haojin2 commented on a change in pull request #17254: [numpy] change unary
infer type
URL: https://github.com/apache/incubator-mxnet/pull/17254#discussion_r366778186
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File path: src/operator/tensor/elemwise_binary_op.h
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@@ -525,6 +525,67 @@ class ElemwiseBinaryOp : public OpBase {
});
}
+ template<typename xpu, typename OP>
+ static void MixedUnaryBackwardUseInCompute(const nnvm::NodeAttrs &attrs,
+ const OpContext &ctx,
+ const std::vector<TBlob> &inputs,
+ const std::vector<OpReqType> &req,
+ const std::vector<TBlob>
&outputs) {
+ using namespace mxnet_op;
+ if (req[0] == kNullOp) return;
+ Stream<xpu> *s = ctx.get_stream<xpu>();
+ CHECK_EQ(inputs.size(), 2U);
+ CHECK_EQ(outputs.size(), 1U);
+ if (!mxnet::common::is_float(inputs[1].type_flag_)) {
+ LOG(FATAL) << "Operator " << attrs.op->name <<
+ " does not support type " << inputs[1].type_flag_;
+ }
+ if (outputs[0].type_flag_ == mshadow::kBool) {
+ LOG(FATAL) << "Operator " << attrs.op->name << " does not support
boolean type";
+ }
+ MXNET_ASSIGN_REQ_SWITCH(req[0], Req, {
+ MSHADOW_TYPE_SWITCH(outputs[0].type_flag_, DType, {
+ const size_t size = (minthree(outputs[0].Size(), inputs[0].Size(),
inputs[1].Size())
+ + DataType<DType>::kLanes - 1) / DataType<DType>::kLanes;
+ if (size != 0) {
+ Kernel<mxnet_op::op_with_req<OP, Req>, xpu>::Launch(s, size,
+ outputs[0].dptr<DType>(),
+ inputs[0].dptr<DType>(), inputs[1].dptr<DType>());
+ }
+ });
+ });
+ }
+
+ template<typename xpu, typename OP>
+ static void MixedUnaryBackwardUseInOutCompute(const nnvm::NodeAttrs &attrs,
+ const OpContext &ctx,
+ const std::vector<TBlob> &inputs,
+ const std::vector<OpReqType> &req,
+ const std::vector<TBlob> &outputs) {
+ using namespace mxnet_op;
+ if (req[0] == kNullOp) return;
+ Stream<xpu> *s = ctx.get_stream<xpu>();
+ CHECK_EQ(inputs.size(), 3U);
+ CHECK_EQ(outputs.size(), 1U);
+ if (mxnet::common::is_int(outputs[0].type_flag_)) {
+ LOG(FATAL) << "Operator " << attrs.op->name << " does not support int
type";
+ }
+ if (outputs[0].type_flag_ == mshadow::kBool) {
Review comment:
this case and the above case could be merged.
Plus, the error message is not meaningful enough.
`mshadow::dtype_string(outputs[0].type_flag_)` will give you the
corresponding string that represents the data type.
Also the problem with showing the op's name is that it will be something in
the form of `_backward_npi_xxx`. I think here simply say that "gradient
computation for xxx type is not supported" is better. ("xxx" should be the
string returned by call to `dtype_string`)
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