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.
35 lines
1.1 KiB
Markdown
35 lines
1.1 KiB
Markdown
# Insert Content Guidelines
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## insert_content
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```xml
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<insert_content>
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<path>File path here</path>
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<operations>
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[{"start_line":10,"content":"New code"}]
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</operations>
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</insert_content>
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```
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### Required Parameters:
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- `path`: The file path to modify
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- `operations`: JSON array of insertion operations
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### Each Operation Must Include:
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- `start_line`: The line number where content should be inserted (REQUIRED)
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- `content`: The content to insert (REQUIRED)
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### Common Errors to Avoid:
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- Missing `start_line` parameter
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- Missing `content` parameter
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- Invalid JSON format in operations array
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- Using non-numeric values for start_line
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- Attempting to insert at line numbers beyond file length
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- Attempting to modify non-existent files
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### Best Practices:
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- Always verify the file exists before attempting to modify it
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- Check file length before specifying start_line
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- Use read_file first to confirm file content and structure
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- Ensure proper JSON formatting in the operations array
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- Use for adding new content rather than modifying existing content
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- Prefer for documentation additions and new code blocks |