From 47a838a0bb25bd28c2ab7e091a96d33397d7efbf Mon Sep 17 00:00:00 2001
From: Neil Tan <neil@utensor.ai>
Date: Sat, 20 Jul 2024 11:51:52 +0800
Subject: [PATCH] added some re-arch comments to kick off discussions

---
 src/uTensor/ops/trigonometric.hpp | 6 +++---
 tanh_model/tanh_main.cpp          | 2 +-
 2 files changed, 4 insertions(+), 4 deletions(-)

diff --git a/src/uTensor/ops/trigonometric.hpp b/src/uTensor/ops/trigonometric.hpp
index 99ab2c52..8b3cb959 100644
--- a/src/uTensor/ops/trigonometric.hpp
+++ b/src/uTensor/ops/trigonometric.hpp
@@ -12,20 +12,20 @@ namespace ReferenceOperators {
 // adapt to tanh_kernel
 
 template <typename OutputT, typename InputT>
-class TanhOperator : public OperatorInterface<1, 1> {
+class TanhOperator : public OperatorInterface<1, 1> { // suggestion: remove the FastOperatorInterface and move its functionality to other places
  public:
   enum names_in : uint8_t { act_in };
   enum names_out : uint8_t { act_out };
 
  protected:
   virtual void compute() {
-    Tensor& in = inputs[act_in].tensor();
+    Tensor& in = inputs[act_in].tensor(); // suggestion: operator[] returns pointers to tensors and allow debug hooks insertion
     Tensor& out = outputs[act_out].tensor();
 
     const uint32_t flat_size = in->get_shape().get_linear_size();
 
     int32_t in_zero_point =
-        in->get_quantization_params().get_zeroP_for_channel(0);
+        in->get_quantization_params().get_zeroP_for_channel(0); // suggestion: quantization_params as composition
     float in_scale = in->get_quantization_params().get_scale_for_channel(0);
 
     int32_t out_zero_point =
diff --git a/tanh_model/tanh_main.cpp b/tanh_model/tanh_main.cpp
index 39681579..3c40c167 100644
--- a/tanh_model/tanh_main.cpp
+++ b/tanh_model/tanh_main.cpp
@@ -23,7 +23,7 @@ int main(int argc, const char** argv) {
   for (size_t i = 0; i < 128; ++i) {
     inputs_data[i] = dist(rengine);
   }
-  Tensor in_tensor = new RomTensor({128}, inputs_data);
+  Tensor in_tensor = new RomTensor({128}, inputs_data); // suggestion: implement function analogous to construct_at(p, 4, 'a');
   Tensor out_tensor = new RamTensor({128}, flt);
   tanh_model.set_inputs({{TanhModel::input_0, in_tensor}})
       .set_outputs({{TanhModel::output_0, out_tensor}})