Add tests for BEiT

tests/jax/models/beit/base/test_beit_base.py

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+# SPDX-FileCopyrightText: (c) 2025 Tenstorrent AI ULC
+#
+# SPDX-License-Identifier: Apache-2.0
+
+
+from typing import Callable
+
+import pytest
+from infra import RunMode
+from utils import compile_fail, record_model_test_properties
+
+from ..tester import FlaxBeitForImageClassificationTester
+
+MODEL_PATH = "microsoft/beit-base-patch16-224"
+MODEL_NAME = "beit-base"
+
+
+# ----- Fixtures -----
+
+
+@pytest.fixture
+def inference_tester() -> FlaxBeitForImageClassificationTester:
+    return FlaxBeitForImageClassificationTester(MODEL_PATH)
+
+
+@pytest.fixture
+def training_tester() -> FlaxBeitForImageClassificationTester:
+    return FlaxBeitForImageClassificationTester(MODEL_PATH, RunMode.TRAINING)
+
+
+# ----- Tests -----
+
+
+@pytest.mark.xfail(reason=compile_fail("failed to legalize operation 'ttir.gather'"))
+def test_flax_beit_base_inference(
+    inference_tester: FlaxBeitForImageClassificationTester,
+    record_tt_xla_property: Callable,
+):
+    record_model_test_properties(record_tt_xla_property, MODEL_NAME)
+
+    inference_tester.test()
+
+
+@pytest.mark.skip(reason="Support for training not implemented")
+def test_flax_beit_base_training(
+    training_tester: FlaxBeitForImageClassificationTester,
+    record_tt_xla_property: Callable,
+):
+    record_model_test_properties(record_tt_xla_property, MODEL_NAME)
+
+    training_tester.test()

tests/jax/models/beit/large/test_beit_large.py

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+# SPDX-FileCopyrightText: (c) 2025 Tenstorrent AI ULC
+#
+# SPDX-License-Identifier: Apache-2.0
+
+from typing import Callable
+
+import pytest
+from infra import RunMode
+from utils import compile_fail, record_model_test_properties
+
+from ..tester import FlaxBeitForImageClassificationTester
+
+MODEL_PATH = "microsoft/beit-large-patch16-224"
+MODEL_NAME = "beit-large"
+
+
+# ----- Fixtures -----
+
+
+@pytest.fixture
+def inference_tester() -> FlaxBeitForImageClassificationTester:
+    return FlaxBeitForImageClassificationTester(MODEL_PATH)
+
+
+@pytest.fixture
+def training_tester() -> FlaxBeitForImageClassificationTester:
+    return FlaxBeitForImageClassificationTester(MODEL_PATH, RunMode.TRAINING)
+
+
+# ----- Tests -----
+
+
+@pytest.mark.xfail(reason=compile_fail("failed to legalize operation 'ttir.gather'"))
+def test_flax_beit_large_inference(
+    inference_tester: FlaxBeitForImageClassificationTester,
+    record_tt_xla_property: Callable,
+):
+    record_model_test_properties(record_tt_xla_property, MODEL_NAME)
+
+    inference_tester.test()
+
+
+@pytest.mark.skip(reason="Support for training not implemented")
+def test_flax_beit_large_training(
+    training_tester: FlaxBeitForImageClassificationTester,
+    record_tt_xla_property: Callable,
+):
+    record_model_test_properties(record_tt_xla_property, MODEL_NAME)
+
+    training_tester.test()

tests/jax/models/beit/tester.py

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+# SPDX-FileCopyrightText: (c) 2025 Tenstorrent AI ULC
+#
+# SPDX-License-Identifier: Apache-2.0
+
+from typing import Dict, Sequence
+
+import jax
+from flax import linen as nn
+from infra import ComparisonConfig, ModelTester, RunMode
+from transformers import BeitImageProcessor, FlaxBeitForImageClassification
+
+
+class FlaxBeitForImageClassificationTester(ModelTester):
+    """Tester for Beit family of models on image classification tasks."""
+
+    def __init__(
+        self,
+        model_name: str,
+        comparison_config: ComparisonConfig = ComparisonConfig(),
+        run_mode: RunMode = RunMode.INFERENCE,
+    ) -> None:
+        self._model_name = model_name
+        super().__init__(comparison_config, run_mode)
+
+    # @override
+    def _get_model(self) -> nn.Module:
+        return FlaxBeitForImageClassification.from_pretrained(self._model_name)
+
+    # @override
+    def _get_input_activations(self) -> Sequence[jax.Array]:
+        image = jax.random.uniform(jax.random.PRNGKey(42), (1, 3, 224, 224))
+        preprocessor = BeitImageProcessor.from_pretrained(
+            self._model_name, do_rescale=False
+        )
+        inputs = preprocessor(image, return_tensors="np")
+        return inputs
+
+    # @override
+    def _get_forward_method_kwargs(self) -> Dict[str, jax.Array]:
+        assert hasattr(self._model, "params")
+        return {
+            "params": self._model.params,
+            **self._get_input_activations(),
+        }