Question

在我问为什么GAE无法在此找到TensorFlow库之前https://stackoverflow.com/questions/40241846/why-googleappengine-gives-me-importerror-no-module-named-tensorflow

Dmytro Sadovnychyi告诉我，GAE无法运行TensorFlow，但GAE可以灵活运行。

所以我在USA区创建了我的项目并尝试部署我的简单项目：

import webapp2
import tensorflow as tf

class MainHandler(webapp2.RequestHandler):
    def get(self):
        hello = tf.constant('Hello, TensorFlow!')
        sess = tf.Session()
        self.response.write(sess.run(hello))
        a = tf.constant(10)
        b = tf.constant(32)
        self.response.write(sess.run(a + b))
        #self.response.write('asd');


app = webapp2.WSGIApplication([
    ('/', MainHandler)
], debug=True)

在yaml中有vm: true。

这是yaml：

application: tstmchnlrn
version: 1
runtime: python27
vm: true
api_version: 1
threadsafe: yes

handlers:
- url: /favicon\.ico
  static_files: favicon.ico
  upload: favicon\.ico

- url: .*
  script: main.app

libraries:
- name: webapp2
  version: "2.5.2"

部署成功，但在appspot访问我的应用时收到服务器内部错误，而控制台仍向我显示ImportError: No module named tensorflow。

我需要做些什么才能使基于TensorFlow的应用在flexible enviroment中运行？

Answer 1

这听起来好像没有被推送到实例。

创建一个requirements.txt文件和list your dependencies，包括那里的Tensor Flow。

Answer 2

为了帮助其他人，我正在使用 Python 3 发布我的hello world tensor流量代码for google app engine灵活环境（我知道原始问题被要求用于python 2.7）。另请注意，webapp2尚未与python 3兼容，因此我使用的是Flask。

完整的代码是

<强> requirements.txt

Flask==0.12.2
gunicorn==19.7.1
tensorflow==1.3.0

<强>的app.yaml

runtime: python
threadsafe: yes
env: flex
entrypoint: gunicorn -b :$PORT main:app

runtime_config:
  python_version: 3

<强> main.py

# Copyright 2015 Google Inc. 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.

# [START app]
import logging
import platform
import tensorflow as tf

from flask import Flask


app = Flask(__name__)


@app.route('/')
def hello():
    """Return a friendly HTTP greeting."""
    # Simple hello world using TensorFlow

    # Create a Constant op
    # The op is added as a node to the default graph.
    #
    # The value returned by the constructor represents the output
    # of the Constant op.
    hello = tf.constant('Hello, TensorFlow!')

    # Start tf session
    sess = tf.Session()

    return sess.run(hello).decode()+' Python '+ platform.python_version()


@app.errorhandler(500)
def server_error(e):
    logging.exception('An error occurred during a request.')
    return """
    An internal error occurred: <pre>{}</pre>
    See logs for full stacktrace.
    """.format(e), 500


if __name__ == '__main__':
    # This is used when running locally. Gunicorn is used to run the
    # application on Google App Engine. See entrypoint in app.yaml.
    app.run(host='127.0.0.1', port=8080, debug=True)
# [END app]

此相同的代码也发布在github here

上

如何在Google App Engine Flexible Enviroment中运行TensorFlow？

2 个答案: