Baruch Tabanpour
fb47ff01cd
PiperOrigin-RevId: 869822624 Change-Id: Ic20db1dcc2e7287752b273c4ad986066cceccad9
112 lines
3.2 KiB
Python
112 lines
3.2 KiB
Python
# Copyright 2026 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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import functools
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import os
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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 io
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from mujoco.mjx._src import forward
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import mujoco.mjx.warp as mjxw
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from mujoco.mjx.warp import test_util as tu
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from mujoco.mjx.warp import warp as wp # pylint: disable=g-importing-member
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import numpy as np
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_FORCE_TEST = os.environ.get('MJX_WARP_FORCE_TEST', '0') == '1'
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class RenderTest(parameterized.TestCase):
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def setUp(self):
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super().setUp()
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if mjxw.WARP_INSTALLED:
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tempdir = '/tmp/wp_kernel_cache_dir_RenderTest'
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wp.config.kernel_cache_dir = tempdir
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np.random.seed(0)
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@parameterized.product(
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xml=(
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'humanoid/humanoid.xml',
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),
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batch_size=(1, 16),
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)
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def test_render(self, xml: str, batch_size: int):
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"""Tests MJX render pipeline."""
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if not _FORCE_TEST:
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if not mjxw.WARP_INSTALLED:
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self.skipTest('Warp not installed.')
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if not io.has_cuda_gpu_device():
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self.skipTest('No CUDA GPU device available.')
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m = tu.load_test_file(xml)
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d = mujoco.MjData(m)
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mujoco.mj_forward(m, d)
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mx = mjx.put_model(m, impl='warp')
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worldids = jp.arange(batch_size)
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dx_batch = jax.vmap(functools.partial(tu.make_data, m))(worldids)
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key = jax.random.PRNGKey(0)
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keys = jax.random.split(key, batch_size)
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qpos0 = jp.array(m.qpos0)
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rand_qpos = jax.vmap(
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lambda k: qpos0 + jax.random.uniform(
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k, (m.nq,), minval=-0.2, maxval=0.05
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)
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)(keys)
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dx_batch = jax.vmap(
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lambda dx, q: dx.replace(qpos=q)
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)(dx_batch, rand_qpos)
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dx_batch = jax.jit(
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jax.vmap(forward.forward, in_axes=(None, 0))
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)(mx, dx_batch)
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width, height = 32, 32
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rc = mjx.create_render_context(
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mjm=m,
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nworld=batch_size,
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cam_res=(width, height),
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use_textures=True,
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use_shadows=True,
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render_rgb=True,
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render_depth=True,
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enabled_geom_groups=[0, 1, 2],
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)
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dx_batch = jax.jit(
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jax.vmap(mjx.refit_bvh, in_axes=(None, 0, None))
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)(mx, dx_batch, rc)
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out_batch = jax.jit(
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jax.vmap(mjx.render, in_axes=(None, 0, None))
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)(mx, dx_batch, rc)
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rgb = np.asarray(out_batch[0])
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depth = np.asarray(out_batch[1])
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self.assertGreater(np.count_nonzero(rgb), 0)
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self.assertGreater(np.count_nonzero(depth), 0)
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self.assertNotEqual(np.unique(rgb).shape[0], 1)
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self.assertNotEqual(np.unique(depth).shape[0], 1)
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if __name__ == '__main__':
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absltest.main()
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