# Copyright 2019 DeepMind Technologies Limited. 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 # limitations under the License. # ============================================================================== """Utilities to generate random pytrees.""" from typing import Callable import chex import jax from jax import tree_util as jtu from optax._src import base def _tree_rng_keys_split( rng_key: chex.PRNGKey, target_tree: chex.ArrayTree ) -> chex.ArrayTree: """Split keys to match structure of target tree. Args: rng_key: the key to split. target_tree: the tree whose structure to match. Returns: a tree of rng keys. """ tree_def = jtu.tree_structure(target_tree) keys = jax.random.split(rng_key, tree_def.num_leaves) return jtu.tree_unflatten(tree_def, keys) def tree_random_like( rng_key: chex.PRNGKey, target_tree: chex.ArrayTree, sampler: Callable[ [chex.PRNGKey, base.Shape], chex.Array ] = jax.random.normal, ) -> chex.ArrayTree: """Create tree with random entries of the same shape as target tree. Args: rng_key: the key for the random number generator. target_tree: the tree whose structure to match. Leaves must be arrays. sampler: the noise sampling function, by default ``jax.random.normal``. Returns: a random tree with the same structure as ``target_tree``, whose leaves have distribution ``sampler``. .. versionadded:: 0.2.1 """ keys_tree = _tree_rng_keys_split(rng_key, target_tree) return jtu.tree_map( lambda l, k: sampler(k, l.shape), target_tree, keys_tree, )