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

.whl file is depend on your python version or cuda version…
second
you write the command line and setup.py 22 because you have to set up the google-cloud-ml setting.
related link is this  submit_job_to_ml-engine 13
you write the setup.py 22 file to describe your setup.
the related link is this write_setup.py_file 7
this is my command code and setup.py 22 file
“command 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 22” code
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 36
you have to follow above link and know how to pack files.