Remove useless arguments from non xarray API

pyproject.toml

@@ -163,6 +163,7 @@ lines-after-imports = 2
 "tests/link/numba/**/test_*.py" = ["E402"]
 "tests/link/pytorch/**/test_*.py" = ["E402"]
 "tests/link/mlx/**/test_*.py" = ["E402"]
+"tests/xtensor/**/test_*.py" = ["E402"]
 
 
 

pytensor/xtensor/shape.py

 import typing
 import warnings
-from collections.abc import Hashable, Sequence
+from collections.abc import Sequence
 from types import EllipsisType
 from typing import Literal
 
@@ -384,28 +384,10 @@ class Squeeze(XOp):
         return Apply(self, [x], [out])
 
 
-def squeeze(x, dim=None, drop=False, axis=None):
+def squeeze(x, dim: str | Sequence[str] | None = None):
     """Remove dimensions of size 1 from an XTensorVariable."""
     x = as_xtensor(x)
 
-    # drop parameter is ignored in pytensor.xtensor
-    if drop is not None:
-        warnings.warn("drop parameter has no effect in pytensor.xtensor", UserWarning)
-
-    # dim and axis are mutually exclusive
-    if dim is not None and axis is not None:
-        raise ValueError("Cannot specify both `dim` and `axis`")
-
-    # if axis is specified, it must be a sequence of ints
-    if axis is not None:
-        if not isinstance(axis, Sequence):
-            axis = [axis]
-        if not all(isinstance(a, int) for a in axis):
-            raise ValueError("axis must be an integer or a sequence of integers")
-
-        # convert axis to dims
-        dims = tuple(x.type.dims[i] for i in axis)
-
     # if dim is specified, it must be a string or a sequence of strings
     if dim is None:
         dims = tuple(d for d, s in zip(x.type.dims, x.type.shape) if s == 1)
@@ -461,33 +443,18 @@ class ExpandDims(XOp):
         return Apply(self, [x, size], [out])
 
 
-def expand_dims(x, dim=None, create_index_for_new_dim=None, axis=None, **dim_kwargs):
+def expand_dims(x, dim=None, axis=None, **dim_kwargs):
     """Add one or more new dimensions to an XTensorVariable."""
     x = as_xtensor(x)
 
     # Store original dimensions for axis handling
     original_dims = x.type.dims
 
-    # Warn if create_index_for_new_dim is used (not supported)
-    if create_index_for_new_dim is not None:
-        warnings.warn(
-            "create_index_for_new_dim=False has no effect in pytensor.xtensor",
-            UserWarning,
-            stacklevel=2,
-        )
-
     if dim is None:
         dim = dim_kwargs
     elif dim_kwargs:
         raise ValueError("Cannot specify both `dim` and `**dim_kwargs`")
 
-    # Check that dim is Hashable or a sequence of Hashable or dict
-    if not isinstance(dim, Hashable):
-        if not isinstance(dim, Sequence | dict):
-            raise TypeError(f"unhashable type: {type(dim).__name__}")
-        if not all(isinstance(d, Hashable) for d in dim):
-            raise TypeError(f"unhashable type in {type(dim).__name__}")
-
     # Normalize to a dimension-size mapping
     if isinstance(dim, str):
         dims_dict = {dim: 1}
@@ -496,9 +463,7 @@ def expand_dims(x, dim=None, create_index_for_new_dim=None, axis=None, **dim_kwa
     elif isinstance(dim, dict):
         dims_dict = {}
         for name, val in dim.items():
-            if isinstance(val, str):
-                raise TypeError(f"Dimension size cannot be a string: {val}")
-            if isinstance(val, Sequence | np.ndarray):
+            if isinstance(val, list | tuple | np.ndarray):
                 warnings.warn(
                     "When a sequence is provided as a dimension size, only its length is used. "
                     "The actual values (which would be coordinates in xarray) are ignored.",

pytensor/xtensor/type.py

@@ -687,7 +687,7 @@ class XTensorVariable(Variable[_XTensorTypeType, OptionalApplyType]):
             The name(s) of the dimension(s) to remove. If None, all dimensions of size 1
             (known statically) will be removed. Dimensions with unknown static shape will be retained, even if they have size 1 at runtime.
         drop : bool, optional
-            If drop=True, drop squeezed coordinates instead of making them scalar.
+            Ignored by PyTensor.
         axis : int or iterable of int, optional
             The axis(es) to remove. If None, all dimensions of size 1 will be removed.
         Returns
@@ -695,12 +695,21 @@ class XTensorVariable(Variable[_XTensorTypeType, OptionalApplyType]):
         XTensorVariable
             A new tensor with the specified dimension(s) removed.
         """
-        return px.shape.squeeze(self, dim, drop, axis)
+        if axis is not None:
+            if dim is not None:
+                raise ValueError("Cannot specify both `dim` and `axis`")
+
+            if not isinstance(axis, Sequence):
+                axis = (axis,)
+
+            dim = tuple(self.type.dims[i] for i in axis)
+
+        return px.shape.squeeze(self, dim)
 
     def expand_dims(
         self,
         dim: str | Sequence[str] | dict[str, int | Sequence] | None = None,
-        create_index_for_new_dim: bool = True,
+        create_index_for_new_dim: bool | None = None,
         axis: int | Sequence[int] | None = None,
         **dim_kwargs,
     ):
@@ -714,7 +723,7 @@ class XTensorVariable(Variable[_XTensorTypeType, OptionalApplyType]):
 
             - int: the new size
             - sequence: coordinates (length determines size)
-        create_index_for_new_dim : bool, default: True
+        create_index_for_new_dim : bool, optional
             Ignored by PyTensor
         axis : int | Sequence[int] | None, default: None
             Not implemented yet. In xarray, specifies where to insert the new dimension(s).
@@ -730,7 +739,6 @@ class XTensorVariable(Variable[_XTensorTypeType, OptionalApplyType]):
         return px.shape.expand_dims(
             self,
             dim,
-            create_index_for_new_dim=create_index_for_new_dim,
             axis=axis,
             **dim_kwargs,
         )

tests/xtensor/test_indexing.py

@@ -2,6 +2,8 @@ import pytest
 
 
 pytest.importorskip("xarray")
+pytestmark = pytest.mark.filterwarnings("error")
+
 
 import re
 

tests/xtensor/test_linalg.py

@@ -3,6 +3,7 @@ import pytest
 
 pytest.importorskip("xarray")
 pytest.importorskip("xarray_einstats")
+pytestmark = pytest.mark.filterwarnings("error")
 
 import numpy as np
 from xarray import DataArray

tests/xtensor/test_math.py

@@ -2,6 +2,7 @@ import pytest
 
 
 pytest.importorskip("xarray")
+pytestmark = pytest.mark.filterwarnings("error")
 
 import inspect
 

tests/xtensor/test_random.py

+import pytest
+
+
+pytest.importorskip("xarray")
+pytestmark = pytest.mark.filterwarnings("error")
+
 import inspect
 import re
 from copy import deepcopy
 
 import numpy as np
-import pytest
 
 import pytensor.tensor.random as ptr
 import pytensor.xtensor.random as pxr

tests/xtensor/test_reduction.py

@@ -2,6 +2,7 @@ import pytest
 
 
 pytest.importorskip("xarray")
+pytestmark = pytest.mark.filterwarnings("error")
 
 from pytensor.xtensor.type import xtensor
 from tests.xtensor.util import xr_arange_like, xr_assert_allclose, xr_function

tests/xtensor/test_shape.py

@@ -2,6 +2,7 @@ import pytest
 
 
 pytest.importorskip("xarray")
+pytestmark = pytest.mark.filterwarnings("error")
 
 import re
 from itertools import chain, combinations
@@ -33,9 +34,6 @@ from tests.xtensor.util import (
 )
 
 
-pytest.importorskip("xarray")
-
-
 def powerset(iterable, min_group_size=0):
     "Subsequences of the iterable from shortest to longest."
     # powerset([1,2,3]) → () (1,) (2,) (3,) (1,2) (1,3) (2,3) (1,2,3)
@@ -322,7 +320,7 @@ def test_squeeze():
     xr_assert_allclose(fn5(x5_test), x5_test.squeeze(axis=1))
 
     # Test axis parameter with negative index
-    y5 = x5.squeeze(axis=-1)  # squeeze dimension at index -2 (b)
+    y5 = x5.squeeze(axis=-2)  # squeeze dimension at index -2 (b)
     fn5 = xr_function([x5], y5)
     x5_test = xr_arange_like(x5)
     xr_assert_allclose(fn5(x5_test), x5_test.squeeze(axis=-2))
@@ -333,12 +331,9 @@ def test_squeeze():
     x2_test = xr_arange_like(x2)
     xr_assert_allclose(fn6(x2_test), x2_test.squeeze(axis=[1, 2]))
 
-    # Test drop parameter warning
+    # Test drop parameter ignored, but accepted
     x7 = xtensor("x7", dims=("a", "b"), shape=(2, 1))
-    with pytest.warns(
-        UserWarning, match="drop parameter has no effect in pytensor.xtensor"
-    ):
-        y7 = x7.squeeze("b", drop=True)  # squeeze and drop coordinate
+    y7 = x7.squeeze("b", drop=True)
     fn7 = xr_function([x7], y7)
     x7_test = xr_arange_like(x7)
     xr_assert_allclose(fn7(x7_test), x7_test.squeeze("b", drop=True))
@@ -391,7 +386,8 @@ def test_expand_dims():
     xr_assert_allclose(fn(x_test), x_test.expand_dims(country=2, state=3))
 
     # Test with a dict of name-coord array pairs
-    y = x.expand_dims({"country": np.array([1, 2]), "state": np.array([3, 4, 5])})
+    with pytest.warns(UserWarning, match="only its length is used"):
+        y = x.expand_dims({"country": np.array([1, 2]), "state": np.array([3, 4, 5])})
     fn = xr_function([x], y)
     xr_assert_allclose(
         fn(x_test),
@@ -471,7 +467,7 @@ def test_expand_dims_errors():
     # TypeError: unhashable type: 'numpy.ndarray'
 
     # Test with a numpy array as dim (not supported)
-    with pytest.raises(TypeError, match="unhashable type"):
+    with pytest.raises(TypeError, match="Invalid type for `dim`"):
         y.expand_dims(np.array([1, 2]))
 
 

tests/xtensor/test_type.py

@@ -2,6 +2,7 @@ import pytest
 
 
 pytest.importorskip("xarray")
+pytestmark = pytest.mark.filterwarnings("error")
 
 import numpy as np
 from xarray import DataArray