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_r398849702
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File path: src/relay/qnn/op/op_common.h
##########
@@ -30,14 +30,151 @@
#include <tvm/relay/qnn/attrs.h>
#include <vector>
#include "../../op/type_relations.h"
+#include "../../transforms/infer_layout_util.h"
+#include "../util.h"
namespace tvm {
namespace relay {
namespace qnn {
-static inline bool QnnBroadcastRel(const Array<Type>& types, int num_inputs,
const Attrs& attrs,
+/*
+ * Number of inputs for the Qnn binary operators.
+ * Refer the QNN_REGISTER_BINARY_OP macro to see
+ * what the operators are.
+ */
+static constexpr int numQnnBinaryOpInputs = 8;
+
+/*
+ * Number of expected arg types.
+ */
+static constexpr int numQnnBinaryOpArgTypes = 9;
+
+/*
+ * \brief Simple struct to organize the inputs to the Qnn
+ * binary operators. The main reason to have a struct
+ * is to be able to perform the common checks needed at a
+ * central location.
+ */
+struct QnnBinaryOpArguments {
+ Expr lhs;
+ Expr rhs;
+ Expr lhs_scale;
+ Expr lhs_zero_point;
+ Expr rhs_scale;
+ Expr rhs_zero_point;
+ Expr output_scale;
+ Expr output_zero_point;
+
+ explicit QnnBinaryOpArguments(const Array<Expr>& new_args) {
+ CHECK_EQ(new_args.size(), numQnnBinaryOpInputs);
+ int idx = 0;
+ lhs = new_args[idx++];
+ rhs = new_args[idx++];
+ lhs_scale = new_args[idx++];
+ lhs_zero_point = new_args[idx++];
+ rhs_scale = new_args[idx++];
+ rhs_zero_point = new_args[idx++];
+ output_scale = new_args[idx++];
+ output_zero_point = new_args[idx++];
+ CHECK_EQ(idx, numQnnBinaryOpInputs);
+ }
+};
+
+/*
+ * \brief Simple structure to hold the input tensor's dtype
+ * and shape. This structure allows a common point to do
+ * all the validation checks.
+ */
+struct QnnBinaryOpTypes {
Review comment:
QnnBinaryOpType? Seems this is singular?
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