| # Copyright 2021 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. | |
| # ============================================================================== | |
| """Tests for `factorized.py`.""" | |
| from absl.testing import absltest | |
| from absl.testing import parameterized | |
| import chex | |
| import jax.numpy as jnp | |
| from optax._src import factorized | |
| class FactorizedTest(parameterized.TestCase): | |
| def setUp(self): | |
| super().setUp() | |
| self.init_params = (jnp.array([1., 2.]), jnp.array([3., 4.])) | |
| self.per_step_updates = (jnp.array([500., 5.]), jnp.array([300., 3.])) | |
| def test_scale_by_factored_rms(self): | |
| params = self.init_params | |
| scaler = factorized.scale_by_factored_rms() | |
| init_fn = self.variant(scaler.init) | |
| transform_fn = self.variant(scaler.update) | |
| state = init_fn(params) | |
| chex.assert_tree_all_finite(state) | |
| updates, state = transform_fn(self.per_step_updates, state, params) | |
| chex.assert_tree_all_finite((params, updates, state)) | |
| chex.assert_trees_all_equal_shapes(params, updates) | |
| if __name__ == '__main__': | |
| absltest.main() | |