add weights

python/tools/mdl2fluid/mdl2fluid.py

@@ -14,6 +14,7 @@ class Converter:
 
     def __init__(self, mdl_json_path):
         self.mdl_json_path = mdl_json_path
+        print mdl_json_path
         self.mdl_json = load_mdl(self.mdl_json_path)
         self.program_desc = framework_pb2.ProgramDesc()
 
@@ -38,39 +39,57 @@ class Converter:
 
             layers_ = self.mdl_json['layer']
             for layer in layers_:
-                desc_ops = block_desc.ops.add()
+                desc_ops_add = block_desc.ops.add()
 
                 # print layer
                 # for i in layer:
                 #     print i
                 if 'name' in layer:
                     l_name = layer['name']
-
+                if 'type' in layer:
+                    l_type = layer['type']
+                    # print l_type
+                    # print mdl2fluid_op_layer_dict.get(l_type)
+                    desc_ops_add.type = types.mdl2fluid_op_layer_dict.get(l_type)
                 if 'weight' in layer:
                     l_weights = layer['weight']
 
+                    op_tup = types.op_io_dict.get(desc_ops_add.type).get(types.mdl_weight_key)
+                    # print len(op_tup)
+
+                    for i, val in enumerate(op_tup):
+                        print i
+                        print val
+                        inputs_add = desc_ops_add.inputs.add()
+                        # print w
+                        inputs_add.parameter = op_tup[i]
+                        inputs_add.arguments.append(l_weights[i])
+
+                    # for w in l_weights:
+                    #     inputs_add = desc_ops_add.inputs.add()
+                    #     # print w
+                    #     inputs_add.parameter = op_tup[0]
+                    #     inputs_add.arguments.append(w)
                 if 'param' in layer:
                     l_params = layer['param']
 
                 if 'output' in layer:
                     l_outputs = layer['output']
+                    for o in l_outputs:
+                        # print o
+                        outputs_add = desc_ops_add.outputs.add()
+                        outputs_add.parameter = types.op_io_dict.get(desc_ops_add.type).get(types.mdl_outputs_key)
+                        outputs_add.arguments.append(o)
 
                 if 'input' in layer:
                     l_inputs = layer['input']
-                    inputs_add = desc_ops.inputs.add()
                     for i in l_inputs:
+                        inputs_add = desc_ops_add.inputs.add()
                         # print i
-                        inputs_add.parameter = ''
+                        inputs_add.parameter = types.op_io_dict.get(desc_ops_add.type).get(types.mdl_inputs_key)
                         inputs_add.arguments.append(i)
 
-                if 'type' in layer:
-                    l_type = layer['type']
-                    # print l_type
-                    # print mdl2fluid_op_layer_dict.get(l_type)
-                    desc_ops.type = types.mdl2fluid_op_layer_dict.get(l_type)
 
-
-mdl_path = "multiobjects/YOLO_Universal.json"
 # print mdl_path
 # # model
 # mdl_model = load_mdl(mdl_path)
@@ -107,6 +126,6 @@ mdl_path = "multiobjects/YOLO_Universal.json"
 #
 # package()
 
-
+mdl_path = "/Users/xiebaiyuan/PaddleProject/paddle-mobile/python/tools/mdl2fluid/multiobjects/YOLO_Universal.json"
 converter = Converter(mdl_path)
 converter.convert()

python/tools/mdl2fluid/op_types.py

@@ -5,12 +5,25 @@ mdl2fluid_op_layer_dict = {
     'PointwiseConvolutionLayer': 'fusion_conv_add'
 }
 
+mdl_outputs_key = "outputs"
+mdl_inputs_key = "inputs"
+mdl_weight_key = "weights"
+# inputs_key = "inputs"
+
 fusion_conv_add_dict = {
-    'inputs': 'Input',
-    'outputs': 'Out'
+    mdl_inputs_key: 'Input',
+    mdl_outputs_key: 'Out',
+    mdl_weight_key: ('Filter', 'Y')
 }
 
 relu_dict = {
-    'inputs': 'X',
-    'outputs': 'Out'
+    mdl_inputs_key: 'X',
+    mdl_outputs_key: 'Out',
+    mdl_weight_key: ()
+
+}
+op_io_dict = {
+    'fusion_conv_add': fusion_conv_add_dict,
+    'relu': relu_dict
+
 }