optimize add, sub, mul, div mapper

mindinsight/mindconverter/graph_based_converter/mapper/impl/ops/add_mapper.py

@@ -51,6 +51,15 @@ class AddMapper(ONNXToMindSporeMapper):
         if not op:
             raise ValueError("Can not get MindSpore operation name.")
         if not weights:
+            variable_slot = "var_0"
+            construct_template = \
+                f"opt_{{{variable_slot}}} = {op}()({{{ExchangeMessageKeywords.VariableScope.value.INPUTS.value}}})"
+            template = {
+                variable_slot: {
+                    TemplateKeywords.INIT.value: [],
+                    TemplateKeywords.CONSTRUCT.value: [construct_template]
+                }
+            }
             return template, exchange_msg, outputs_list, outputs_mapping
 
         tensor = AddMapper._find_val_by_index(0, weights)
@@ -58,7 +67,6 @@ class AddMapper(ONNXToMindSporeMapper):
         bias_location = AddMapper._find_location_by_index(0, weights)
 
         variable_slot = "var_0"
-        init_template = f"self.{{{variable_slot}}} = {op}({', '.join(['%s={%s}' % (p, p) for p in args])})"
         inputs_in_construct = [f"{{{ExchangeMessageKeywords.VariableScope.value.INPUTS.value}}}"]
         if bias_location != -1:
             inputs_in_construct.insert(bias_location, f"self.{{{variable_slot}}}_bias")
@@ -72,11 +80,10 @@ class AddMapper(ONNXToMindSporeMapper):
             args["bias_value"] = tensor.tolist()
             init_tensor = f"self.{{{variable_slot}}}_bias = {{bias_value}}"
 
-        construct_template = f"opt_{{{variable_slot}}} = self.{{{variable_slot}}}" \
-                             f"({', '.join(inputs_in_construct)})"
+        construct_template = f"opt_{{{variable_slot}}} = {' + '.join(inputs_in_construct)}"
         template = {
             variable_slot: {
-                TemplateKeywords.INIT.value: [init_template, init_tensor],
+                TemplateKeywords.INIT.value: [init_tensor],
                 TemplateKeywords.CONSTRUCT.value: [construct_template]
             }
         }

mindinsight/mindconverter/graph_based_converter/mapper/impl/ops/div_mapper.py

@@ -49,6 +49,15 @@ class DivMapper(ONNXToMindSporeMapper):
         weights = kwargs.get("weights")
         trainable_params = kwargs.get("trainable_params", dict())
         if not weights:
+            variable_slot = "var_0"
+            construct_template = \
+                f"opt_{{{variable_slot}}} = {op}()({{{ExchangeMessageKeywords.VariableScope.value.INPUTS.value}}}) "
+            template = {
+                variable_slot: {
+                    TemplateKeywords.INIT.value: [],
+                    TemplateKeywords.CONSTRUCT.value: [construct_template]
+                }
+            }
             return template, exchange_msg, outputs_list, outputs_mapping
 
         tensor = DivMapper._find_val_by_index(0, weights)
@@ -57,7 +66,6 @@ class DivMapper(ONNXToMindSporeMapper):
         w_location = DivMapper._find_location_by_index(0, weights)
 
         variable_slot = "var_0"
-        init_template = f"self.{{{variable_slot}}} = {op}()"
         inputs_in_construct = [f"{{{ExchangeMessageKeywords.VariableScope.value.INPUTS.value}}}"]
         if w_location != -1:
             inputs_in_construct.insert(w_location, f"self.{{{variable_slot}}}_w")
@@ -72,9 +80,8 @@ class DivMapper(ONNXToMindSporeMapper):
             args["w_value"] = tensor.tolist()
             init_tensor = f"self.{{{variable_slot}}}_w = {{w_value}}"
 
-        construct_template = f"opt_{{{variable_slot}}} = self.{{{variable_slot}}}" \
-                             f"({', '.join(inputs_in_construct)})"
-        template = reset_init_or_construct(template, variable_slot, [init_template, init_tensor],
+        construct_template = f"opt_{{{variable_slot}}} = {' / '.join(inputs_in_construct)}"
+        template = reset_init_or_construct(template, variable_slot, [init_tensor],
                                            TemplateKeywords.INIT.value)
         template = reset_init_or_construct(template, variable_slot, [construct_template],
                                            TemplateKeywords.CONSTRUCT.value)

mindinsight/mindconverter/graph_based_converter/mapper/impl/ops/mul_mapper.py

@@ -50,6 +50,15 @@ class MulMapper(ONNXToMindSporeMapper):
         weights = kwargs.get("weights")
         trainable_params = kwargs.get('trainable_params', dict())
         if not weights:
+            variable_slot = "var_0"
+            construct_template = \
+                f"opt_{{{variable_slot}}} = {op}()({{{ExchangeMessageKeywords.VariableScope.value.INPUTS.value}}})"
+            template = {
+                variable_slot: {
+                    TemplateKeywords.INIT.value: [],
+                    TemplateKeywords.CONSTRUCT.value: [construct_template]
+                }
+            }
             return template, exchange_msg, outputs_list, outputs_mapping
 
         tensor = MulMapper._find_val_by_index(0, weights)
@@ -57,7 +66,6 @@ class MulMapper(ONNXToMindSporeMapper):
         w_location = MulMapper._find_location_by_index(0, weights)
 
         variable_slot = "var_0"
-        init_template = f"self.{{{variable_slot}}} = {op}()"
         inputs_in_construct = [f"{{{ExchangeMessageKeywords.VariableScope.value.INPUTS.value}}}"]
         if w_location != -1:
             inputs_in_construct.insert(w_location, f"self.{{{variable_slot}}}_w")
@@ -70,9 +78,8 @@ class MulMapper(ONNXToMindSporeMapper):
             args["w_value"] = tensor.tolist()
             init_tensor = f"self.{{{variable_slot}}}_w = {{w_value}}"
 
-        construct_template = f"opt_{{{variable_slot}}} = self.{{{variable_slot}}}" \
-                             f"({', '.join(inputs_in_construct)})"
-        template = reset_init_or_construct(template, variable_slot, [init_template, init_tensor],
+        construct_template = f"opt_{{{variable_slot}}} = {' * '.join(inputs_in_construct)}"
+        template = reset_init_or_construct(template, variable_slot, [init_tensor],
                                            TemplateKeywords.INIT.value)
         template = reset_init_or_construct(template, variable_slot, [construct_template],
                                            TemplateKeywords.CONSTRUCT.value)

mindinsight/mindconverter/graph_based_converter/mapper/impl/ops/sub_mapper.py

@@ -50,6 +50,15 @@ class SubMapper(ONNXToMindSporeMapper):
         if not op:
             raise ValueError("Can not get MindSpore operation name.")
         if not weights:
+            variable_slot = "var_0"
+            construct_template = \
+                f"opt_{{{variable_slot}}} = {op}()({{{ExchangeMessageKeywords.VariableScope.value.INPUTS.value}}})"
+            template = {
+                variable_slot: {
+                    TemplateKeywords.INIT.value: [],
+                    TemplateKeywords.CONSTRUCT.value: [construct_template]
+                }
+            }
             return template, exchange_msg, outputs_list, outputs_mapping
 
         tensor = SubMapper._find_val_by_index(0, weights)
@@ -58,7 +67,6 @@ class SubMapper(ONNXToMindSporeMapper):
         bias_location = SubMapper._find_location_by_index(0, weights)
 
         variable_slot = "var_0"
-        init_template = f"self.{{{variable_slot}}} = {op}()"
         inputs_in_construct = [f"{{{ExchangeMessageKeywords.VariableScope.value.INPUTS.value}}}"]
         if bias_location != -1:
             inputs_in_construct.insert(bias_location, f"self.{{{variable_slot}}}_bias")
@@ -73,11 +81,10 @@ class SubMapper(ONNXToMindSporeMapper):
             args["bias_value"] = tensor.tolist()
             init_tensor = f"self.{{{variable_slot}}}_bias = {{bias_value}}"
 
-        construct_template = f"opt_{{{variable_slot}}} = self.{{{variable_slot}}}" \
-                             f"({', '.join(inputs_in_construct)})"
+        construct_template = f"opt_{{{variable_slot}}} = {' - '.join(inputs_in_construct)}"
         template = {
             variable_slot: {
-                TemplateKeywords.INIT.value: [init_template, init_tensor],
+                TemplateKeywords.INIT.value: [init_tensor],
                 TemplateKeywords.CONSTRUCT.value: [construct_template]
             }
         }