Add fallback to TensorCPU if there are unsupported types for IDEEP Tensor #9667
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yinghai
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…nsor (pytorch#9667) Summary: Pull Request resolved: pytorch#9667 MKL-DNN doesn't support 64-bit integger (https://github.com/intel/mkl-dnn/blob/cfee61bf81322b1ca315d5ed6cb9a9419618426b/include/mkldnn_types.h#L62-L75). So force converting from `TensorCPU<long>` to `s32` Ideep tensor will cause memory issue. This diff gives an alternative solution, where we just fall through to TensorCPU. The reasoning is that since MKL-DNN doesn't support 64 bit integer tensor, downstream ops have to be in CPUConext. So there is no reason force converting to ideep tensor and back. Differential Revision: D8943544 fbshipit-source-id: 492fa39199d915579a8baf942305f92a231127cd
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Test failures are due to infra error.. |
jramseyer
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Jul 30, 2018
…nsor (pytorch#9667) Summary: Pull Request resolved: pytorch#9667 MKL-DNN doesn't support 64-bit integger (https://github.com/intel/mkl-dnn/blob/cfee61bf81322b1ca315d5ed6cb9a9419618426b/include/mkldnn_types.h#L62-L75). So force converting from `TensorCPU<long>` to `s32` Ideep tensor will cause memory issue. This diff gives an alternative solution, where we just fall through to TensorCPU. The reasoning is that since MKL-DNN doesn't support 64 bit integer tensor, downstream ops have to be in CPUConext. So there is no reason force converting to ideep tensor and back. Reviewed By: pjh5 Differential Revision: D8943544 fbshipit-source-id: f514903cda27e34b8887271c9df56c8220895116
goodlux
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Aug 15, 2018
…nsor (pytorch#9667) Summary: Pull Request resolved: pytorch#9667 MKL-DNN doesn't support 64-bit integger (https://github.com/intel/mkl-dnn/blob/cfee61bf81322b1ca315d5ed6cb9a9419618426b/include/mkldnn_types.h#L62-L75). So force converting from `TensorCPU<long>` to `s32` Ideep tensor will cause memory issue. This diff gives an alternative solution, where we just fall through to TensorCPU. The reasoning is that since MKL-DNN doesn't support 64 bit integer tensor, downstream ops have to be in CPUConext. So there is no reason force converting to ideep tensor and back. Reviewed By: pjh5 Differential Revision: D8943544 fbshipit-source-id: f514903cda27e34b8887271c9df56c8220895116
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Summary: MKL-DNN doesn't support 64-bit integger (https://github.com/intel/mkl-dnn/blob/cfee61bf81322b1ca315d5ed6cb9a9419618426b/include/mkldnn_types.h#L62-L75). So force converting from
TensorCPU<long>tos32Ideep tensor will cause memory issue. This diff gives an alternative solution, where we just fall through to TensorCPU. The reasoning is that since MKL-DNN doesn't support 64 bit integer tensor, downstream ops have to be in CPUConext. So there is no reason force converting to ideep tensor and back.Differential Revision: D8943544