GCP Custom Prediction Routine unable to include jsonschema depency specified in setup.py

Question

According to GCP AI Platform's documentation here, Custom Prediction Routine deployment should allow to include PyPI dependencies. I included my dependency of jsonschema like below in my setup.py script:

from setuptools import setup
from setuptools import find_packages


REQUIRED_PACKAGES = ['jsonschema']

setup(
    name='custom_code',
    version='1.0.2',
    scripts=['predictor.py', 'preprocess.py'],
    install_requires=REQUIRED_PACKAGES,
    packages=find_packages(),
    include_package_data=True
)

but got this error message when deploying:

ERROR: (gcloud.beta.ai-platform.versions.create) Create Version failed. Bad model detected with error:  "Failed to load model: Unexpected error when loading the model: 'str' object has no attribute 'decode' (Error code: 0)"

The same error persisted when specifying a version like so REQUIRED_PACKAGES = ['jsonschema==3.2.0']. I then used a lower version:

from setuptools import setup
from setuptools import find_packages


REQUIRED_PACKAGES = ['jsonschema==3.0.0']

setup(
    name='custom_code',
    version='1.0.2',
    scripts=['predictor.py', 'preprocess.py'],
    install_requires=REQUIRED_PACKAGES,
    packages=find_packages(),
    include_package_data=True
)

but now got this error:

ERROR: (gcloud.beta.ai-platform.versions.create) Create Version failed. Bad model detected with error:  "Failed to load model: Unexpected error when loading the model: problem in predictor - DistributionNotFound: The 'jsonschema' distribution was not found and is required by the application (Error code: 0)"

What can go wrong here?

Answer 1

It turns out the initial error Bad model detected with error: "Failed to load model: Unexpected error when loading the model: 'str' object has no attribute 'decode' (Error code: 0)" was actually driven by a model format issue. This seems to be a known issue with TensorFlow Keras (although my TF version is 1.15, the quoted TF version was 2.1.0). Once I used the TensorFlow SavedModel format, the error immediately went away, and I was also able to include jsonchema dependency with the setup.py file as is.