Endpoint dependencies error

Describe the bug I am using a package called Farm to perform the training and the inference. The training works fine: I pass the requirements.txt and all the packages are correctly installed. When I try to deploy it, there is also no problem. But at the moment of inference, when it is required to import farm, I get an error showing that the package doesn't exist.

To reproduce

estimator = PyTorch(
    base_job_name="imdb",
    max_run= 60*30,
    entry_point="train_aws.py",
    source_dir="source",  
    framework_version="1.5",
    py_version = 'py3',
    instance_count=1,
    role=role, 
    hyperparameters=hyperparameters,
    instance_type= "ml.p3.2xlarge", 
    output_path="s3://<bucket>/opt/ml/model", # the S3 path where model is outputted 
)

estimator.fit(
    {'training': '/'.join(training_input_path.split('/')[:-1])}, 
    wait=True
)

model = estimator.create_model(role=role, entry_point='inference.py')
mdm = multidatamodel.MultiDataModel(name="Models",
                                    model_data_prefix="s3://<bucket>/opt/ml/model/", 
                                    model = model,
                                    sagemaker_session=sess
                                   )
predictor = mdm.deploy(initial_instance_count=1,instance_type='ml.t2.medium', endpoint_name="inference")

Note: when I create the model.tar.gz, I include 'requirements.txt' and 'inference.py' on code folder.

Expected behavior

Inference should be working, but the packages are not being correctly installed. I try to do it using brute force, including these lines on inference.py:

import subprocess
import sys
subprocess.check_call([sys.executable, '-m', 'pip', 'install', 'farm'])

But then it says that another package is missing: ImportError: cannot import name 'rng_integers'

Is there a better way to install the packages I want inside the inference container?

aws / sagemaker-pytorch-inference-toolkit

Endpoint dependencies error #91