{"action":"created","issue":{"url":"https://api.github.com/repos/GoogleCloudPlatform/cloudml-samples/issues/314","repository_url":"https://api.github.com/repos/GoogleCloudPlatform/cloudml-samples","labels_url":"https://api.github.com/repos/GoogleCloudPlatform/cloudml-samples/issues/314/labels{/name}","comments_url":"https://api.github.com/repos/GoogleCloudPlatform/cloudml-samples/issues/314/comments","events_url":"https://api.github.com/repos/GoogleCloudPlatform/cloudml-samples/issues/314/events","html_url":"https://github.com/GoogleCloudPlatform/cloudml-samples/issues/314","id":382964037,"node_id":"MDU6SXNzdWUzODI5NjQwMzc=","number":314,"title":"Training step for Criteo_tft example does not work on google cloud","user":{"login":"PicarusW","id":43196561,"node_id":"MDQ6VXNlcjQzMTk2NTYx","avatar_url":"https://avatars2.githubusercontent.com/u/43196561?v=4","gravatar_id":"","url":"https://api.github.com/users/PicarusW","html_url":"https://github.com/PicarusW","followers_url":"https://api.github.com/users/PicarusW/followers","following_url":"https://api.github.com/users/PicarusW/following{/other_user}","gists_url":"https://api.github.com/users/PicarusW/gists{/gist_id}","starred_url":"https://api.github.com/users/PicarusW/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/PicarusW/subscriptions","organizations_url":"https://api.github.com/users/PicarusW/orgs","repos_url":"https://api.github.com/users/PicarusW/repos","events_url":"https://api.github.com/users/PicarusW/events{/privacy}","received_events_url":"https://api.github.com/users/PicarusW/received_events","type":"User","site_admin":false},"labels":[],"state":"open","locked":false,"assignee":null,"assignees":[],"milestone":null,"comments":9,"created_at":"2018-11-21T05:42:54Z","updated_at":"2018-11-28T23:37:11Z","closed_at":null,"author_association":"NONE","body":"**Describe the bug**\r\nI am running the Criteo example, documented[ here](https://cloud.google.com/blog/products/gcp/using-google-cloud-machine-learning-to-predict-clicks-at-scale). I can run the preprocess step fine but when trying to run the training step (linear model fails) running on Google Cloud I get the following errors:\r\n\r\n> Command \"python setup.py egg_info\" failed with error code 1 in /tmp/pip-install-guzRvj/fastavro/\r\n> Command '['pip', 'install', '--user', u'trainer-1.0.tar.gz']' returned non-zero exit status 1\r\n> \r\nthe error message in Google ML engine is:\r\n load raise ImportError(\"%r has no %r attribute\" % (entry, attr)) ImportError: <module 'setuptools.dist' from '/usr/lib/python2.7/dist-packages/setuptools/dist.pyc'> has no 'check_specifier' attribute\r\n\r\n**What sample is this bug related to?**\r\n\r\nI cloned this repo a couple of days ago.\r\n\r\n**Source code / logs**\r\n\r\nSee above\r\n\r\n**To Reproduce**\r\nLocation is us-east1 (if that is relevant)\r\n\r\nJOB_ID=\"largeclicks_linear_${USER}_$(date +%Y%m%d_%H%M%S)\"\r\ncd ~/cloudml-samples/criteo_tft/\r\ngcloud beta ml-engine jobs submit  training \"$JOB_ID\" \\\r\n  --module-name trainer.task \\\r\n  --package-path trainer \\\r\n  --staging-bucket \"$BUCKET\" \\\r\n  --region \"$LOCATION\" \\\r\n  --config config-small.yaml \\\r\n  -- \\\r\n  --dataset small \\\r\n  --model_type linear \\\r\n  --ignore_crosses \\\r\n  --l2_regularization 1000 \\\r\n  --output_path \"${GCS_PATH}/output/${JOB_ID}\" \\\r\n  --metadata_path \"${GCS_PATH}/preproc/metadata.json\" \\\r\n  --eval_data_paths \"${GCS_PATH}/preproc/features_eval*\" \\\r\n  --train_data_paths \"${GCS_PATH}/preproc/features_train*\"\r\n\r\n**Expected behavior**\r\nthe job to start execution\r\n\r\n**System Information**\r\n- **OS Platform and Distribution (e.g., Linux Ubuntu 16.04)**: Google Cloud Shell\r\n- **Framework and version (Tensorflow, scikit-learn, XGBoost)**:\r\n- **Python version**: 2.7 (both on Cloud Shell and remotely, no version specified in gcloud call) as it seems that Tensorflow-transform does not support 3.x\r\n- **Exact command to reproduce**: See above\r\n- **Tensorflow Transform environment (if applicable, see below)**: I have tried to specify many different versions in the requirements.txt, requires.txt and setup.py but does not seem to be relevant. Default values on the mentioned files do not work.\r\n- **Setuptools** is version 40.6.2\r\n\r\n**Additional context**\r\nYou can find a reduced version of  the data [here](https://s3-eu-west-1.amazonaws.com/kaggle-display-advertising-challenge-dataset/dac.tar.gz). From the train dataset, you can generate a train and eval dataset. It is 10Gb so much less than the original 1Tb.\r\n\r\n"},"comment":{"url":"https://api.github.com/repos/GoogleCloudPlatform/cloudml-samples/issues/comments/442648022","html_url":"https://github.com/GoogleCloudPlatform/cloudml-samples/issues/314#issuecomment-442648022","issue_url":"https://api.github.com/repos/GoogleCloudPlatform/cloudml-samples/issues/314","id":442648022,"node_id":"MDEyOklzc3VlQ29tbWVudDQ0MjY0ODAyMg==","user":{"login":"PicarusW","id":43196561,"node_id":"MDQ6VXNlcjQzMTk2NTYx","avatar_url":"https://avatars2.githubusercontent.com/u/43196561?v=4","gravatar_id":"","url":"https://api.github.com/users/PicarusW","html_url":"https://github.com/PicarusW","followers_url":"https://api.github.com/users/PicarusW/followers","following_url":"https://api.github.com/users/PicarusW/following{/other_user}","gists_url":"https://api.github.com/users/PicarusW/gists{/gist_id}","starred_url":"https://api.github.com/users/PicarusW/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/PicarusW/subscriptions","organizations_url":"https://api.github.com/users/PicarusW/orgs","repos_url":"https://api.github.com/users/PicarusW/repos","events_url":"https://api.github.com/users/PicarusW/events{/privacy}","received_events_url":"https://api.github.com/users/PicarusW/received_events","type":"User","site_admin":false},"created_at":"2018-11-28T23:37:11Z","updated_at":"2018-11-28T23:37:11Z","author_association":"NONE","body":"Well, now the job completes successfully.\r\nIt was a matter of \r\nUsing runtime-version=1.4 as parameter,\r\nchanging the requirements.txt to use tf 1.4 (not sure if that is redundant), I am a bit confused with the local and cloud execution.\r\nAnd then some parameters had to be added (compared to the blog post), your sample code was enough.\r\nIt took just 10 mins to execute with the small configuration.\r\n\r\nWhile a workaround has been provided I would like to keep the issue open until the example is updated to a newer version  (if you are ok with that).\r\n\r\nAbout versions, may I suggest to use tf 1.10, or any other that is compatible with tf/Adanet (tf 1.12 seems not to be)."}}
{"actor":{"display_login":"PicarusW"}}