reminisce commented on a change in pull request #10889: [MXNET-382] Shape and
Size Operator
URL: https://github.com/apache/incubator-mxnet/pull/10889#discussion_r195603907
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File path: src/operator/tensor/elemwise_unary_op_basic.cc
##########
@@ -398,6 +398,106 @@ NNVM_REGISTER_OP(reshape_like)
.add_argument("lhs", "NDArray-or-Symbol", "First input.")
.add_argument("rhs", "NDArray-or-Symbol", "Second input.");
+template<>
+void ShapeCompute<cpu>(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(), 1U);
+ CHECK_EQ(outputs.size(), 1U);
+ CHECK_EQ(req.size(), 1U);
+ const TBlob& in_data = inputs[0];
+ const TBlob& out_data = outputs[0];
+ mshadow::Stream<cpu> *s = ctx.get_stream<cpu>();
+ const TShape& in_shape = in_data.shape_;
+ MSHADOW_TYPE_SWITCH(out_data.type_flag_, DType, {
+ mxnet_op::Kernel<mshadow_op::identity_with_cast, cpu>::Launch(
+ s, in_data.ndim(), out_data.dptr<DType>(), in_shape.data());
+ });
+}
+
+NNVM_REGISTER_OP(shape_array)
+.describe(R"code(Returns a 1D int64 array containing the shape of data.
+
+Example::
+
+ shape_nd([[1,2,3,4], [5,6,7,8]]) = [2,4]
+
+)code" ADD_FILELINE)
+.set_num_inputs(1)
+.set_num_outputs(1)
+.set_attr<FCompute>("FCompute<cpu>", ShapeCompute<cpu>)
+.set_attr<nnvm::FInferShape>("FInferShape",
+ [](const nnvm::NodeAttrs& attrs,
+ std::vector<TShape> *in_attrs,
+ std::vector<TShape> *out_attrs) {
+ CHECK_EQ(in_attrs->size(), 1U);
+ CHECK_EQ(out_attrs->size(), 1U);
+ TShape target_shape(1);
+ target_shape[0] = in_attrs->at(0).ndim();
+ SHAPE_ASSIGN_CHECK(*out_attrs, 0, target_shape);
+ return !shape_is_none(out_attrs->at(0));
+ })
+.set_attr<nnvm::FInferType>("FInferType",
+ [](const nnvm::NodeAttrs& attrs,
+ std::vector<int>* in_attrs,
+ std::vector<int>* out_attrs) {
+ CHECK_EQ(in_attrs->size(), 1U);
+ CHECK_EQ(out_attrs->size(), 1U);
+ TYPE_ASSIGN_CHECK(*out_attrs, 0, mshadow::kInt64);
+ return out_attrs->at(0) != -1;
+ })
+.add_argument("data", "NDArray-or-Symbol", "Input Array.");
+
+template<>
+void SizeCompute<cpu>(const nnvm::NodeAttrs& attrs,
+ const OpContext& ctx,
+ const std::vector<TBlob>& inputs,
+ const std::vector<OpReqType>& req,
+ const std::vector<TBlob>& outputs) {
+ using namespace mshadow;
+ using namespace mxnet_op;
+ CHECK_EQ(inputs.size(), 1U);
+ CHECK_EQ(outputs.size(), 1U);
+ CHECK_EQ(req.size(), 1U);
+ const TBlob& in_data = inputs[0];
+ const TBlob& out_data = outputs[0];
+ mshadow::Stream<cpu> *s = ctx.get_stream<cpu>();
+ mxnet_op::Kernel<mshadow_op::size_kernel, cpu>::Launch(
Review comment:
If it's just simply copying one element, no need to use kernel launch scheme.
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