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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 | |