tf.parse_tensor()

tf.parse_tensor(serialized, out_type, name=None) Transforms a serialized tensorflow.TensorProto proto into a Tensor.

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tf.TextLineReader.serialize_state()

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

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tf.QueueBase.dequeue()

tf.QueueBase.dequeue(name=None) Dequeues one element from this queue. If the queue is empty when

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tf.QueueBase.size()

tf.QueueBase.size(name=None) Compute the number of elements in this queue. Args:

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tf.train.limit_epochs()

tf.train.limit_epochs(tensor, num_epochs=None, name=None) Returns tensor num_epochs times and then raises an

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tf.WholeFileReader.read_up_to()

tf.WholeFileReader.read_up_to(queue, num_records, name=None) Returns up to num_records (key, value pairs) produced by a reader

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tf.IdentityReader.serialize_state()

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

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tf.FixedLenSequenceFeature.allow_missing

tf.FixedLenSequenceFeature.allow_missing Alias for field number 2

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tf.train.input_producer()

tf.train.input_producer(input_tensor, element_shape=None, num_epochs=None, shuffle=True, seed=None, capacity=32, shared_name=None, summary_name=None, name=None)

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tf.IdentityReader.num_records_produced()

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

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