How to setup pytorch in google-cloud-ml - pytorch

Question

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.'
)
and throw the job to the google-cloud-ml, but it doesn't work
with error message
{
insertId: "3m78xtf9czd0u"
jsonPayload: {
created: 1516845879.49039
levelname: "ERROR"
lineno: 829
message: "Command '['pip', 'install', '--user', '--upgrade', '--force-reinstall', '--no-deps', u'trainer-0.1.tar.gz']' returned non-zero exit status 1"
pathname: "/runcloudml.py"
}
labels: {
compute.googleapis.com/resource_id: "6637909247101536087"
compute.googleapis.com/resource_name: "cmle-training-master-5502b52646-0-ql9ds"
compute.googleapis.com/zone: "us-central1-c"
ml.googleapis.com/job_id: "run_ml_engine_pytorch_test_20180125_015752"
ml.googleapis.com/job_id/log_area: "root"
ml.googleapis.com/task_name: "master-replica-0"
ml.googleapis.com/trial_id: ""
}
logName: "projects/exem-191100/logs/master-replica-0"
receiveTimestamp: "2018-01-25T02:04:55.421517460Z"
resource: {
labels: {…}
type: "ml_job"
}
severity: "ERROR"
timestamp: "2018-01-25T02:04:39.490387916Z"
}
====================================================================
See detailed message here
so how can i use pytorch in google cloud ml engine?

Answer 1

i find solution about setting up PYTORCH in google-cloud-ml
first
you have to get a .whl file about pytorch and store it to google storage bucket.
and you will get the link for bucket link.
gs://bucketname/directory/torch-0.3.0.post4-cp27-cp27mu-linux_x86_64.whl
the .whl file is depend on your python version or cuda version....
second
you write the command line and setup.py because you have to set up the google-cloud-ml setting.
related link is this submit_job_to_ml-engine
you write the setup.py file to describe your setup.
the related link is this write_setup.py_file
this is my command code and setup.py file
=====================================================================
"command"
#commandline code
JOB_NAME="run_ml_engine_pytorch_test_$(date +%Y%m%d_%H%M%S)"
REGION=us-central1
OUTPUT_PATH=gs://yourbucket
gcloud ml-engine jobs submit training $JOB_NAME \
--job-dir $OUTPUT_PATH \
--runtime-version 1.4 \
--module-name models.pytorch_test \
--package-path models/ \
--packages gs://yourbucket/directory/torch-0.3.0.post4-cp27-cp27mu-linux_x86_64.whl \
--region $REGION \
-- \
--verbosity DEBUG
=====================================================================
"setup.py"
from setuptools import find_packages
from setuptools import setup
REQUIRED_PACKAGES = ['torchvision']
setup(
name='trainer',
version='0.1',
install_requires=REQUIRED_PACKAGES,
packages=find_packages(),
include_package_data=True,
description='My pytorch trainer application package.'
)
=====================================================================
third
if you have experience submitting job to the ml-engine.
you might know the file structure about submitting ml-engine
packaging_training_model.
you have to follow above link and know how to pack files.

Answer 2

The actual error message is a bit buried, but it is this:
'install_requires' must be a string or list of strings containing
valid project/version requirement specifiers; Invalid requirement,
parse error at "'://downl'"
To use packages not hosted on PyPI, you need to use dependency_links (see this documentation). Something like this ought to work:
from setuptools import find_packages
from setuptools import setup
REQUIRED_PACKAGES = ['torchvision']
DEPENDENCY_LINKS = ['http://download.pytorch.org/whl/cpu/torch-0.3.0.post4-cp27-cp27mu-linux_x86_64.whl']
setup(
name='trainer',
version='0.1',
install_requires=REQUIRED_PACKAGES,
dependency_links=DEPENDENCY_LINKS,
packages=find_packages(),
include_package_data=True,
description='My keras trainer application package.'
)