aws / aws/sagemaker-python-sdk
Local processing job replaces local output location with S3 URI
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Descripción
**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
Guía de contribución
Línea de trabajo
Lee sagemaker-core/src/sagemaker/core/processing.py en Processor._normalize_outputs() y reproduce el problema con LocalSession, FrameworkProcessor y una URI de ProcessingOutput file://. Está hecho cuando el procesamiento local conserva la ubicación de salida file:// especificada en lugar de reemplazarla por una URI de S3.
Escrito por el modelo de indexación a partir del texto del issue.
Evaluación
- Stack tecnológico
- aws, python
- Área
- cloud, machine-learning
- Tipo de issue
- Error
- Dificultad
- 2/5
- Tiempo estimado
- 1-3 horas
- Estado de actividad
- Estancado
- Claridad
- Bien especificado
- Aptitud para principiantes
- 45/100