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

tf.TextLineReader.reader_ref Op that implements the reader.

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

tf.WholeFileReader.num_work_units_completed(name=None) Returns the number of work units this reader has finished processing.

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

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

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

tf.FixedLenFeature.__getnewargs__() Return self as a plain tuple. Used by copy and pickle.

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

class tf.VarLenFeature Configuration for parsing a variable-length input feature. Fields: dtype:

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

tf.TextLineReader.restore_state(state, name=None) Restore a reader to a previously saved state. Not

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

tf.parse_example(serialized, features, name=None, example_names=None) Parses Example protos into a dict

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

tf.VarLenFeature.__getstate__() Exclude the OrderedDict from pickling

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

tf.IdentityReader.num_work_units_completed(name=None) Returns the number of work units this reader has finished processing.

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