tensorflow::Tensor::unaligned_flat()

TTypes<T>::UnalignedConstFlat tensorflow::Tensor::unaligned_flat() const

tf.contrib.graph_editor.matcher.__init__()

tf.contrib.graph_editor.matcher.__init__(positive_filter) Graph match constructor.

tf.contrib.bayesflow.stochastic_tensor.BetaWithSoftplusABTensor.graph

tf.contrib.bayesflow.stochastic_tensor.BetaWithSoftplusABTensor.graph

Ops

Contents Metrics (contrib)Ops for evaluation metrics and summary statistics.API Metric Ops tf.contrib.metrics.streaming_accuracy(predictions, labels, weights=None, metrics_collections=None, updates_collections=None, name=None) tf.contrib.metrics.streaming_mean(values, weights=None, metrics_collections=None, updates_collections=None, name=None) tf.contrib.metrics.streaming_recall(*args, **kwargs) tf.contrib.metrics.streaming_precision(*args, **kwargs) tf.contrib.metrics.streaming_auc(predictio

tensorflow::Tensor::flat()

TTypes<T>::ConstFlat tensorflow::Tensor::flat() const

tf.contrib.learn.DNNRegressor.config

tf.contrib.learn.DNNRegressor.config

tf.OpError.node_def

tf.OpError.node_def The NodeDef proto representing the op that failed.

tf.contrib.distributions.NormalWithSoftplusSigma

class tf.contrib.distributions.NormalWithSoftplusSigma Normal with softplus applied to sigma.

tf.errors.DataLossError.__init__()

tf.errors.DataLossError.__init__(node_def, op, message) Creates a DataLossError.

tf.rsqrt()

tf.rsqrt(x, name=None) Computes reciprocal of square root of x element-wise. I.e., \(y = 1 / \sqrt{x}\). Args: x: A Tensor. Must be one of the following types: half, float32, float64, complex64, complex128. name: A name for the operation (optional). Returns: A Tensor. Has the same type as x.