Note

You are reading the documentation for MMClassification 0.x, which will soon be deprecated at the end of 2022. We recommend you upgrade to MMClassification 1.0 to enjoy fruitful new features and better performance brought by OpenMMLab 2.0. Check the installation tutorial, migration tutorial and changelog for more details.

mmcls.apis.multi_gpu_test¶

mmcls.apis.multi_gpu_test(model, data_loader, tmpdir=None, gpu_collect=False)[source]¶

Test model with multiple gpus.

This method tests model with multiple gpus and collects the results under two different modes: gpu and cpu modes. By setting ‘gpu_collect=True’ it encodes results to gpu tensors and use gpu communication for results collection. On cpu mode it saves the results on different gpus to ‘tmpdir’ and collects them by the rank 0 worker.

Parameters

model (nn.Module) – Model to be tested.
data_loader (nn.Dataloader) – Pytorch data loader.
tmpdir (str) – Path of directory to save the temporary results from different gpus under cpu mode.
gpu_collect (bool) – Option to use either gpu or cpu to collect results.

Returns

The prediction results.

Return type

list