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.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.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.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.PriorityQueue
  • References/Big Data/TensorFlow/TensorFlow Python/Inputs and Readers

class tf.PriorityQueue A queue implementation that dequeues elements in prioritized order. See

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

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

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

tf.QueueBase.dtypes The list of dtypes for each component of a queue element.

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

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

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

tf.decode_csv(records, record_defaults, field_delim=None, name=None) Convert CSV records to tensors. Each column maps to one tensor

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