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Aryan
2024-12-21 15:18:46 +01:00
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@@ -376,6 +376,111 @@ output = pipe(
export_to_video(output, "output.mp4", fps=15)
```
### Memory Usage
LoRA with rank 128, batch size 1, gradient checkpointing, optimizer adamw, `49x512x768` resolutions, **without precomputation**:
```
Memory before training start: {
"memory_allocated": 38.889,
"memory_reserved": 39.02,
"max_memory_allocated": 38.889,
"max_memory_reserved": 39.02
}
Training configuration: {
"trainable parameters": 163577856,
"total samples": 69,
"train epochs": 1,
"train steps": 10,
"batches per device": 1,
"total batches observed per epoch": 69,
"train batch size": 1,
"gradient accumulation steps": 1
}
Memory before validation start: {
"memory_allocated": 39.747,
"memory_reserved": 56.266,
"max_memory_allocated": 51.867,
"max_memory_reserved": 56.266
}
Memory after validation end: {
"memory_allocated": 39.748,
"memory_reserved": 41.445,
"max_memory_allocated": 51.867,
"max_memory_reserved": 58.385
}
Memory after epoch 1: {
"memory_allocated": 39.748,
"memory_reserved": 40.91,
"max_memory_allocated": 39.748,
"max_memory_reserved": 40.91
}
Memory after training end: {
"memory_allocated": 25.288,
"memory_reserved": 27.783,
"max_memory_allocated": 39.748,
"max_memory_reserved": 40.91
}
```
LoRA with rank 128, batch size 1, gradient checkpointing, optimizer adamw, `49x512x768` resolutions, **with precomputation**:
```
Memory after precomputing conditions: {
"memory_allocated": 14.232,
"memory_reserved": 14.336,
"max_memory_allocated": 14.395,
"max_memory_reserved": 14.461
}
Memory after precomputing latents: {
"memory_allocated": 14.717,
"memory_reserved": 14.762,
"max_memory_allocated": 16.759,
"max_memory_reserved": 17.244
}
Memory before training start: {
"memory_allocated": 24.195,
"memory_reserved": 26.039,
"max_memory_allocated": 24.195,
"max_memory_reserved": 26.039
}
Training configuration: {
"trainable parameters": 163577856,
"total samples": 1,
"train epochs": 10,
"train steps": 10,
"batches per device": 1,
"total batches observed per epoch": 1,
"train batch size": 1,
"gradient accumulation steps": 1
}
Memory after epoch 1: {
"memory_allocated": 24.83,
"memory_reserved": 42.387,
"max_memory_allocated": 36.357,
"max_memory_reserved": 42.387
}
Memory before validation start: {
"memory_allocated": 24.842,
"memory_reserved": 42.387,
"max_memory_allocated": 36.977,
"max_memory_reserved": 42.387
}
Memory after validation end: {
"memory_allocated": 39.558,
"memory_reserved": 41.039,
"max_memory_allocated": 43.226,
"max_memory_reserved": 46.947
}
Memory after training end: {
"memory_allocated": 24.842,
"memory_reserved": 26.82,
"max_memory_allocated": 39.558,
"max_memory_reserved": 41.039
}
```
</details>
If you would like to use a custom dataset, refer to the dataset preparation guide [here](./assets/dataset.md).