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Questions tagged [google-cloud-ml-engine]

Google Cloud ML Engine is a managed, scalable service that enables building and training of machine learning models in the cloud as part of the Google Cloud suite of products: including TensorFlow, storage, BigQuery, Dataflow and others.

185 questions
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Mask samples from loss function in Tensorflow

I have a GCMLE experiment which has three learning objectives (consider these Task A, Task B, and Task C) within a single model_fn(). The inputs for all 3 objectives are the same (reading a body of text) and I would like to produce three separate…
reese0106
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How do I use device_filters with tf.contrib.learn.Experiment?

By default, TensorFlow distributed training establishes all-to-all connections between workers and parameter servers, even though in asynchronous distributed training, the only necessary communication is between each individual worker and the…
rhaertel80
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Google Cloud ML Engine fails to create model version of type 'encoded_image_string_tensor'

I trained an object detection model on ML Engine and exported it by invoking: python object_detection/export_inference_graph.py \ --input_type encoded_image_string_tensor .... Then I successfully tested prediction locally by invoking: gcloud…
Jon Bæk Bomme
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Using gcloud ml serving for large images

I have a trained net in tensorflow that i wish to use in gcloud ml-engine serving for prediction. Predict gcloud ml serving should accept numpy array float32 type images with size of 320x240x3 and return 2 tiny matrices as an output. Does anyone…
A. Zan
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ML Engine BigQuery: Request had insufficient authentication scopes

I'm running a tensorflow model submitting the training on ml engine. I have built a pipeline which reads from BigQuery using tf.contrib.cloud.python.ops.bigquery_reader_ops.BigQueryReader as a reader for the queue. Everything works fine using…
Niccolò Rondelli
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Distributed Training with tf.estimator resulting in more training steps

I am experimenting with distributed training options on Cloud ML Engine and I observing some peculiar results. I have basically altered the census custom estimator example to contain a slightly different model and changed my loss function to…
reese0106
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Google ML Engine - Internal Server Error before run of second trial

I am attempting to run a hyper-parameter tuning job on the Google ML Engine, but I seem to have an error whenever I do more than 1 trail within the same job. I get the following error message: Internal error occurred. Please retry in a few minutes.…
J. Zaporteza
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Google Cloud ML Engine "out-of-memory" error when Memory utilization is nearly zero

I am following the Tensorflow Object Detection API tutorial to train a Faster R-CNN model on my own dataset on Google Cloud. But the following "ran out-of-memory" error kept happening. The replica master 0 ran out-of-memory and exited with a…
Changsong Dong
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Google ML Engine - Unable to log objective metric due to exception

I am running a TensorFlow application on the Google ML Engine with hyper-parameter tuning and I've been running into some strange authentication issues. My Data and Permissions Setup My trainer code supports two ways of obtaining input data for my…
Aaron Cheshire
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gcloud ml-engine predict is very slow on inference

I'm testing a segmentation model on gcloud and the inference is incredibly slow. It takes 3 min to get the result (averaged over 5 runs). Same model runs ~2.5 s on my laptop when running through tf-serving. Is it normal? I didn't find any mention in…
Mikhail Sirotenko
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Tensorflow multiple export strategies

I am training a model with the Experiment class and although the documentation seems to suggest you can have more than one export strategy: export_strategies: Iterable of ExportStrategys, or a single one, or None. When I include two I get an…
dobbysock1002
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Exporting Tensorflow model to Google Cloud Storage

I am trying to export my model to Google Cloud Storage. I used tf.contrib.learn to build my model and followed the iris classification example. After my training and evaluation is done I would like to store the model on the cloud so I can make…
Akash Patwal
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Convert Google's SavedModel to Apple's mlmodel

This week Apple announced support for trained ML models. How can one convert a trained Tensorflow model (Google Cloud Machine Learning Engine model in SavedModel format) into an Apple Core ML model (.mlmodel format)?
Chuck Finley
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Locally load saved tensorflow model .pb from google cloud machine learning engine

I'd like to take the tensorflow model i've trained online and run it locally with a python program I distribute. After training, I get a directory /model with two files /saved_model.pb and a folder /variables. What is the simplest way to deploy this…
bw4sz
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Manage scikit-learn model in Google Cloud Platform

We are trying to figure out how to host and run many of our existing scikit-learn and R models (as is) in GCP. It seems ML Engine is pretty specific to Tensorflow. How can I train a scikit-learn model on Google cloud platform and manage my model if…
dobbysock1002
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