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README.md README.md +1 -1

x2paddle/convert.py x2paddle/convert.py +48 -17

x2paddle/utils.py x2paddle/utils.py +3 -6

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--- a/README.md
+++ b/README.md
@@ -121,7 +121,7 @@ x2paddle --framework=caffe --prototxt=deploy.prototxt --weight=deploy.caffemodel
 | --to_lite            | **[可选]** 是否使用opt工具转成Paddle-Lite支持格式，默认为False |
 | --lite_valid_places  | **[可选]** 指定转换类型，可以同时指定多个backend(以逗号分隔)，opt将会自动选择最佳方式，默认为arm |
 | --lite_model_type    | **[可选]** 指定模型转化类型，目前支持两种类型：protobuf和naive_buffer，默认为naive_buffer |
-| --disable_feedback   | **[可选]** 是否关闭用户信息反馈，包括转换框架信息、是否转换成功以及用户ip等，默认为False |
+| --disable_feedback   | **[可选]** 是否关闭X2Paddle使用反馈；X2Paddle默认会统计用户在进行模型转换时的成功率，以及转换框架来源等信息，以便于帮忙X2Paddle根据用户需求进行迭代，不会上传用户的模型文件。如若不想参与反馈，可指定此参数为False即可 |

 #### X2Paddle API
 目前X2Paddle提供API方式转换模型，可参考[X2PaddleAPI](docs/inference_model_convertor/x2paddle_api.md)

--- a/x2paddle/convert.py
+++ b/x2paddle/convert.py
@@ -18,6 +18,7 @@ from x2paddle.utils import ConverterCheck
 import argparse
 import sys
 import logging
+import time


 def arg_parser():
@@ -98,7 +99,7 @@ def arg_parser():
        "--disable_feedback",
        "-df",
        default=False,
-        help="Turn off user info feedback")
+        help="Tune off feedback of model conversion.")
    parser.add_argument(
        "--to_lite", "-tl", default=False, help="convert to Paddle-Lite format")
    parser.add_argument(
@@ -138,8 +139,12 @@ def tf2paddle(model_path,
              lite_valid_places="arm",
              lite_model_type="naive_buffer",
              disable_feedback=False):
+    # for convert_id
+    time_info = int(time.time())
    if not disable_feedback:
-        ConverterCheck(task="TensorFlow", convert_state="Start").start()
+        ConverterCheck(
+            task="TensorFlow", time_info=time_info,
+            convert_state="Start").start()
    # check tensorflow installation and version
    try:
        import os
@@ -172,15 +177,21 @@ def tf2paddle(model_path,
    mapper.paddle_graph.gen_model(save_dir)
    logging.info("Successfully exported Paddle static graph model!")
    if not disable_feedback:
-        ConverterCheck(task="TensorFlow", convert_state="Success").start()
+        ConverterCheck(
+            task="TensorFlow", time_info=time_info,
+            convert_state="Success").start()
    if convert_to_lite:
        logging.info("Now translating model from Paddle to Paddle Lite ...")
        if not disable_feedback:
-            ConverterCheck(task="TensorFlow", lite_state="Start").start()
+            ConverterCheck(
+                task="TensorFlow", time_info=time_info,
+                lite_state="Start").start()
        convert2lite(save_dir, lite_valid_places, lite_model_type)
        logging.info("Successfully exported Paddle Lite support model!")
        if not disable_feedback:
-            ConverterCheck(task="TensorFlow", lite_state="Success").start()
+            ConverterCheck(
+                task="TensorFlow", time_info=time_info,
+                lite_state="Success").start()


 def caffe2paddle(proto_file,
@@ -191,8 +202,11 @@ def caffe2paddle(proto_file,
                 lite_valid_places="arm",
                 lite_model_type="naive_buffer",
                 disable_feedback=False):
+    # for convert_id
+    time_info = int(time.time())
    if not disable_feedback:
-        ConverterCheck(task="Caffe", convert_state="Start").start()
+        ConverterCheck(
+            task="Caffe", time_info=time_info, convert_state="Start").start()
    from x2paddle.decoder.caffe_decoder import CaffeDecoder
    from x2paddle.op_mapper.caffe2paddle.caffe_op_mapper import CaffeOpMapper
    import google.protobuf as gpb
@@ -214,15 +228,18 @@ def caffe2paddle(proto_file,
    mapper.paddle_graph.gen_model(save_dir)
    logging.info("Successfully exported Paddle static graph model!")
    if not disable_feedback:
-        ConverterCheck(task="Caffe", convert_state="Success").start()
+        ConverterCheck(
+            task="Caffe", time_info=time_info, convert_state="Success").start()
    if convert_to_lite:
        logging.info("Now translating model from Paddle to Paddle Lite ...")
        if not disable_feedback:
-            ConverterCheck(task="Caffe", lite_state="Start").start()
+            ConverterCheck(
+                task="Caffe", time_info=time_info, lite_state="Start").start()
        convert2lite(save_dir, lite_valid_places, lite_model_type)
        logging.info("Successfully exported Paddle Lite support model!")
        if not disable_feedback:
-            ConverterCheck(task="Caffe", lite_state="Success").start()
+            ConverterCheck(
+                task="Caffe", time_info=time_info, lite_state="Success").start()


 def onnx2paddle(model_path,
@@ -231,8 +248,11 @@ def onnx2paddle(model_path,
                lite_valid_places="arm",
                lite_model_type="naive_buffer",
                disable_feedback=False):
+    # for convert_id
+    time_info = int(time.time())
    if not disable_feedback:
-        ConverterCheck(task="ONNX", convert_state="Start").start()
+        ConverterCheck(
+            task="ONNX", time_info=time_info, convert_state="Start").start()
    # check onnx installation and version
    try:
        import onnx
@@ -261,15 +281,18 @@ def onnx2paddle(model_path,
    mapper.paddle_graph.gen_model(save_dir)
    logging.info("Successfully exported Paddle static graph model!")
    if not disable_feedback:
-        ConverterCheck(task="ONNX", convert_state="Success").start()
+        ConverterCheck(
+            task="ONNX", time_info=time_info, convert_state="Success").start()
    if convert_to_lite:
        logging.info("Now translating model from Paddle to Paddle Lite ...")
        if not disable_feedback:
-            ConverterCheck(task="ONNX", lite_state="Start").start()
+            ConverterCheck(
+                task="ONNX", time_info=time_info, lite_state="Start").start()
        convert2lite(save_dir, lite_valid_places, lite_model_type)
        logging.info("Successfully exported Paddle Lite support model!")
        if not disable_feedback:
-            ConverterCheck(task="ONNX", lite_state="Success").start()
+            ConverterCheck(
+                task="ONNX", time_info=time_info, lite_state="Success").start()


 def pytorch2paddle(module,
@@ -281,8 +304,11 @@ def pytorch2paddle(module,
                   lite_valid_places="arm",
                   lite_model_type="naive_buffer",
                   disable_feedback=False):
+    # for convert_id
+    time_info = int(time.time())
    if not disable_feedback:
-        onverterCheck(task="PyTorch", convert_state="Start").start()
+        ConverterCheck(
+            task="PyTorch", time_info=time_info, convert_state="Start").start()
    # check pytorch installation and version
    try:
        import torch
@@ -324,15 +350,20 @@ def pytorch2paddle(module,
        save_dir, jit_type=jit_type, enable_code_optim=enable_code_optim)
    logging.info("Successfully exported Paddle static graph model!")
    if not disable_feedback:
-        ConverterCheck(task="PyTorch", convert_state="Success").start()
+        ConverterCheck(
+            task="PyTorch", time_info=time_info,
+            convert_state="Success").start()
    if convert_to_lite:
        logging.info("Now translating model from Paddle to Paddle Lite ...")
        if not disable_feedback:
-            ConverterCheck(task="PyTorch", lite_state="Start").start()
+            ConverterCheck(
+                task="PyTorch", time_info=time_info, lite_state="Start").start()
        convert2lite(save_dir, lite_valid_places, lite_model_type)
        logging.info("Successfully exported Paddle Lite support model!")
        if not disable_feedback:
-            ConverterCheck(task="PyTorch", lite_state="Success").start()
+            ConverterCheck(
+                task="PyTorch", time_info=time_info,
+                lite_state="Success").start()


 def main():

--- a/x2paddle/utils.py
+++ b/x2paddle/utils.py
@@ -18,7 +18,6 @@ import x2paddle
 import hashlib
 import requests
 import threading
-import time
 import uuid

 stats_api = "http://paddlepaddle.org.cn/paddlehub/stat"
@@ -53,6 +52,7 @@ class ConverterCheck(threading.Thread):

    def __init__(self,
                 task="onnx",
+                 time_info=time_info,
                 convert_state=None,
                 lite_state=None,
                 extra_info=None):
@@ -62,9 +62,7 @@ class ConverterCheck(threading.Thread):
        self._convert_state = convert_state
        self._lite_state = lite_state
        self._extra_info = extra_info
-        self._convert_id = _md5(str(uuid.uuid1())[-12:])
-        self._hash_flag = _md5(str(uuid.uuid1())[-12:]) + "-" + str(
-            int(time.time()))
+        self._convert_id = _md5(str(uuid.uuid1())[-12:]) + "-" + str(time_info)

    def run(self):
        params = {
@@ -73,7 +71,6 @@ class ConverterCheck(threading.Thread):
            'paddle_version': paddle.__version__,
            'convert_state': self._convert_state,
            'convert_id': self._convert_id,
-            'cache_info': self._hash_flag,
            'from': 'x2paddle'
        }
        if self._lite_state is not None:
@@ -82,7 +79,7 @@ class ConverterCheck(threading.Thread):
            params.update(self._extra_info)

        try:
-            requests.get(stats_api, params)
+            requests.get(stats_api, params, timeout=2)
        except Exception:
            pass