# Copyright 2020 Google Research. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
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# ==============================================================================

"""Helper functions to access TensorShape values.

The rank 4 tensor_shape must be of the form [batch_size, height, width, depth].
"""

from __future__ import absolute_import
from __future__ import division
from __future__ import print_function


def get_dim_as_int(dim):
    """Utility to get v1 or v2 TensorShape dim as an int.

    Args:
        dim: The TensorShape dimension to get as an int

    Returns:
        None or an int.
    """
    try:
        return dim.value
    except AttributeError:
        return dim


def get_batch_size(tensor_shape):
    """Returns batch size from the tensor shape.

    Args:
        tensor_shape: A rank 4 TensorShape.

    Returns:
        An integer representing the batch size of the tensor.
    """
    tensor_shape.assert_has_rank(rank=4)
    return get_dim_as_int(tensor_shape[0])


def get_height(tensor_shape):
    """Returns height from the tensor shape.

    Args:
        tensor_shape: A rank 4 TensorShape.

    Returns:
        An integer representing the height of the tensor.
    """
    tensor_shape.assert_has_rank(rank=4)
    return get_dim_as_int(tensor_shape[1])


def get_width(tensor_shape):
    """Returns width from the tensor shape.

    Args:
        tensor_shape: A rank 4 TensorShape.

    Returns:
        An integer representing the width of the tensor.
    """
    tensor_shape.assert_has_rank(rank=4)
    return get_dim_as_int(tensor_shape[2])


def get_depth(tensor_shape):
    """Returns depth from the tensor shape.

    Args:
        tensor_shape: A rank 4 TensorShape.

    Returns:
        An integer representing the depth of the tensor.
    """
    tensor_shape.assert_has_rank(rank=4)
    return get_dim_as_int(tensor_shape[3])
