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# Copyright 2021 DeepMind Technologies Limited
#
# 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
# limitations under the License.
"""Utilities for dealing with shapes of TensorFlow tensors."""
import tensorflow.compat.v1 as tf
def shape_list(x):
"""Return list of dimensions of a tensor, statically where possible.
Like `x.shape.as_list()` but with tensors instead of `None`s.
Args:
x: A tensor.
Returns:
A list with length equal to the rank of the tensor. The n-th element of the
list is an integer when that dimension is statically known otherwise it is
the n-th element of `tf.shape(x)`.
"""
x = tf.convert_to_tensor(x)
# If unknown rank, return dynamic shape
if x.get_shape().dims is None:
return tf.shape(x)
static = x.get_shape().as_list()
shape = tf.shape(x)
ret = []
for i in range(len(static)):
dim = static[i]
if dim is None:
dim = shape[i]
ret.append(dim)
return ret