Fix dequantize output type

mace/core/workspace.cc

@@ -178,12 +178,14 @@ MaceStatus Workspace::LoadModelTensor(const NetDef &net_def,
   if (type == DeviceType::CPU && net_def.has_quantize_info()) {
     for (const auto
           &activation_info: net_def.quantize_info().activation_info()) {
-      MACE_CHECK(HasTensor(activation_info.tensor_name()),
-                 "Quantize info exist for non-existed tensor",
-                 activation_info.tensor_name());
-      Tensor *tensor = GetTensor(activation_info.tensor_name());
-      tensor->SetScale(activation_info.scale());
-      tensor->SetZeroPoint(activation_info.zero_point());
+      if (HasTensor(activation_info.tensor_name())) {
+        Tensor *tensor = GetTensor(activation_info.tensor_name());
+        tensor->SetScale(activation_info.scale());
+        tensor->SetZeroPoint(activation_info.zero_point());
+      } else {
+        LOG(WARNING) << "Quantize info exists for non-existed tensor: "
+            << activation_info.tensor_name();
+      }
     }
   }
 

mace/kernels/softmax.h

@@ -123,7 +123,7 @@ struct SoftmaxFunctor<DeviceType::CPU, float> {
   }
 };
 
-static const int kInputDeltaIntBits = 5;
+static const int kInputDeltaIntBits = 6;
 static const int kSumExpIntBits = 12;
 
 template<>

mace/python/tools/converter_tool/base_converter.py

@@ -368,6 +368,8 @@ class ConverterOption(object):
                 TransformerRule.UPDATE_FLOAT_OP_DATA_TYPE,
                 # Transform finalization
                 TransformerRule.ADD_MACE_INPUT_AND_OUTPUT_NODES,
+                # for quantization entropy calibration use
+                TransformerRule.ADD_QUANTIZE_TENSOR_RANGE,
                 TransformerRule.SORT_BY_EXECUTION,
             ]
             if self._quantize:

mace/python/tools/converter_tool/transformer.py

@@ -1638,6 +1638,7 @@ class Transformer(base_converter.ConverterInterface):
             output_shape = op_def.output_shape.add()
             output_shape.dims.extend(
                 self._producer[output_node.name].output_shape[0].dims)
+            op_def.output_type.extend([mace_pb2.DT_FLOAT])
 
             ConverterUtil.add_data_type_arg(op_def, mace_pb2.DT_UINT8)
 
@@ -1647,6 +1648,9 @@ class Transformer(base_converter.ConverterInterface):
         print("Add quantize tensor range")
         net = self._model
         range_file = self._option.quantize_range_file
+        if not range_file:
+            return
+
         with open(range_file) as f:
             for line in f:
                 tensor_name, minmax = line.split("@@")

tools/converter.py

@@ -481,13 +481,15 @@ def format_model_config(flags):
                     DeviceType.CPU: 0.999,
                     DeviceType.GPU: 0.995,
                     DeviceType.HEXAGON: 0.930,
+                    DeviceType.CPU + "_QUANTIZE": 0.980,
                     }
             for k, v in six.iteritems(validation_threshold):
                 if k.upper() == 'DSP':
                     k = DeviceType.HEXAGON
                 if k.upper() not in (DeviceType.CPU,
                                      DeviceType.GPU,
-                                     DeviceType.HEXAGON):
+                                     DeviceType.HEXAGON,
+                                     DeviceType.CPU + "_QUANTIZE"):
                     raise argparse.ArgumentTypeError(
                             'Unsupported validation threshold runtime: %s' % k)
                 threshold_dict[k.upper()] = v
@@ -1251,6 +1253,10 @@ def run_specific_target(flags, configs, target_abi,
                     model_config[YAMLKeyword.weight_file_path],
                     model_config[YAMLKeyword.weight_sha256_checksum])
 
+                validate_type = device_type
+                if model_config[YAMLKeyword.quantize] == 1:
+                    validate_type = device_type + "_QUANTIZE"
+
                 sh_commands.validate_model(
                     abi=target_abi,
                     serialno=serial_num,
@@ -1266,7 +1272,7 @@ def run_specific_target(flags, configs, target_abi,
                     phone_data_dir=PHONE_DATA_DIR,
                     input_data_types=subgraphs[0][YAMLKeyword.input_data_types],  # noqa
                     caffe_env=flags.caffe_env,
-                    validation_threshold=subgraphs[0][YAMLKeyword.validation_threshold][device_type])  # noqa
+                    validation_threshold=subgraphs[0][YAMLKeyword.validation_threshold][validate_type])  # noqa
             if flags.report and flags.round > 0:
                 tuned = is_tuned and device_type == DeviceType.GPU
                 report_run_statistics(