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update aloha

This commit is contained in:
Remi Cadene 2024-05-19 19:43:21 +00:00
parent 155b3fdcf2
commit a5098d7bf3
2 changed files with 17 additions and 10 deletions
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4
tests/data/save_policy_to_safetensors/aloha_act/actions.safetensors
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@ -1,3 +1,3 @@
version https://git-lfs.github.com/spec/v1 version https://git-lfs.github.com/spec/v1
oid sha256:631e31d6166fa0b38a1b270855a7802a0d748b07a9c3cf21448c5c1ea4f5fa9d oid sha256:523f220f3acbab0cd4aef8a13c77916634488b1af08a06e4e65d1aecafdc2cae
size 51248 size 5104

23
tests/scripts/save_policy_to_safetensor.py
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@ -19,7 +19,6 @@ from pathlib import Path
import torch import torch
from safetensors.torch import save_file from safetensors.torch import save_file
from lerobot import available_policies_per_env
from lerobot.common.datasets.factory import make_dataset from lerobot.common.datasets.factory import make_dataset
from lerobot.common.policies.factory import make_policy from lerobot.common.policies.factory import make_policy
from lerobot.common.utils.utils import init_hydra_config, set_global_seed from lerobot.common.utils.utils import init_hydra_config, set_global_seed
@ -27,14 +26,14 @@ from lerobot.scripts.train import make_optimizer_and_scheduler
from tests.utils import DEFAULT_CONFIG_PATH from tests.utils import DEFAULT_CONFIG_PATH
def get_policy_stats(env_name, policy_name): def get_policy_stats(env_name, policy_name, extra_overrides):
cfg = init_hydra_config( cfg = init_hydra_config(
DEFAULT_CONFIG_PATH, DEFAULT_CONFIG_PATH,
overrides=[ overrides=[
f"env={env_name}", f"env={env_name}",
f"policy={policy_name}", f"policy={policy_name}",
"device=cpu", "device=cpu",
], ] + extra_overrides,
) )
set_global_seed(1337) set_global_seed(1337)
dataset = make_dataset(cfg) dataset = make_dataset(cfg)
@ -88,14 +87,14 @@ def get_policy_stats(env_name, policy_name):
return output_dict, grad_stats, param_stats, actions return output_dict, grad_stats, param_stats, actions
def save_policy_to_safetensors(output_dir, env_name, policy_name): def save_policy_to_safetensors(output_dir, env_name, policy_name, extra_overrides):
env_policy_dir = Path(output_dir) / f"{env_name}_{policy_name}" env_policy_dir = Path(output_dir) / f"{env_name}_{policy_name}"
if env_policy_dir.exists(): if env_policy_dir.exists():
shutil.rmtree(env_policy_dir) shutil.rmtree(env_policy_dir)
env_policy_dir.mkdir(parents=True, exist_ok=True) env_policy_dir.mkdir(parents=True, exist_ok=True)
output_dict, grad_stats, param_stats, actions = get_policy_stats(env_name, policy_name) output_dict, grad_stats, param_stats, actions = get_policy_stats(env_name, policy_name, extra_overrides)
save_file(output_dict, env_policy_dir / "output_dict.safetensors") save_file(output_dict, env_policy_dir / "output_dict.safetensors")
save_file(grad_stats, env_policy_dir / "grad_stats.safetensors") save_file(grad_stats, env_policy_dir / "grad_stats.safetensors")
save_file(param_stats, env_policy_dir / "param_stats.safetensors") save_file(param_stats, env_policy_dir / "param_stats.safetensors")
@ -103,6 +102,14 @@ def save_policy_to_safetensors(output_dir, env_name, policy_name):
if __name__ == "__main__": if __name__ == "__main__":
for env, policies in available_policies_per_env.items(): env_policies = [
for policy in policies: ("xarm", "tdmpc", []),
save_policy_to_safetensors("tests/data/save_policy_to_safetensors", env, policy) (
"pusht",
"diffusion",
["policy.n_action_steps=8", "policy.num_inference_steps=10", "policy.down_dims=[128, 256, 512]"],
),
("aloha", "act", ["policy.n_action_steps=10"]),
]
for env, policy, extra_overrides in env_policies:
save_policy_to_safetensors("tests/data/save_policy_to_safetensors", env, policy, extra_overrides)