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.
27 lines
633 B
Markdown
27 lines
633 B
Markdown
# File Operations Guidelines
|
|
|
|
## read_file
|
|
```xml
|
|
<read_file>
|
|
<path>File path here</path>
|
|
</read_file>
|
|
```
|
|
|
|
### Required Parameters:
|
|
- `path`: The file path to read
|
|
|
|
### Common Errors to Avoid:
|
|
- Attempting to read non-existent files
|
|
- Using incorrect or relative paths
|
|
- Missing the `path` parameter
|
|
|
|
### Best Practices:
|
|
- Always check if a file exists before attempting to modify it
|
|
- Use `read_file` before `apply_diff` or `search_and_replace` to verify content
|
|
- For large files, consider using start_line and end_line parameters to read specific sections
|
|
|
|
## write_to_file
|
|
```xml
|
|
<write_to_file>
|
|
<path>File path here</path>
|