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(...): Computes a 1-D convolution given 3-D input and filter tensors.

conv1d_transpose(...): The transpose of conv1d.

conv2d(...): Computes a 2-D convolution given input and 4-D filters tensors.

conv2d_transpose(...): The transpose of conv2d.

conv3d(...): Computes a 3-D convolution given 5-D input and filters tensors.

conv3d_transpose(...): The transpose of conv3d.

conv_transpose(...): The transpose of convolution.

convolution(...): Computes sums of N-D convolutions (actually cross-correlation).

crelu(...): Computes Concatenated ReLU.

ctc_beam_search_decoder(...): Performs beam search decoding on the logits given in input.

ctc_greedy_decoder(...): Performs greedy decoding on the logits given in input (best path).

ctc_loss(...): Computes CTC (Connectionist Temporal Classification) loss.

ctc_unique_labels(...): Get unique labels and indices for batched labels for tf.nn.ctc_loss.

depth_to_space(...): DepthToSpace for tensors of type T.

depthwise_conv2d(...): Depthwise 2-D convolution.

depthwise_conv2d_backprop_filter(...): Computes the gradients of depthwise convolution with respect to the filter.

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