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"""Modifies TFDS dataset with a map function, updates the feature definition and stores new dataset.""" |
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from functools import partial |
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from absl import app, flags |
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import tensorflow as tf |
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import tensorflow_datasets as tfds |
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from rlds_dataset_mod.mod_functions import TFDS_MOD_FUNCTIONS |
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from rlds_dataset_mod.multithreaded_adhoc_tfds_builder import ( |
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MultiThreadedAdhocDatasetBuilder, |
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) |
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FLAGS = flags.FLAGS |
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flags.DEFINE_string("dataset", None, "Dataset name.") |
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flags.DEFINE_string("data_dir", None, "Directory where source data is stored.") |
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flags.DEFINE_string("target_dir", None, "Directory where modified data is stored.") |
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flags.DEFINE_list("mods", None, "List of modification functions, applied in order.") |
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flags.DEFINE_integer("n_workers", 10, "Number of parallel workers for data conversion.") |
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flags.DEFINE_integer( |
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"max_episodes_in_memory", |
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100, |
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"Number of episodes converted & stored in memory before writing to disk.", |
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) |
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def mod_features(features): |
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"""Modifies feature dict.""" |
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for mod in FLAGS.mods: |
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features = TFDS_MOD_FUNCTIONS[mod].mod_features(features) |
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return features |
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def mod_dataset_generator(builder, split, mods): |
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"""Modifies dataset features.""" |
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ds = builder.as_dataset(split=split) |
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for mod in mods: |
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ds = TFDS_MOD_FUNCTIONS[mod].mod_dataset(ds) |
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for episode in tfds.core.dataset_utils.as_numpy(ds): |
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yield episode |
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def main(_): |
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builder = tfds.builder(FLAGS.dataset, data_dir=FLAGS.data_dir) |
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features = mod_features(builder.info.features) |
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print("############# Target features: ###############") |
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print(features) |
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print("##############################################") |
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assert FLAGS.data_dir != FLAGS.target_dir |
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mod_dataset_builder = MultiThreadedAdhocDatasetBuilder( |
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name=FLAGS.dataset, |
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version=builder.version, |
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features=features, |
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split_datasets={split: builder.info.splits[split] for split in builder.info.splits}, |
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config=builder.builder_config, |
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data_dir=FLAGS.target_dir, |
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description=builder.info.description, |
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generator_fcn=partial(mod_dataset_generator, builder=builder, mods=FLAGS.mods), |
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n_workers=FLAGS.n_workers, |
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max_episodes_in_memory=FLAGS.max_episodes_in_memory, |
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) |
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mod_dataset_builder.download_and_prepare() |
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if __name__ == "__main__": |
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app.run(main) |
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