One NotImplementedError of nn.LSTM and two Warnings

[AAxjcy]

When I use nn.LSTM on GPU Intel A730M, I get the following warning and error:

UserWarning: The operator 'aten::_thnn_fused_lstm_cell' is not currently supported on the DML backend and will fall back to run on the CPU. This may have performance implications. (Triggered internally at C:__w\1\s\pytorch-directml-plugin\torch_directml\csrc\dml\dml_cpu_fallback.cpp:17.)

NotImplementedError: Could not run 'aten::_thnn_fused_lstm_cell' with arguments from the 'CPU' 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::_thnn_fused_lstm_cell' is only available for these backends: [PrivateUse1, Meta, BackendSelect, Python, FuncTorchDynamicLayerBackMode, Functionalize, Named, Conjugate, Negative, ZeroTensor, ADInplaceOrView, AutogradOther, AutogradCPU, AutogradCUDA, AutogradHIP, AutogradXLA, AutogradMPS, AutogradIPU, AutogradXPU, AutogradHPU, AutogradVE, AutogradLazy, AutogradMTIA, AutogradPrivateUse1, AutogradPrivateUse2, AutogradPrivateUse3, AutogradMeta, AutogradNestedTensor, Tracer, AutocastCPU, AutocastXPU, AutocastCUDA, FuncTorchBatched, BatchedNestedTensor, FuncTorchVmapMode, Batched, VmapMode, FuncTorchGradWrapper, PythonTLSSnapshot, FuncTorchDynamicLayerFrontMode, PreDispatch, PythonDispatcher].

Then I put LSTM running on my cpu, and then another warning appeared which should not be related to LSTM:

UserWarning: The operator 'aten::lerp.Scalar_out' is not currently supported on the DML backend and will fall back to run on the CPU. This may have performance implications. (Triggered internally at C:__w\1\s\pytorch-directml-plugin\torch_directml\csrc\dml\dml_cpu_fallback.cpp:17.)