MCPcopy Index your code
hub / github.com/pytorch/pytorch / _AddGradientOperators

Function _AddGradientOperators

caffe2/python/data_parallel_model.py:867–880  ·  view source on GitHub ↗
(devices, model, losses_by_gpu)

Source from the content-addressed store, hash-verified

865
866
867def _AddGradientOperators(devices, model, losses_by_gpu):
868 def create_grad(lossp):
869 return model.ConstantFill(lossp, str(lossp) + "_grad", value=1.0)
870
871 loss_grad = {}
872 # Explicitly need to create gradients on each GPU
873 for gpu_id in devices:
874 device = core.DeviceOption(model._device_type, gpu_id)
875 with core.DeviceScope(device):
876 for l in losses_by_gpu[gpu_id]:
877 lg = create_grad(l)
878 loss_grad[str(l)] = str(lg)
879
880 model.AddGradientOperators(loss_grad)
881
882
883def ExtractPredictorNet(model, inputs, outputs, device):

Callers 2

ParallelizeFunction · 0.85
Parallelize_BMUFFunction · 0.85

Calls 2

create_gradFunction · 0.85
AddGradientOperatorsMethod · 0.45

Tested by

no test coverage detected

Used in the wild real call sites across dependent graphs

searching dependent graphs…