Update OpenX-Embodiment.py
Browse files- OpenX-Embodiment.py +8 -8
OpenX-Embodiment.py
CHANGED
@@ -1,4 +1,4 @@
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-
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from typing import Optional, List
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from dataclasses import dataclass
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from io import BytesIO
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@@ -31,7 +31,7 @@ def load_webdataset(filepath):
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return wds.WebDataset(filepath).decode().map(decode_image)
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-
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'fractal20220817_data': 78,
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'kuka': 448,
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'bridge': 49,
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@@ -88,25 +88,25 @@ _RTX_DATASETS = {
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'berkeley_gnm_cory_hall': 1,
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'berkeley_gnm_sac_son': 3
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}
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@dataclass
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class
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features: Optional[datasets.Features] = None
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class
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VERSION = datasets.Version("1.0.0")
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BUILDER_CONFIG_CLASS =
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BUILDER_CONFIGS = [
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DEFAULT_CONFIG_NAME = "fractal20220817_data"
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def _info(self):
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return datasets.DatasetInfo(features=self.config.features)
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def _split_generators(self, dl_manager: datasets.DownloadManager):
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files = dl_manager.download(
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if self.info.features is None:
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for d in load_webdataset(files[0]):
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self.info.features = datasets.Dataset.from_list([d]).features
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## huggingface datasets: jxu124/OpenX-Embodiment
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from typing import Optional, List
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from dataclasses import dataclass
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from io import BytesIO
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return wds.WebDataset(filepath).decode().map(decode_image)
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_OPENX_DATASETS = {
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'fractal20220817_data': 78,
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'kuka': 448,
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'bridge': 49,
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'berkeley_gnm_cory_hall': 1,
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'berkeley_gnm_sac_son': 3
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}
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_OPENX_DATASETS_URLS = {k: [f"{k}/{k}_{i:05d}.tar" for i in range(v)] for k, v in _OPENX_DATASETS.items()}
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@dataclass
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class OpenXConfig(datasets.BuilderConfig):
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features: Optional[datasets.Features] = None
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class OpenXDataset(datasets.GeneratorBasedBuilder):
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VERSION = datasets.Version("1.0.0")
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BUILDER_CONFIG_CLASS = OpenXConfig
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BUILDER_CONFIGS = [OpenXConfig(name=dn) for dn in _OPENX_DATASETS.keys()]
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DEFAULT_CONFIG_NAME = "fractal20220817_data"
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def _info(self):
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return datasets.DatasetInfo(features=self.config.features)
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def _split_generators(self, dl_manager: datasets.DownloadManager):
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files = dl_manager.download(_OPENX_DATASETS_URLS[self.info.config_name])
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if self.info.features is None:
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for d in load_webdataset(files[0]):
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self.info.features = datasets.Dataset.from_list([d]).features
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