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chore(deps): 消费 unisim-core 2.1.0，interval op payload 对齐 torch-first 契约 #2496

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Merged
TATP-233 merged 2 commits into from
Oct 21, 2026
Merged

chore(deps): 消费 unisim-core 2.1.0，interval op payload 对齐 torch-first 契约 #2496

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33b1245
chore(deps): bump unisim-core pin to 2.1.0 (#2474)
TATP-233 Oct 21, 2026
8f4c67e
fix(base): build interval op payloads as torch tensors for unisim 2.1…
TATP-233 Oct 21, 2026
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4 changes: 2 additions & 2 deletions pyproject.rocm.toml
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Expand Up @@ -23,7 +23,7 @@ classifiers = [
requires-python = ">=3.10,<3.14"
dependencies = [
"numpy",
"unisim-core==2.0.1",
"unisim-core==2.1.0",
"prettytable>=3.10",
"torch==2.14.0",
"triton-rocm==3.8.0 ; sys_platform == 'linux' and platform_machine == 'x86_64'",
Expand Down Expand Up @@ -72,7 +72,7 @@ mujoco = [
"mujoco~=3.11.0",
"mjbatch-uni~=0.2.5",
]
motrix = ["unisim-core[motrix]==2.0.1"]
motrix = ["unisim-core[motrix]==2.1.0"]

[dependency-groups]
# The RL stack (APPO/off-policy/multi-GPU) is merged into unilab itself
Expand Down
6 changes: 3 additions & 3 deletions pyproject.toml
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Expand Up @@ -33,7 +33,7 @@ classifiers = [
requires-python = ">=3.10,<3.14"
dependencies = [
"numpy",
"unisim-core==2.0.1",
"unisim-core==2.1.0",
"prettytable>=3.10",
# A range (not an exact pin) lets ROCm users substitute a ROCm torch
# build; uv.lock pins the tested CUDA builds via tool.uv.sources.
Expand Down Expand Up @@ -106,12 +106,12 @@ newton = [
"pyglet>=2.1.6,<3",
"imgui-bundle>=1.92.0",
]
motrix = ["unisim-core[motrix]==2.0.1"]
motrix = ["unisim-core[motrix]==2.1.0"]
genesis = ["genesis-world==1.3.3"]
# Wheels are CPython 3.12/3.13 Linux x86_64 only; the marker keeps uv lock
# resolvable for the other required-environments.
superdex = [
"unisim-core[superdex]==2.0.1 ; python_version >= '3.12' and sys_platform == 'linux' and platform_machine == 'x86_64'",
"unisim-core[superdex]==2.1.0 ; python_version >= '3.12' and sys_platform == 'linux' and platform_machine == 'x86_64'",
]

[dependency-groups]
Expand Down
16 changes: 10 additions & 6 deletions tests/base/test_genesis_backend.py
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Expand Up @@ -566,12 +566,14 @@ def test_dr_capabilities_and_tensor_reset_randomization_boundary(
def test_interval_randomization_and_body_force(fake_genesis, tiny_model_file: str) -> None:
backend = _backend(tiny_model_file)
solver = backend._scene.sim.rigid_solver
force = np.ones((4, 2, 3), dtype=np.float32)
force = torch.ones((4, 2, 3), dtype=torch.float32)
backend.apply_interval_randomization(
IntervalRandomizationPlan(
ops=(
IntervalTermOp(
INTERVAL_TERM_BODY_FORCE, force, body_ids=np.array([1, 3], dtype=np.int32)
INTERVAL_TERM_BODY_FORCE,
force,
body_ids=torch.as_tensor([1, 3], dtype=torch.int32),
),
)
)
Expand All @@ -583,7 +585,7 @@ def test_interval_randomization_and_body_force(fake_genesis, tiny_model_file: st

with pytest.raises(NotImplementedError, match="does not support interval term 'push'"):
backend.apply_interval_randomization(
IntervalRandomizationPlan(ops=(IntervalTermOp(INTERVAL_TERM_PUSH, np.ones((1, 3))),))
IntervalRandomizationPlan(ops=(IntervalTermOp(INTERVAL_TERM_PUSH, torch.ones((1, 3))),))
)
with pytest.raises(
NotImplementedError, match="does not support interval term 'body_linear_velocity_delta'"
Expand All @@ -593,8 +595,8 @@ def test_interval_randomization_and_body_force(fake_genesis, tiny_model_file: st
ops=(
IntervalTermOp(
INTERVAL_TERM_BODY_LINEAR_VELOCITY_DELTA,
np.zeros((4, 1, 3), dtype=np.float32),
body_ids=np.array([1], dtype=np.int32),
torch.zeros((4, 1, 3), dtype=torch.float32),
body_ids=torch.as_tensor([1], dtype=torch.int32),
),
)
)
Expand All @@ -603,7 +605,9 @@ def test_interval_randomization_and_body_force(fake_genesis, tiny_model_file: st
backend.apply_interval_randomization(
IntervalRandomizationPlan(
ops=(
IntervalTermOp(INTERVAL_TERM_BODY_FORCE, np.zeros((4, 1, 3), dtype=np.float32)),
IntervalTermOp(
INTERVAL_TERM_BODY_FORCE, torch.zeros((4, 1, 3), dtype=torch.float32)
),
)
)
)
Expand Down
7 changes: 4 additions & 3 deletions tests/base/test_mjwarp_capabilities.py
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Expand Up @@ -8,6 +8,7 @@

import numpy as np
import pytest
import torch
from unisim.backend.mjwarp.dependencies import load_mjwarp_dependencies
from unisim.dr.types import (
INTERVAL_TERM_BODY_LINEAR_VELOCITY_DELTA,
Expand Down Expand Up @@ -73,7 +74,7 @@ def test_interval_push_and_velocity_require_named_bodies() -> None:
with pytest.raises(NotImplementedError, match="push target body"):
backend.apply_interval_randomization(
IntervalRandomizationPlan(
ops=(IntervalTermOp(INTERVAL_TERM_PUSH, np.ones((3,), dtype=np.float32)),)
ops=(IntervalTermOp(INTERVAL_TERM_PUSH, torch.ones((3,), dtype=torch.float32)),)
)
)
with pytest.raises(NotImplementedError, match="exactly one free joint"):
Expand All @@ -82,8 +83,8 @@ def test_interval_push_and_velocity_require_named_bodies() -> None:
ops=(
IntervalTermOp(
INTERVAL_TERM_BODY_LINEAR_VELOCITY_DELTA,
np.zeros((1, 1, 3), dtype=np.float32),
body_ids=np.asarray([1], dtype=np.int32),
torch.zeros((1, 1, 3), dtype=torch.float32),
body_ids=torch.as_tensor([1], dtype=torch.int32),
),
)
)
Expand Down
24 changes: 15 additions & 9 deletions tests/base/test_mjwarp_dr.py
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Expand Up @@ -316,15 +316,15 @@ def test_heavier_world_accelerates_less_under_identical_body_force(backend: Any)
randomization=_tensor_payload(body_mass=body_mass),
)

force = np.zeros((backend.num_envs, 1, 3), dtype=np.float32)
force = torch.zeros((backend.num_envs, 1, 3), dtype=torch.float32)
force[:, 0, 0] = 300.0
backend.apply_interval_randomization(
IntervalRandomizationPlan(
ops=(
IntervalTermOp(
INTERVAL_TERM_BODY_FORCE,
force,
body_ids=np.asarray([backend._base_body_id]),
body_ids=torch.as_tensor([backend._base_body_id]),
),
)
)
Expand All @@ -348,7 +348,11 @@ def test_push_robots_stages_one_step_force(backend: Any) -> None:
_reset_all(backend)
backend.apply_interval_randomization(
IntervalRandomizationPlan(
ops=(IntervalTermOp(INTERVAL_TERM_PUSH, np.asarray([80.0, 0.0, 0.0])),)
ops=(
IntervalTermOp(
INTERVAL_TERM_PUSH, torch.tensor([80.0, 0.0, 0.0], dtype=torch.float64)
),
)
)
)
assert backend._xfrc_pending
Expand All @@ -363,21 +367,23 @@ def test_push_robots_stages_one_step_force(backend: Any) -> None:
def test_interval_velocity_delta_kicks_selected_rows(backend: Any) -> None:
_reset_all(backend)
before = backend.get_base_lin_vel().copy()
delta = np.zeros((backend.num_envs, 1, 3), dtype=np.float32)
delta[[0, 3], 0, :] = np.asarray([[0.4, -0.2, 0.0], [-0.3, 0.1, 0.0]], dtype=np.float32)
delta = torch.zeros((backend.num_envs, 1, 3), dtype=torch.float32)
delta[[0, 3], 0, :] = torch.tensor([[0.4, -0.2, 0.0], [-0.3, 0.1, 0.0]], dtype=torch.float32)
backend.apply_interval_randomization(
IntervalRandomizationPlan(
ops=(
IntervalTermOp(
INTERVAL_TERM_BODY_LINEAR_VELOCITY_DELTA,
delta,
body_ids=np.asarray([backend._base_body_id], dtype=np.int32),
body_ids=torch.as_tensor([backend._base_body_id], dtype=torch.int32),
),
)
)
)
after = backend.get_base_lin_vel()
np.testing.assert_allclose(after[[0, 3]], before[[0, 3]] + delta[[0, 3], 0, :], atol=1e-6)
np.testing.assert_allclose(
after[[0, 3]], before[[0, 3]] + delta[[0, 3], 0, :].numpy(), atol=1e-6
)
np.testing.assert_allclose(after[[1, 2]], before[[1, 2]], atol=1e-6)
# The kick commits through the forward barrier, keeping sensors coherent.
assert np.isfinite(backend.get_sensor_data("torso_upvector")).all()
Expand Down Expand Up @@ -419,15 +425,15 @@ def test_low_friction_world_changes_kick_response(backend: Any) -> None:
randomization=_tensor_payload(geom_friction=geom_friction),
)
start = backend.get_base_pos()[:, :2].copy()
delta = np.zeros((backend.num_envs, 1, 3), dtype=np.float32)
delta = torch.zeros((backend.num_envs, 1, 3), dtype=torch.float32)
delta[:, 0, 0] = 1.5
backend.apply_interval_randomization(
IntervalRandomizationPlan(
ops=(
IntervalTermOp(
INTERVAL_TERM_BODY_LINEAR_VELOCITY_DELTA,
delta,
body_ids=np.asarray([backend._base_body_id], dtype=np.int32),
body_ids=torch.as_tensor([backend._base_body_id], dtype=torch.int32),
),
)
)
Expand Down
5 changes: 3 additions & 2 deletions tests/base/test_motrix_backend_options.py
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Original file line number Diff line number Diff line change
Expand Up @@ -5,6 +5,7 @@

import numpy as np
import pytest
import torch
from unisim.dr.types import (
INTERVAL_TERM_BODY_FORCE,
RESET_TERM_BODY_IPOS,
Expand Down Expand Up @@ -517,8 +518,8 @@ def test_motrix_backend_interval_body_force_uses_link_external_force_delta() ->
ops=(
IntervalTermOp(
INTERVAL_TERM_BODY_FORCE,
np.asarray([[[1.0, 2.0, 3.0]], [[4.0, 5.0, 6.0]]], dtype=np.float64),
body_ids=np.asarray([0], dtype=np.int32),
torch.as_tensor([[[1.0, 2.0, 3.0]], [[4.0, 5.0, 6.0]]], dtype=torch.float64),
body_ids=torch.as_tensor([0], dtype=torch.int32),
),
)
)
Expand Down
58 changes: 35 additions & 23 deletions tests/base/test_sim_backend_smoke.py
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Expand Up @@ -176,13 +176,17 @@ def test_mujoco_interval_root_velocity_kick_is_row_selective_and_refreshes_senso
body_ids = bkd.get_body_ids(("base",))
state_before = bkd.get_physics_state().copy()
body_velocity_before = _sensor(bkd, "track_linvel_w_base").copy()
delta = np.zeros((NUM_ENVS, 1, 3), dtype=np.float64)
delta[1, 0] = (0.25, -0.4, 0.15)
delta = torch.zeros((NUM_ENVS, 1, 3), dtype=torch.float64)
delta[1, 0] = torch.tensor([0.25, -0.4, 0.15], dtype=torch.float64)

bkd.apply_interval_randomization(
IntervalRandomizationPlan(
ops=(
IntervalTermOp(INTERVAL_TERM_BODY_LINEAR_VELOCITY_DELTA, delta, body_ids=body_ids),
IntervalTermOp(
INTERVAL_TERM_BODY_LINEAR_VELOCITY_DELTA,
delta,
body_ids=torch.as_tensor(body_ids),
),
)
)
)
Expand All @@ -203,12 +207,12 @@ def test_mujoco_interval_root_velocity_kick_is_row_selective_and_refreshes_senso
)
np.testing.assert_allclose(
state_after[1, idx_qvel : idx_qvel + 3],
state_before[1, idx_qvel : idx_qvel + 3] + delta[1, 0],
state_before[1, idx_qvel : idx_qvel + 3] + delta[1, 0].numpy(),
atol=1e-7,
)
np.testing.assert_allclose(
body_velocity_after[1],
body_velocity_before[1] + delta[1, 0],
body_velocity_before[1] + delta[1, 0].numpy(),
atol=1e-6,
)

Expand All @@ -223,14 +227,16 @@ def test_mujoco_interval_root_velocity_kick_rejects_invalid_contracts():
base_name="base",
)
body_ids = bkd.get_body_ids(("base",))
delta = np.zeros((NUM_ENVS, 1, 3), dtype=np.float64)
delta = torch.zeros((NUM_ENVS, 1, 3), dtype=torch.float64)

with pytest.raises(RuntimeError, match="requires a materialized backend"):
bkd.apply_interval_randomization(
IntervalRandomizationPlan(
ops=(
IntervalTermOp(
INTERVAL_TERM_BODY_LINEAR_VELOCITY_DELTA, delta, body_ids=body_ids
INTERVAL_TERM_BODY_LINEAR_VELOCITY_DELTA,
delta,
body_ids=torch.as_tensor(body_ids),
),
)
)
Expand All @@ -244,7 +250,7 @@ def test_mujoco_interval_root_velocity_kick_rejects_invalid_contracts():
IntervalTermOp(
INTERVAL_TERM_BODY_LINEAR_VELOCITY_DELTA,
delta,
body_ids=body_ids.astype(np.float64),
body_ids=torch.as_tensor(body_ids.astype(np.float64)),
),
)
)
Expand All @@ -256,7 +262,7 @@ def test_mujoco_interval_root_velocity_kick_rejects_invalid_contracts():
IntervalTermOp(
INTERVAL_TERM_BODY_LINEAR_VELOCITY_DELTA,
delta,
body_ids=np.asarray([body_ids[0] + 1], dtype=np.int32),
body_ids=torch.as_tensor([int(body_ids[0]) + 1], dtype=torch.int32),
),
)
)
Expand All @@ -267,8 +273,8 @@ def test_mujoco_interval_root_velocity_kick_rejects_invalid_contracts():
ops=(
IntervalTermOp(
INTERVAL_TERM_BODY_LINEAR_VELOCITY_DELTA,
np.zeros((NUM_ENVS + 1, 1, 3), dtype=np.float64),
body_ids=body_ids,
torch.zeros((NUM_ENVS + 1, 1, 3), dtype=torch.float64),
body_ids=torch.as_tensor(body_ids),
),
)
)
Expand All @@ -279,22 +285,22 @@ def test_mujoco_interval_root_velocity_kick_rejects_invalid_contracts():
ops=(
IntervalTermOp(
INTERVAL_TERM_BODY_LINEAR_VELOCITY_DELTA,
np.zeros((NUM_ENVS, 3), dtype=np.float64),
body_ids=body_ids,
torch.zeros((NUM_ENVS, 3), dtype=torch.float64),
body_ids=torch.as_tensor(body_ids),
),
)
)
)
invalid = delta.copy()
invalid[0, 0, 0] = np.nan
invalid = delta.clone()
invalid[0, 0, 0] = torch.nan
with pytest.raises(ValueError, match="contains NaN or Inf"):
bkd.apply_interval_randomization(
IntervalRandomizationPlan(
ops=(
IntervalTermOp(
INTERVAL_TERM_BODY_LINEAR_VELOCITY_DELTA,
invalid,
body_ids=body_ids,
body_ids=torch.as_tensor(body_ids),
),
)
)
Expand Down Expand Up @@ -322,13 +328,17 @@ def test_mujoco_interval_root_angular_velocity_kick_converts_to_body_frame():
_set_state(bkd, np.arange(NUM_ENVS, dtype=np.int32), qpos, qvel)

body_ids = bkd.get_body_ids(("base",))
delta = np.zeros((NUM_ENVS, 1, 3), dtype=np.float64)
delta[1, 0] = (0.5, 0.0, 0.0) # world-frame +x angular rate
delta = torch.zeros((NUM_ENVS, 1, 3), dtype=torch.float64)
delta[1, 0] = torch.tensor([0.5, 0.0, 0.0], dtype=torch.float64) # world-frame +x angular rate

bkd.apply_interval_randomization(
IntervalRandomizationPlan(
ops=(
IntervalTermOp(INTERVAL_TERM_BODY_ANGULAR_VELOCITY_DELTA, delta, body_ids=body_ids),
IntervalTermOp(
INTERVAL_TERM_BODY_ANGULAR_VELOCITY_DELTA,
delta,
body_ids=torch.as_tensor(body_ids),
),
)
)
)
Expand Down Expand Up @@ -396,17 +406,19 @@ def test_mujoco_interval_body_force_and_torque_have_observable_effect(tmp_path):
idx_qvel = 1 + bkd.nq
baseline = bkd.get_physics_state()[:, idx_qvel : idx_qvel + 6].copy()

force = np.zeros((NUM_ENVS, 1, 3), dtype=np.float64)
force = torch.zeros((NUM_ENVS, 1, 3), dtype=torch.float64)
force[:, 0, 2] = 10.0 # N, world +z
torque = np.zeros((NUM_ENVS, 1, 3), dtype=np.float64)
torque = torch.zeros((NUM_ENVS, 1, 3), dtype=torch.float64)
torque[:, 0, 2] = 1.0 # Nm, world z

_set_state(bkd, ids, qpos, qvel0)
bkd.apply_interval_randomization(
IntervalRandomizationPlan(
ops=(
IntervalTermOp(INTERVAL_TERM_BODY_FORCE, force, body_ids=body_ids),
IntervalTermOp(INTERVAL_TERM_BODY_TORQUE, torque, body_ids=body_ids),
IntervalTermOp(INTERVAL_TERM_BODY_FORCE, force, body_ids=torch.as_tensor(body_ids)),
IntervalTermOp(
INTERVAL_TERM_BODY_TORQUE, torque, body_ids=torch.as_tensor(body_ids)
),
)
)
)
Expand Down
10 changes: 5 additions & 5 deletions uv.lock
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