tensorflow::Tensor::NumElements()

int64 tensorflow::Tensor::NumElements() const Convenience accessor for the tensor shape.

tf.contrib.learn.DNNRegressor.dnn_bias_

tf.contrib.learn.DNNRegressor.dnn_bias_ Returns bias of deep neural network part.

tf.contrib.bayesflow.stochastic_tensor.MixtureTensor.loss()

tf.contrib.bayesflow.stochastic_tensor.MixtureTensor.loss(final_loss, name='Loss')

tf.contrib.learn.monitors.StepCounter.set_estimator()

tf.contrib.learn.monitors.StepCounter.set_estimator(estimator)

tf.contrib.learn.monitors.GraphDump.end()

tf.contrib.learn.monitors.GraphDump.end(session=None) Callback at the end of training/evaluation. Args: session: A tf.Session object that can be used to run ops. Raises: ValueError: if we've not begun a run.

tf.contrib.bayesflow.stochastic_tensor.PoissonTensor.mean()

tf.contrib.bayesflow.stochastic_tensor.PoissonTensor.mean(name='mean')

tensorflow::Tensor::vec()

TTypes<T>::ConstVec tensorflow::Tensor::vec() const Const versions of all the methods above.

tf.contrib.bayesflow.stochastic_tensor.ExponentialWithSoftplusLamTensor.__init__()

tf.contrib.bayesflow.stochastic_tensor.ExponentialWithSoftplusLamTensor.__init__(name=None, dist_value_type=None, loss_fn=score_function, **dist_args)

tf.contrib.bayesflow.stochastic_tensor.Chi2Tensor.entropy()

tf.contrib.bayesflow.stochastic_tensor.Chi2Tensor.entropy(name='entropy')

tf.FixedLengthRecordReader.restore_state()

tf.FixedLengthRecordReader.restore_state(state, name=None) Restore a reader to a previously saved state. Not all Readers support being restored, so this can produce an Unimplemented error. Args: state: A string Tensor. Result of a SerializeState of a Reader with matching type. name: A name for the operation (optional). Returns: The created Operation.