Repack inference model with requirements.txt inside source_dir without installing them during the process in SageMaker

After training a custom model, i need to create an inference model and then deploy the relevant endpoint.

When, in the execution of the pipeline, i have to inject a custom inference script, a model repacking process is triggered. The inference model needs to have the requirements.txt file (the same as the trained model).

When the repacking process is started, a default machine ml.m5.large with the training image sagemaker-scikit-learn:0.23-1-cpu-py3 is instantiated. If the requirements.txt file is present in the inference code folder, this process will try to install the packages (although it is not necessary, should be a simple repacking of a tar.gz!).

Unfortunately, having specified particular library versions, it will fail.

For example:

ERROR: Ignored the following versions that require a different python version: 1.22.0 Requires-Python >=3.8; 1.22.0rc1 Requires-Python >=3.8; 1.22. 0rc2 Requires-Python >=3.8; 1.22.0rc3 Requires-Python >=3.8; 1.22.1 Requires-Python >=3.8; 1.22.2 Requires-Python >=3.8; 1.22.3 Requires-Python >=3. 8; 1.22.4 Requires-Python >=3.8; 1.23.0 Requires-Python >=3.8; 1.23.0rc1 Requires-Python >=3.8; 1.23.0rc2 Requires-Python >=3.8; 1.23. 0rc3 Requires-Python >=3.8; 1.23.1 Requires-Python >=3.8; 1.23.2 Requires-Python >=3.8; 1.23.3 Requires-Python >=3.8; 1.23.4 Requires-Python >=3.8
ERROR: Could not find a version that satisfies the requirement numpy==1.23.0

This is the code I'm running:

inf_img_uri = sagemaker.image_uris.retrieve(
    framework='pytorch',
    region=region,
    image_scope='inference',
    version="1.12.0",
    instance_type='ml.m5.xlarge',
    py_version='py38'
)

pytorch_model = Model(
    image_uri=inf_img_uri,
    model_data=step_train.properties.ModelArtifacts.S3ModelArtifacts,
    role=role,
    entry_point='inference.py',
    sagemaker_session=PipelineSession(),
    source_dir=os.path.join(LIB_DIR, "test"),  # here is inference.py and requirements.txt
    name=model_name,
)

step_create_model = ModelStep(
    name="infTest",
    step_args=pytorch_model.create(instance_type="ml.m5.xlarge"),
    description = 'Create model for inference'
)

Is there any way to prevent the template repack from trying to install packages from the requirements.txt?

My current solution: I have omitted the file in the directory and manually install the packages with subprocess.check_call([sys.executable, "-m", "pip", "install", package]) in the inference code. But I find this approach wrong for Batch Inference processes (since it would be executed every time) and also inconsistent.

from Repack inference model with requirements.txt inside source_dir without installing them during the process in SageMaker