hangX/lerobot
1
0
Fork 0
forked from tangger/lerobot
Code Pull Requests Activity

Added normalization schemes and style checks

Browse Source
This commit is contained in:
Michel Aractingi
2024-12-29 12:51:21 +00:00
parent 08ec971086
commit dc54d357ca
10 changed files with 150 additions and 156 deletions
Download Patch File Download Diff File Expand all files Collapse all files

8
lerobot/scripts/eval_on_robot.py
View File

@@ -24,7 +24,7 @@ python lerobot/scripts/eval_on_robot.py \
```
**NOTE** (michel-aractingi): This script is incomplete and it is being prepared
for running training on the real robot.
for running training on the real robot.
"""
import argparse
@@ -47,7 +47,7 @@ from lerobot.common.utils.utils import (
def rollout(robot: Robot, policy: Policy, fps: int, control_time_s: float = 20, use_amp: bool = True) -> dict:
"""Run a batched policy rollout on the real robot.
"""Run a batched policy rollout on the real robot.
The return dictionary contains:
"robot": A a dictionary of (batch, sequence + 1, *) tensors mapped to observation
@@ -64,7 +64,7 @@ def rollout(robot: Robot, policy: Policy, fps: int, control_time_s: float = 20,
extraneous elements from the sequences above.
Args:
robot: The robot class that defines the interface with the real robot.
robot: The robot class that defines the interface with the real robot.
policy: The policy. Must be a PyTorch nn module.
Returns:
@@ -77,7 +77,7 @@ def rollout(robot: Robot, policy: Policy, fps: int, control_time_s: float = 20,
listener, events = init_keyboard_listener()
# Reset the policy. TODO (michel-aractingi) add real policy evaluation once the code is ready.
# policy.reset()
# policy.reset()
# Get observation from real robot
observation = robot.capture_observation()