r"""Applies Batch Normalization over a 4d input that is seen as a mini-batch of 3d inputs .. math:: y = \frac{x - mean[x]}{ \sqrt{Va

Data Parallel with a replication callback. An replication callback `__data_parallel_replicate__` of each module will be invoked after being

A thread-safe future implementation. Used only as one-to-one pipe.

Compute L2 contrastive loss

Pipe for master-slave communication.

An abstract `SyncMaster` object. - During the replication, as the data parallel will trigger an callback of each module, all slave devices should

Computes and stores the average and current value

A re-implementation of batch normalization, used for testing the numerical stability. Author: acgtyrant See also: https://github

Same architecture as the image discriminator

Defines a PatchGAN discriminator

Trainer creates the model and optimizers, and uses them to updates the weights of the network while reporting losses and the latest visua

Trainer creates the model and optimizers, and uses them to updates the weights of the network while reporting losses and the latest visua

r"""Applies Synchronized Batch Normalization over a 2d or 3d input that is seen as a mini-batch. .. math:: y = \frac{x - mean[x]}{ \

r"""Applies Batch Normalization over a 5d input that is seen as a mini-batch of 4d inputs .. math:: y = \frac{x - mean[x]}{ \sqrt{Va