MLFlow run passing Google Application credentials - docker

Question

I want to pass my GOOGLE_APPLICATION_CREDENTIALS environmental variable when I run mlflow run using a Docker container:
This is my current docker run when using mlflow run:
Running command 'docker run --rm -e MLFLOW_RUN_ID=f18667e37ecb486cac4631cbaf279903 -e MLFLOW_TRACKING_URI=http://3.1.1.11:5000 -e MLFLOW_EXPERIMENT_ID=0 mlflow_gcp:33156ee python -m trainer.task --job-dir /tmp/ \
--num-epochs 10 \
--train-steps 1000 \
--eval-steps 1 \
--train-files gs://cloud-samples-data/ml-engine/census/data/adult.data.csv \
--eval-files gs://cloud-samples-data/ml-engine/census/data/adult.test.csv \
--batch-size 128
This is how I would normally pass it:
docker run \
-p 9090:${PORT} \
-e PORT=${PORT} \
-e GOOGLE_APPLICATION_CREDENTIALS=/tmp/keys/[FILE_NAME].json
What is the best way to option to pass this value to mlflow? I'm writing files in GCS and Docker requires access to GCP.
MLproject contents
name: mlflow_gcp
docker_env:
image: mlflow-gcp-example
entry_points:
main:
parameters:
job_dir:
type: string
default: '/tmp/'
num_epochs:
type: int
default: 10
train_steps:
type: int
default: 1000
eval_steps:
type: int
default: 1
batch_size:
type: int
default: 64
train_files:
type: string
default: 'gs://cloud-samples-data/ml-engine/census/data/adult.data.csv'
eval_files:
type: string
default: 'gs://cloud-samples-data/ml-engine/census/data/adult.test.csv'
mlflow_tracking_uri:
type: uri
default: ''
command: |
python -m trainer.task --job-dir {job_dir} \
--num-epochs {num_epochs} \
--train-steps {train_steps} \
--eval-steps {eval_steps} \
--train-files {train_files} \
--eval-files {eval_files} \
--batch-size {batch_size} \
--mlflow-tracking-uri {mlflow_tracking_uri}
I already tried in Python file and fails since Docker has no access to local file system:
import os
os.environ["GOOGLE_APPLICATION_CREDENTIALS"] = "/Users/user/key.json"