add params merge

x2paddle/convert.py

@@ -68,6 +68,11 @@ def arg_parser():
                         action="store_true",
                         default=False,
                         help="define input shape for tf model")
+    parser.add_argument("--params_merge",
+                        "-pm",
+                        action="store_true",
+                        default=False,
+                        help="define whether merge the params")
 
     return parser
 
@@ -75,7 +80,8 @@ def arg_parser():
 def tf2paddle(model_path,
               save_dir,
               without_data_format_optimization=False,
-              define_input_shape=False):
+              define_input_shape=False,
+              params_merge=False):
     # check tensorflow installation and version
     try:
         import os
@@ -104,10 +110,10 @@ def tf2paddle(model_path,
     optimizer.strip_graph()
     #        optimizer.merge_activation()
     #        optimizer.merge_bias()
-    mapper.save_inference_model(save_dir)
+    mapper.save_inference_model(save_dir, params_merge)
 
 
-def caffe2paddle(proto, weight, save_dir, caffe_proto):
+def caffe2paddle(proto, weight, save_dir, caffe_proto, params_merge=False):
     from x2paddle.decoder.caffe_decoder import CaffeDecoder
     from x2paddle.op_mapper.caffe_op_mapper import CaffeOpMapper
     from x2paddle.optimizer.caffe_optimizer import CaffeOptimizer
@@ -124,10 +130,10 @@ def caffe2paddle(proto, weight, save_dir, caffe_proto):
     optimizer = CaffeOptimizer(mapper)
     optimizer.merge_bn_scale()
     optimizer.merge_op_activation()
-    mapper.save_inference_model(save_dir)
+    mapper.save_inference_model(save_dir, params_merge)
 
 
-def onnx2paddle(model_path, save_dir):
+def onnx2paddle(model_path, save_dir, params_merge=False):
     # check onnx installation and version
     try:
         import onnx
@@ -150,7 +156,7 @@ def onnx2paddle(model_path, save_dir):
     optimizer = ONNXOptimizer(mapper)
 
     optimizer.delete_redundance_code()
-    mapper.save_inference_model(save_dir)
+    mapper.save_inference_model(save_dir, params_merge)
 
 
 def main():
@@ -193,20 +199,29 @@ def main():
         assert args.model is not None, "--model should be defined while translating tensorflow model"
         without_data_format_optimization = False
         define_input_shape = False
+        params_merge = False
         if args.without_data_format_optimization:
             without_data_format_optimization = True
         if args.define_input_shape:
             define_input_shape = True
+        if args.params_merge:
+            params_merge = True
         tf2paddle(args.model, args.save_dir, without_data_format_optimization,
-                  define_input_shape)
+                  define_input_shape, params_merge)
 
     elif args.framework == "caffe":
         assert args.prototxt is not None and args.weight is not None, "--prototxt and --weight should be defined while translating caffe model"
+        params_merge = False
+        if args.params_merge:
+            params_merge = True
         caffe2paddle(args.prototxt, args.weight, args.save_dir,
-                     args.caffe_proto)
+                     args.caffe_proto, params_merge)
     elif args.framework == "onnx":
         assert args.model is not None, "--model should be defined while translating onnx model"
-        onnx2paddle(args.model, args.save_dir)
+        params_merge = False
+        if args.params_merge:
+            params_merge = True
+        onnx2paddle(args.model, args.save_dir, params_merge)
     else:
         raise Exception("--framework only support tensorflow/caffe/onnx now")
 

x2paddle/core/op_mapper.py

@@ -110,7 +110,7 @@ class OpMapper(object):
         self.add_codes("import paddle.fluid as fluid")
         self.add_codes("")
 
-    def save_inference_model(self, save_dir):
+    def save_inference_model(self, save_dir, params_merge):
         self.save_python_model(save_dir)
 
         import sys
@@ -138,7 +138,14 @@ class OpMapper(object):
                                py_code_dir,
                                fluid.default_main_program(),
                                predicate=if_exist)
-
+            if params_merge:
+                fluid.io.save_inference_model(dirname=os.path.join(
+                    save_dir, "inference_model"),
+                                              feeded_var_names=input_names,
+                                              target_vars=outputs,
+                                              executor=exe,
+                                              params_filename="__params__")
+            else:
                 fluid.io.save_inference_model(dirname=os.path.join(
                     save_dir, "inference_model"),
                                               feeded_var_names=input_names,