Local processing job replaces local output location with S3 URI

**PySDK Version**
- [ ] PySDK V2 (2.x)
- [x] PySDK V3 (3.x)

**Describe the bug**
When using `LocalSession` with `FrameworkProcessor`, the SDK ignores `file://` URIs specified in `ProcessingOutput.s3_output.s3_uri` and replaces them with S3 URIs. This prevents local processing jobs from saving outputs to local directories as intended.

The issue is in `Processor._normalize_outputs()` (line 489 in `sagemaker-core/src/sagemaker/core/processing.py`), which replaces any non-S3 URI with an S3 URI without checking if the session is a `LocalSession` that should preserve `file://` URIs.

**To reproduce**
```python
from sagemaker.core import FrameworkProcessor
from sagemaker.core.local import LocalSession
from sagemaker.core.shapes import ProcessingOutput, ProcessingS3Output
from sagemaker.core.image_uris import retrieve
import os

# Create local session
local_session = LocalSession()

# Get processor image
processor_image_uri = retrieve(
framework="sklearn",
version="1.4-2",
region=local_session.boto_region_name
)

# Define outputs with file:// URIs
local_processing_dir = os.path.abspath("processing")
os.makedirs(f"{local_processing_dir}/train", exist_ok=True)

local_processing_outputs = [
ProcessingOutput(
output_name="train",
s3_output=ProcessingS3Output(
s3_uri=f"file://{local_processing_dir}/train",
local_path="/opt/ml/processing/output/train",
s3_upload_mode="EndOfJob")
)
]

# Create processor with LocalSession
processor = FrameworkProcessor(
image_uri=processor_image_uri,
role="arn:aws:iam::123456789012:role/DummyRole",
instance_type="local",
instance_count=1,
sagemaker_session=local_session,
base_job_name='test-local-processing',
command=["python3"]
)

# Create a simple processing script
os.makedirs("processing_code", exist_ok=True)
with open("processing_code/test.py", "w") as f:
f.write("""
import os
with open('/opt/ml/processing/output/train/output.txt', 'w') as f:
f.write('test output')
print('Processing complete')
""")

# Run processor
processor.run(
code="test.py",
source_dir="./processing_code",
outputs=local_processing_outputs,
wait=False,
logs=True
)

# Check where outputs went
print(f"Expected output location: {local_processing_dir}/train/output.txt")
print(f"File exists locally: {os.path.exists(f'{local_processing_dir}/train/output.txt')}")
```

**Expected behavior**
When using LocalSession with `file://` URIs in `ProcessingOutput`, the outputs should be saved to the specified local directories, not uploaded to S3.

**Screenshots or logs**
N/A

**System information**
- **SageMaker Python SDK version**: 3.4.0 (sagemaker-core 2.4.0)
- **Framework name (eg. PyTorch) or algorithm (eg. KMeans)**: scikit-learn
- **Framework version**: 1.4-2
- **Python version**: 3.10
- **CPU or GPU**: CPU
- **Custom Docker image (Y/N)**: N

**Additional context**
N/A

Lies sagemaker-core/src/sagemaker/core/processing.py bei Processor._normalize_outputs() und reproduziere das Problem mit LocalSession, FrameworkProcessor und einer file:// ProcessingOutput-URI. Erledigt ist es, wenn die lokale Verarbeitung den angegebenen file://-Ausgabeort beibehält, anstatt ihn durch eine S3-URI zu ersetzen.

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