google-cloud-ml

Converting google-cloud-ml github Reddit example from regression to classification and adding keys?

由 大城市里の小女人 提交于 2020-01-01 05:36:11
问题 I've been trying to adapt the reddit_tft example from the cloud-ml github samples repo to my needs. I've been able to get it running as per the tutorial readme. However what i want to use it for is a binary classification problem and also output keys in batch prediction. So i have made copy of the tutorial code here and have changed it in a few places to be able to have a model type of deep_classifier that would use a DNNClasifier instead of a DNNRegressor . I've changed the score variable to

How to setup pytorch in google-cloud-ml

由 人走茶凉 提交于 2019-12-31 04:48:11
问题 I try to throw job with Pytorch code in google-cloud-ml. so I code the "setup.py" file. And add option "install_requires" "setup.py" from setuptools import find_packages from setuptools import setup REQUIRED_PACKAGES = ['http://download.pytorch.org/whl/cpu/torch-0.3.0.post4-cp27-cp27mu-linux_x86_64.whl','torchvision'] setup( name='trainer', version='0.1', install_requires=REQUIRED_PACKAGES, packages=find_packages(), include_package_data=True, description='My keras trainer application package.

Google Cloud ML FAILED_PRECONDITION

由 随声附和 提交于 2019-12-30 22:56:39
问题 I am trying to use Google Cloud ML to host a Tensorflow model and get predictions. I have a pretrained model that I have uploaded to the cloud and I have created a model and version in my Cloud ML console. I followed the instructions from here to prepare my data for requesting online predictions. For both the Python method and the glcoud method I get the same error. For simplicity, I'll post the gcloud method: I run gcloud ml-engine predict --model spell_correction --json-instances test.json

Google Cloud ML FAILED_PRECONDITION

由 狂风中的少年 提交于 2019-12-30 22:56:03
问题 I am trying to use Google Cloud ML to host a Tensorflow model and get predictions. I have a pretrained model that I have uploaded to the cloud and I have created a model and version in my Cloud ML console. I followed the instructions from here to prepare my data for requesting online predictions. For both the Python method and the glcoud method I get the same error. For simplicity, I'll post the gcloud method: I run gcloud ml-engine predict --model spell_correction --json-instances test.json

Google Cloud ML Engine - Job failed due to an internal error . Can't execute a job

由 白昼怎懂夜的黑 提交于 2019-12-30 11:39:09
问题 This is a ml-job I previously trained successfully . But when I tried it today it's not working . So after that I tried removing all the things is the bucket and start over . Still it's not working . Giving the following error . Internal error occurred. Please retry in a few minutes. If you still experience errors, contact Cloud ML. 来源： https://stackoverflow.com/questions/45609164/google-cloud-ml-engine-job-failed-due-to-an-internal-error-cant-execute-a-j

reading files in google cloud machine learning

由 被刻印的时光 ゝ 提交于 2019-12-29 05:35:11
问题 I tried to run tensorflow-wavenet on the google cloud ml-engine with gcloud ml-engine jobs submit training but the cloud job crashed when it was trying to read the json configuration file: with open(args.wavenet_params, 'r') as f: wavenet_params = json.load(f) arg.wavenet_params is simply a file path to a json file which I uploaded to the google cloud storage bucket. The file path looks like this: gs://BUCKET_NAME/FILE_PATH.json . I double-checked that the file path is correct and I'm sure

reading files in google cloud machine learning

由 ∥☆過路亽．° 提交于 2019-12-29 05:34:06
问题 I tried to run tensorflow-wavenet on the google cloud ml-engine with gcloud ml-engine jobs submit training but the cloud job crashed when it was trying to read the json configuration file: with open(args.wavenet_params, 'r') as f: wavenet_params = json.load(f) arg.wavenet_params is simply a file path to a json file which I uploaded to the google cloud storage bucket. The file path looks like this: gs://BUCKET_NAME/FILE_PATH.json . I double-checked that the file path is correct and I'm sure

cloud machine learning predict

由 大憨熊 提交于 2019-12-25 16:47:17
问题 When I use prediction command of Google Cloud Machine Learning (https://cloud.google.com/ml/docs/quickstarts/prediction), I frequently get an error below: $ gcloud beta ml predict --model=mnist --instances=data/predict_sample.tensor.json ERROR: (gcloud.beta.ml.predict) HTTP request failed. Response: <!DOCTYPE html> <html lang=en> <meta charset=utf-8> <meta name=viewport content="initial-scale=1, minimum-scale=1, width=device-width"> <title>Error 502 (Server Error)!!1</title> <style> *{margin

“(403) Forbidden” when trying to send an image to my custom AutoML model via the REST API

由 本小妞迷上赌 提交于 2019-12-25 03:24:50
问题 I am having issues with implementing a custom AutoML model in a .NET web app that allows sending images via the REST API to be recognized. I keep getting errors. The remote server returned an error: (403) Forbidden. I have an image and converted it into a string of bytes called imageBytesString and have created the jsonRequest object like this: string jsonRequest = "{\"payload\":{\"image\":{\"imageBytes\":\"" + imageBytesString + "\"},}}";` Then I'm doing a POST request like follows:

Keras on Google ML Engine error: You must feed a value for placeholder tensor

由 故事扮演 提交于 2019-12-25 02:29:14
问题 I have deployed a model on Google Cloud ML Engine, but when I try to perform a prediction (I'm using curl), this is the result I obtain: {"error": "Prediction failed: Error during model execution: AbortionError(code=StatusCode.INVALID_ARGUMENT, details=\"You must feed a value for placeholder tensor 'lstm_1/keras_learning_phase' with dtype bool\n\t [[Node: lstm_1/keras_learning_phase = Placeholder[dtype=DT_BOOL, shape=[], _device=\"/job:localhost/replica:0/task:0/device:CPU:0\"]()]]\")"} How
订阅 google-cloud-ml