"Train": executable file not found in $PATH

**BUG Description**
**I am facing an error that does not give any direction to resolve it when migrating to run on Sagemaker.**

The code runs perfectly on the local machine.

**To reproduce**
```python
role = "arn:..."

estimator = PyTorch(
image_uri="1...ecr...amazonaws.com/...:prototype",
git_config={"repo": "https://github.com/celsofranssa/LightningPrototype.git", "branch": "sagemaker"},
entry_point="main.py",
role=role,
region="us-...",
instance_type="local", # ml.g4dn.2xlarge
instance_count=1,
volume_size=225,
hyperparameters=hparams
)
estimator.fit()
```

**Expected behavior**
The model is expected to start to train and log metrics and losses.

**Screenshots or logs**
```python
Cloning into '/tmp/tmpycpzvkcn'...
remote: Enumerating objects: 246, done.
remote: Counting objects: 100% (246/246), done.
remote: Compressing objects: 100% (190/190), done.
remote: Total 246 (delta 40), reused 232 (delta 29), pack-reused 0
Receiving objects: 100% (246/246), 39.10 MiB | 27.69 MiB/s, done.
Resolving deltas: 100% (40/40), done.
Branch 'sagemaker' set up to track remote branch 'sagemaker' from 'origin'.
Switched to a new branch 'sagemaker'
[2023-10-12 19:22:15,073][sagemaker][INFO] - Creating training-job with name: xmtc-2023-10-13-02-22-09-781
[2023-10-12 19:22:15,116][sagemaker.local.image][INFO] - 'Docker Compose' found using Docker CLI.
[2023-10-12 19:22:15,117][sagemaker.local.local_session][INFO] - Starting training job
[2023-10-12 19:22:15,118][sagemaker.local.image][INFO] - Using the long-lived AWS credentials found in session
[2023-10-12 19:22:15,121][sagemaker.local.image][INFO] - docker compose file:
networks:
sagemaker-local:
name: sagemaker-local
services:
algo-1-55row:
command: train
container_name: 1l7x1nzly6-algo-1-55row
environment:
- '[Masked]'
- '[Masked]'
- '[Masked]'
- '[Masked]'
- '[Masked]'
image: 179395270822.dkr.ecr.us-east-2.amazonaws.com/xmtc:prototype
networks:
sagemaker-local:
aliases:
- algo-1-55row
stdin_open: true
tty: true
volumes:
- /tmp/tmpsvd2b_wm/algo-1-55row/output/data:/opt/ml/output/data
- /tmp/tmpsvd2b_wm/algo-1-55row/input:/opt/ml/input
- /tmp/tmpsvd2b_wm/algo-1-55row/output:/opt/ml/output
- /tmp/tmpsvd2b_wm/model:/opt/ml/model
version: '2.3'

[2023-10-12 19:22:15,121][sagemaker.local.image][INFO] - docker command: docker compose -f /tmp/tmpsvd2b_wm/docker-compose.yaml up --build --abort-on-container-exit
time="2023-10-12T19:22:15-07:00" level=warning msg="a network with name sagemaker-local exists but was not created for project \"tmpsvd2b_wm\".\nSet `external: true` to use an existing network"
Container 1l7x1nzly6-algo-1-55row Creating
Container 1l7x1nzly6-algo-1-55row Created
Attaching to 1l7x1nzly6-algo-1-55row
Error response from daemon: failed to create task for container: failed to create shim task: OCI runtime create failed: runc create failed: unable to start container process: exec: "train": executable file not found in $PATH: unknown
Error executing job with overrides: []
Traceback (most recent call last):
File "/home/celso/projects/venvs/LightningPrototype/lib/python3.8/site-packages/sagemaker/local/image.py", line 296, in train
_stream_output(process)
File "/home/celso/projects/venvs/LightningPrototype/lib/python3.8/site-packages/sagemaker/local/image.py", line 984, in _stream_output
raise RuntimeError("Process exited with code: %s" % exit_code)
RuntimeError: Process exited with code: 1

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
File "run_on_sagemaker.py", line 28, in run_on_sagemaker
estimator.fit()
File "/home/celso/projects/venvs/LightningPrototype/lib/python3.8/site-packages/sagemaker/workflow/pipeline_context.py", line 311, in wrapper
return run_func(*args, **kwargs)
File "/home/celso/projects/venvs/LightningPrototype/lib/python3.8/site-packages/sagemaker/estimator.py", line 1311, in fit
self.latest_training_job = _TrainingJob.start_new(self, inputs, experiment_config)
File "/home/celso/projects/venvs/LightningPrototype/lib/python3.8/site-packages/sagemaker/estimator.py", line 2374, in start_new
estimator.sagemaker_session.train(**train_args)
File "/home/celso/projects/venvs/LightningPrototype/lib/python3.8/site-packages/sagemaker/session.py", line 941, in train
self._intercept_create_request(train_request, submit, self.train.__name__)
File "/home/celso/projects/venvs/LightningPrototype/lib/python3.8/site-packages/sagemaker/session.py", line 5618, in _intercept_create_request
return create(request)
File "/home/celso/projects/venvs/LightningPrototype/lib/python3.8/site-packages/sagemaker/session.py", line 939, in submit
self.sagemaker_client.create_training_job(**request)
File "/home/celso/projects/venvs/LightningPrototype/lib/python3.8/site-packages/sagemaker/local/local_session.py", line 203, in create_training_job
training_job.start(
File "/home/celso/projects/venvs/LightningPrototype/lib/python3.8/site-packages/sagemaker/local/entities.py", line 243, in start
self.model_artifacts = self.container.train(
File "/home/celso/projects/venvs/LightningPrototype/lib/python3.8/site-packages/sagemaker/local/image.py", line 301, in train
raise RuntimeError(msg)
RuntimeError: Failed to run: ['docker', 'compose', '-f', '/tmp/tmpsvd2b_wm/docker-compose.yaml', 'up', '--build', '--abort-on-container-exit'], Process exited with code: 1

```

**System information**
A description of your system. Please provide:
- **SageMaker Python SDK version**: sagemaker 2.192.0
- **Framework name (eg. PyTorch) or algorithm (eg. KMeans)**: Pytorch 2.0.1
- **Python version**: Python 3.10
- **Docker**: 24.0.6
- **Custom Docker image (Y/N)**: Yes, on ECR.

Start with sagemaker/local/image.py, especially the train path and the generated Docker Compose command shown in the traceback. Reproduce the failure with the supplied custom ECR image and determine why the container cannot resolve train; done means the local training job starts and logs metrics and losses.

Written by the indexing model from the issue text.