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Fixes for datasets 2.18 -> 2.19 update (#88)

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Simon Alibert 2024-04-20 15:06:11 +02:00 committed by GitHub
parent 2a59825a00
commit c0cc53cb54
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7 changed files with 31 additions and 34 deletions
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31
.github/poetry/cpu/poetry.lock generated vendored
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@ -1,4 +1,4 @@
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# This file is automatically @generated by Poetry 1.8.2 and should not be changed by hand.
[[package]]
name = "absl-py"
@ -522,21 +522,21 @@ toml = ["tomli"]
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name = "datasets"
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version = "2.19.0"
description = "HuggingFace community-driven open-source library of datasets"
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@ -3919,4 +3914,4 @@ xarm = ["gym-xarm"]
[metadata]
lock-version = "2.0"
python-versions = "^3.10"
content-hash = "bd9c506d2499d5e1e3b5e8b1a0f65df45c8feef38d89d0daeade56847fdb6a2e"
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2
.github/poetry/cpu/pyproject.toml vendored
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@ -53,7 +53,7 @@ pre-commit = {version = "^3.7.0", optional = true}
debugpy = {version = "^1.8.1", optional = true}
pytest = {version = "^8.1.0", optional = true}
pytest-cov = {version = "^5.0.0", optional = true}
datasets = "^2.18.0"
datasets = "^2.19.0"
[tool.poetry.extras]

2
lerobot/common/datasets/utils.py
View File

@ -58,7 +58,7 @@ def hf_transform_to_torch(items_dict):
def load_hf_dataset(dataset_id, version, root, split) -> datasets.Dataset:
"""hf_dataset contains all the observations, states, actions, rewards, etc."""
if root is not None:
hf_dataset = load_from_disk(Path(root) / dataset_id / split)
hf_dataset = load_from_disk(str(Path(root) / dataset_id / split))
else:
# TODO(rcadene): remove dataset_id everywhere and use repo_id instead
repo_id = f"lerobot/{dataset_id}"

25
poetry.lock generated
View File

@ -1,4 +1,4 @@
# This file is automatically @generated by Poetry 1.8.1 and should not be changed by hand.
# This file is automatically @generated by Poetry 1.8.2 and should not be changed by hand.
[[package]]
name = "absl-py"
@ -522,21 +522,21 @@ toml = ["tomli"]
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name = "datasets"
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description = "HuggingFace community-driven open-source library of datasets"
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tensorflow = ["tensorflow (>=2.2.0,!=2.6.0,!=2.6.1)", "tensorflow-macos"]
tensorflow-gpu = ["tensorflow-gpu (>=2.2.0,!=2.6.0,!=2.6.1)"]
tests = ["Pillow (>=6.2.1)", "absl-py", "apache-beam (>=2.26.0)", "elasticsearch (<8.0.0)", "faiss-cpu (>=1.6.4)", "jax (>=0.3.14)", "jaxlib (>=0.3.14)", "joblib (<1.3.0)", "joblibspark", "librosa", "lz4", "py7zr", "pyspark (>=3.4)", "pytest", "pytest-datadir", "pytest-xdist", "rarfile (>=4.0)", "s3fs (>=2021.11.1)", "soundfile (>=0.12.1)", "sqlalchemy", "tensorflow (>=2.3,!=2.6.0,!=2.6.1)", "tensorflow-macos", "tiktoken", "torch (>=2.0.0)", "transformers", "typing-extensions (>=4.6.1)", "zstandard"]
tensorflow = ["tensorflow (>=2.6.0)"]
tensorflow-gpu = ["tensorflow (>=2.6.0)"]
tests = ["Pillow (>=6.2.1)", "absl-py", "apache-beam (>=2.26.0)", "elasticsearch (<8.0.0)", "faiss-cpu (>=1.6.4)", "jax (>=0.3.14)", "jaxlib (>=0.3.14)", "joblib (<1.3.0)", "joblibspark", "librosa", "lz4", "polars[timezone] (>=0.20.0)", "protobuf (<4.0.0)", "py7zr", "pyspark (>=3.4)", "pytest", "pytest-datadir", "pytest-xdist", "rarfile (>=4.0)", "s3fs (>=2021.11.1)", "soundfile (>=0.12.1)", "sqlalchemy", "tensorflow (>=2.6.0)", "tiktoken", "torch (>=2.0.0)", "transformers", "typing-extensions (>=4.6.1)", "zstandard"]
torch = ["torch"]
vision = ["Pillow (>=6.2.1)"]
@ -2909,7 +2909,6 @@ files = [
{file = "PyYAML-6.0.1-cp311-cp311-win_amd64.whl", hash = "sha256:bf07ee2fef7014951eeb99f56f39c9bb4af143d8aa3c21b1677805985307da34"},
{file = "PyYAML-6.0.1-cp312-cp312-macosx_10_9_x86_64.whl", hash = "sha256:855fb52b0dc35af121542a76b9a84f8d1cd886ea97c84703eaa6d88e37a2ad28"},
{file = "PyYAML-6.0.1-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:40df9b996c2b73138957fe23a16a4f0ba614f4c0efce1e9406a184b6d07fa3a9"},
{file = "PyYAML-6.0.1-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:a08c6f0fe150303c1c6b71ebcd7213c2858041a7e01975da3a99aed1e7a378ef"},
{file = "PyYAML-6.0.1-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:6c22bec3fbe2524cde73d7ada88f6566758a8f7227bfbf93a408a9d86bcc12a0"},
{file = "PyYAML-6.0.1-cp312-cp312-musllinux_1_1_x86_64.whl", hash = "sha256:8d4e9c88387b0f5c7d5f281e55304de64cf7f9c0021a3525bd3b1c542da3b0e4"},
{file = "PyYAML-6.0.1-cp312-cp312-win32.whl", hash = "sha256:d483d2cdf104e7c9fa60c544d92981f12ad66a457afae824d146093b8c294c54"},
@ -4195,4 +4194,4 @@ xarm = ["gym-xarm"]
[metadata]
lock-version = "2.0"
python-versions = "^3.10"
content-hash = "01ad4eb04061ec9f785d4574bf66d3e5cb4549e2ea11ab175895f94cb62c1f1c"
content-hash = "7f5afa48aead953f598e686e767891d3d23f2862b80144f76dc064101ef80b4a"

3
pyproject.toml
View File

@ -53,7 +53,8 @@ pre-commit = {version = "^3.7.0", optional = true}
debugpy = {version = "^1.8.1", optional = true}
pytest = {version = "^8.1.0", optional = true}
pytest-cov = {version = "^5.0.0", optional = true}
datasets = "^2.18.0"
datasets = "^2.19.0"
[tool.poetry.extras]
pusht = ["gym-pusht"]

1
tests/test_datasets.py
View File

@ -92,6 +92,7 @@ def test_compute_stats_on_xarm():
We compare with taking a straight min, mean, max, std of all the data in one pass (which we can do
because we are working with a small dataset).
"""
# TODO(rcadene): Reduce size of dataset sample on which stats compute is tested
from lerobot.common.datasets.xarm import XarmDataset
data_dir = Path(os.environ["DATA_DIR"]) if "DATA_DIR" in os.environ else None

1
tests/test_examples.py
View File

@ -1,3 +1,4 @@
# TODO(aliberts): Mute logging for these tests
import subprocess
from pathlib import Path