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

tf.matching_files(pattern, name=None) Returns the set of files matching a pattern. Note that this

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

tf.TFRecordReader.reader_ref Op that implements the reader.

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

tf.RandomShuffleQueue.__init__(capacity, min_after_dequeue, dtypes, shapes=None, names=None, seed=None, shared_name=None, name='random_shuffle_queue')

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

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

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

tf.QueueBase.from_list(index, queues) Create a queue using the queue reference from queues[index].

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

tf.FixedLenFeature.default_value Alias for field number 2

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

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

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

tf.train.match_filenames_once(pattern, name=None) Save the list of files matching pattern, so it is only computed once.

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

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

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

tf.FixedLenFeature.dtype Alias for field number 1

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