jackwish commented on a change in pull request #4611: {QNN] Making
scale/zero_points as expr instead of attrs.
URL: https://github.com/apache/incubator-tvm/pull/4611#discussion_r362707098
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File path: src/relay/qnn/op/concatenate.cc
##########
@@ -34,19 +34,48 @@ namespace tvm {
namespace relay {
namespace qnn {
-TVM_REGISTER_NODE_TYPE(QnnConcatenateAttrs);
-
-Expr MakeQnnConcatenate(Expr data, Array<tvm::Expr> input_scales,
- Array<tvm::Expr> input_zero_points, double
output_scale,
- int32_t output_zero_point, int axis) {
- auto attrs = make_object<QnnConcatenateAttrs>();
- attrs->input_scales = std::move(input_scales);
- attrs->input_zero_points = std::move(input_zero_points);
- attrs->output_scale = output_scale;
- attrs->output_zero_point = output_zero_point;
+bool QnnConcatenateRel(const Array<Type>& types, int num_inputs, const Attrs&
attrs,
+ const TypeReporter& reporter) {
+ CHECK_EQ(types.size(), 6);
+
+ // Check the scale and zero point types
+ const auto* input_scales_tuple = types[1].as<TupleTypeNode>();
+ if (input_scales_tuple == nullptr) {
+ throw relay::Error(
+ RELAY_ERROR("qnn concatenate requires a tuple of scales as the second
argument, found "
+ << PrettyPrint(types[1])));
+ }
+ for (auto input_scale : input_scales_tuple->fields) {
+ CHECK(IsScalarType(input_scale, DataType::Float(32))); //
input_scales[idx]
+ }
+
+ const auto* input_zero_points_tuple = types[2].as<TupleTypeNode>();
+ if (input_zero_points_tuple == nullptr) {
+ throw relay::Error(
+ RELAY_ERROR("qnn concatenate requires a tuple of zero_points as the
third argument, found "
+ << PrettyPrint(types[2])));
+ }
+ for (auto input_zero_point : input_zero_points_tuple->fields) {
Review comment:
could be `auto&`?
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