reminisce commented on a change in pull request #15973: Numpy . implement numpy
op exp2 with tvm
URL: https://github.com/apache/incubator-mxnet/pull/15973#discussion_r317888810
##########
File path: src/operator/contrib/tvmop/ufunc.cc
##########
@@ -144,6 +144,61 @@ NNVM_REGISTER_OP(_backward_contrib_tvm_vadd)
.set_attr<mxnet::FCompute>("FCompute<cpu>",
mxnet::op::TVMBinaryBackwardComputeUseNone<func_bakcward_vadd_cpu>);
+
+static constexpr char func_exp2_cpu[] = "exp2";
+static constexpr char func_epx2_gpu[] = "cuda_exp2";
+static constexpr char func_backward_epx2_cpu[] = "backward_exp2";
+static constexpr char func_backward_epx2_gpu[] = "cuda_backward_exp2";
+
+template<const char* func>
+void TVMOpExp2Compute(const nnvm::NodeAttrs& attrs,
+ const mxnet::OpContext& ctx,
+ const std::vector<TBlob>& inputs,
+ const std::vector<OpReqType>& req,
+ const std::vector<TBlob>& outputs) {
+ CHECK_EQ(inputs.size(), 1U);
+ CHECK_EQ(outputs.size(), 1U);
+ tvm::runtime::TVMOpModule::Get()->Call(func, ctx, {inputs[0], outputs[0]});
+}
+
+template<const char* func>
+void TVMExp2Backward(const nnvm::NodeAttrs& attrs,
+ const OpContext& ctx,
+ const std::vector<TBlob>& inputs,
+ const std::vector<OpReqType>& req,
+ const std::vector<TBlob>& outputs) {
+ CHECK_EQ(inputs.size(), 3U);
+ CHECK_EQ(outputs.size(), 1U);
+ CHECK_EQ(req.size(), 1U);
+ using namespace mshadow;
+ const TBlob& out_grad = inputs[0];
+ const TBlob& in_data1 = inputs[1];
+ const TBlob& in_data2 = inputs[2];
+ const TBlob& in_grad = outputs[0];
+ tvm::runtime::TVMOpModule::Get()->Call(func, ctx, {out_grad, in_data1,
in_data2, in_grad});
+}
+
+NNVM_REGISTER_OP(_npi_exp2)
+ .set_num_inputs(1)
Review comment:
no indentation
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