Add MJX and bump version number to 3.0.0.
Co-authored-by: Baruch Tabanpour <btaba@google.com> PiperOrigin-RevId: 574327508 Change-Id: Ia9b62fbc929c6869dfcec87636b2e10d405a1060
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committed by
Saran Tunyasuvunakool
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# Copyright 2023 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 support."""
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from absl.testing import absltest
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from absl.testing import parameterized
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import jax
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from jax import numpy as jp
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import mujoco
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from mujoco import mjx
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from mujoco.mjx._src import support
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from mujoco.mjx._src import test_util
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import numpy as np
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class SupportTest(parameterized.TestCase):
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@parameterized.parameters(set(test_util.TEST_FILES) - {'convex.xml'})
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def test_jac(self, fname):
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np.random.seed(0)
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m = test_util.load_test_file(fname)
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d = mujoco.MjData(m)
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mujoco.mj_step(m, d)
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mx = mjx.device_put(m)
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dx = mjx.device_put(d)
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point = np.random.randn(3)
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body = np.random.choice(m.nbody)
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jacp, jacr = jax.jit(support.jac)(mx, dx, point, body)
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jacp_expected, jacr_expected = np.zeros((3, m.nv)), np.zeros((3, m.nv))
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mujoco.mj_jac(m, d, jacp_expected, jacr_expected, point, body)
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np.testing.assert_almost_equal(jacp, jacp_expected.T, 6)
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np.testing.assert_almost_equal(jacr, jacr_expected.T, 6)
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def test_xfrc_accumulate(self):
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"""Tests that xfrc_accumulate ouput matches mj_xfrcAccumulate."""
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np.random.seed(0)
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m = test_util.load_test_file('ant.xml')
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d = mujoco.MjData(m)
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mujoco.mj_step(m, d)
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mx = mjx.device_put(m)
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dx = mjx.device_put(d)
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self.assertFalse((dx.xipos == 0.0).all())
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xfrc = np.random.rand(*dx.xfrc_applied.shape)
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d.xfrc_applied[:] = xfrc
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dx = dx.replace(xfrc_applied=jp.array(xfrc))
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qfrc = jax.jit(support.xfrc_accumulate)(mx, dx)
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qfrc_expected = np.zeros(m.nv)
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for i in range(1, m.nbody):
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mujoco.mj_applyFT(
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m,
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d,
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d.xfrc_applied[i, :3],
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d.xfrc_applied[i, 3:],
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d.xipos[i],
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i,
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qfrc_expected,
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)
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np.testing.assert_almost_equal(qfrc, qfrc_expected, 6)
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if __name__ == '__main__':
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absltest.main()
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