The python module mmcv.parallel.MMDistributedDataParallel is a method that provides distributed data parallelism for training models in PyTorch. It is specifically designed to scale the training process to multiple GPUs or multiple machines, allowing for faster and more efficient training. MMDistributedDataParallel ensures that each GPU or machine receives the same input data, and then synchronizes the gradients across all the devices during the backward pass. This parallelism technique helps to accelerate the training process by leveraging the computational power of multiple devices simultaneously.
Python MMDistributedDataParallel - 30 examples found. These are the top rated real world Python examples of mmcv.parallel.MMDistributedDataParallel extracted from open source projects. You can rate examples to help us improve the quality of examples.