Source code for nvtripy.frontend.ops.squeeze

# SPDX-FileCopyrightText: Copyright (c) 2025 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
# SPDX-License-Identifier: Apache-2.0
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
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#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
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from typing import Sequence, Union

from nvtripy import export, utils
from nvtripy.common import datatype as dt
from nvtripy.frontend.ops import utils as op_utils
from nvtripy.frontend.ops._registry import register_tensor_method
from nvtripy.frontend import wrappers
from nvtripy.frontend.constraints import GetInput, GetReturn, OneOf




@register_tensor_method("squeeze")
@export.public_api(document_under="operations/functions")
@wrappers.interface(
    input_requirements=OneOf(
        GetInput("input").dtype, [dt.float32, dt.float16, dt.bfloat16, dt.int8, dt.int32, dt.int64, dt.bool]
    ),
    output_guarantees=GetReturn(0).dtype == GetInput("input").dtype,
)
def squeeze(input: "nvtripy.Tensor", dims: Union[Sequence[int], int]) -> "nvtripy.Tensor":
    """
    Returns a new tensor with the specified singleton dimensions of the input tensor removed.

    Args:
        input: The input tensor.
        dims: The dimension(s) to remove. These must have a length of 1.

    Returns:
        A new tensor.

    .. code-block:: python
        :linenos:
        :caption: Squeeze All Dimensions

        input = tp.iota((1, 2, 1), dtype=tp.float32)
        output = tp.squeeze(input, dims=(0, 2))
        assert np.array_equal(cp.from_dlpack(output).get(), np.squeeze(cp.from_dlpack(input).get()))


    .. code-block:: python
        :linenos:
        :caption: Squeeze First Dimension

        input = tp.iota((1, 2, 1), dtype=tp.float32)
        output = tp.squeeze(input, 0)
        assert np.array_equal(cp.from_dlpack(output).get(), np.squeeze(cp.from_dlpack(input).get(), 0))

    .. code-block:: python
        :linenos:
        :caption: Squeeze First And Third Dimension

        input = tp.iota((1, 2, 1), dtype=tp.float32)
        output = tp.squeeze(input, (0, 2))

        assert np.array_equal(cp.from_dlpack(output).get(), np.squeeze(cp.from_dlpack(input).get(), (0, 2)))
    """
    from nvtripy.frontend.ops.reshape import reshape

    dims = utils.utils.make_tuple(dims)

    if not dims:
        return input

    dims = tuple(op_utils.process_dim(dim, input.rank) for dim in dims)

    shape = input.shape
    new_shape = [dim for idx, dim in enumerate(shape) if idx not in dims]
    return reshape(input, new_shape)