Update numpy deprecated imports

- replaced np.AxisError with np.exceptions.AxisError
- the `numpy.core` submodule has been renamed to `numpy._core`
- some parts of `numpy.core` have been moved to `numpy.lib.array_utils`

Except for `AxisError`, the updated imports are conditional on
the version of numpy, so the imports should work for numpy >= 1.26.

pytensor/link/c/basic.py

@@ -1367,8 +1367,8 @@ def cmodule_key_(
 
         # We must always add the numpy ABI version here as
         # DynamicModule always add the include <numpy/arrayobject.h>
-        if np.lib.NumpyVersion(np.__version__) < "1.16.0a":
-            ndarray_c_version = np.core.multiarray._get_ndarray_c_version()
+        if np.lib.NumpyVersion(np.__version__) > "1.27.0":
+            ndarray_c_version = np._core._multiarray_umath._get_ndarray_c_version()
         else:
             ndarray_c_version = np.core._multiarray_umath._get_ndarray_c_version()
         sig.append(f"NPY_ABI_VERSION=0x{ndarray_c_version:X}")

pytensor/link/numba/dispatch/elemwise.py

@@ -4,7 +4,14 @@
 import numba
 import numpy as np
 from numba.core.extending import overload
-from numpy.core.numeric import normalize_axis_index, normalize_axis_tuple
+
+
+try:
+    from numpy.lib.array_utils import normalize_axis_index, normalize_axis_tuple
+except ModuleNotFoundError:
+    # numpy < 2.0
+    from numpy.core.multiarray import normalize_axis_index
+    from numpy.core.numeric import normalize_axis_tuple
 
 from pytensor.graph.op import Op
 from pytensor.link.numba.dispatch import basic as numba_basic

pytensor/tensor/__init__.py

@@ -123,7 +123,7 @@ def _get_vector_length_Constant(op: Op | Variable, var: Constant) -> int:
 
 # isort: on
 # Allow accessing numpy constants from pytensor.tensor
-from numpy import e, euler_gamma, inf, infty, nan, newaxis, pi
+from numpy import e, euler_gamma, inf, nan, newaxis, pi
 
 from pytensor.tensor.basic import *
 from pytensor.tensor.blas import batched_dot, batched_tensordot

pytensor/tensor/basic.py

@@ -14,8 +14,17 @@
 from typing import cast as type_cast
 
 import numpy as np
-from numpy.core.multiarray import normalize_axis_index
-from numpy.core.numeric import normalize_axis_tuple
+
+
+try:
+    from numpy.lib.array_utils import normalize_axis_index, normalize_axis_tuple
+except ModuleNotFoundError:
+    # numpy < 2.0
+    from numpy.core.multiarray import normalize_axis_index
+    from numpy.core.numeric import normalize_axis_tuple
+
+
+from numpy.exceptions import AxisError
 
 import pytensor
 import pytensor.scalar.sharedvar
@@ -228,7 +237,7 @@ def constant(x, name=None, ndim=None, dtype=None) -> TensorConstant:
         elif x_.ndim > ndim:
             try:
                 x_ = np.squeeze(x_, axis=tuple(range(x_.ndim - ndim)))
-            except np.AxisError:
+            except AxisError:
                 raise ValueError(
                     f"ndarray could not be cast to constant with {int(ndim)} dimensions"
                 )
@@ -4406,7 +4415,7 @@ def expand_dims(a: np.ndarray | TensorVariable, axis: Sequence[int]) -> TensorVa
         axis = (axis,)
 
     out_ndim = len(axis) + a.ndim
-    axis = np.core.numeric.normalize_axis_tuple(axis, out_ndim)
+    axis = normalize_axis_tuple(axis, out_ndim)
 
     if not axis:
         return a

pytensor/tensor/conv/abstract_conv.py

@@ -8,6 +8,7 @@
 from math import gcd
 
 import numpy as np
+from numpy.exceptions import ComplexWarning
 
 
 try:
@@ -2338,7 +2339,7 @@ def conv(
             bval = _bvalfromboundary("fill")
 
             with warnings.catch_warnings():
-                warnings.simplefilter("ignore", np.ComplexWarning)
+                warnings.simplefilter("ignore", ComplexWarning)
                 for b in range(img.shape[0]):
                     for g in range(self.num_groups):
                         for n in range(output_channel_offset):

pytensor/tensor/einsum.py

@@ -6,11 +6,25 @@
 from typing import cast
 
 import numpy as np
-from numpy.core.einsumfunc import _find_contraction, _parse_einsum_input  # type: ignore
-from numpy.core.numeric import (  # type: ignore
-    normalize_axis_index,
-    normalize_axis_tuple,
-)
+
+
+try:
+    from numpy._core.einsumfunc import (  # type: ignore
+        _find_contraction,
+        _parse_einsum_input,
+    )
+except ModuleNotFoundError:
+    from numpy.core.einsumfunc import (  # type: ignore
+        _find_contraction,
+        _parse_einsum_input,
+    )
+
+try:
+    from numpy.lib.array_utils import normalize_axis_index, normalize_axis_tuple
+except ModuleNotFoundError:
+    # numpy < 2.0
+    from numpy.core.multiarray import normalize_axis_index  # type: ignore
+    from numpy.core.numeric import normalize_axis_tuple  # type: ignore
 
 from pytensor.compile.builders import OpFromGraph
 from pytensor.tensor import TensorLike

pytensor/tensor/elemwise.py

@@ -4,7 +4,13 @@
 from typing import Literal
 
 import numpy as np
-from numpy.core.numeric import normalize_axis_tuple
+
+
+try:
+    from numpy.lib.array_utils import normalize_axis_tuple
+except ModuleNotFoundError:
+    # numpy < 2.0
+    from numpy.core.numeric import normalize_axis_tuple
 
 import pytensor.tensor.basic
 from pytensor.configdefaults import config

pytensor/tensor/extra_ops.py

@@ -2,7 +2,15 @@
 from collections.abc import Collection, Iterable
 
 import numpy as np
-from numpy.core.multiarray import normalize_axis_index
+from numpy.exceptions import AxisError
+
+
+try:
+    from numpy.lib.array_utils import normalize_axis_index, normalize_axis_tuple
+except ModuleNotFoundError:
+    # numpy < 2.0
+    from numpy.core.multiarray import normalize_axis_index
+    from numpy.core.numeric import normalize_axis_tuple
 
 import pytensor
 import pytensor.scalar.basic as ps
@@ -596,9 +604,9 @@ def squeeze(x, axis=None):
 
     # scalar inputs are treated as 1D regarding axis in this `Op`
     try:
-        axis = np.core.numeric.normalize_axis_tuple(axis, ndim=max(1, _x.ndim))
-    except np.AxisError:
-        raise np.AxisError(axis, ndim=_x.ndim)
+        axis = normalize_axis_tuple(axis, ndim=max(1, _x.ndim))
+    except AxisError:
+        raise AxisError(axis, ndim=_x.ndim)
 
     if not axis:
         # Nothing to do

pytensor/tensor/math.py

@@ -5,7 +5,13 @@
 from typing import TYPE_CHECKING, Optional
 
 import numpy as np
-from numpy.core.numeric import normalize_axis_tuple
+
+
+try:
+    from numpy.lib.array_utils import normalize_axis_tuple
+except ModuleNotFoundError:
+    # numpy < 2.0
+    from numpy.core.numeric import normalize_axis_tuple
 
 from pytensor import config, printing
 from pytensor import scalar as ps

pytensor/tensor/nlinalg.py

@@ -4,7 +4,14 @@
 from typing import Literal, cast
 
 import numpy as np
-from numpy.core.numeric import normalize_axis_tuple  # type: ignore
+
+
+try:
+    from numpy.lib.array_utils import normalize_axis_tuple
+except ModuleNotFoundError:
+    # numpy < 2.0
+    from numpy.core.numeric import normalize_axis_tuple  # type: ignore
+
 
 from pytensor import scalar as ps
 from pytensor.compile.builders import OpFromGraph

pytensor/tensor/shape.py

@@ -4,7 +4,13 @@
 from typing import cast
 
 import numpy as np
-from numpy.core.numeric import normalize_axis_tuple  # type: ignore
+
+
+try:
+    from numpy.lib.array_utils import normalize_axis_tuple
+except ModuleNotFoundError:
+    # numpy < 2.0
+    from numpy.core.numeric import normalize_axis_tuple  # type: ignore
 
 import pytensor
 from pytensor.gradient import DisconnectedType

pytensor/tensor/slinalg.py

@@ -6,6 +6,7 @@
 
 import numpy as np
 import scipy.linalg
+from numpy.exceptions import ComplexWarning
 
 import pytensor
 import pytensor.tensor as pt
@@ -767,7 +768,7 @@ def perform(self, node, inputs, outputs):
         Y = U.dot(V.T.dot(gA).dot(U) * X).dot(V.T)
 
         with warnings.catch_warnings():
-            warnings.simplefilter("ignore", np.ComplexWarning)
+            warnings.simplefilter("ignore", ComplexWarning)
             out[0] = Y.astype(A.dtype)
 
 

pytensor/tensor/utils.py

@@ -3,7 +3,13 @@
 from typing import cast
 
 import numpy as np
-from numpy.core.numeric import normalize_axis_tuple  # type: ignore
+
+
+try:
+    from numpy.lib.array_utils import normalize_axis_tuple
+except ModuleNotFoundError:
+    # numpy < 2.0
+    from numpy.core.numeric import normalize_axis_tuple  # type: ignore
 
 import pytensor
 from pytensor.graph import FunctionGraph, Variable
@@ -236,8 +242,8 @@ def normalize_reduce_axis(axis, ndim: int) -> tuple[int, ...] | None:
     if axis is not None:
         try:
             axis = normalize_axis_tuple(axis, ndim=max(1, ndim))
-        except np.AxisError:
-            raise np.AxisError(axis, ndim=ndim)
+        except np.exceptions.AxisError:
+            raise np.exceptions.AxisError(axis, ndim=ndim)
 
     # TODO: If axis tuple is equivalent to None, return None for more canonicalization?
     return cast(tuple, axis)

tests/tensor/test_elemwise.py

@@ -672,7 +672,7 @@ def test_scalar_input(self):
         assert self.op(ps.add, axis=(-1,))(x).eval({x: 5}) == 5
 
         with pytest.raises(
-            np.AxisError,
+            np.exceptions.AxisError,
             match=re.escape("axis (-2,) is out of bounds for array of dimension 0"),
         ):
             self.op(ps.add, axis=(-2,))(x)

tests/tensor/test_extra_ops.py

@@ -469,7 +469,7 @@ def test_scalar_input(self):
         assert squeeze(x, axis=(0,)).eval({x: 5}) == 5
 
         with pytest.raises(
-            np.AxisError,
+            np.exceptions.AxisError,
             match=re.escape("axis (1,) is out of bounds for array of dimension 0"),
         ):
             squeeze(x, axis=1)

tests/tensor/test_io.py

@@ -49,7 +49,7 @@ def test_memmap(self):
         path = Variable(Generic(), None)
         x = load(path, "int32", (None,), mmap_mode="c")
         fn = function([path], x)
-        assert isinstance(fn(self.filename), np.core.memmap)
+        assert type(fn(self.filename)) == np.memmap
 
     def teardown_method(self):
         (pytensor.config.compiledir / "_test.npy").unlink()