f3c77b1750
- Implemented the WiFi DensePose model in PyTorch, including CSI phase processing, modality translation, and DensePose prediction heads. - Added a comprehensive training utility for the model, including loss functions and training steps. - Created a CSV file to document hardware specifications, architecture details, training parameters, performance metrics, and advantages of the model.
1.1 KiB
1.1 KiB
Insert Content Guidelines
insert_content
<insert_content>
<path>File path here</path>
<operations>
[{"start_line":10,"content":"New code"}]
</operations>
</insert_content>
Required Parameters:
path: The file path to modifyoperations: JSON array of insertion operations
Each Operation Must Include:
start_line: The line number where content should be inserted (REQUIRED)content: The content to insert (REQUIRED)
Common Errors to Avoid:
- Missing
start_lineparameter - Missing
contentparameter - Invalid JSON format in operations array
- Using non-numeric values for start_line
- Attempting to insert at line numbers beyond file length
- Attempting to modify non-existent files
Best Practices:
- Always verify the file exists before attempting to modify it
- Check file length before specifying start_line
- Use read_file first to confirm file content and structure
- Ensure proper JSON formatting in the operations array
- Use for adding new content rather than modifying existing content
- Prefer for documentation additions and new code blocks