[WIP] MIOPEN Conv Ops Refactoring #17777
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petrex
commented
Mar 7, 2019
petrex
commented
- Enable miopen DepthWise conv ops
- Drop dilation constraint on miopen group conv
* upstream/master: (24 commits) Automatic update of fbcode/onnx to 96c58ceeacf0f2b73d752e413e4fd78787a12da3 (pytorch#17676) Set the default ONNX opset to the latest stable opset (i.e., 9) (pytorch#17736) Add module attributes (pytorch#17309) - refactoring serialization of ONNX initializers to be name-based (pytorch#17420) ONNX Export for Max and Average Pooling in CEIL_MODE use flake8-mypy (pytorch#17721) use fp16<->fp32 intrinsic (pytorch#17496) Implement a Caffe2 standalone LSTM operator (pytorch#17726) caffe2:libtorch_cuda depends on caffe2:caffe2_gpu (pytorch#17729) add tensor and cost inference functions (pytorch#17684) ONNX Export Narrow op Keep the dim_type of hinted shape as BATCH if possible (pytorch#17734) fix different round behavior on CPU and GPU pytorch#16498 (pytorch#17443) Warn about memory overlaps on expanded tensors (pytorch#17576) fix exp fam. formula refactor caffe2 operator constructors - 10/9 (pytorch#17659) Improve ONNX symbolic for logsoftmax and softmax (pytorch#17672) Enable using CMD when building cpp extensions on Windows Do not rename net boundary inputs/outputs during ssaRewrite. (pytorch#17545) Reapply D14078519 (pytorch#17596) ...
bddppq
reviewed
Mar 8, 2019
| @@ -49,17 +49,15 @@ class MIOPENConvOpBase : public ConvPoolOpBase<HIPContext> { | |||
| MIOPEN_ENFORCE(miopenCreateTensorDescriptor(&top_desc_for_bias_)); | |||
| MIOPEN_ENFORCE(miopenCreateConvolutionDescriptor(&conv_desc_)); | |||
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| if (group_ > 1) { | |||
| if ((operator_def.type().substr(0, 15) == "DepthWiseConv") || | |||
There was a problem hiding this comment.
We are moving away from using OperatorDef. You can instead add a template parameter
typename <bool DepthWise>
class MIOPENConvOpBase : ...
and then set mode_ based on DepthWise
* upstream/master: (87 commits) Make Variable::set_data non-const; cosmetic fixes. remove warning for upsample code (pytorch#17921) Optimize TileOp (pytorch#17290) Optimize channel_stats_op (pytorch#16243) enable shape inference for elementwise operators (pytorch#17885) Remove remaining test jit expects redux (pytorch#17924) Handle Scalars Better (pytorch#17875) Fixed a formatting issue in doc comments (pytorch#17505) Add nbytes, itemsize, element_size to at::Tensor. (pytorch#17810) Fix lint in test_distributions.py Fix lint in test_jit.py Fix lint errors in test_autograd Added a few extra python bindings to help with walking the IR graph from Python (pytorch#17822) kthvalue consistency with sort in the presence of NaN (pytorch#17824) Fix minor grammatical mistakes in torch/nn/modules/loss.py (pytorch#17892) Remove (almost all) TensorOptions from native_functions.yaml (pytorch#17385) Restore full Windows tests (pytorch#17102) Prevent VS2017 from emitting ambiguous symbol errors (second time) Fix windows test hang (pytorch#17778) torch.btrifact for tensors with greater than 3 dimensions (pytorch#14964) ...
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ping @petrex |
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@bddppq We have consolidated the design of miopen Conv. The enum |
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