athena.data.datasets.language_set

audio dataset

Module Contents

Classes

LanguageDatasetBuilder

LanguageDatasetBuilder

class athena.data.datasets.language_set.LanguageDatasetBuilder(config=None)

Bases: athena.data.datasets.base.BaseDatasetBuilder

LanguageDatasetBuilder

default_config

num_class

@property

Returns:the max_index of the vocabulary Return type:int

input_vocab_size

@property

Returns:the input vocab size Return type:int

sample_type

@property

Returns:sample_type of the dataset:

{
    "input": tf.int32,
    "input_length": tf.int32,
    "output": tf.int32,
    "output_length": tf.int32,
}

Return type:dict

sample_shape

@property

Returns:sample_shape of the dataset:

{
    "input": tf.TensorShape([None]),
    "input_length": tf.TensorShape([]),
    "output": tf.TensorShape([None]),
    "output_length": tf.TensorShape([]),
}

Return type:dict

sample_signature

@property

Returns:sample_signature of the dataset:

{
    "input": tf.TensorSpec(shape=(None, None), dtype=tf.int32),
    "input_length": tf.TensorSpec(shape=([None]), dtype=tf.int32),
    "output": tf.TensorSpec(shape=(None, None), dtype=tf.int32),
    "output_length": tf.TensorSpec(shape=([None]), dtype=tf.int32),
}

Return type:dict

load_csv(self, file_path)

load csv file

__getitem__(self, index)

get a sample

Parameters:index (int) – index of the entries Returns:sample:

{
    "input": input_labels,
    "input_length": input_length,
    "output": output_labels,
    "output_length": output_length,
}

Return type:dict

__len__(self)

return the number of data samples