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

tf.FixedLenFeature.__repr__() Return a nicely formatted representation string

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

tf.WholeFileReader.num_records_produced(name=None) Returns the number of records this reader has produced. This

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

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

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

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

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

tf.TFRecordReader.num_records_produced(name=None) Returns the number of records this reader has produced. This

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

tf.ReaderBase.__init__(reader_ref, supports_serialize=False) Creates a new ReaderBase. Args:

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

tf.read_file(filename, name=None) Reads and outputs the entire contents of the input filename. Args:

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

tf.placeholder_with_default(input, shape, name=None) A placeholder op that passes though input when its output is

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

tf.FixedLengthRecordReader.reader_ref Op that implements the reader.

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

tf.train.batch(tensors, batch_size, num_threads=1, capacity=32, enqueue_many=False, shapes=None, dynamic_pad=False, allow_smaller_final_batch=False, shared_name=None

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