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@ -11,7 +11,6 @@ import multiprocessing
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import numpy as np
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import numpy as np
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import paddle.v2 as paddle
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import paddle.v2 as paddle
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from threading import local
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from threading import local
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import atexit
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from data_utils.utility import read_manifest
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from data_utils.utility import read_manifest
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from data_utils.utility import xmap_readers_mp
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from data_utils.utility import xmap_readers_mp
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from data_utils.augmentor.augmentation import AugmentationPipeline
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from data_utils.augmentor.augmentation import AugmentationPipeline
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@ -194,8 +193,9 @@ class DataGenerator(object):
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raise ValueError("Unknown shuffle method %s." %
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raise ValueError("Unknown shuffle method %s." %
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shuffle_method)
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shuffle_method)
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# prepare batches
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# prepare batches
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instance_reader = self._instance_reader_creator(manifest)
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instance_reader, cleanup = self._instance_reader_creator(manifest)
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batch = []
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batch = []
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try:
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for instance in instance_reader():
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for instance in instance_reader():
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batch.append(instance)
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batch.append(instance)
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if len(batch) == batch_size:
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if len(batch) == batch_size:
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@ -203,6 +203,8 @@ class DataGenerator(object):
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batch = []
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batch = []
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if len(batch) >= min_batch_size:
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if len(batch) >= min_batch_size:
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yield self._padding_batch(batch, padding_to, flatten)
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yield self._padding_batch(batch, padding_to, flatten)
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finally:
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cleanup()
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self._epoch += 1
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self._epoch += 1
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return batch_reader
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return batch_reader
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@ -280,10 +282,7 @@ class DataGenerator(object):
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lambda instance: self.process_utterance(instance["audio_filepath"], instance["text"]),
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lambda instance: self.process_utterance(instance["audio_filepath"], instance["text"]),
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reader, self._num_threads, 4096)
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reader, self._num_threads, 4096)
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# register callback to main process
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return reader, cleanup_callback
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atexit.register(cleanup_callback)
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return reader
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def _padding_batch(self, batch, padding_to=-1, flatten=False):
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def _padding_batch(self, batch, padding_to=-1, flatten=False):
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"""
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"""
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