Add MJX and bump version number to 3.0.0.

Co-authored-by: Baruch Tabanpour <btaba@google.com>
PiperOrigin-RevId: 574327508
Change-Id: Ia9b62fbc929c6869dfcec87636b2e10d405a1060

mjx/mujoco/mjx/_src/support.py

@@ -0,0 +1,81 @@
+# Copyright 2023 DeepMind Technologies Limited
+#
+# 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.
+# ==============================================================================
+"""Engine support functions."""
+
+from typing import Tuple
+
+import jax
+from jax import numpy as jp
+from mujoco.mjx._src import scan
+# pylint: disable=g-importing-member
+from mujoco.mjx._src.types import Data
+from mujoco.mjx._src.types import Model
+# pylint: enable=g-importing-member
+
+
+def jac(
+    m: Model, d: Data, point: jax.Array, body_id: jax.Array
+) -> Tuple[jax.Array, jax.Array]:
+  """Compute pair of (NV, 3) Jacobians of global point attached to body."""
+  fn = lambda carry, b: b if carry is None else b + carry
+  mask = (jp.arange(m.nbody) == body_id) * 1
+  mask = scan.body_tree(m, fn, 'b', 'b', mask, reverse=True)
+  mask = mask[jp.array(m.dof_bodyid)] > 0
+
+  offset = point - d.subtree_com[jp.array(m.body_rootid)[body_id]]
+  jacp = jax.vmap(lambda a, b=offset: a[3:] + jp.cross(a[:3], b))(d.cdof)
+  jacp = jax.vmap(jp.multiply)(jacp, mask)
+  jacr = jax.vmap(jp.multiply)(d.cdof[:, :3], mask)
+
+  return jacp, jacr
+
+
+def jac_dif_pair(
+    m: Model,
+    d: Data,
+    pos: jax.Array,
+    body_1: jax.Array,
+    body_2: jax.Array,
+) -> jax.Array:
+  """Compute Jacobian difference for two body points."""
+  jacp2, _ = jac(m, d, pos, body_2)
+  jacp1, _ = jac(m, d, pos, body_1)
+  return jacp2 - jacp1
+
+
+def apply_ft(
+    m: Model,
+    d: Data,
+    force: jax.Array,
+    torque: jax.Array,
+    point: jax.Array,
+    body_id: jax.Array,
+) -> jax.Array:
+  """Apply Cartesian force and torque."""
+  jacp, jacr = jac(m, d, point, body_id)
+  return jacp @ force + jacr @ torque
+
+
+def xfrc_accumulate(m: Model, d: Data) -> jax.Array:
+  """Accumulate xfrc_applied into a qfrc."""
+  qfrc = jax.vmap(apply_ft, in_axes=(None, None, 0, 0, 0, 0))(
+      m,
+      d,
+      d.xfrc_applied[:, :3],
+      d.xfrc_applied[:, 3:],
+      d.xipos,
+      jp.arange(m.nbody),
+  )
+  return jp.sum(qfrc, axis=0)