RuntimeError: Could not run 'aten::_softmax_backward_data' with arguments from the 'DML' backend.

[LucaRo29]

Even though aten::_softmax_backward_data is apparently supported, I am getting this runtime error with the code below.

`def train(model, train_dataloader, loss_function, optimizer):

model.train()

running_loss= 0
for X, y in train_dataloader:
    optimiser.zero_grad()

    X= X.to(DEVICE, dtype=torch.float)
    y= y.to(DEVICE, dtype=torch.long)

    y_pred= model(X)
    loss = loss_function(y_pred, y)
    loss.backward()

    optimizer.step()
    running_loss += loss.item()

print(f"Loss: {running_loss/ len(train_dataloader)}")

`

`RuntimeError: Could not run 'aten::_softmax_backward_data' with arguments from the 'DML' backend. This could be because the operator doesn't exist for this backend, or was omitted during the selective/custom build process (if using custom build). If you are a Facebook employee using PyTorch on mobile, please visit https://fburl.com/ptmfixes for possible resolutions. 'aten::_softmax_backward_data' is only available for these backends: [CPU, BackendSelect, Named, AutogradOther, AutogradCPU, AutogradCUDA, AutogradXLA, AutogradNestedTensor, UNKNOWN_TENSOR_TYPE_ID, AutogradPrivateUse1, AutogradPrivateUse2, AutogradPrivateUse3, Tracer, Autocast, Batched, VmapMode].

CPU: registered at D:\a_work\1\s\pytorch-directml\build\aten\src\ATen\RegisterCPU.cpp:5926 [kernel] BackendSelect: fallthrough registered at D:\a_work\1\s\pytorch-directml\aten\src\ATen\core\BackendSelectFallbackKernel.cpp:3 [backend fallback] Named: registered at D:\a_work\1\s\pytorch-directml\aten\src\ATen\core\NamedRegistrations.cpp:7 [backend fallback] AutogradOther: registered at D:\a_work\1\s\pytorch-directml\torch\csrc\autograd\generated\VariableType_1.cpp:9683 [autograd kernel] AutogradCPU: registered at D:\a_work\1\s\pytorch-directml\torch\csrc\autograd\generated\VariableType_1.cpp:9683 [autograd kernel] AutogradCUDA: registered at D:\a_work\1\s\pytorch-directml\torch\csrc\autograd\generated\VariableType_1.cpp:9683 [autograd kernel] AutogradXLA: registered at D:\a_work\1\s\pytorch-directml\torch\csrc\autograd\generated\VariableType_1.cpp:9683 [autograd kernel] AutogradNestedTensor: registered at D:\a_work\1\s\pytorch-directml\torch\csrc\autograd\generated\VariableType_1.cpp:9683 [autograd kernel] UNKNOWN_TENSOR_TYPE_ID: registered at D:\a_work\1\s\pytorch-directml\torch\csrc\autograd\generated\VariableType_1.cpp:9683 [autograd kernel] AutogradPrivateUse1: registered at D:\a_work\1\s\pytorch-directml\torch\csrc\autograd\generated\VariableType_1.cpp:9683 [autograd kernel] AutogradPrivateUse2: registered at D:\a_work\1\s\pytorch-directml\torch\csrc\autograd\generated\VariableType_1.cpp:9683 [autograd kernel] AutogradPrivateUse3: registered at D:\a_work\1\s\pytorch-directml\torch\csrc\autograd\generated\VariableType_1.cpp:9683 [autograd kernel] Tracer: registered at D:\a_work\1\s\pytorch-directml\torch\csrc\autograd\generated\TraceType_1.cpp:11324 [kernel] Autocast: fallthrough registered at D:\a_work\1\s\pytorch-directml\aten\src\ATen\autocast_mode.cpp:250 [backend fallback] Batched: registered at D:\a_work\1\s\pytorch-directml\aten\src\ATen\BatchingRegistrations.cpp:1016 [backend fallback] VmapMode: fallthrough registered at D:\a_work\1\s\pytorch-directml\aten\src\ATen\VmapModeRegistrations.cpp:33 [backend fallback]`

[Adele101]

Hi @LucaRo29, thanks for reaching out. We are currently working on support for aten::_softmax_backward_data which will be available in our next release coming very soon.

[zhangxiang1993]

aten::_softmax_backward_data has been implemented in the latest torch-directml, please try out