Spaces:
Running
Running
File size: 2,406 Bytes
e178784 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 |
# Pipeline Parallelism Dash Visualizer
This is an interactive Dash-based visualizer for pipeline parallelism scheduling, complementing the existing Matplotlib-based visualization.
## Features
- **Static image generation** similar to the Matplotlib version
- **Interactive web-based visualization** with Dash
- **Download functionality** to save the visualization as PNG
- **Progress indication** during figure creation and image generation
- **Compatible API** with the existing visualizer
## Installation
Install the required dependencies:
```bash
pip install -r requirements-dash.txt
```
## Usage
### From Python
```python
from pipeline import create_1f1b_schedule
from dash_visualizer import visualize_pipeline_parallelism_dash, save_pipeline_visualization_plotly
# Create a schedule
schedule = create_1f1b_schedule(
num_stages=4,
num_batches=8,
forward_times=[1.0, 1.0, 1.0, 1.0],
backward_times=[2.0, 2.0, 2.0, 2.0],
)
# Generate a static image
save_pipeline_visualization_plotly(
schedule=schedule,
schedule_type="1f1b",
output_file="pipeline_plotly.png"
)
# OR launch an interactive Dash app
visualize_pipeline_parallelism_dash(
schedule=schedule,
schedule_type="1f1b",
port=8050,
debug=False
)
```
### Using the Command Line
You can use the updated command line interface:
```bash
# Generate a static image with Dash/Plotly
python pipeline.py --visualizer dash --output-file pipeline_viz.png
# Launch an interactive Dash app
python pipeline.py --visualizer dash-interactive
# Use the original Matplotlib visualizer
python pipeline.py --visualizer matplotlib
```
You can also use the dash_visualizer.py script directly for testing:
```bash
# Generate a static image
python dash_visualizer.py --output test_viz.png
# Launch an interactive app
python dash_visualizer.py --interactive
```
## Differences from Matplotlib Visualizer
The Dash-based visualizer provides all the same visual elements as the Matplotlib version:
- Color-coded rectangles for forward, backward, and optimizer operations
- Batch numbers displayed inside each rectangle
- Device labels on the y-axis
- Clear legend
Additional features:
- Interactive web interface
- Hovering over elements to see details
- Download button to save the visualization
- Progress bars for tracking visualization creation
- Responsive layout that works well on different screen sizes |