tf.nn.rnn_cell.BasicRNNCell.output_size
  • References/Big Data/TensorFlow/TensorFlow Python/Neural Network RNN Cells

tf.nn.rnn_cell.BasicRNNCell.output_size

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

tf.IdentityReader.reader_ref Op that implements the reader.

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tf.contrib.distributions.TransformedDistribution.pmf()
  • References/Big Data/TensorFlow/TensorFlow Python/Statistical distributions

tf.contrib.distributions.TransformedDistribution.pmf(value, name='pmf') Probability mass function. Args:

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

tf.TFRecordReader.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.nn.rnn_cell.LSTMCell
  • References/Big Data/TensorFlow/TensorFlow Python/Neural Network RNN Cells

class tf.nn.rnn_cell.LSTMCell Long short-term memory unit (LSTM) recurrent network cell. The default

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tf.nn.rnn_cell.LSTMCell.
  • References/Big Data/TensorFlow/TensorFlow Python/Neural Network RNN Cells

tf.nn.rnn_cell.LSTMCell.__call__(inputs, state, scope=None) Run one step of LSTM. Args:

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tf.contrib.distributions.Exponential.event_shape()
  • References/Big Data/TensorFlow/TensorFlow Python/Statistical distributions

tf.contrib.distributions.Exponential.event_shape(name='event_shape') Shape of a single sample from a single batch as a 1-D int32

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

tf.VarLenFeature.dtype Alias for field number 0

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tf.contrib.learn.monitors.CaptureVariable.end()
  • References/Big Data/TensorFlow/TensorFlow Python/Monitors

tf.contrib.learn.monitors.CaptureVariable.end(session=None)

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tf.contrib.distributions.InverseGamma.param_static_shapes()
  • References/Big Data/TensorFlow/TensorFlow Python/Statistical distributions

tf.contrib.distributions.InverseGamma.param_static_shapes(cls, sample_shape) param_shapes with static (i.e. TensorShape) shapes

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