Modular nvmsgbroker pipeline#95
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November 2, 2025 14:32
- Refactored buffer_probe into process_tensor_operations and create_message_metadata - Fixed Consumer Dockerfile path: database/consumer.py - End-to-end testing successful: Pipeline → nvmsgbroker → MQTT → Consumer → MongoDB - Ready for code reuse in future pipelines
lyuzinmaxim
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Nov 3, 2025
| l_user = l_user.next | ||
| return classification_results | ||
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| def create_message_metadata(batch_meta, frame_meta, frame_number, classification_results): |
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this function isn't just creating - it also adds new info in-place. Please change the name to represent this
lyuzinmaxim
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Nov 3, 2025
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| probs = np.ctypeslib.as_array(ptr, shape=(83,)) | ||
| exp_probs = np.exp(probs - np.max(probs)) | ||
| normalized_probs = exp_probs / np.sum(exp_probs) | ||
| top_indices = np.argsort(normalized_probs)[-5:][::-1] |
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this seems to me also as a standalone function
lyuzinmaxim
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Nov 3, 2025
- Added type hints to all functions - Renamed create_message_metadata to create_and_add_message_metadata - Extracted apply_softmax_normalization as separate function - Added docstrings for better code documentation - Updated documentation with simplified script paths
lyuzinmaxim
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Nov 4, 2025
This was referenced Nov 12, 2025
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Task #91: Make nvmsgbroker_pipeline modular for future use
Changes Made:
buffer_probefunction into two separate modular functions:process_tensor_operations()- handles tensor processing, softmax normalization, and classificationcreate_message_metadata()- creates nvmsgbroker metadata for MQTT transmissionconsumer.pytodatabase/consumer.pyTesting:
✅ End-to-end testing completed successfully:
Benefits:
DoD Completed:
✅ Modular probe function working in the same way as before
Closes #91