[Backend] integrate x2paddle tool (#1148)

* integrate x2paddle tool

* fix caffe convertion bug

* add post support

* fix tar file path

* add download api

* add tips for users

Author: rainyfly

requirements.txt

@@ -10,3 +10,5 @@ matplotlib
 pandas
 multiprocess
 packaging
+x2paddle
+rarfile

visualdl/component/inference/__init__.py

@@ -0,0 +1,14 @@
+# Copyright (c) 2022 VisualDL Authors. All Rights Reserve.
+#
+# 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.
+# =======================================================================

visualdl/component/inference/model_convert_server.py

@@ -0,0 +1,136 @@
+# Copyright (c) 2022 VisualDL Authors. All Rights Reserve.
+#
+# 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.
+# =======================================================================
+import base64
+import json
+import os
+import tempfile
+from collections import deque
+from threading import Lock
+
+from flask import request
+from x2paddle.convert import caffe2paddle
+from x2paddle.convert import onnx2paddle
+
+from .xarfile import archive
+from .xarfile import unarchive
+from visualdl.server.api import gen_result
+from visualdl.server.api import result
+
+
+class ModelConvertApi(object):
+    def __init__(self):
+        self.supported_formats = {'onnx', 'caffe'}
+        self.lock = Lock()
+        self.translated_models = deque(
+            maxlen=5)  # used to store user's translated model for download
+        self.request_id = 0  # used to store user's request
+
+    @result()
+    def convert_model(self, format):
+        file_handle = request.files['file']
+        data = file_handle.stream.read()
+        if format not in self.supported_formats:
+            raise RuntimeError('Model format {} is not supported. \
+          Only onnx and caffe models are supported now.'.format(format))
+        result = {}
+        result['from'] = format
+        result['to'] = 'paddle'
+        # call x2paddle to convert models
+        with tempfile.TemporaryDirectory(
+                suffix='x2paddle_translated_models') as tmpdirname:
+            with tempfile.NamedTemporaryFile() as fp:
+                fp.write(data)
+                fp.flush()
+                try:
+                    if format == 'onnx':
+                        try:
+                            import onnx  # noqa: F401
+                        except Exception:
+                            raise RuntimeError(
+                                "[ERROR] onnx is not installed, use \"pip install onnx==1.6.0\"."
+                            )
+                        onnx2paddle(fp.name, tmpdirname)
+                    elif format == 'caffe':
+                        with tempfile.TemporaryDirectory() as unarchivedir:
+                            unarchive(fp.name, unarchivedir)
+                            prototxt_path = None
+                            weight_path = None
+                            for dirname, subdirs, filenames in os.walk(
+                                    unarchivedir):
+                                for filename in filenames:
+                                    if '.prototxt' in filename:
+                                        prototxt_path = os.path.join(
+                                            dirname, filename)
+                                    if '.caffemodel' in filename:
+                                        weight_path = os.path.join(
+                                            dirname, filename)
+                            if prototxt_path is None or weight_path is None:
+                                raise RuntimeError(
+                                    ".prototxt or .caffemodel file is missing in your archive file, \
+                    please check files uploaded.")
+                            caffe2paddle(prototxt_path, weight_path,
+                                         tmpdirname, None)
+                except Exception as e:
+                    raise RuntimeError(
+                        "[Convertion error] {}.\n Please open an issue at \
+                            https://github.com/PaddlePaddle/X2Paddle/issues to report your problem."
+                        .format(e))
+                with self.lock:
+                    origin_dir = os.getcwd()
+                    os.chdir(os.path.dirname(tmpdirname))
+                    archive_path = os.path.join(
+                        os.path.dirname(tmpdirname),
+                        archive(os.path.basename(tmpdirname)))
+                    os.chdir(origin_dir)
+                    result['request_id'] = self.request_id
+                    self.request_id += 1
+            with open(archive_path, 'rb') as archive_fp:
+                self.translated_models.append((result['request_id'],
+                                               archive_fp.read()))
+            with open(
+                    os.path.join(tmpdirname, 'inference_model',
+                                 'model.pdmodel'), 'rb') as model_fp:
+                model_encoded = base64.b64encode(
+                    model_fp.read()).decode('utf-8')
+            result['pdmodel'] = model_encoded
+            if os.path.exists(archive_path):
+                os.remove(archive_path)
+
+        return result
+
+    @result('application/octet-stream')
+    def download_model(self, request_id):
+        for stored_request_id, data in self.translated_models:
+            if str(stored_request_id) == request_id:
+                return data
+
+
+def create_model_convert_api_call():
+    api = ModelConvertApi()
+    routes = {
+        'convert': (api.convert_model, ['format']),
+        'download': (api.download_model, ['request_id'])
+    }
+
+    def call(path: str, args):
+        route = routes.get(path)
+        if not route:
+            return json.dumps(gen_result(
+                status=1, msg='api not found')), 'application/json', None
+        method, call_arg_names = route
+        call_args = [args.get(name) for name in call_arg_names]
+        return method(*call_args)
+
+    return call