support converting models to 2.0 compatibility

README.md

@@ -97,6 +97,11 @@ When the version of DeePMD-kit used to training model is different from the that
 
 DeePMD-kit guarantees that the codes with the same major and minor revisions are compatible. That is to say v0.12.5 is compatible to v0.12.0, but is not compatible to v0.11.0 nor v1.0.0. 
 
+One can convert the model trained with DeePMD-kit v1.3 to v2 compatible by using the command 
+```shell
+dp convert-to 2.0 -i frozen_model.pb  -o frozen_model_2.0.pb
+```
+
 ## Installation: inadequate versions of gcc/g++
 Sometimes you may use a gcc/g++ of version <4.9. If you have a gcc/g++ of version > 4.9, say, 7.2.0, you may choose to use it by doing 
 ```bash

source/train/CMakeLists.txt

@@ -2,7 +2,7 @@
 
 configure_file("RunOptions.py.in" "${CMAKE_CURRENT_BINARY_DIR}/RunOptions.py" @ONLY)
 
-file(GLOB LIB_PY main.py common.py env.py compat.py calculator.py Network.py Deep*.py Data.py DataSystem.py Model*.py Descrpt*.py Fitting.py Loss.py LearningRate.py Trainer.py TabInter.py EwaldRecp.py DataModifier.py ${CMAKE_CURRENT_BINARY_DIR}/RunOptions.py transform.py argcheck.py doc.py)
+file(GLOB LIB_PY main.py common.py env.py compat.py calculator.py Network.py Deep*.py Data.py DataSystem.py Model*.py Descrpt*.py Fitting.py Loss.py LearningRate.py Trainer.py TabInter.py EwaldRecp.py DataModifier.py ${CMAKE_CURRENT_BINARY_DIR}/RunOptions.py transform.py argcheck.py doc.py convert_to.py)
 
 file(GLOB CLS_PY  Local.py Slurm.py)
 

source/train/convert_to.py

@@ -0,0 +1,61 @@
+import os
+from deepmd.env import tf
+from google.protobuf import text_format
+from tensorflow.python.platform import gfile
+from tensorflow.python import pywrap_tensorflow
+from tensorflow.python.framework import graph_util
+
+def convert_13_to_20(args):
+    convert_pb_to_pbtxt(args.input_model, 'frozen_model.pbtxt')
+    convert_dp13_to_dp20('frozen_model.pbtxt')
+    convert_pbtxt_to_pb('frozen_model.pbtxt', args.output_model)
+    if os.path.isfile('frozen_model.pbtxt'):
+        os.remove('frozen_model.pbtxt')
+    print("the converted output model(2.0 support) is saved in %s" % args.output_model)
+
+def convert_pb_to_pbtxt(pbfile, pbtxtfile):
+    with gfile.FastGFile(pbfile, 'rb') as f:
+        graph_def = tf.GraphDef()
+        graph_def.ParseFromString(f.read())
+        tf.import_graph_def(graph_def, name='')
+        tf.train.write_graph(graph_def, './', pbtxtfile, as_text=True)
+
+def convert_pbtxt_to_pb(pbtxtfile, pbfile):
+    with tf.gfile.FastGFile(pbtxtfile, 'r') as f:
+        graph_def = tf.GraphDef()
+        file_content = f.read()
+        # Merges the human-readable string in `file_content` into `graph_def`.
+        text_format.Merge(file_content, graph_def)
+        tf.train.write_graph(graph_def, './', pbfile, as_text=False)
+
+def convert_dp13_to_dp20(fname):
+    with open(fname) as fp:
+        file_content = fp.read()
+    file_content += """
+node {
+  name: "model_attr/model_version"
+  op: "Const"
+  attr {
+    key: "dtype"
+    value {
+      type: DT_STRING
+    }
+  }
+  attr {
+    key: "value"
+    value {
+      tensor {
+        dtype: DT_STRING
+        tensor_shape {
+        }
+        string_val: "1.0"
+      }
+    }
+  }
+}
+"""
+    file_content = file_content\
+                   .replace('DescrptSeA', 'ProdEnvMatA')\
+                   .replace('DescrptSeR', 'ProdEnvMatR')
+    with open(fname, 'w') as fp:
+        fp.write(file_content)

source/train/main.py

@@ -6,6 +6,7 @@
 from .test import test
 from .transform import transform
 from .doc import doc_train_input
+from .convert_to import convert_13_to_20
 
 def main () :    
     parser = argparse.ArgumentParser(
@@ -61,6 +62,15 @@ def main () :
     parser_tst.add_argument("-d", "--detail-file", type=str, 
                             help="The file containing details of energy force and virial accuracy")
 
+    parser_transform = subparsers.add_parser('convert-to', help='convert dp-1.3 model to higher model compatibility')
+    parser_transform.add_argument('TO', type = str,
+                                  choices = ['2.0'],
+                                  help="The target model compatibility")
+    parser_transform.add_argument('-i', "--input-model", default = "frozen_model.pb", type=str, 
+				  help = "the input dp-1.3 model")
+    parser_transform.add_argument("-o","--output-model", default = "convert_out.pb", type=str, 
+				  help='the output model')
+
     parser_train = subparsers.add_parser('doc-train-input', 
                                          help='print the documentation (in rst format) of input training parameters.')
 
@@ -79,6 +89,11 @@ def main () :
         test(args)
     elif args.command == 'transform' :
         transform(args)
+    elif args.command == 'convert-to' :
+        if args.TO == '2.0':
+            convert_13_to_20(args)
+        else:
+            raise RuntimeError('unsupported model compatibility ' + args.TO)
     elif args.command == 'doc-train-input' :
         doc_train_input(args)
     else :