Module: tf.nn

Wrappers for primitive Neural Net (NN) Operations.

Classes

class RNNCellDeviceWrapper: Operator that ensures an RNNCell runs on a particular device.

class RNNCellDropoutWrapper: Operator adding dropout to inputs and outputs of the given cell.

class RNNCellResidualWrapper: RNNCell wrapper that ensures cell inputs are added to the outputs.

Functions

all_candidate_sampler(...): Generate the set of all classes.

atrous_conv2d(...): Atrous convolution (a.k.a. convolution with holes or dilated convolution).

atrous_conv2d_transpose(...): The transpose of atrous_conv2d.

avg_pool(...): Performs the avg pooling on the input.

avg_pool1d(...): Performs the average pooling on the input.

avg_pool2d(...): Performs the average pooling on the input.

avg_pool3d(...): Performs the average pooling on the input.

batch_norm_with_global_normalization(...): Batch normalization.

batch_normalization(...): Batch normalization.

bias_add(...): Adds bias to value.

collapse_repeated(...): Merge repeated labels into single labels.

compute_accidental_hits(...): Compute the position ids in sampled_candidates matching true_classes.

compute_average_loss(...): Scales per-example losses with sample_weights and computes their average.

conv1d(...)<