!7836 add smoke for mindir weight quant

Merge pull request !7836 from ghzl/add-smoke-for-mindir-weight-quant

mindspore/lite/src/ops/primitive_c.cc

@@ -240,6 +240,14 @@ void PrimitiveC::PopulaterQuantParam(const Primitive &prim, const std::vector<An
     input_quant_param_.emplace_back(quants);
   }
 
+  // fill input_quant_param_ by not inited quant_parm
+  if (input_quant_param_.size() < inputs.size()) {
+    quants.clear();
+    schema::QuantParamT tmpQuantParam;
+    quants.emplace_back(tmpQuantParam);
+    input_quant_param_.insert(input_quant_param_.end(), inputs.size() - input_quant_param_.size(), quants);
+  }
+
   if (input_quant_param_.size() == kDoubleNum) {
     quants.clear();
     quantParam.min = 0.0;
@@ -250,14 +258,6 @@ void PrimitiveC::PopulaterQuantParam(const Primitive &prim, const std::vector<An
     input_quant_param_.emplace_back(quants);
   }
 
-  // fill input_quant_param_ by not inited quant_parm
-  if (input_quant_param_.size() < inputs.size()) {
-    quants.clear();
-    schema::QuantParamT tmpQuantParam;
-    quants.emplace_back(tmpQuantParam);
-    input_quant_param_.insert(input_quant_param_.end(), inputs.size() - 1 - input_quant_param_.size(), quants);
-  }
-
   quants.clear();
   auto outputMin = prim.GetAttr("output_minq");
   auto outputMax = prim.GetAttr("output_maxq");

mindspore/lite/test/models_mindspore_weightquant.cfg

@@ -0,0 +1,3 @@
+retinaface.mindir
+mobilefacenet.mindir
+#efficientnet.mindir

mindspore/lite/test/run_benchmark_nets.sh

@@ -163,7 +163,7 @@ function Run_Converter() {
         fi
     done < ${models_fp16_config}
 
-    # Convert weightquant models:
+    # Convert tflite weightquant models:
     while read line; do
         model_name=${line}
         if [[ $model_name == \#* ]]; then
@@ -179,6 +179,22 @@ function Run_Converter() {
         fi
     done < ${models_tflite_weightquant_config}
 
+    # Convert mindir weightquant models:
+    while read line; do
+        model_name=${line}
+        if [[ $model_name == \#* ]]; then
+          continue
+        fi
+        echo ${model_name} >> "${run_converter_log_file}"
+        echo './converter_lite  --fmk=MINDIR --modelFile='${models_path}'/'${model_name}' --outputFile='${ms_models_path}'/'${model_name}'--quantType=WeightQuant --bitNum=8 --quantWeightSize=500 --quantWeightChannel=16' >> "${run_converter_log_file}"
+        ./converter_lite  --fmk=MINDIR --modelFile=$models_path/${model_name} --outputFile=${ms_models_path}/${model_name}_weightquant --quantType=WeightQuant --bitNum=8 --quantWeightSize=500 --quantWeightChannel=16
+        if [ $? = 0 ]; then
+            converter_result='converter weight_quant '${model_name}' pass';echo ${converter_result} >> ${run_converter_result_file}
+        else
+            converter_result='converter weight_quant '${model_name}' failed';echo ${converter_result} >> ${run_converter_result_file};return 1
+        fi
+    done < ${models_mindspore_weightquant_config}
+
     # Convert models which do not need to be cared about the accuracy:
     while read line; do
         model_name=${line}
@@ -378,6 +394,24 @@ function Run_x86() {
         fi
     done < ${models_tflite_weightquant_config}
 
+    # Run mindir weight quantization converted models:
+    while read line; do
+        model_name=${line}
+        if [[ $model_name == \#* ]]; then
+          continue
+        fi
+        echo ${model_name} >> "${run_x86_log_file}"
+        echo 'cd  '${x86_path}'/mindspore-lite-'${version}'-runtime-x86-'${process_unit_x86} >> "${run_x86_log_file}"
+        cd ${x86_path}/mindspore-lite-${version}-runtime-x86-${process_unit_x86} || return 1
+        echo 'export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:./lib:./third_party/libjpeg-turbo/lib:./third_party/opencv/lib;./benchmark/benchmark --modelFile='${ms_models_path}'/'${model_name}'.ms --inDataFile=/home/workspace/mindspore_dataset/mslite/models/hiai/input_output/input/'${model_name}'.ms.bin --benchmarkDataFile=/home/workspace/mindspore_dataset/mslite/models/hiai/input_output/output/'${model_name}'.ms.out' >> "${run_x86_log_file}"
+        export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:./lib:./third_party/libjpeg-turbo/lib:./third_party/opencv/lib;./benchmark/benchmark --modelFile=${ms_models_path}/${model_name}_weightquant.ms --inDataFile=/home/workspace/mindspore_dataset/mslite/models/hiai/input_output/input/${model_name}.ms.bin --benchmarkDataFile=/home/workspace/mindspore_dataset/mslite/models/hiai/input_output/output/${model_name}.weightquant.ms.out >> "${run_x86_log_file}"
+        if [ $? = 0 ]; then
+            run_result='x86: '${model_name}' pass'; echo ${run_result} >> ${run_benchmark_result_file}
+        else
+            run_result='x86: '${model_name}' failed'; echo ${run_result} >> ${run_benchmark_result_file}; return 1
+        fi
+    done < ${models_mindspore_weightquant_config}
+
     # Run converted models which do not need to be cared about the accuracy:
     while read line; do
         model_name=${line}
@@ -890,6 +924,7 @@ models_fp16_config=${basepath}/models_fp16.cfg
 models_mindspore_config=${basepath}/models_mindspore.cfg
 models_mindspore_train_config=${basepath}/models_mindspore_train.cfg
 models_tflite_gpu_config=${basepath}/models_fp32_gpu.cfg
+models_mindspore_weightquant_config=${basepath}/models_mindspore_weightquant.cfg
 models_fp16_gpu_config=${basepath}/models_fp16_gpu.cfg
 models_arm32_config=${basepath}/models_arm32.cfg
 models_compatibility_config=${basepath}/models_compatibility.cfg

mindspore/lite/tools/anf_exporter/anf_exporter.cc

@@ -102,9 +102,9 @@ int AnfExporter::ConvertQuantParam(const std::unique_ptr<schema::MetaGraphT> &me
   if (!input_quant_params.empty()) {
     for (size_t i = 0; i < input_quant_params.size(); i++) {
       if (i >= dst_node->inputIndex.size()) {
-        MS_LOG(ERROR) << "node: " << dst_node->name << " input has " << input_quant_params.size()
-                      << " quant_params; but only " << dst_node->inputIndex.size() << " input";
-        return RET_PARAM_INVALID;
+        MS_LOG(INFO) << "node: " << dst_node->name << " input has " << input_quant_params.size()
+                     << " quant_params; but only " << dst_node->inputIndex.size() << " input";
+        break;
       }
       auto activate_index = dst_node->inputIndex[i];
       auto tensor_input = meta_graph->allTensors[activate_index].get();