Seqio_mixture_dataset = datasets.load_dataset("seqio_loader",temperature=0.
DATA GENERATOR TENSORFLOW GENERATOR
Where the seqio_mixture_dataset is the generator that i wanted to be wrapped in HF dataset.Īlso additionally, could you please tell me how do i set the default_rate=0.7 args where seqio_mixture is defined to be made as a custom option in the HF load_dataset() method, some classes to work with Keras (included in TensorFlow) that generates batches of frames from video files. Seqio_mixture_dataset = seqio.get_mixture_or_task("seqio_mixture").get_dataset(įor _, ex in zip(range(15), seqio_mixture_dataset): Keras sequence generators for video data. Seqio_train_list.append(seqio_train_dataset) Shard_info=seqio.ShardInfo(index=0, num_shards=10), Seqio_train_dataset = seqio.get_mixture_or_task(dataset_name).get_dataset( _DESCRIPTION = "a custom seqio based mixed samples on a given temperature value, that again returns a dataset in HF dataset format well samples on the Mixture temperature"Ĭlass CustomSeqio(datasets.GeneratorBasedBuilder):ĭataset_fn=functools.partial(dataset_fn, dataset_path=lang), """Assign the value from the dataset to target_key in key_map""" Output_signature=tf.TensorSpec(shape=(), dtype=tf.string, target_to_key(x, key_map, target_key):
The following is my code for the same: import datasetsįrom seqio import FunctionDataSource, utilsĭata_path = glob.glob("/home/stephen/Desktop/MEGA_CORPUS/COMBINED_CORPUS/*", recursive=False)ĭef gen_dataset(split, shuffle=False, seed=None, column="text", dataset_path=None):ĭef dataset_fn(split, shuffle_files, seed=None, dataset_path=None):įunctools.partial(gen_dataset, split, shuffle_files, seed, dataset_path=dataset_path), i was skipping the def _split_generators(self, dl_manager): function. , hey i did as you instructed, but sadly i cannot get pass through the download_manager, as i dont have anything to download. I have my data stored in a pandas DataFrame with the features being file paths.
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