neural_compressor.data.dataloaders.tensorflow_dataloader
¶
TensorFlow Dataloader implementation.
Module Contents¶
Classes¶
Tensorflow dataloader class. |
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Subclass of DefaultDataLoader. |
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Subclass of DefaultDataLoader. |
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DataLoader for framework Tensorflow. |
- class neural_compressor.data.dataloaders.tensorflow_dataloader.TFDataDataLoader(dataset, batch_size=1, last_batch='rollover')¶
Bases:
neural_compressor.data.dataloaders.base_dataloader.BaseDataLoader
Tensorflow dataloader class.
In tensorflow1.x dataloader is coupled with the graph, but it also support feed_dict method to do session run, this dataloader is designed to satisfy the usage of feed dict in tf1.x. Although it’s a general dataloader and can be used in MXNet and PyTorch.
- Parameters:
dataset – obj. wrapper of needed data.
batch_size – int. batch size
- batch(batch_size, last_batch='rollover')¶
Dataset return data per batch.
- class neural_compressor.data.dataloaders.tensorflow_dataloader.TensorflowBertDataLoader(dataset, batch_size=1, last_batch='rollover', collate_fn=None, sampler=None, batch_sampler=None, num_workers=0, pin_memory=False, shuffle=False, distributed=False)¶
Bases:
neural_compressor.data.dataloaders.default_dataloader.DefaultDataLoader
Subclass of DefaultDataLoader.
this dataloader is designed to satisfy the usage of Bert models.
- class neural_compressor.data.dataloaders.tensorflow_dataloader.TensorflowModelZooBertDataLoader(dataset, batch_size=1, last_batch='rollover', collate_fn=None, sampler=None, batch_sampler=None, num_workers=0, pin_memory=False, shuffle=False, distributed=False)¶
Bases:
neural_compressor.data.dataloaders.default_dataloader.DefaultDataLoader
Subclass of DefaultDataLoader.
this dataloader is designed to satisfy the usage of Model Zoo Bert models.
- class neural_compressor.data.dataloaders.tensorflow_dataloader.TensorflowDataLoader(dataset, batch_size=1, last_batch='rollover', collate_fn=None, sampler=None, batch_sampler=None, num_workers=0, pin_memory=False, shuffle=False, distributed=False)¶
Bases:
neural_compressor.data.dataloaders.base_dataloader.BaseDataLoader
DataLoader for framework Tensorflow.
if it’s a tf.data.Dataset we will directly use the dataloader in the other case will use DefaultDataLoader instead.