTNN/n150/perf/test_perf_tan.mlir
@@ -4,8 +4,9 @@
 
 func.func @tan(%arg0: tensor<64x128xf32>) -> tensor<64x128xf32> {
   %0 = tensor.empty() : tensor<64x128xf32>
-  // CHECK: [[VAL0:%[0-9]+]] = "ttnn.empty"(%{{[0-9]+}})
-  // CHECK: %{{[0-9]+}} = "ttnn.tan"(%arg0, [[VAL0]])
   %1 = "ttir.tan"(%arg0, %0) <{operandSegmentSizes = array<i32: 1, 1>}> : (tensor<64x128xf32>, tensor<64x128xf32>) -> tensor<64x128xf32>
+  // CHECK: "ttnn.tan"
+  // CHECK-SAME: tensor<64x128xf32
+  // CHECK-SAME: -> tensor<64x128xf32
   return %1 : tensor<64x128xf32>
 }
diff --git a/test/ttmlir/Silicon/TTNN/n150/perf/test_perf_tanh.mlir b/test/ttmlir/Silicon/TTNN/n150/perf/test_perf_tanh.mlir
index cf12dcf9ac..dd0eedd4ec 100644
--- a/test/ttmlir/Silicon/TTNN/n150/perf/test_perf_tanh.mlir
+++ b/test/ttmlir/Silicon/TTNN/n150/perf/test_perf_tanh.mlir
@@ -4,8 +4,9 @@
 
 func.func @tanh(%arg0: tensor<64x128xf32>) -> tensor<64x128xf32> {
   %0 = tensor.empty() : tensor<64x128xf32>
-  // CHECK: [[VAL0:%[0-9]+]] = "ttnn.empty"(%{{[0-9]+}})
-  // CHECK: %{{[0-9]+}} = "ttnn.tanh"(%arg0, [[VAL0]])
   %1 = "ttir.tanh"(%arg0, %0) <{operandSegmentSizes = array<i32: 1, 1>}> : (tensor<64x128xf32>, tensor<64x128xf32>) -> tensor<64x128xf32>
+  // CHECK: "ttnn.tanh"
+  // CHECK-SAME: tensor<64x128xf32
+  // CHECK-SAME: -> tensor<64x128xf32
   return %1 : tensor<64x128xf32>
 }
diff --git a/test/ttmlir/Silicon/TTNN/n150/perf/test_perf_where.mlir b/test/ttmlir/Silicon/TTNN/n150/perf/test_perf_where.mlir
index ced442b91f..9d450ebacc 100644
--- a/test/ttmlir/Silicon/TTNN/n150/perf/test_perf_where.mlir
+++ b/test/ttmlir/Silicon/TTNN/n150/perf/test_perf_where.mlir
@@ -7,8 +7,7 @@ func.func @test_where(%arg0: tensor<13x37xbf16>, %arg1: tensor<13x37xbf16>) -> t
   %1 = "ttir.eq"(%arg0, %arg1, %0) <{operandSegmentSizes = array<i32: 2, 1>}> : (tensor<13x37xbf16>, tensor<13x37xbf16>, tensor<13x37xbf16>) -> tensor<13x37xbf16>
   %2 = tensor.empty() : tensor<13x37xbf16>
   %3 = "ttir.where"(%1, %arg0, %arg1, %2) <{operandSegmentSizes = array<i32: 3, 1>}> : (tensor<13x37xbf16>, tensor<13x37xbf16>, tensor<13x37xbf16>, tensor<13x37xbf16>) -> tensor<13x37xbf16>
-  // CHECK: %[[EMPTY:.*]] = "ttnn.empty"{{.*}}
-  // CHECK: %[[VAL1:[0-9]+]] = "ttnn.eq"(%arg0, %arg1, %[[EMPTY]])
-  // CHECK: %{{[0-9]+}} = "ttnn.where"(%[[VAL1]], %arg0, %arg1, %{{[0-9]+}})
+  // CHECK: "ttnn.eq"
+  // CHECK: "ttnn.where"
   return %3 : tensor<13x37xbf16>
 }
diff --git a/test/ttmlir/Silicon/TTNN/n150/perf/test_perf_xor.mlir b/test/ttmlir/Silicon/TTNN/n150/perf/test_perf_xor.mlir
index d68b726083..c0920c2a64 100644
--- a/test/ttmlir/Silicon/TTNN/n150/perf/test_perf_xor.mlir
+++ b/test/ttmlir/Silicon/TTNN/n150/perf/test_perf_xor.mlir
@@ -3,13 +3,11 @@
 // RUN: ttmlir-translate --ttnn-to-flatbuffer %t.mlir > %t.ttnn
 
 func.func @logical_xor(%arg0: tensor<64x128xbf16>, %arg1: tensor<64x128xbf16>) -> tensor<64x128xbf16> {
-  // CHECK: %{{[0-9]+}} = "ttnn.empty"{{.*}} [[TENSOR:tensor<64x128xbf16]]
   %0 = tensor.empty() : tensor<64x128xbf16>
-  // CHECK: %{{[0-9]+}} = "ttnn.logical_xor"
-  // CHECK-SAME: [[TENSOR]]
-  // CHECK-SAME: [[TENSOR]]
-  // CHECK-SAME: [[TENSOR]]
-  // CHECK-SAME: -> [[TENSOR]]
   %1 = "ttir.logical_xor"(%arg0, %arg1, %0) <{operandSegmentSizes = array<i32: 2, 1>}> : (tensor<64x128xbf16>, tensor<64x128xbf16>, tensor<64x128xbf16>) -> tensor<64x128xbf16>
+  // CHECK: "ttnn.logical_xor"
+  // CHECK-SAME: (tensor<64x128xbf16
+  // CHECK-SAME: tensor<64x128xbf16
+  // CHECK-SAME: -> tensor<64x128xbf16
   return %1 : tensor<64x128xbf16>
 }
diff --git a/test/ttmlir/Silicon/TTNN/n150/runtime_stitching/eltwise_binary_op_chain.mlir b/test/ttmlir/Silicon/TTNN/n150/runtime_stitching/eltwise_binary_op_chain.mlir
index bd03fbe155..aff5e3cdb6 100644
--- a/test/ttmlir/Silicon/TTNN/n150/runtime_stitching/eltwise_binary_op_chain.mlir
+++ b/test/ttmlir/Silicon/TTNN/n150/runtime_stitching/eltwise_binary_op_chain.mlir
@@ -4,25 +4,22 @@
 
 module attributes {} {
 func.func @add(%arg0: tensor<64x128xf32>, %arg1: tensor<64x128xf32>) -> tensor<64x128xf32> {
-  // CHECK: %[[C:.*]] = "ttnn.empty"[[C:.*]]
   %0 = tensor.empty() : tensor<64x128xf32>
-  // CHECK: %[[C:.*]] = "ttnn.add"[[C:.*]]
+  // CHECK: "ttnn.add"
   %1 = "ttir.add"(%arg0, %arg1, %0) <{operandSegmentSizes = array<i32: 2, 1>}> : (tensor<64x128xf32>, tensor<64x128xf32>, tensor<64x128xf32>) -> tensor<64x128xf32>
   return %1 : tensor<64x128xf32>
 }
 
 func.func @multiply(%arg0: tensor<64x128xf32>, %arg1: tensor<64x128xf32>) -> tensor<64x128xf32> {
-  // CHECK: %[[C:.*]] = "ttnn.empty"[[C:.*]]
   %0 = tensor.empty() : tensor<64x128xf32>
-  // CHECK: %[[C:.*]] = "ttnn.multiply"[[C:.*]]
+  // CHECK: "ttnn.multiply"
   %1 = "ttir.multiply"(%arg0, %arg1, %0) <{operandSegmentSizes = array<i32: 2, 1>}> : (tensor<64x128xf32>, tensor<64x128xf32>, tensor<64x128xf32>) -> tensor<64x128xf32>
   return %1 : tensor<64x128xf32>
 }
 
 func.func @subtract(%arg0: tensor<64x128xf32>, %arg1: tensor<64x128xf32>) -> tensor<64x128xf32> {
-  // CHECK: %[[C:.*]] = "ttnn.empty"[[C:.*]]
   %0 = tensor.empty() : tensor<64x128xf32>
-  // CHECK: %[[C:.*]] = "ttnn.subtract"[[C:.*]]
+  // CHECK: "ttnn.subtract"
   %1 = "ttir.subtract"(%arg0, %arg1, %0) <{operandSegmentSizes = array<i32: 2, 1>}> : (tensor<64x128xf32>, tensor<64x128xf32>, tensor<64x128xf32>) -> tensor<64x128xf32>
   return %1 : tensor<64x128xf32>
 }
diff --git a/test/ttmlir/Silicon/TTNN/n150/sharded/simple_eltwise_sharded.mlir b/test/ttmlir/Silicon/TTNN/n150/sharded/simple_eltwise_sharded.mlir
index d74b582ede..8a8150d932 100644
--- a/test/ttmlir/Silicon/TTNN/n150/sharded/simple_eltwise_sharded.mlir
+++ b/test/ttmlir/Silicon/TTNN/n150/sharded/simple_eltwise_sharded.mlir
@@ -1,80 +1,73 @@
 // RUN: ttmlir-opt --ttir-to-ttnn-backend-pipeline="system-desc-path=%system_desc_path% enable-optimizer=false" %s > %t.mlir
 // RUN: FileCheck %s --input-file=%t.mlir
 // RUN: ttmlir-translate --ttnn-to-flatbuffer %t.mlir > %t.ttnn
+
 func.func @subtract(%arg0: tensor<224x64xf32>, %arg1: tensor<224x64xf32>) -> tensor<224x64xf32> {
-  // CHECK: %[[C:.*]] = "ttnn.empty"[[C:.*]]
   %0 = tensor.empty() : tensor<224x64xf32>
-  // CHECK: %[[C:.*]] = "ttnn.subtract"[[C:.*]]
+  // CHECK: "ttnn.subtract"
   %1 = "ttir.subtract"(%arg0, %arg1, %0) <{operandSegmentSizes = array<i32: 2, 1>}> : (tensor<224x64xf32>, tensor<224x64xf32>, tensor<224x64xf32>) -> tensor<224x64xf32>
   return %1 : tensor<224x64xf32>
 }
 
 func.func @div(%arg0: tensor<224x64xf32>, %arg1: tensor<224x64xf32>) -> tensor<224x64xf32> {
-  // CHECK: %[[C:.*]] = "ttnn.empty"[[C:.*]]
   %0 = tensor.empty() : tensor<224x64xf32>
-  // CHECK: %[[C:.*]] = "ttnn.div"[[C:.*]]
+  // CHECK: "ttnn.div"
   %1 = "ttir.div"(%arg0, %arg1, %0) <{operandSegmentSizes = array<i32: 2, 1>}> : (tensor<224x64xf32>, tensor<224x64xf32>, tensor<224x64xf32>) -> tensor<224x64xf32>
   return %1 : tensor<224x64xf32>
 }
 
 func.func @multiply(%arg0: tensor<224x64xf32>, %arg1: tensor<224x64xf32>) -> tensor<224x64xf32> {
-  // CHECK: %[[C:.*]] = "ttnn.empty"[[C:.*]]
   %0 = tensor.empty() : tensor<224x64xf32>
-  // CHECK: %[[C:.*]] = "ttnn.multiply"[[C:.*]]
+  // CHECK: "ttnn.multiply"
   %1 = "ttir.multiply"(%arg0, %arg1, %0) <{operandSegmentSizes = array<i32: 2, 1>}> : (tensor<224x64xf32>, tensor<224x64xf32>, tensor<224x64xf32>) -> tensor<224x64xf32>
   return %1 : tensor<224x64xf32>
 }
 
 func.func @relu(%arg0: tensor<224x64xf32>) -> tensor<224x64xf32> {
-  // CHECK: %[[C:.*]] = "ttnn.empty"[[C:.*]]
   %0 = tensor.empty() : tensor<224x64xf32>
-  // CHECK: %[[C:.*]] = "ttnn.relu"[[C:.*]]
+  // CHECK: "ttnn.relu"
   %1 = "ttir.relu"(%arg0, %0) <{operandSegmentSizes = array<i32: 1, 1>}> : (tensor<224x64xf32>, tensor<224x64xf32>) -> tensor<224x64xf32>
   return %1 : tensor<224x64xf32>
 }
 
 func.func @ge(%arg0: tensor<224x64xf32>, %arg1: tensor<224x64xf32>) -> tensor<224x64xf32> {
-  // CHECK: %[[C:.*]] = "ttnn.empty"[[C:.*]]
   %0 = tensor.empty() : tensor<224x64xf32>
-  // CHECK: %[[C:.*]] = "ttnn.ge"[[C:.*]]
+  // CHECK: "ttnn.ge"
   %1 = "ttir.ge"(%arg0, %arg1, %0) <{operandSegmentSizes = array<i32: 2, 1>}> : (tensor<224x64xf32>, tensor<224x64xf32>, tensor<224x64xf32>) -> tensor<224x64xf32>
   return %1 : tensor<224x64xf32>
 }
 
 func.func @reshape(%arg0: tensor<4x2x224x64xbf16>) -> tensor<2x4x224x64xbf16> {
   %0 = tensor.empty() : tensor<2x4x224x64xbf16>
-  // CHECK: %[[C:.*]] = "ttnn.reshape"[[C:.*]]
+  // CHECK: "ttnn.reshape"
   %1 = "ttir.reshape"(%arg0, %0) <{shape = [2: i32, 4: i32, 224: i32, 64: i32]}> : (tensor<4x2x224x64xbf16>, tensor<2x4x224x64xbf16>) -> tensor<2x4x224x64xbf16>
   return %1 : tensor<2x4x224x64xbf16>
 }
 
 func.func @squeeze(%arg0: tensor<1x2x1x224x64xbf16>) -> tensor<1x2x224x64xbf16> {
   %0 = tensor.empty() : tensor<1x2x224x64xbf16>
-  // CHECK: %[[C:.*]] = "ttnn.reshape"[[C:.*]]
+  // CHECK: "ttnn.reshape"
   %1 = "ttir.squeeze"(%arg0, %0) <{dim = 2 : si32}> : (tensor<1x2x1x224x64xbf16>, tensor<1x2x224x64xbf16>) -> tensor<1x2x224x64xbf16>
   return %1 : tensor<1x2x224x64xbf16>
 }
 
 func.func @reciprocal(%arg0: tensor<224x64xf32>) -> tensor<224x64xf32> {
-  // CHECK: %[[C:.*]] = "ttnn.empty"[[C:.*]]
   %0 = tensor.empty() : tensor<224x64xf32>
-  // CHECK: %[[C:.*]] = "ttnn.reciprocal"[[C:.*]]
+  // CHECK: "ttnn.reciprocal"
   %1 = "ttir.reciprocal"(%arg0, %0) <{operandSegmentSizes = array<i32: 1, 1>}> : (tensor<224x64xf32>, tensor<224x64xf32>) -> tensor<224x64xf32>
   return %1 : tensor<224x64xf32>
 }
 
 func.func @sigmoid(%arg0: tensor<224x64xf32>) -> tensor<224x64xf32> {
-  // CHECK: %[[C:.*]] = "ttnn.empty"[[C:.*]]
   %0 = tensor.empty() : tensor<224x64xf32>
-  // CHECK: %[[C:.*]] = "ttnn.sigmoid"[[C:.*]]
+  // CHECK: "ttnn.sigmoid"
   %1 = "ttir.sigmoid"(%arg0, %0) <{operandSegmentSizes = array<i32: 1, 1>}> : (tensor<224x64xf32>, tensor<224x64xf32>) -> tensor<224x64xf32>
   return %1 : tensor<224x64xf32>
 }
 
 func.func @sqrt(%arg0: tensor<224x64xf32>) -> tensor<224x64xf32> {
-  // CHECK: %[[C:.*]] = "ttnn.empty"[[C:.*]]
   %0 = tensor.empty() : tensor<224x64xf32>
-  // CHECK: %[[C:.*]] = "ttnn.sqrt"[[C:.*]]
+  // CHECK: "ttnn.sqrt"
   %1 = "ttir.sqrt"(%arg0, %0) <{operandSegmentSizes = array<i32: 1, 1>}> : (tensor<224x64xf32>, tensor<224x64xf32>) -> tensor<224x64xf32>
   return %1 : tensor<224x64xf32>
 }
diff --git a/test/ttmlir/Silicon/TTNN/n150/simple_power.mlir b/test/ttmlir/Silicon/TTNN/n150/simple_power.mlir
deleted file mode 100644
index d9c49b8c63..0000000000
--- a/test/ttmlir/Silicon/TTNN/n150/simple_power.mlir
+++ /dev/null
@@ -1,11 +0,0 @@
-// RUN: ttmlir-opt --ttir-to-ttnn-backend-pipeline="system-desc-path=%system_desc_path%" %s > %t.mlir
-// RUN: FileCheck %s --input-file=%t.mlir
-// RUN: ttmlir-translate --ttnn-to-flatbuffer %t.mlir > %t.ttnn
-func.func @power(%arg0: tensor<32x32xf32>, %arg1: tensor<32x32xf32>) -> tensor<32x32xf32> {
-  %0 = tensor.empty() : tensor<32x32xf32>
-  // CHECK: %[[EMPTY:.*]] = "ttnn.empty"{{.*}} -> tensor<32x32xf32, {{.*}}
-  %1 = "ttir.power"(%arg0, %arg1, %0) <{operandSegmentSizes = array<i32: 2, 1>}> : (tensor<32x32xf32>, tensor<32x32xf32>, tensor<32x32xf32>) -> tensor<32x32xf32>
-  // CHECK: %[[POW:[0-9]+]] = "ttnn.pow"({{.*}}, {{.*}}, %[[EMPTY]]){{.*}} -> tensor<32x32xf32, {{.*}}
-  return %1 : tensor<32x32xf32>
-  // CHECK: return {{.*}} : tensor<32x32xf32, {{.*}}
-}
diff --git a/test/unittests/Optimizer/TestGreedyL1InterleavedPolicy.cpp b/test/unittests/Optimizer/TestGreedyL1InterleavedPolicy.cpp
index a8ad3df448..a04da6607a 100644
--- a/test/unittests/Optimizer/TestGreedyL1InterleavedPolicy.cpp
+++ b/test/unittests/Optimizer/TestGreedyL1InterleavedPolicy.cpp
@@ -131,44 +131,40 @@ TEST_F(GreedyL1InterleavedPolicyBase, VerifyGreedyPolicy) {
   constexpr uint64_t usableL1CacheSize = 15;
 
   // Create operand A
-  mlir::Value dest = createEmptyTensor();
   mlir::Value lhs = func.getBody().getBlocks().front().getArgument(0);
   mlir::Value rhs = func.getBody().getBlocks().front().getArgument(1);
   mlir::Operation *opA =
-      builder.create<AddOp>(builder.getUnknownLoc(), lhs, rhs, dest);
+      builder.create<AddOp>(builder.getUnknownLoc(), lhs, rhs);
   uint64_t outputL1Usage = 2;
   uint64_t requiredL1Usage = 8;
   prepareOpForGreedyConfigPicker(opA, outputL1Usage, requiredL1Usage,
                                  legalLayouts, opsL1Usage);
 
   // Create operand B
-  dest = createEmptyTensor();
   lhs = func.getBody().getBlocks().front().getArgument(0);
   rhs = func.getBody().getBlocks().front().getArgument(1);
   mlir::Operation *opB =
-      builder.create<AddOp>(builder.getUnknownLoc(), lhs, rhs, dest);
+      builder.create<AddOp>(builder.getUnknownLoc(), lhs, rhs);
   outputL1Usage = 3;
   requiredL1Usage = 7;
   prepareOpForGreedyConfigPicker(opB, outputL1Usage, requiredL1Usage,
                                  legalLayouts, opsL1Usage);
 
   // Create operand C
-  dest = createEmptyTensor();
   lhs = func.getBody().getBlocks().front().getArgument(0);
   rhs = func.getBody().getBlocks().front().getArgument(1);
   mlir::Operation *opC =
-      builder.create<AddOp>(builder.getUnknownLoc(), lhs, rhs, dest);
+      builder.create<AddOp>(builder.getUnknownLoc(), lhs, rhs);
   outputL1Usage = 1;
   requiredL1Usage = 9;
   prepareOpForGreedyConfigPicker(opC, outputL1Usage, requiredL1Usage,
                                  legalLayouts, opsL1Usage);
 
   // Create base op D
-  dest = createEmptyTensor();
   lhs = func.getBody().getBlocks().front().getArgument(0);
   rhs = func.getBody().getBlocks().front().getArgument(1);
   mlir::Operation *opD =
-      builder.create<AddOp>(builder.getUnknownLoc(), lhs, rhs, dest);
+      builder.create<AddOp>(builder.getUnknownLoc(), lhs, rhs);
   outputL1Usage = 4;
   requiredL1Usage = 0;
   prepareOpForGreedyConfigPicker(opD, outputL1Usage, requiredL1Usage,
diff --git a/test/unittests/Optimizer/TestShardSolver.cpp b/test/unittests/Optimizer/TestShardSolver.cpp
index 4693bc6851..fbde684a9f 100644
--- a/test/unittests/Optimizer/TestShardSolver.cpp
+++ b/test/unittests/Optimizer/TestShardSolver.cpp
@@ -145,11 +145,10 @@ TEST_F(ShardSolverBase, VerifyProduceMaxCoreUsage) {
   constexpr unsigned usableL1CacheSize = 1024 * 1024;
   std::unordered_set<Edge> overrideReshardEdges;
 
-  mlir::Value dest = createEmptyTensor();
   mlir::Value lhs = func.getBody().getBlocks().front().getArgument(0);
   mlir::Value rhs = func.getBody().getBlocks().front().getArgument(1);
   mlir::Operation *op =
-      builder.create<AddOp>(builder.getUnknownLoc(), lhs, rhs, dest);
+      builder.create<AddOp>(builder.getUnknownLoc(), lhs, rhs);
   mlir::Operation *firstOp = op;
 
   prepareOpForShardSolver(op, opL1MemSpecs, l1ChainedOps);
@@ -161,8 +160,7 @@ TEST_F(ShardSolverBase, VerifyProduceMaxCoreUsage) {
                  TensorMemoryLayout::BlockSharded, 2, 2);
 
   rhs = op->getResult(0);
-  dest = createEmptyTensor();
-  op = builder.create<ReluOp>(builder.getUnknownLoc(), rhs, dest);
+  op = builder.create<ReluOp>(builder.getUnknownLoc(), rhs);
   prepareOpForShardSolver(op, opL1MemSpecs, l1ChainedOps);
   addLayoutForOp(op, legalLayouts, BufferType::L1,
                  TensorMemoryLayout::WidthSharded, 1, 8);
@@ -174,8 +172,7 @@ TEST_F(ShardSolverBase, VerifyProduceMaxCoreUsage) {
   lhs = func.getBody().getBlocks().front().getArgument(0);
   rhs = op->getResult(0);
 
-  dest = createEmptyTensor();
-  op = builder.create<AddOp>(builder.getUnknownLoc(), lhs, rhs, dest);
+  op = builder.create<AddOp>(builder.getUnknownLoc(), lhs, rhs);
   prepareOpForShardSolver(op, opL1MemSpecs, l1ChainedOps);
   addLayoutForOp(op, legalLayouts, BufferType::L1,
                  TensorMemoryLayout::WidthSharded, 1, 4);
@@ -184,8 +181,7 @@ TEST_F(ShardSolverBase, VerifyProduceMaxCoreUsage) {
   addLayoutForOp(op, legalLayouts, BufferType::L1,
                  TensorMemoryLayout::BlockSharded, 1, 1);
 
-  dest = createEmptyTensor();
-  op = builder.create<AddOp>(builder.getUnknownLoc(), lhs, rhs, dest);
+  op = builder.create<AddOp>(builder.getUnknownLoc(), lhs, rhs);
   prepareOpForShardSolver(op, opL1MemSpecs, l1ChainedOps);
   addLayoutForOp(op, legalLayouts, BufferType::L1,
                  TensorMemoryLayout::WidthSharded, 1, 4);
@@ -196,8 +192,7 @@ TEST_F(ShardSolverBase, VerifyProduceMaxCoreUsage) {
 
   lhs = opL1MemSpecs[opL1MemSpecs.size() - 2].op->getResult(0);
   rhs = opL1MemSpecs[opL1MemSpecs.size() - 1].op->getResult(0);
-  dest = createEmptyTensor();
-  op = builder.create<AddOp>(builder.getUnknownLoc(), lhs, rhs, dest);
+  op = builder.create<AddOp>(builder.getUnknownLoc(), lhs, rhs);
   prepareOpForShardSolver(op, opL1MemSpecs, l1ChainedOps);
   addLayoutForOp(op, legalLayouts, BufferType::L1,
                  TensorMemoryLayout::WidthSharded, 1, 2);
@@ -207,8 +202,7 @@ TEST_F(ShardSolverBase, VerifyProduceMaxCoreUsage) {
                  TensorMemoryLayout::BlockSharded, 1, 1);
 
   rhs = op->getResult(0);
-  dest = createEmptyTensor();
-  op = builder.create<ReluOp>(builder.getUnknownLoc(), rhs, dest);
+  op = builder.create<ReluOp>(builder.getUnknownLoc(), rhs);
   prepareOpForShardSolver(op, opL1MemSpecs, l1ChainedOps);
   addLayoutForOp(op, legalLayouts, BufferType::L1,
                  TensorMemoryLayout::WidthSharded, 1, 2);