Rename is_sparse_array -> is_pydata_sparse.

array_api_compat/common/_helpers.py

@@ -50,7 +50,7 @@ def is_numpy_array(x):
     is_torch_array
     is_dask_array
     is_jax_array
-    is_sparse_array
+    is_pydata_sparse
     """
     # Avoid importing NumPy if it isn't already
     if 'numpy' not in sys.modules:
@@ -80,7 +80,7 @@ def is_cupy_array(x):
     is_torch_array
     is_dask_array
     is_jax_array
-    is_sparse_array
+    is_pydata_sparse
     """
     # Avoid importing NumPy if it isn't already
     if 'cupy' not in sys.modules:
@@ -107,7 +107,7 @@ def is_torch_array(x):
     is_cupy_array
     is_dask_array
     is_jax_array
-    is_sparse_array
+    is_pydata_sparse
     """
     # Avoid importing torch if it isn't already
     if 'torch' not in sys.modules:
@@ -134,7 +134,7 @@ def is_dask_array(x):
     is_cupy_array
     is_torch_array
     is_jax_array
-    is_sparse_array
+    is_pydata_sparse
     """
     # Avoid importing dask if it isn't already
     if 'dask.array' not in sys.modules:
@@ -161,7 +161,7 @@ def is_jax_array(x):
     is_cupy_array
     is_torch_array
     is_dask_array
-    is_sparse_array
+    is_pydata_sparse
     """
     # Avoid importing jax if it isn't already
     if 'jax' not in sys.modules:
@@ -172,7 +172,7 @@ def is_jax_array(x):
     return isinstance(x, jax.Array) or _is_jax_zero_gradient_array(x)
 
 
-def is_sparse_array(x) -> bool:
+def is_pydata_sparse(x) -> bool:
     """
     Return True if `x` is an array from the `sparse` package.
 
@@ -219,7 +219,7 @@ def is_array_api_obj(x):
         or is_torch_array(x) \
         or is_dask_array(x) \
         or is_jax_array(x) \
-        or is_sparse_array(x) \
+        or is_pydata_sparse(x) \
         or hasattr(x, '__array_namespace__')
 
 def _check_api_version(api_version):
@@ -288,7 +288,7 @@ def your_function(x, y):
     is_torch_array
     is_dask_array
     is_jax_array
-    is_sparse_array
+    is_pydata_sparse
 
     """
     if use_compat not in [None, True, False]:
@@ -348,7 +348,7 @@ def your_function(x, y):
                 # not have a wrapper submodule for it.
                 import jax.experimental.array_api as jnp
             namespaces.add(jnp)
-        elif is_sparse_array(x):
+        elif is_pydata_sparse(x):
             if use_compat is True:
                 _check_api_version(api_version)
                 raise ValueError("`sparse` does not have an array-api-compat wrapper")
@@ -451,7 +451,7 @@ def device(x: Array, /) -> Device:
             return x.device()
         else:
             return x.device
-    elif is_sparse_array(x):
+    elif is_pydata_sparse(x):
         # `sparse` will gain `.device`, so check for this first.
         x_device = getattr(x, 'device', None)
         if x_device is not None:
@@ -583,7 +583,7 @@ def to_device(x: Array, device: Device, /, *, stream: Optional[Union[int, Any]]
         # This import adds to_device to x
         import jax.experimental.array_api # noqa: F401
         return x.to_device(device, stream=stream)
-    elif is_sparse_array(x) and device == _device(x):
+    elif is_pydata_sparse(x) and device == _device(x):
         # Perform trivial check to return the same array if
         # device is same instead of err-ing.
         return x
@@ -613,7 +613,7 @@ def size(x):
     "is_jax_array",
     "is_numpy_array",
     "is_torch_array",
-    "is_sparse_array",
+    "is_pydata_sparse",
     "size",
     "to_device",
 ]