tf.QueueBase
  • References/Big Data/TensorFlow/TensorFlow Python/Inputs and Readers

class tf.QueueBase Base class for queue implementations. A queue is a TensorFlow data structure

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tf.FixedLengthRecordReader
  • References/Big Data/TensorFlow/TensorFlow Python/Inputs and Readers

class tf.FixedLengthRecordReader A Reader that outputs fixed-length records from a file. See ReaderBase

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tf.PaddingFIFOQueue
  • References/Big Data/TensorFlow/TensorFlow Python/Inputs and Readers

class tf.PaddingFIFOQueue A FIFOQueue that supports batching variable-sized tensors by padding. A

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tf.FixedLengthRecordReader.supports_serialize
  • References/Big Data/TensorFlow/TensorFlow Python/Inputs and Readers

tf.FixedLengthRecordReader.supports_serialize Whether the Reader implementation can serialize its state.

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tf.parse_single_example()
  • References/Big Data/TensorFlow/TensorFlow Python/Inputs and Readers

tf.parse_single_example(serialized, features, name=None, example_names=None) Parses a single Example proto.

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tf.TFRecordReader.serialize_state()
  • References/Big Data/TensorFlow/TensorFlow Python/Inputs and Readers

tf.TFRecordReader.serialize_state(name=None) Produce a string tensor that encodes the state of a reader. Not

2025-01-10 15:47:30
tf.TFRecordReader
  • References/Big Data/TensorFlow/TensorFlow Python/Inputs and Readers

class tf.TFRecordReader A Reader that outputs the records from a TFRecords file. See ReaderBase

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tf.VarLenFeature.
  • References/Big Data/TensorFlow/TensorFlow Python/Inputs and Readers

tf.VarLenFeature.__new__(_cls, dtype) Create new instance of VarLenFeature(dtype,)

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tf.ReaderBase.read()
  • References/Big Data/TensorFlow/TensorFlow Python/Inputs and Readers

tf.ReaderBase.read(queue, name=None) Returns the next record (key, value pair) produced by a reader. Will

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tf.FixedLengthRecordReader.serialize_state()
  • References/Big Data/TensorFlow/TensorFlow Python/Inputs and Readers

tf.FixedLengthRecordReader.serialize_state(name=None) Produce a string tensor that encodes the state of a reader.

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