anijain2305 commented on a change in pull request #5153: Adding support for QNN
subtract op
URL: https://github.com/apache/incubator-tvm/pull/5153#discussion_r398784846
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File path: src/relay/qnn/op/mul.cc
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@@ -42,22 +42,10 @@ namespace qnn {
Expr QnnMulCanonicalize(const Attrs& attrs, const Array<Expr>& new_args,
const Array<tvm::relay::Type>& arg_types) {
// Get the attrs.
- CHECK_EQ(new_args.size(), 8);
- auto& lhs = new_args[0];
- auto& rhs = new_args[1];
- auto& lhs_scale = new_args[2];
- auto& lhs_zero_point = new_args[3];
- auto& rhs_scale = new_args[4];
- auto& rhs_zero_point = new_args[5];
- auto& output_scale = new_args[6];
- auto& output_zero_point = new_args[7];
+ QnnBinaryOpArguments args(new_args);
// Get the input dtype and shape.
- CHECK_EQ(arg_types.size(), 9);
- auto tensor_type = arg_types[0].as<TensorTypeNode>();
- CHECK(tensor_type != nullptr);
- auto input_dtype = tensor_type->dtype;
- auto input_shape = tensor_type->shape;
+ QnnBinaryOpDtypeAndShape inputShapeAndDtype(arg_types);
Review comment:
s/QnnBinaryOpDtypeAndShape/QnnBinaryType
s/inputShapeAndDtype/input_types (need to use _ for variable names)
In Relay Type means (dtype, shape)
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