ageron / ageron/handson-ml2

Chapter 19 : Training and Deploying TF Models at scale

Abierto
#205 1 comentario 0 reacciones 0 asignados Ver en GitHub
Lenguaje dominante
Jupyter Notebook
Estrellas
30k
Forks
13.1k
Métricas de merge de PR
Sin PR fusionados en 30 d

Descripción

Hello, I successfully reproduced the process described in "Using the Prediction Service" p682-683 of the book with the toy model "my_mnist_model' (turns the trained model into a serverless cloud model). However, when it failed when I tried with a more evolved model (a Mask-RCNN running on 1600*1900 images), because the json format is not adapted to images ("Rest Json call not working : Request payload size exceeds the limit: 1572864 bytes.")

I'm trying to switch to gRPC, but it seems that the Google API doesn't provide an easy way to do this. If I'm wrong, could you please provide a code for the "predict(X)" function on page 684(* or in section Deploy the model to Google Cloud AI Platform of the Chapter 19 Notebook in github) that uses gRPC instead of Json to transfer the input data ?

If you have any other way to feed large images to a serverless model, I'm all ears.
Thanks for your help .

Guía de contribución

No hay ninguna guía de contribución indexada para este repositorio

Evaluación

Este issue todavía no se ha evaluado.

Recibe los nuevos issues en tu correo

Un resumen breve de issues de GitHub para principiantes.