FM / array

/opt/cloudlinux/venv/lib/python3.11/site-packages/numpy/array_api/

/opt/cloudlinux/venv/lib/python3.11/site-packages/numpy/array_api

Name	Size	Mode	Actions
tests/	-	0755	rm
__pycache__/	-	0755	rm
linalg.py	18221	0644	edit dl rm
setup.py	341	0644	edit dl rm
_array_object.py	43739	0644	edit dl rm
_constants.py	66	0644	edit dl rm
_creation_functions.py	10050	0644	edit dl rm
_data_type_functions.py	6288	0644	edit dl rm
_dtypes.py	4823	0644	edit dl rm
_elementwise_functions.py	25992	0644	edit dl rm
_indexing_functions.py	601	0644	edit dl rm
_manipulation_functions.py	3317	0644	edit dl rm
_searching_functions.py	1715	0644	edit dl rm
_set_functions.py	2948	0644	edit dl rm
_sorting_functions.py	2031	0644	edit dl rm
_statistical_functions.py	3584	0644	edit dl rm
_typing.py	1228	0644	edit dl rm
_utility_functions.py	824	0644	edit dl rm
__init__.py	10355	0644	edit dl rm

Edit: /opt/cloudlinux/venv/lib/python3.11/site-packages/numpy/array_api/_manipulation_functions.py (3317B)

from __future__ import annotations

from ._array_object import Array
from ._data_type_functions import result_type

from typing import List, Optional, Tuple, Union

import numpy as np

# Note: the function name is different here
def concat(
    arrays: Union[Tuple[Array, ...], List[Array]], /, *, axis: Optional[int] = 0
) -> Array:
    """
    Array API compatible wrapper for :py:func:`np.concatenate <numpy.concatenate>`.

See its docstring for more information.
    """
    # Note: Casting rules here are different from the np.concatenate default
    # (no for scalars with axis=None, no cross-kind casting)
    dtype = result_type(*arrays)
    arrays = tuple(a._array for a in arrays)
    return Array._new(np.concatenate(arrays, axis=axis, dtype=dtype))

def expand_dims(x: Array, /, *, axis: int) -> Array:
    """
    Array API compatible wrapper for :py:func:`np.expand_dims <numpy.expand_dims>`.

See its docstring for more information.
    """
    return Array._new(np.expand_dims(x._array, axis))

def flip(x: Array, /, *, axis: Optional[Union[int, Tuple[int, ...]]] = None) -> Array:
    """
    Array API compatible wrapper for :py:func:`np.flip <numpy.flip>`.

See its docstring for more information.
    """
    return Array._new(np.flip(x._array, axis=axis))

# Note: The function name is different here (see also matrix_transpose).
# Unlike transpose(), the axes argument is required.
def permute_dims(x: Array, /, axes: Tuple[int, ...]) -> Array:
    """
    Array API compatible wrapper for :py:func:`np.transpose <numpy.transpose>`.

See its docstring for more information.
    """
    return Array._new(np.transpose(x._array, axes))

# Note: the optional argument is called 'shape', not 'newshape'
def reshape(x: Array, 
            /, 
            shape: Tuple[int, ...],
            *,
            copy: Optional[Bool] = None) -> Array:
    """
    Array API compatible wrapper for :py:func:`np.reshape <numpy.reshape>`.

See its docstring for more information.
    """

data = x._array
    if copy:
        data = np.copy(data)

reshaped = np.reshape(data, shape)

if copy is False and not np.shares_memory(data, reshaped):
        raise AttributeError("Incompatible shape for in-place modification.")

return Array._new(reshaped)

def roll(
    x: Array,
    /,
    shift: Union[int, Tuple[int, ...]],
    *,
    axis: Optional[Union[int, Tuple[int, ...]]] = None,
) -> Array:
    """
    Array API compatible wrapper for :py:func:`np.roll <numpy.roll>`.

See its docstring for more information.
    """
    return Array._new(np.roll(x._array, shift, axis=axis))

def squeeze(x: Array, /, axis: Union[int, Tuple[int, ...]]) -> Array:
    """
    Array API compatible wrapper for :py:func:`np.squeeze <numpy.squeeze>`.

See its docstring for more information.
    """
    return Array._new(np.squeeze(x._array, axis=axis))

def stack(arrays: Union[Tuple[Array, ...], List[Array]], /, *, axis: int = 0) -> Array:
    """
    Array API compatible wrapper for :py:func:`np.stack <numpy.stack>`.

See its docstring for more information.
    """
    # Call result type here just to raise on disallowed type combinations
    result_type(*arrays)
    arrays = tuple(a._array for a in arrays)
    return Array._new(np.stack(arrays, axis=axis))

from __future__ import annotations from ._array_object import Array from ._data_type_functions import result_type from typing import List, Optional, Tuple, Union import numpy as np # Note: the function name is different here def concat( arrays: Union[Tuple[Array, ...], List[Array]], /, *, axis: Optional[int] = 0 ) -> Array: """ Array API compatible wrapper for :py:func:`np.concatenate `. See its docstring for more information. """ # Note: Casting rules here are different from the np.concatenate default # (no for scalars with axis=None, no cross-kind casting) dtype = result_type(*arrays) arrays = tuple(a._array for a in arrays) return Array._new(np.concatenate(arrays, axis=axis, dtype=dtype)) def expand_dims(x: Array, /, *, axis: int) -> Array: """ Array API compatible wrapper for :py:func:`np.expand_dims `. See its docstring for more information. """ return Array._new(np.expand_dims(x._array, axis)) def flip(x: Array, /, *, axis: Optional[Union[int, Tuple[int, ...]]] = None) -> Array: """ Array API compatible wrapper for :py:func:`np.flip `. See its docstring for more information. """ return Array._new(np.flip(x._array, axis=axis)) # Note: The function name is different here (see also matrix_transpose). # Unlike transpose(), the axes argument is required. def permute_dims(x: Array, /, axes: Tuple[int, ...]) -> Array: """ Array API compatible wrapper for :py:func:`np.transpose `. See its docstring for more information. """ return Array._new(np.transpose(x._array, axes)) # Note: the optional argument is called 'shape', not 'newshape' def reshape(x: Array, /, shape: Tuple[int, ...], *, copy: Optional[Bool] = None) -> Array: """ Array API compatible wrapper for :py:func:`np.reshape `. See its docstring for more information. """ data = x._array if copy: data = np.copy(data) reshaped = np.reshape(data, shape) if copy is False and not np.shares_memory(data, reshaped): raise AttributeError("Incompatible shape for in-place modification.") return Array._new(reshaped) def roll( x: Array, /, shift: Union[int, Tuple[int, ...]], *, axis: Optional[Union[int, Tuple[int, ...]]] = None, ) -> Array: """ Array API compatible wrapper for :py:func:`np.roll `. See its docstring for more information. """ return Array._new(np.roll(x._array, shift, axis=axis)) def squeeze(x: Array, /, axis: Union[int, Tuple[int, ...]]) -> Array: """ Array API compatible wrapper for :py:func:`np.squeeze `. See its docstring for more information. """ return Array._new(np.squeeze(x._array, axis=axis)) def stack(arrays: Union[Tuple[Array, ...], List[Array]], /, *, axis: int = 0) -> Array: """ Array API compatible wrapper for :py:func:`np.stack `. See its docstring for more information. """ # Call result type here just to raise on disallowed type combinations result_type(*arrays) arrays = tuple(a._array for a in arrays) return Array._new(np.stack(arrays, axis=axis))