Source code for tripy.frontend.ops.flatten

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# SPDX-License-Identifier: Apache-2.0
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# Licensed under the Apache License, Version 2.0 (the "License");
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# http://www.apache.org/licenses/LICENSE-2.0
#
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import math

from tripy import constraints, export
from tripy.common.exception import raise_error




@export.public_api(document_under="operations/functions")
@constraints.dtypes(
    constraints={"input": "T1", constraints.RETURN_VALUE: "T1"},
    variables={"T1": ["float32", "float16", "bfloat16", "float8", "int4", "int8", "int32", "int64", "bool"]},
)
def flatten(input: "tripy.Tensor", start_dim: int = 0, end_dim: int = -1) -> "tripy.Tensor":
    """
    Flattens the input tensor from start_dim to end_dim.

    Args:
        input: The input tensor to be flattened.
        start_dim: The first dimension to flatten (default is 0).
        end_dim: The last dimension to flatten (default is -1, which includes the last dimension).

    Returns:
        A flattened tensor.

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

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

    .. code-block:: python
        :linenos:
        :caption: Flatten Starting from First Dimension

        input = tp.iota((2, 3, 4), dtype=tp.float32)
        output = tp.flatten(input, start_dim=1)
        assert np.array_equal(cp.from_dlpack(output).get(), cp.from_dlpack(input).get().reshape(2, -1))

    .. code-block:: python
        :linenos:
        :caption: Flatten a Specific Range of Dimensions

        input = tp.iota((2, 3, 4, 5), dtype=tp.float32)
        output = tp.flatten(input, start_dim=1, end_dim=2)
        assert np.array_equal(cp.from_dlpack(output).get(), cp.from_dlpack(input).get().reshape(2, -1, 5))
    """
    from tripy.frontend.trace.ops.reshape import reshape

    # Infer the actual dimensions to flatten based on start_dim and end_dim.
    if start_dim < 0:
        start_dim += input.rank

    if end_dim < 0:
        end_dim += input.rank

    # Ensure start_dim and end_dim are within the valid range.
    if not (0 <= start_dim < input.rank) or not (start_dim <= end_dim < input.rank):
        raise_error(f"Invalid dimensions: start_dim={start_dim}, end_dim={end_dim}, rank={input.rank}.")

    shape = input.shape
    flattened_dim_size = math.prod(shape[start_dim : end_dim + 1])
    flattened_shape = shape[:start_dim] + [flattened_dim_size] + shape[end_dim + 1 :]
    return reshape(input, flattened_shape)