Baruch Tabanpour
5e3464f475
PiperOrigin-RevId: 960553589 Change-Id: I76caca5a82dd7f96b39e51c5b67b7382ebd1726d
133 lines
4.4 KiB
Python
133 lines
4.4 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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"""Integration tests for render + get_rgb / get_depth / get_segmentation."""
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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 forward
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from mujoco.mjx._src import io
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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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import numpy as np
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_FORCE_TEST = os.environ.get('MJX_WARP_FORCE_TEST', '0') == '1'
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_WIDTH, _HEIGHT = 32, 32
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def _setup(batch_size):
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"""Returns (mx, dx_batch, rc) for humanoid with segmentation enabled."""
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m = tu.load_test_file('humanoid/humanoid.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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dx_batch = jax.jit(jax.vmap(forward.forward, in_axes=(None, 0)))(
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mx, dx_batch
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)
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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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render_rgb=True,
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render_depth=True,
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render_seg=True,
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enabled_geom_groups=[0, 1, 2],
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)
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dx_batch = jax.jit(mjx.refit_bvh)(mx, dx_batch, rc.pytree())
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return mx, dx_batch, rc
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class RenderIntegrationTest(parameterized.TestCase):
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"""Tests the full render → unpack pipeline."""
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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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import warp # pylint: disable=g-import-not-at-top
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warp.config.kernel_cache_dir = '/tmp/wp_kernel_cache_dir_RenderIntTest'
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np.random.seed(0)
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def _maybe_skip(self):
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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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@parameterized.parameters(1, 4)
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def test_render_unpack(self, batch_size):
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"""render_with_segmentation → get_rgb / get_depth / get_segmentation."""
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self._maybe_skip()
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mx, dx_batch, rc = _setup(batch_size)
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rgb_packed, depth_packed, seg_packed, dx_batch = jax.jit(
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mjx.render_with_segmentation
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)(mx, dx_batch, rc.pytree())
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rc_pytree = rc.pytree()
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rgb = mjx.get_rgb(rc_pytree, 0, rgb_packed)
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depth = mjx.get_depth(rc_pytree, 0, depth_packed, 5.0)
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seg = mjx.get_segmentation(rc_pytree, 0, seg_packed)
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self.assertEqual(rgb.shape, (batch_size, _HEIGHT, _WIDTH, 3))
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self.assertEqual(depth.shape, (batch_size, _HEIGHT, _WIDTH, 1))
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self.assertEqual(seg.shape, (batch_size, _HEIGHT, _WIDTH))
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self.assertGreater(np.count_nonzero(np.asarray(rgb)), 0)
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self.assertGreater(np.count_nonzero(np.asarray(depth)), 0)
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self.assertTrue(np.any(np.asarray(seg) != -1))
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@parameterized.parameters((4,),)
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def test_render_unpack_vmap(self, batch_size):
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"""render_with_segmentation → vmap(get_rgb / get_depth / get_seg)."""
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self._maybe_skip()
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mx, dx_batch, rc = _setup(batch_size)
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rgb_packed, depth_packed, seg_packed, dx_batch = jax.jit(
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mjx.render_with_segmentation
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)(mx, dx_batch, rc.pytree())
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rc_pytree = rc.pytree()
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rgb = jax.vmap(mjx.get_rgb, in_axes=(None, None, 0))(
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rc_pytree, 0, rgb_packed
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)
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depth = jax.vmap(mjx.get_depth, in_axes=(None, None, 0, None))(
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rc_pytree, 0, depth_packed, 5.0
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)
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seg = jax.vmap(mjx.get_segmentation, in_axes=(None, None, 0))(
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rc_pytree, 0, seg_packed
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)
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self.assertEqual(rgb.shape, (batch_size, _HEIGHT, _WIDTH, 3))
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self.assertEqual(depth.shape, (batch_size, _HEIGHT, _WIDTH, 1))
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self.assertEqual(seg.shape, (batch_size, _HEIGHT, _WIDTH))
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self.assertGreater(np.count_nonzero(np.asarray(rgb)), 0)
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self.assertGreater(np.count_nonzero(np.asarray(depth)), 0)
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self.assertTrue(np.any(np.asarray(seg) != -1))
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if __name__ == '__main__':
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absltest.main()
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