mirror of
https://github.com/google-deepmind/deepmind-research.git
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Josh Abramson
86 lines
3.1 KiB
Python
86 lines
3.1 KiB
Python
# Lint as: python2, python3
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# pylint: disable=g-bad-file-header
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# Copyright 2019 DeepMind Technologies Limited. All Rights Reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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# ============================================================================
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"""nest utils."""
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from __future__ import absolute_import
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from __future__ import division
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from __future__ import print_function
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import numpy as np
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from six.moves import range
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from tensorflow.contrib import framework as contrib_framework
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nest = contrib_framework.nest
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def _nest_apply_over_list(list_of_nests, fn):
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"""Equivalent to fn, but works on list-of-nests.
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Transforms a list-of-nests to a nest-of-lists, then applies `fn`
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to each of the inner lists.
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It is assumed that all nests have the same structure. Elements of the nest may
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be None, in which case they are ignored, i.e. they do not form part of the
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stack. This is useful when stacking agent states where parts of the state nest
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have been filtered.
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Args:
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list_of_nests: A Python list of nests.
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fn: the function applied on the list of leaves.
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Returns:
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A nest-of-arrays, where the arrays are formed by `fn`ing a list.
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"""
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list_of_flat_nests = [nest.flatten(n) for n in list_of_nests]
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flat_nest_of_stacks = []
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for position in range(len(list_of_flat_nests[0])):
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new_list = [flat_nest[position] for flat_nest in list_of_flat_nests]
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new_list = [x for x in new_list if x is not None]
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flat_nest_of_stacks.append(fn(new_list))
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return nest.pack_sequence_as(
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structure=list_of_nests[0], flat_sequence=flat_nest_of_stacks)
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def _take_indices(inputs, indices):
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return nest.map_structure(lambda t: np.take(t, indices, axis=0), inputs)
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def nest_stack(list_of_nests, axis=0):
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"""Equivalent to np.stack, but works on list-of-nests.
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Transforms a list-of-nests to a nest-of-lists, then applies `np.stack`
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to each of the inner lists.
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It is assumed that all nests have the same structure. Elements of the nest may
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be None, in which case they are ignored, i.e. they do not form part of the
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stack. This is useful when stacking agent states where parts of the state nest
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have been filtered.
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Args:
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list_of_nests: A Python list of nests.
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axis: Optional, the `axis` argument for `np.stack`.
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Returns:
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A nest-of-arrays, where the arrays are formed by `np.stack`ing a list.
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"""
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return _nest_apply_over_list(list_of_nests, lambda l: np.stack(l, axis=axis))
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def nest_unstack(batched_inputs, batch_size):
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"""Splits a sequence of numpy arrays along 0th dimension."""
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return [_take_indices(batched_inputs, idx) for idx in range(batch_size)]
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