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Merge remote-tracking branch 'origin/main' into user/alexander-soare/multistep_policy_and_serial_env

This commit is contained in:
Alexander Soare 2024-03-15 13:05:35 +00:00
parent a222c88c99 9c88071bc7
commit a45896dc8d
10 changed files with 144 additions and 54 deletions
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4
.github/poetry/cpu/poetry.lock generated vendored
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@ -1,4 +1,4 @@
# This file is automatically @generated by Poetry 1.8.2 and should not be changed by hand. # This file is automatically @generated by Poetry 1.8.1 and should not be changed by hand.
[[package]] [[package]]
name = "absl-py" name = "absl-py"
@ -3123,4 +3123,4 @@ testing = ["big-O", "jaraco.functools", "jaraco.itertools", "more-itertools", "p
[metadata] [metadata]
lock-version = "2.0" lock-version = "2.0"
python-versions = "^3.10" python-versions = "^3.10"
content-hash = "66c60543d2f59ac3d0e1fcda298ea14c0c60a8c6bcea73902f4f6aa3dd47661b" content-hash = "4aa6a1e3f29560dd4a1c24d493ee1154089da4aa8d2190ad1f786c125ab2b735"

1
.github/poetry/cpu/pyproject.toml vendored
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@ -51,6 +51,7 @@ torchvision = {version = "^0.17.1", source = "torch-cpu"}
h5py = "^3.10.0" h5py = "^3.10.0"
dm = "^1.3" dm = "^1.3"
dm-control = "^1.0.16" dm-control = "^1.0.16"
huggingface-hub = "^0.21.4"
[tool.poetry.group.dev.dependencies] [tool.poetry.group.dev.dependencies]

19
README.md
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@ -146,6 +146,25 @@ Run tests
DATA_DIR="tests/data" pytest -sx tests DATA_DIR="tests/data" pytest -sx tests
``` ```
**Datasets**
To add a pytorch rl dataset to the hub, first login and use a token generated from [huggingface settings](https://huggingface.co/settings/tokens) with write access:
```
huggingface-cli login --token $HUGGINGFACE_TOKEN --add-to-git-credential
```
Then you can upload it to the hub with:
```
HF_HUB_ENABLE_HF_TRANSFER=1 huggingface-cli upload --repo-type dataset $HF_USER/$DATASET data/$DATASET
```
For instance, for [cadene/pusht](https://huggingface.co/datasets/cadene/pusht), we used:
```
HF_USER=cadene
DATASET=pusht
```
## Acknowledgment ## Acknowledgment
- Our Diffusion policy and Pusht environment are adapted from [Diffusion Policy](https://diffusion-policy.cs.columbia.edu/) - Our Diffusion policy and Pusht environment are adapted from [Diffusion Policy](https://diffusion-policy.cs.columbia.edu/)
- Our TDMPC policy and Simxarm environment are adapted from [FOWM](https://www.yunhaifeng.com/FOWM/) - Our TDMPC policy and Simxarm environment are adapted from [FOWM](https://www.yunhaifeng.com/FOWM/)

29
lerobot/common/datasets/abstract.py
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@ -1,4 +1,3 @@
import abc
import logging import logging
from pathlib import Path from pathlib import Path
from typing import Callable from typing import Callable
@ -7,8 +6,8 @@ import einops
import torch import torch
import torchrl import torchrl
import tqdm import tqdm
from huggingface_hub import snapshot_download
from tensordict import TensorDict from tensordict import TensorDict
from torchrl.data.datasets.utils import _get_root_dir
from torchrl.data.replay_buffers.replay_buffers import TensorDictReplayBuffer from torchrl.data.replay_buffers.replay_buffers import TensorDictReplayBuffer
from torchrl.data.replay_buffers.samplers import SliceSampler from torchrl.data.replay_buffers.samplers import SliceSampler
from torchrl.data.replay_buffers.storages import TensorStorage, _collate_id from torchrl.data.replay_buffers.storages import TensorStorage, _collate_id
@ -23,7 +22,7 @@ class AbstractExperienceReplay(TensorDictReplayBuffer):
batch_size: int = None, batch_size: int = None,
*, *,
shuffle: bool = True, shuffle: bool = True,
root: Path = None, root: Path | None = None,
pin_memory: bool = False, pin_memory: bool = False,
prefetch: int = None, prefetch: int = None,
sampler: SliceSampler = None, sampler: SliceSampler = None,
@ -33,11 +32,8 @@ class AbstractExperienceReplay(TensorDictReplayBuffer):
): ):
self.dataset_id = dataset_id self.dataset_id = dataset_id
self.shuffle = shuffle self.shuffle = shuffle
self.root = _get_root_dir(self.dataset_id) if root is None else root self.root = root
self.root = Path(self.root) storage = self._download_or_load_dataset()
self.data_dir = self.root / self.dataset_id
storage = self._download_or_load_storage()
super().__init__( super().__init__(
storage=storage, storage=storage,
@ -98,19 +94,12 @@ class AbstractExperienceReplay(TensorDictReplayBuffer):
torch.save(stats, stats_path) torch.save(stats, stats_path)
return stats return stats
@abc.abstractmethod def _download_or_load_dataset(self) -> torch.StorageBase:
def _download_and_preproc(self) -> torch.StorageBase: if self.root is None:
raise NotImplementedError() self.data_dir = snapshot_download(repo_id=f"cadene/{self.dataset_id}", repo_type="dataset")
def _download_or_load_storage(self):
if not self._is_downloaded():
storage = self._download_and_preproc()
else: else:
storage = TensorStorage(TensorDict.load_memmap(self.data_dir)) self.data_dir = self.root / self.dataset_id
return storage return TensorStorage(TensorDict.load_memmap(self.data_dir))
def _is_downloaded(self) -> bool:
return self.data_dir.is_dir()
def _compute_stats(self, num_batch=100, batch_size=32): def _compute_stats(self, num_batch=100, batch_size=32):
rb = TensorDictReplayBuffer( rb = TensorDictReplayBuffer(

9
lerobot/common/datasets/aloha.py
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@ -87,7 +87,7 @@ class AlohaExperienceReplay(AbstractExperienceReplay):
batch_size: int = None, batch_size: int = None,
*, *,
shuffle: bool = True, shuffle: bool = True,
root: Path = None, root: Path | None = None,
pin_memory: bool = False, pin_memory: bool = False,
prefetch: int = None, prefetch: int = None,
sampler: SliceSampler = None, sampler: SliceSampler = None,
@ -124,8 +124,9 @@ class AlohaExperienceReplay(AbstractExperienceReplay):
def image_keys(self) -> list: def image_keys(self) -> list:
return [("observation", "image", cam) for cam in CAMERAS[self.dataset_id]] return [("observation", "image", cam) for cam in CAMERAS[self.dataset_id]]
def _download_and_preproc(self): def _download_and_preproc_obsolete(self):
raw_dir = self.data_dir.parent / f"{self.data_dir.name}_raw" assert self.root is not None
raw_dir = self.root / f"{self.dataset_id}_raw"
if not raw_dir.is_dir(): if not raw_dir.is_dir():
download(raw_dir, self.dataset_id) download(raw_dir, self.dataset_id)
@ -174,7 +175,7 @@ class AlohaExperienceReplay(AbstractExperienceReplay):
if ep_id == 0: if ep_id == 0:
# hack to initialize tensordict data structure to store episodes # hack to initialize tensordict data structure to store episodes
td_data = ep_td[0].expand(total_num_frames).memmap_like(self.data_dir) td_data = ep_td[0].expand(total_num_frames).memmap_like(self.root / f"{self.dataset_id}")
td_data[idxtd : idxtd + len(ep_td)] = ep_td td_data[idxtd : idxtd + len(ep_td)] = ep_td
idxtd = idxtd + len(ep_td) idxtd = idxtd + len(ep_td)

7
lerobot/common/datasets/factory.py
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@ -7,7 +7,10 @@ from torchrl.data.replay_buffers import PrioritizedSliceSampler, SliceSampler
from lerobot.common.envs.transforms import NormalizeTransform, Prod from lerobot.common.envs.transforms import NormalizeTransform, Prod
DATA_DIR = Path(os.environ.get("DATA_DIR", "data")) # DATA_DIR specifies to location where datasets are loaded. By default, DATA_DIR is None and
# we load from `$HOME/.cache/huggingface/hub/datasets`. For our unit tests, we set `DATA_DIR=tests/data`
# to load a subset of our datasets for faster continuous integration.
DATA_DIR = Path(os.environ["DATA_DIR"]) if "DATA_DIR" in os.environ else None
def make_offline_buffer( def make_offline_buffer(
@ -77,9 +80,9 @@ def make_offline_buffer(
offline_buffer = clsfunc( offline_buffer = clsfunc(
dataset_id=dataset_id, dataset_id=dataset_id,
root=DATA_DIR,
sampler=sampler, sampler=sampler,
batch_size=batch_size, batch_size=batch_size,
root=DATA_DIR,
pin_memory=pin_memory, pin_memory=pin_memory,
prefetch=prefetch if isinstance(prefetch, int) else None, prefetch=prefetch if isinstance(prefetch, int) else None,
) )

9
lerobot/common/datasets/pusht.py
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@ -90,7 +90,7 @@ class PushtExperienceReplay(AbstractExperienceReplay):
batch_size: int = None, batch_size: int = None,
*, *,
shuffle: bool = True, shuffle: bool = True,
root: Path = None, root: Path | None = None,
pin_memory: bool = False, pin_memory: bool = False,
prefetch: int = None, prefetch: int = None,
sampler: SliceSampler = None, sampler: SliceSampler = None,
@ -111,8 +111,9 @@ class PushtExperienceReplay(AbstractExperienceReplay):
transform=transform, transform=transform,
) )
def _download_and_preproc(self): def _download_and_preproc_obsolete(self):
raw_dir = self.data_dir.parent / f"{self.data_dir.name}_raw" assert self.root is not None
raw_dir = self.root / f"{self.dataset_id}_raw"
zarr_path = (raw_dir / PUSHT_ZARR).resolve() zarr_path = (raw_dir / PUSHT_ZARR).resolve()
if not zarr_path.is_dir(): if not zarr_path.is_dir():
raw_dir.mkdir(parents=True, exist_ok=True) raw_dir.mkdir(parents=True, exist_ok=True)
@ -208,7 +209,7 @@ class PushtExperienceReplay(AbstractExperienceReplay):
if episode_id == 0: if episode_id == 0:
# hack to initialize tensordict data structure to store episodes # hack to initialize tensordict data structure to store episodes
td_data = ep_td[0].expand(total_frames).memmap_like(self.data_dir) td_data = ep_td[0].expand(total_frames).memmap_like(self.root / f"{self.dataset_id}")
td_data[idxtd : idxtd + len(ep_td)] = ep_td td_data[idxtd : idxtd + len(ep_td)] = ep_td

9
lerobot/common/datasets/simxarm.py
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@ -43,7 +43,7 @@ class SimxarmExperienceReplay(AbstractExperienceReplay):
batch_size: int = None, batch_size: int = None,
*, *,
shuffle: bool = True, shuffle: bool = True,
root: Path = None, root: Path | None = None,
pin_memory: bool = False, pin_memory: bool = False,
prefetch: int = None, prefetch: int = None,
sampler: SliceSampler = None, sampler: SliceSampler = None,
@ -64,11 +64,12 @@ class SimxarmExperienceReplay(AbstractExperienceReplay):
transform=transform, transform=transform,
) )
def _download_and_preproc(self): def _download_and_preproc_obsolete(self):
assert self.root is not None
# TODO(rcadene): finish download # TODO(rcadene): finish download
download() download()
dataset_path = self.data_dir / "buffer.pkl" dataset_path = self.root / f"{self.dataset_id}_raw" / "buffer.pkl"
print(f"Using offline dataset '{dataset_path}'") print(f"Using offline dataset '{dataset_path}'")
with open(dataset_path, "rb") as f: with open(dataset_path, "rb") as f:
dataset_dict = pickle.load(f) dataset_dict = pickle.load(f)
@ -110,7 +111,7 @@ class SimxarmExperienceReplay(AbstractExperienceReplay):
if episode_id == 0: if episode_id == 0:
# hack to initialize tensordict data structure to store episodes # hack to initialize tensordict data structure to store episodes
td_data = episode[0].expand(total_frames).memmap_like(self.data_dir) td_data = episode[0].expand(total_frames).memmap_like(self.root / f"{self.dataset_id}")
td_data[idx0:idx1] = episode td_data[idx0:idx1] = episode

110
poetry.lock generated
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@ -914,6 +914,78 @@ files = [
[package.dependencies] [package.dependencies]
numpy = ">=1.17.3" numpy = ">=1.17.3"
[[package]]
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]
[[package]] [[package]]
name = "huggingface-hub" name = "huggingface-hub"
version = "0.21.4" version = "0.21.4"
@ -928,6 +1000,7 @@ files = [
[package.dependencies] [package.dependencies]
filelock = "*" filelock = "*"
fsspec = ">=2023.5.0" fsspec = ">=2023.5.0"
hf-transfer = {version = ">=0.1.4", optional = true, markers = "extra == \"hf_transfer\""}
packaging = ">=20.9" packaging = ">=20.9"
pyyaml = ">=5.1" pyyaml = ">=5.1"
requests = "*" requests = "*"
@ -1270,13 +1343,13 @@ source = ["Cython (>=3.0.7)"]
[[package]] [[package]]
name = "markdown" name = "markdown"
version = "3.5.2" version = "3.6"
description = "Python implementation of John Gruber's Markdown." description = "Python implementation of John Gruber's Markdown."
optional = false optional = false
python-versions = ">=3.8" python-versions = ">=3.8"
files = [ files = [
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] ]
[package.extras] [package.extras]
@ -2726,13 +2799,13 @@ test = ["asv", "gmpy2", "hypothesis", "mpmath", "pooch", "pytest", "pytest-cov",
[[package]] [[package]]
name = "sentry-sdk" name = "sentry-sdk"
version = "1.41.0" version = "1.42.0"
description = "Python client for Sentry (https://sentry.io)" description = "Python client for Sentry (https://sentry.io)"
optional = false optional = false
python-versions = "*" python-versions = "*"
files = [ files = [
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] ]
[package.dependencies] [package.dependencies]
@ -2756,6 +2829,7 @@ grpcio = ["grpcio (>=1.21.1)"]
httpx = ["httpx (>=0.16.0)"] httpx = ["httpx (>=0.16.0)"]
huey = ["huey (>=2)"] huey = ["huey (>=2)"]
loguru = ["loguru (>=0.5)"] loguru = ["loguru (>=0.5)"]
openai = ["openai (>=1.0.0)", "tiktoken (>=0.3.0)"]
opentelemetry = ["opentelemetry-distro (>=0.35b0)"] opentelemetry = ["opentelemetry-distro (>=0.35b0)"]
opentelemetry-experimental = ["opentelemetry-distro (>=0.40b0,<1.0)", "opentelemetry-instrumentation-aiohttp-client (>=0.40b0,<1.0)", "opentelemetry-instrumentation-django (>=0.40b0,<1.0)", "opentelemetry-instrumentation-fastapi (>=0.40b0,<1.0)", "opentelemetry-instrumentation-flask (>=0.40b0,<1.0)", "opentelemetry-instrumentation-requests (>=0.40b0,<1.0)", "opentelemetry-instrumentation-sqlite3 (>=0.40b0,<1.0)", "opentelemetry-instrumentation-urllib (>=0.40b0,<1.0)"] opentelemetry-experimental = ["opentelemetry-distro (>=0.40b0,<1.0)", "opentelemetry-instrumentation-aiohttp-client (>=0.40b0,<1.0)", "opentelemetry-instrumentation-django (>=0.40b0,<1.0)", "opentelemetry-instrumentation-fastapi (>=0.40b0,<1.0)", "opentelemetry-instrumentation-flask (>=0.40b0,<1.0)", "opentelemetry-instrumentation-requests (>=0.40b0,<1.0)", "opentelemetry-instrumentation-sqlite3 (>=0.40b0,<1.0)", "opentelemetry-instrumentation-urllib (>=0.40b0,<1.0)"]
pure-eval = ["asttokens", "executing", "pure-eval"] pure-eval = ["asttokens", "executing", "pure-eval"]
@ -2871,18 +2945,18 @@ test = ["pytest"]
[[package]] [[package]]
name = "setuptools" name = "setuptools"
version = "69.1.1" version = "69.2.0"
description = "Easily download, build, install, upgrade, and uninstall Python packages" description = "Easily download, build, install, upgrade, and uninstall Python packages"
optional = false optional = false
python-versions = ">=3.8" python-versions = ">=3.8"
files = [ files = [
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[package.extras] [package.extras]
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testing = ["build[virtualenv]", "filelock (>=3.4.0)", "flake8-2020", "ini2toml[lite] (>=0.9)", "jaraco.develop (>=7.21)", "jaraco.envs (>=2.2)", "jaraco.path (>=3.2.0)", "packaging (>=23.2)", "pip (>=19.1)", "pytest (>=6)", "pytest-checkdocs (>=2.4)", "pytest-cov", "pytest-enabler (>=2.2)", "pytest-home (>=0.5)", "pytest-mypy (>=0.9.1)", "pytest-perf", "pytest-ruff (>=0.2.1)", "pytest-timeout", "pytest-xdist", "tomli-w (>=1.0.0)", "virtualenv (>=13.0.0)", "wheel"] testing = ["build[virtualenv]", "filelock (>=3.4.0)", "importlib-metadata", "ini2toml[lite] (>=0.9)", "jaraco.develop (>=7.21)", "jaraco.envs (>=2.2)", "jaraco.path (>=3.2.0)", "mypy (==1.9)", "packaging (>=23.2)", "pip (>=19.1)", "pytest (>=6)", "pytest-checkdocs (>=2.4)", "pytest-cov", "pytest-enabler (>=2.2)", "pytest-home (>=0.5)", "pytest-mypy (>=0.9.1)", "pytest-perf", "pytest-ruff (>=0.2.1)", "pytest-timeout", "pytest-xdist (>=3)", "tomli", "tomli-w (>=1.0.0)", "virtualenv (>=13.0.0)", "wheel"]
testing-integration = ["build[virtualenv] (>=1.0.3)", "filelock (>=3.4.0)", "jaraco.envs (>=2.2)", "jaraco.path (>=3.2.0)", "packaging (>=23.2)", "pytest", "pytest-enabler", "pytest-xdist", "tomli", "virtualenv (>=13.0.0)", "wheel"] testing-integration = ["build[virtualenv] (>=1.0.3)", "filelock (>=3.4.0)", "jaraco.envs (>=2.2)", "jaraco.path (>=3.2.0)", "packaging (>=23.2)", "pytest", "pytest-enabler", "pytest-xdist", "tomli", "virtualenv (>=13.0.0)", "wheel"]
[[package]] [[package]]
@ -3040,7 +3114,7 @@ protobuf = ">=3.20"
[[package]] [[package]]
name = "tensordict" name = "tensordict"
version = "0.4.0+551331d" version = "0.4.0+f1c833e"
description = "" description = ""
optional = false optional = false
python-versions = "*" python-versions = "*"
@ -3061,7 +3135,7 @@ tests = ["pytest", "pytest-benchmark", "pytest-instafail", "pytest-rerunfailures
type = "git" type = "git"
url = "https://github.com/pytorch/tensordict" url = "https://github.com/pytorch/tensordict"
reference = "HEAD" reference = "HEAD"
resolved_reference = "ed22554d6860731610df784b2f5d09f31d3dbc7a" resolved_reference = "f1c833ecf495aa61f3f76bf09f94dd708db496ec"
[[package]] [[package]]
name = "termcolor" name = "termcolor"
@ -3437,20 +3511,20 @@ jupyter = ["ipytree (>=0.2.2)", "ipywidgets (>=8.0.0)", "notebook"]
[[package]] [[package]]
name = "zipp" name = "zipp"
version = "3.17.0" version = "3.18.1"
description = "Backport of pathlib-compatible object wrapper for zip files" description = "Backport of pathlib-compatible object wrapper for zip files"
optional = false optional = false
python-versions = ">=3.8" python-versions = ">=3.8"
files = [ files = [
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testing = ["big-O", "jaraco.functools", "jaraco.itertools", "more-itertools", "pytest (>=6)", "pytest-black (>=0.3.7)", "pytest-checkdocs (>=2.4)", "pytest-cov", "pytest-enabler (>=2.2)", "pytest-ignore-flaky", "pytest-mypy (>=0.9.1)", "pytest-ruff"] testing = ["big-O", "jaraco.functools", "jaraco.itertools", "more-itertools", "pytest (>=6)", "pytest-checkdocs (>=2.4)", "pytest-cov", "pytest-enabler (>=2.2)", "pytest-ignore-flaky", "pytest-mypy", "pytest-ruff (>=0.2.1)"]
[metadata] [metadata]
lock-version = "2.0" lock-version = "2.0"
python-versions = "^3.10" python-versions = "^3.10"
content-hash = "d7c551c44380ac26e784390f077d902287c40582127db91f9a85ab5d7707ad59" content-hash = "3bf6532037cfea563819989806d5cd171e33ceb077b0d6afddf54710cbbb3c74"

1
pyproject.toml
View File

@ -52,6 +52,7 @@ h5py = "^3.10.0"
robomimic = "0.2.0" robomimic = "0.2.0"
timm = "^0.9.16" timm = "^0.9.16"
dm-control = "1.0.14" dm-control = "1.0.14"
huggingface-hub = {extras = ["hf-transfer"], version = "^0.21.4"}
[tool.poetry.group.dev.dependencies] [tool.poetry.group.dev.dependencies]