add module creator func

paddle_hub/__init__.py

@@ -8,3 +8,5 @@ from paddle_hub.module import Module
 from paddle_hub.module import ModuleConfig
 from paddle_hub.module import ModuleUtils
 from paddle_hub.downloader import download_and_uncompress
+from paddle_hub.signature import create_signature
+from paddle_hub.module_creator import create_module

paddle_hub/module_creator.py

+#   Copyright (c) 2019  PaddlePaddle Authors. All Rights Reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License"
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+from __future__ import absolute_import
+from __future__ import division
+from __future__ import print_function
+
+import paddle_hub.module_desc_pb2 as modulepb
+import paddle.fluid as fluid
+from paddle_hub.utils import to_list
+from paddle_hub.signature import Signature
+
+import os
+
+
+def create_module(sign_arr, program, path=None, assets=None):
+    assert isinstance(
+        program, fluid.Program), "program should be instance of fluid.Program"
+    assert sign_arr, "signarture array should not be None"
+
+    if not path:
+        path = "."
+
+    path = os.path.join(path, "hub_module")
+    assert not os.path.exists(path), "path %s should not be existed" % path
+
+    module = modulepb.ModuleDesc()
+    program = program.clone()
+
+    os.makedirs(path)
+    # TODO(wuzewu): save assets data
+    if not assets:
+        module.contain_assets = False
+    else:
+        module.contain_assets = True
+        os.makedirs(os.path.join(path, "assets"))
+
+    # save fluid Parameter
+    for param in program.global_block().iter_parameters():
+        parameter = module.parameters.add()
+        parameter.name = param.name
+        parameter.learning_rate = param.optimize_attr["learning_rate"]
+        parameter.trainable = param.trainable
+
+    # save signarture info
+    sign_map = module.sign2var
+    sign_arr = to_list(sign_arr)
+    for sign in sign_arr:
+        assert isinstance(sign,
+                          Signature), "sign_arr should be list of Signature"
+
+        if sign.get_name() in sign_map:
+            raise "Error! sign_arr contains repeat signatrue %s" % sign
+
+        var = sign_map[sign.get_name()]
+        feed_desc = var.feed_desc
+        fetch_desc = var.fetch_desc
+        for input in sign.get_inputs():
+            feed_var = feed_desc.add()
+            feed_var.var_name = input.name
+
+        for output in sign.get_outputs():
+            fetch_var = fetch_desc.add()
+            fetch_var.var_name = output.name
+
+    # save inference program
+    exe = fluid.Executor(place=fluid.CPUPlace())
+    model_path = os.path.join(path, "model")
+    os.makedirs(model_path)
+    first_sign = sign_arr[0]
+    fluid.io.save_inference_model(
+        model_path,
+        feeded_var_names=[var.name for var in first_sign.get_inputs()],
+        target_vars=first_sign.get_outputs(),
+        executor=exe)
+
+    # save to dist
+    data = module.SerializeToString()
+    metafile = os.path.join(path, "meta.pb")
+    with open(metafile, "wb") as f:
+        f.write(data)