MLflow 1.2.0 define MLproject file - docker

Question

Trying to run mlflow run by specifying MLproject and code which lives in a different location as MLproject file.
I have the following directory structure:
/root/mflow_test
.
├── conda
│   ├── conda.yaml
│   └── MLproject
├── docker
│   ├── Dockerfile
│   └── MLproject
├── README.md
├── requirements.txt
└── trainer
├── __init__.py
├── task.py
└── utils.py
When I'm run from: /root/
mlflow run mlflow_test/docker
I get:
/root/miniconda3/bin/python: Error while finding module specification for 'trainer.task' (ImportError: No module named 'trainer')
Since my MLproject file can't find the Python code.
I moved MLproject to mflow_test and this works fine.
This is my MLproject entry point:
name: mlflow_sample
docker_env:
image: mlflow-docker-sample
entry_points:
main:
parameters:
job_dir:
type: string
default: '/tmp/'
command: |
python -m trainer.task --job-dir {job_dir}
How can I run mlflow run and pass the MLproject and ask it to look in a different folder?
I tried:
"cd .. && python -m trainer.task --job-dir {job_dir}"
and I get:
/entrypoint.sh: line 5: exec: cd: not found
Dockerfile
# docker build -t mlflow-gcp-example -f Dockerfile .
FROM gcr.io/deeplearning-platform-release/tf-cpu
RUN git clone github.com/GoogleCloudPlatform/ml-on-gcp.git
WORKDIR ml-on-gcp/tutorials/tensorflow/mlflow_gcp
RUN pip install -r requirements.txt