bartekkuncer commented on a change in pull request #20904:
URL: https://github.com/apache/incubator-mxnet/pull/20904#discussion_r827412144
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File path: src/operator/tensor/elemwise_binary_scalar_op_extended.cc
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@@ -49,8 +49,38 @@ MXNET_OPERATOR_REGISTER_BINARY(_backward_minimum_scalar)
.set_attr_parser(ParamParser<NumpyBinaryScalarParam>)
.set_attr<FCompute>("FCompute<cpu>", BinaryScalarOp::Backward<cpu,
mshadow_op::le>);
+#if MXNET_USE_ONEDNN == 1
+bool PowerStorageType(const nnvm::NodeAttrs& attrs,
+ const int dev_mask,
+ DispatchMode* dispatch_mode,
+ std::vector<int>* inputs,
+ std::vector<int>* outputs) {
+ CHECK_EQ(inputs->size(), 1);
+ CHECK_EQ(outputs->size(), 1);
+
+ return DNNLStorageType(attrs, dev_mask, true, dispatch_mode, inputs,
outputs);
+}
+
+void PowerComputeExCPU(const nnvm::NodeAttrs& attrs,
+ const OpContext& ctx,
+ const std::vector<mxnet::NDArray>& inputs,
+ const std::vector<OpReqType>& req,
+ const std::vector<mxnet::NDArray>& outputs) {
+ if (SupportDNNL(inputs[0])) {
Review comment:
This function allows only ndim equal to 1, 2 and 4. Are you sure this
function should be so strict?
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