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https://github.com/huggingface/lerobot.git
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fix(vlabench): align gripper action range
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@@ -43,8 +43,8 @@ from .utils import _LazyAsyncVectorEnv
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logger = logging.getLogger(__name__)
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logger = logging.getLogger(__name__)
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ACTION_DIM = 7 # pos(3) + euler(3) + gripper(1)
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ACTION_DIM = 7 # pos(3) + euler(3) + gripper(1)
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ACTION_LOW = -1.0
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ACTION_LOW = np.array([-1.0, -1.0, -1.0, -1.0, -1.0, -1.0, 0.0], dtype=np.float32)
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ACTION_HIGH = 1.0
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ACTION_HIGH = np.array([1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0], dtype=np.float32)
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# Default max episode steps per task type
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# Default max episode steps per task type
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DEFAULT_MAX_EPISODE_STEPS = 500
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DEFAULT_MAX_EPISODE_STEPS = 500
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@@ -177,9 +177,7 @@ class VLABenchEnv(gym.Env):
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else:
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else:
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raise ValueError(f"Unsupported obs_type: {self.obs_type}")
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raise ValueError(f"Unsupported obs_type: {self.obs_type}")
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self.action_space = spaces.Box(
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self.action_space = spaces.Box(low=ACTION_LOW, high=ACTION_HIGH, dtype=np.float32)
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low=ACTION_LOW, high=ACTION_HIGH, shape=(ACTION_DIM,), dtype=np.float32
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)
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# Max attempts to rebuild the underlying env when MuJoCo throws
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# Max attempts to rebuild the underlying env when MuJoCo throws
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# `PhysicsError` (e.g. mjWARN_BADQACC) during VLABench's 20-step
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# `PhysicsError` (e.g. mjWARN_BADQACC) during VLABench's 20-step
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@@ -346,6 +344,19 @@ class VLABenchEnv(gym.Env):
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dtype=np.float64,
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dtype=np.float64,
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)
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)
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@staticmethod
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def _normalize_gripper_action(gripper: float) -> float:
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"""Normalize the scalar gripper command to VLABench's [0, 1] convention.
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The native VLABench collector uses 0=open and 1=closed. Older LeRobot
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integrations often assumed a symmetric [-1, 1] gripper channel, so we
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preserve backward compatibility by remapping negative values from
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[-1, 1] -> [0, 1] before clipping.
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"""
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if gripper < 0.0:
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gripper = 0.5 * (float(np.clip(gripper, -1.0, 1.0)) + 1.0)
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return float(np.clip(gripper, 0.0, 1.0))
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def _build_ctrl_from_action(self, action: np.ndarray, ctrl_dim: int) -> np.ndarray:
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def _build_ctrl_from_action(self, action: np.ndarray, ctrl_dim: int) -> np.ndarray:
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"""Convert a 7D EEF action into the `ctrl_dim`-sized joint command vector.
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"""Convert a 7D EEF action into the `ctrl_dim`-sized joint command vector.
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@@ -367,7 +378,7 @@ class VLABenchEnv(gym.Env):
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pos = np.asarray(action[:3], dtype=np.float64)
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pos = np.asarray(action[:3], dtype=np.float64)
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rx, ry, rz = float(action[3]), float(action[4]), float(action[5])
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rx, ry, rz = float(action[3]), float(action[4]), float(action[5])
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gripper = float(action[6])
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gripper = self._normalize_gripper_action(float(action[6]))
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quat = self._euler_xyz_to_quat_wxyz(rx, ry, rz)
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quat = self._euler_xyz_to_quat_wxyz(rx, ry, rz)
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assert self._env is not None
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assert self._env is not None
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@@ -390,7 +401,7 @@ class VLABenchEnv(gym.Env):
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# Gripper: action scalar in [0, 1] (0=open, 1=closed). Map linearly to
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# Gripper: action scalar in [0, 1] (0=open, 1=closed). Map linearly to
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# finger qpos in [CLOSED, OPEN]. Franka has 2 mirrored fingers.
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# finger qpos in [CLOSED, OPEN]. Franka has 2 mirrored fingers.
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g = float(np.clip(gripper, 0.0, 1.0))
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g = gripper
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finger_qpos = self._FRANKA_FINGER_OPEN + g * (self._FRANKA_FINGER_CLOSED - self._FRANKA_FINGER_OPEN)
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finger_qpos = self._FRANKA_FINGER_OPEN + g * (self._FRANKA_FINGER_CLOSED - self._FRANKA_FINGER_OPEN)
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ctrl = np.zeros(ctrl_dim, dtype=np.float64)
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ctrl = np.zeros(ctrl_dim, dtype=np.float64)
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@@ -0,0 +1,40 @@
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#!/usr/bin/env python
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# Copyright 2025 The HuggingFace Inc. team. All rights reserved.
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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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import numpy as np
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from lerobot.envs.vlabench import ACTION_HIGH, ACTION_LOW, VLABenchEnv
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def test_vlabench_action_space_uses_zero_to_one_gripper_channel():
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env = VLABenchEnv()
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np.testing.assert_array_equal(env.action_space.low, ACTION_LOW)
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np.testing.assert_array_equal(env.action_space.high, ACTION_HIGH)
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assert env.action_space.shape == (7,)
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assert env.action_space.low[-1] == 0.0
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assert env.action_space.high[-1] == 1.0
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np.testing.assert_array_equal(env.action_space.low[:6], np.full(6, -1.0, dtype=np.float32))
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np.testing.assert_array_equal(env.action_space.high[:6], np.full(6, 1.0, dtype=np.float32))
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def test_vlabench_gripper_action_normalization_keeps_backward_compatibility():
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assert VLABenchEnv._normalize_gripper_action(-1.0) == 0.0
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assert VLABenchEnv._normalize_gripper_action(-0.5) == 0.25
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assert VLABenchEnv._normalize_gripper_action(0.0) == 0.0
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assert VLABenchEnv._normalize_gripper_action(0.5) == 0.5
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assert VLABenchEnv._normalize_gripper_action(1.0) == 1.0
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assert VLABenchEnv._normalize_gripper_action(1.5) == 1.0
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