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Jun 14, 2025
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Add missing features to xtensor.squeeze() #1473

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35 changes: 20 additions & 15 deletions pytensor/xtensor/shape.py
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Original file line number Diff line number Diff line change
Expand Up @@ -354,24 +354,29 @@ def make_node(self, x):
return Apply(self, [x], [out])


def squeeze(x, dim=None):
"""Remove dimensions of size 1 from an XTensorVariable.
def squeeze(x, dim=None, drop=False, axis=None):
"""Remove dimensions of size 1 from an XTensorVariable."""
x = as_xtensor(x)

Parameters
----------
x : XTensorVariable
The input tensor
dim : str or None or iterable of str, optional
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 parameter is ignored in pytensor.xtensor
if drop is not None:
warnings.warn("drop parameter has no effect in pytensor.xtensor", UserWarning)

Returns
-------
XTensorVariable
A new tensor with the specified dimension(s) removed.
"""
x = as_xtensor(x)
# 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)
elif isinstance(dim, str):
Expand Down
26 changes: 21 additions & 5 deletions pytensor/xtensor/type.py
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Original file line number Diff line number Diff line change
Expand Up @@ -474,17 +474,33 @@ def thin(self, indexers: dict[str, Any] | int | None = None, **indexers_kwargs):
def squeeze(
self,
dim: Sequence[str] | str | None = None,
drop: bool = False,
drop=None,
axis: int | Sequence[int] | None = None,
):
if axis is not None:
raise NotImplementedError("Squeeze with axis not Implemented")
return px.shape.squeeze(self, dim)
"""Remove dimensions of size 1 from an XTensorVariable.

Parameters
----------
x : XTensorVariable
The input tensor
dim : str or None or iterable of str, optional
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.
axis : int or iterable of int, optional
The axis(es) to remove. If None, all dimensions of size 1 will be removed.
Returns
-------
XTensorVariable
A new tensor with the specified dimension(s) removed.
"""
return px.shape.squeeze(self, dim, drop, axis)

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=None,
axis: int | Sequence[int] | None = None,
**dim_kwargs,
):
Expand Down
121 changes: 50 additions & 71 deletions tests/xtensor/test_shape.py
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Original file line number Diff line number Diff line change
Expand Up @@ -14,7 +14,6 @@
from pytensor.tensor import scalar
from pytensor.xtensor.shape import (
concat,
squeeze,
stack,
transpose,
unstack,
Expand Down Expand Up @@ -265,89 +264,74 @@ def test_concat_scalar():
xr_assert_allclose(res, expected_res)


def test_squeeze_explicit_dims():
"""Test squeeze with explicit dimension(s)."""
def test_squeeze():
"""Test squeeze."""

# Single dimension
x1 = xtensor("x1", dims=("city", "country"), shape=(3, 1))
y1 = squeeze(x1, "country")
y1 = x1.squeeze("country")
fn1 = xr_function([x1], y1)
x1_test = xr_arange_like(x1)
xr_assert_allclose(fn1(x1_test), x1_test.squeeze("country"))

# Multiple dimensions
# Multiple dimensions and order independence
x2 = xtensor("x2", dims=("a", "b", "c", "d"), shape=(2, 1, 1, 3))
y2 = squeeze(x2, ["b", "c"])
fn2 = xr_function([x2], y2)
x2_test = xr_arange_like(x2)
xr_assert_allclose(fn2(x2_test), x2_test.squeeze(["b", "c"]))

# Order independence
x3 = xtensor("x3", dims=("a", "b", "c"), shape=(2, 1, 1))
y3a = squeeze(x3, ["b", "c"])
y3b = squeeze(x3, ["c", "b"])
fn3a = xr_function([x3], y3a)
fn3b = xr_function([x3], y3b)
x3_test = xr_arange_like(x3)
xr_assert_allclose(fn3a(x3_test), fn3b(x3_test))

# Redundant dimensions
y3c = squeeze(x3, ["b", "b"])
fn3c = xr_function([x3], y3c)
xr_assert_allclose(fn3c(x3_test), x3_test.squeeze(["b", "b"]))

# Empty list = no-op
y3d = squeeze(x3, [])
fn3d = xr_function([x3], y3d)
xr_assert_allclose(fn3d(x3_test), x3_test)


def test_squeeze_implicit_dims():
"""Test squeeze with implicit dim=None (all size-1 dimensions)."""

# All dimensions size 1
x1 = xtensor("x1", dims=("a", "b"), shape=(1, 1))
y1 = squeeze(x1)
fn1 = xr_function([x1], y1)
x1_test = xr_arange_like(x1)
xr_assert_allclose(fn1(x1_test), x1_test.squeeze())

# No dimensions size 1 = no-op
x2 = xtensor("x2", dims=("row", "col", "batch"), shape=(2, 3, 4))
y2 = squeeze(x2)
fn2 = xr_function([x2], y2)
y2a = x2.squeeze(["b", "c"])
y2b = x2.squeeze(["c", "b"]) # Test order independence
y2c = x2.squeeze(["b", "b"]) # Test redundant dimensions
y2d = x2.squeeze([]) # Test empty list (no-op)
fn2a = xr_function([x2], y2a)
fn2b = xr_function([x2], y2b)
fn2c = xr_function([x2], y2c)
fn2d = xr_function([x2], y2d)
x2_test = xr_arange_like(x2)
xr_assert_allclose(fn2(x2_test), x2_test)
xr_assert_allclose(fn2a(x2_test), x2_test.squeeze(["b", "c"]))
xr_assert_allclose(fn2b(x2_test), x2_test.squeeze(["c", "b"]))
xr_assert_allclose(fn2c(x2_test), x2_test.squeeze(["b", "b"]))
xr_assert_allclose(fn2d(x2_test), x2_test)

# Symbolic shape where runtime shape is 1 → should squeeze
# Unknown shapes
x3 = xtensor("x3", dims=("a", "b", "c")) # shape unknown
y3 = squeeze(x3, "b")
y3 = x3.squeeze("b")
x3_test = xr_arange_like(xtensor(dims=x3.dims, shape=(2, 1, 3)))
fn3 = xr_function([x3], y3)
xr_assert_allclose(fn3(x3_test), x3_test.squeeze("b"))

# Mixed static + symbolic shapes, where symbolic shape is 1
# Mixed known + unknown shapes
x4 = xtensor("x4", dims=("a", "b", "c"), shape=(None, 1, 3))
y4 = squeeze(x4, "b")
y4 = x4.squeeze("b")
x4_test = xr_arange_like(xtensor(dims=x4.dims, shape=(4, 1, 3)))
fn4 = xr_function([x4], y4)
xr_assert_allclose(fn4(x4_test), x4_test.squeeze("b"))

"""
This test documents that we intentionally don't squeeze dimensions with symbolic shapes
(static_shape=None) even when they are 1 at runtime, while xarray does squeeze them.
"""
# Create a tensor with a symbolic dimension that will be 1 at runtime
x = xtensor("x", dims=("a", "b", "c")) # shape unknown
y = squeeze(x) # implicit dim=None should not squeeze symbolic dimensions
x_test = xr_arange_like(xtensor(dims=x.dims, shape=(2, 1, 3)))
fn = xr_function([x], y)
res = fn(x_test)
# Test axis parameter
x5 = xtensor("x5", dims=("a", "b", "c"), shape=(2, 1, 3))
y5 = x5.squeeze(axis=1) # squeeze dimension at index 1 (b)
fn5 = xr_function([x5], y5)
x5_test = xr_arange_like(x5)
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)
fn5 = xr_function([x5], y5)
x5_test = xr_arange_like(x5)
xr_assert_allclose(fn5(x5_test), x5_test.squeeze(axis=-2))

# Test axis parameter with sequence of ints
y6 = x2.squeeze(axis=[1, 2])
fn6 = xr_function([x2], y6)
x2_test = xr_arange_like(x2)
xr_assert_allclose(fn6(x2_test), x2_test.squeeze(axis=[1, 2]))

# Our implementation should not squeeze the symbolic dimension
assert "b" in res.dims
# While xarray would squeeze it
assert "b" not in x_test.squeeze().dims
# Test drop parameter warning
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
fn7 = xr_function([x7], y7)
x7_test = xr_arange_like(x7)
xr_assert_allclose(fn7(x7_test), x7_test.squeeze("b", drop=True))


def test_squeeze_errors():
Expand All @@ -356,15 +340,15 @@ def test_squeeze_errors():
# Non-existent dimension
x1 = xtensor("x1", dims=("city", "country"), shape=(3, 1))
with pytest.raises(ValueError, match="Dimension .* not found"):
squeeze(x1, "time")
x1.squeeze("time")

# Dimension size > 1
with pytest.raises(ValueError, match="has static size .* not 1"):
squeeze(x1, "city")
x1.squeeze("city")

# Symbolic shape: dim is not 1 at runtime → should raise
x2 = xtensor("x2", dims=("a", "b", "c")) # shape unknown
y2 = squeeze(x2, "b")
y2 = x2.squeeze("b")
x2_test = xr_arange_like(xtensor(dims=x2.dims, shape=(2, 2, 3)))
fn2 = xr_function([x2], y2)
with pytest.raises(Exception):
Expand Down Expand Up @@ -471,11 +455,6 @@ def test_expand_dims_errors():
with pytest.raises(ValueError, match="already exists"):
y.expand_dims("new")

# Find out what xarray does with a numpy array as dim
# x_test = xr_arange_like(x)
# x_test.expand_dims(np.array([1, 2]))
# TypeError: unhashable type: 'numpy.ndarray'

# Test with a numpy array as dim (not supported)
with pytest.raises(TypeError, match="unhashable type"):
y.expand_dims(np.array([1, 2]))