From a2e35010825959e9c5dbc1d29a1d77a6a371c418 Mon Sep 17 00:00:00 2001
From: yeyunpeng2020 <yeyunpeng1@huawei.com>
Date: Thu, 20 Jan 2022 11:51:28 +0800
Subject: [PATCH] fix dynamic quant kernel bug && dynamic matmul multi threads
 bug

---
 .../runtime/kernel/arm/int8/dynamic_quant.cc  |  2 +-
 .../kernel/arm/int8/matmul_dynamic_int8.cc    | 48 ++++---------------
 .../quantizer/config/dynamic_quant.cfg        |  4 --
 3 files changed, 11 insertions(+), 43 deletions(-)

diff --git a/mindspore/lite/src/runtime/kernel/arm/int8/dynamic_quant.cc b/mindspore/lite/src/runtime/kernel/arm/int8/dynamic_quant.cc
index 9e69fb47bdd..6015bca3e2a 100644
--- a/mindspore/lite/src/runtime/kernel/arm/int8/dynamic_quant.cc
+++ b/mindspore/lite/src/runtime/kernel/arm/int8/dynamic_quant.cc
@@ -121,7 +121,7 @@ void DynamicQuantCPUKernel::CalculateScaleZp() {
   quant_parm.zeroPoint = zp;
   quant_parm.bitNum = k8Bit;
   quant_parm.inited = true;
-  this->out_tensors_.front()->AddQuantParam(quant_parm);
+  this->out_tensors_.front()->set_quant_params({quant_parm});
   return;
 }
 
diff --git a/mindspore/lite/src/runtime/kernel/arm/int8/matmul_dynamic_int8.cc b/mindspore/lite/src/runtime/kernel/arm/int8/matmul_dynamic_int8.cc
index 1025a647f10..ee394006179 100644
--- a/mindspore/lite/src/runtime/kernel/arm/int8/matmul_dynamic_int8.cc
+++ b/mindspore/lite/src/runtime/kernel/arm/int8/matmul_dynamic_int8.cc
@@ -50,9 +50,17 @@ int MatmulDynamicInt8CPUKernel::RunImpl(int task_id) {
   if (cur_oc <= 0) {
     return RET_OK;
   }
-  DynamicMatmulInt8AIWI(pack_a_ptr_, batch_b_ptr_ + cur_stride * param_->deep_align_, fp32_bias_ptr_,
+  float *bias_ptr = fp32_bias_ptr_;
+  if (fp32_bias_ptr_ != nullptr) {
+    bias_ptr += cur_stride;
+  }
+  float *filter_scale = quant_param_->filter_scale_;
+  if (filter_per_channel_) {
+    filter_scale += cur_stride;
+  }
+  DynamicMatmulInt8AIWI(pack_a_ptr_, batch_b_ptr_ + cur_stride * param_->deep_align_, bias_ptr,
                         batch_c_ptr_ + cur_stride, param_->row_, cur_oc, param_->deep_align_,
-                        quant_param_->input_scale_, quant_param_->filter_scale_, param_->col_, filter_per_channel_);
+                        quant_param_->input_scale_, filter_scale, param_->col_, filter_per_channel_);
   return RET_OK;
 }
 
@@ -139,54 +147,18 @@ int MatmulDynamicInt8CPUKernel::InitInputQuantParam() {
 void MatmulDynamicInt8CPUKernel::InitParameter() {
   param_->a_const_ = (in_tensors_[kInputIndex]->data() != nullptr);
   param_->b_const_ = (in_tensors_[kWeightIndex]->data() != nullptr);
-#ifdef ENABLE_ARM32
-  row_tile_ = C4NUM;
-  col_tile_ = C2NUM;
-  deep_tile_ = C16NUM;
-#elif ENABLE_ARM64
-  support_sdot_ = mindspore::lite::IsSupportSDot();
-  row_tile_ = C4NUM;
-  if (support_sdot_) {
-    col_tile_ = C16NUM;
-    deep_tile_ = C4NUM;
-  } else {
-    col_tile_ = C4NUM;
-    deep_tile_ = C16NUM;
-  }
-#else
   row_tile_ = C4NUM;
   col_tile_ = C4NUM;
   deep_tile_ = C16NUM;
-#endif
   if (param_->a_transpose_) {
     a_pack_func_ = RowMajor2Col16x4MajorInt8;
   } else {
     a_pack_func_ = RowMajor2Row16x4MajorInt8;
   }
   if (param_->b_transpose_) {
-#ifdef ENABLE_ARM32
-    b_pack_func_ = RowMajor2Row2x16MajorInt8;
-#elif ENABLE_ARM64
-    if (support_sdot_) {
-      b_pack_func_ = RowMajor2Row4x16MajorInt8;
-    } else {
-      b_pack_func_ = RowMajor2Row16x4MajorInt8;
-    }
-#else
     b_pack_func_ = RowMajor2Row16x4MajorInt8;
-#endif
   } else {
-#ifdef ENABLE_ARM32
-    b_pack_func_ = RowMajor2Col16x2MajorInt8;
-#elif ENABLE_ARM64
-    if (support_sdot_) {
-      b_pack_func_ = RowMajor2Col4x16MajorInt8;
-    } else {
-      b_pack_func_ = RowMajor2Col16x4MajorInt8;
-    }
-#else
     b_pack_func_ = RowMajor2Col16x4MajorInt8;
-#endif
   }
   return;
 }
diff --git a/mindspore/lite/tools/converter/quantizer/config/dynamic_quant.cfg b/mindspore/lite/tools/converter/quantizer/config/dynamic_quant.cfg
index 164a31d86d2..d11325e778c 100644
--- a/mindspore/lite/tools/converter/quantizer/config/dynamic_quant.cfg
+++ b/mindspore/lite/tools/converter/quantizer/config/dynamic_quant.cfg
@@ -1,7 +1,3 @@
 [common_quant_param]
 quant_type=DYNAMIC_QUANT
 bit_num=8
-# Layers with size of weights exceeds threshold `min_quant_weight_size` will be quantized.
-min_quant_weight_size=0
-# Layers with channel size of weights exceeds threshold `min_quant_weight_channel` will be quantized.
-min_quant_weight_channel=16