sagemaker.local bug when inputs are binary files

[vojavocni]

Describe the bug
Hello, I think I encountered a bug in sagemaker.local. I'm trying to test a batch transform with images as input, but I get the following error even before I reach the input_fn of my custom inference script

│   345 │   │   for element in self.splitter.split(file):
│ ❱ 346 │   │   │   if _payload_size_within_limit(buffer + element, size):
│   347 │   │   │   │   buffer += element
│   348 │   │   │   else:
│   349 │   │   │   │   tmp = buffer
╰──────────────────────────────────────────────────────────────────────────────────────────────────╯
TypeError: can only concatenate str (not "bytes") to str

I am not using a splitter (splitter type is None), as it's not necessary on images.

I believe the problem is in line 343 of MultRecordStrategy class

sagemaker-python-sdk/src/sagemaker/local/data.py

Lines 326 to 352 in ae3cc1c

	class MultiRecordStrategy(BatchStrategy):
	"""Feed multiple records at a time for batch inference.
	Will group up as many records as possible within the payload specified.
	"""
	def pad(self, file, size=6):
	"""Group together as many records as possible to fit in the specified size.
	Args:
	file (str): file path to read the records from.
	size (int): maximum size in MB that each group of records will be
	fitted to. passing 0 means unlimited size.
	Returns:
	generator of records
	"""
	buffer = ""
	for element in self.splitter.split(file):
	if _payload_size_within_limit(buffer + element, size):
	buffer += element
	else:
	tmp = buffer
	buffer = element
	yield tmp
	if _validate_payload_size(buffer, size):
	yield buffer

We can see that the buffer variable is assumed to be a string, which means it's assumed that the file variable would not refer to a binary object, which should be possible.

To reproduce
Just run local batch transform with a single image as input. The model doesn't really matter I think, it will fail before any prediction or interaction between data and the model is made.

Expected behavior
I would expect the buffer to be sensitive to weather the file is a string like json or csv, or a binary type like png.

Screenshots or logs
See above.

System information
A description of your system. Please provide:

• SageMaker Python SDK version: 2.237.0
• Framework name (eg. PyTorch) or algorithm (eg. KMeans): Pytorch, custom inference and model
• Framework version: 2.5.1
• Python version: 3.11
• CPU or GPU: Both
• Custom Docker image (Y/N): Y, extending the pytorch-inference:2.5.1-gpu-py311-cu124-ubuntu22.04-sagemaker image

Additional context
Add any other context about the problem here.

[vojavocni]

I have a fix in my local environment after which the whole batch transform job works:

buffer = b"" if isinstance(next(self.splitter.split(file)), bytes) else ""

So I can confirm this is the issue.
I can make a small PR if this seems ok?