serving

问题 the tensorflow serving build denpend on large tensorflow; but i already build tensorflow successfully. so i want to use it. I do these things: I change the tensorflow serving WORKSPACE(org: https://github.com/tensorflow/serving/blob/master/WORKSPACE) workspace(name = "tf_serving") # To update TensorFlow to a new revision. # 1. Update the 'git_commit' args below to include the new git hash. # 2. Get the sha256 hash of the archive with a command such as... # curl -L https://github.com

来源： https://stackoverflow.com/questions/28703642/will-i-be-able-to-use-curl-to-get-http-2-headers

问题 I'm currently working on serving a static html page in Dropwizard at the root path "/". So far, I've only received an error page stating "HTTP ERROR 404 Problem accessing /. Reason: Not Found". I've followed the Dropwizard documentation for 1.2.2 in doing this, as well as this tutorial here, with some changes to the code for my services to work. My root path in my .yml file is /profile/v1 to allow my getAll services to work (when I first started, I was getting an error for having Multiple

问题 Right now we are successfully able to serve models using Tensorflow Serving. We have used following method to export the model and host it with Tensorflow Serving. ------------ For exporting ------------------ from tensorflow.contrib.session_bundle import exporter K.set_learning_phase(0) export_path = ... # where to save the exported graph export_version = ... # version number (integer) saver = tf.train.Saver(sharded=True) model_exporter = exporter.Exporter(saver) signature = exporter

问题 I want to serve videos (flv) in my web application, video files are user generated content, and it is increasing enormously. I would like to serve back the content but without any abuse, for example I dont want some script crawling and downloading all flvs that I got. What methods could I use to prevent this sort of abuse? What should I read to gain knowledge on that matter? Any pointer will be really appreciated Thanks, 来源： https://stackoverflow.com/questions/5140677/secure-way-of-serving

问题 I need your help I'm a little bit stuck right now. I retrain a classification tensorflow model that gives quite nice results. Now I want to serve it through tensorflow serving. I managed to serve it but when i'm using it, it always gives me same results no matter what the input is. I think there is something wrong the way I export the model but I can't figure what. Below is my code. Can somebody help me ? Thanks a lot guys This is the function that transform my input image into a readable

问题 I am want to take advantage of the web optimization for pdfs by allowing users to download them a page at a time. The pdfs are configured for fast web view. I am serving the pdfs from sql server 2008. The c# .net 3.5 web app untilises linq to SQL to load the files into a binary array from the database. The file is opended in PDF reader plugin on the client in IE. Any help or a shove in the right direction would be greatly appreciated. Thanks 回答1: If you simply want to send a PDF to the client

问题 I'm following the official documentation in order to serve static files but I'm recieving error 404 in the development console. I'm using 'django.contrib.staticfiles', so static files should be automatically served. This is my setup: Settings: STATIC_ROOT = '' STATIC_URL = '/static/' Template header: {% load staticfiles %} <link rel="stylesheet" href="{% static "css/app.css" %}"> Directory tree: django_project \apps \static \css app.css \templates index.html I can see in firefox console that

问题 I know there is no such thing as a dumb question but this is: Can you serve contextual based ads via adsense or others on a site that is entirely behind https? 回答1: Yes, as long as the website is not protected by SSL certificates (in that the client accessing the website needs to have a certificate) Google is perfectly capable of indexing your site for keywords to cater the right ads for your website. I am not sure if Google makes the adsense code available over SSL as well, if not your

问题 In app engine I can serve cloudstorage files like a pdf using the default bucket of my application: http://storage.googleapis.com/<appid>.appspot.com/<file_name> But how can I serve local cloudstorage files in the SDK, without making use of a blob_key? I write to the default bucket like this: gcs_file_name = '/%s/%s' % (app_identity.get_default_gcs_bucket_name(), file_name) with gcs.open(gcs_file_name, 'w') as f: f.write(data) The name of the default bucket in the SDK = 'app_default_bucket'