Baruch Tabanpour
47bc16a37c
PiperOrigin-RevId: 789366860 Change-Id: I84b49e744552092434df49d855f1052b04291b87
70 lines
2.2 KiB
Python
70 lines
2.2 KiB
Python
# Copyright 2025 DeepMind Technologies Limited
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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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"""Tests for custom PyTreeNode object."""
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from absl.testing import absltest
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import jax
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from jax import numpy as jp
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from mujoco.mjx._src import dataclasses
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import numpy as np
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class Obj(dataclasses.PyTreeNode):
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a: int
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b: np.ndarray
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c: tuple[int, ...]
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d: tuple[np.ndarray, ...]
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e: jax.Array
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f: tuple[jax.Array, ...]
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class DataclassesTest(absltest.TestCase):
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def test_pytree_structure(self):
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obj = Obj(
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a=1,
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b=np.array([1, 2, 3]),
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c=(4, 5, 6),
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d=(np.array([7, 8]), np.array([9, 10])),
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e=jax.numpy.array([11, 12]),
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f=(jax.numpy.array([13, 14]), jax.numpy.array([15, 16])),
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)
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data, meta = jax.tree_util.tree_flatten_with_path(obj)
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# data fields
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self.assertLen(data, 3)
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self.assertEqual(data[0][0][0].name, 'e')
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np.testing.assert_array_equal(data[0][1], jp.array([11, 12]))
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self.assertEqual(data[1][0][0].name, 'f')
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np.testing.assert_array_equal(data[1][1], jp.array([13, 14]))
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self.assertEqual(data[2][0][0].name, 'f')
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np.testing.assert_array_equal(data[2][1], jp.array([15, 16]))
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# meta fields
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unflattened_meta = meta.unflatten([x[1] for x in data])
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self.assertEqual(unflattened_meta.a, 1)
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np.testing.assert_array_equal(unflattened_meta.b, np.array([1, 2, 3]))
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self.assertEqual(unflattened_meta.c, (4, 5, 6))
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np.testing.assert_array_equal(unflattened_meta.d[0], np.array([7, 8]))
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np.testing.assert_array_equal(unflattened_meta.d[1], np.array([9, 10]))
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# ensure hashable meta
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hash(meta)
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if __name__ == '__main__':
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absltest.main()
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