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Aryan
@@ -148,12 +148,6 @@ export_to_video(video, "output.mp4", fps=8)
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LoRA with rank 128, batch size 1, gradient checkpointing, optimizer adamw, `49x512x768` resolution, **without precomputation**:
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```
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Memory before training start: {
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"memory_allocated": 13.486,
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"memory_reserved": 13.879,
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"max_memory_allocated": 13.486,
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"max_memory_reserved": 13.879
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}
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Training configuration: {
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"trainable parameters": 117440512,
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"total samples": 69,
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@@ -164,53 +158,21 @@ Training configuration: {
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"train batch size": 1,
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"gradient accumulation steps": 1
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}
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Memory before validation start: {
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"memory_allocated": 14.146,
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"memory_reserved": 16.809,
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"max_memory_allocated": 15.527,
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"max_memory_reserved": 17.623
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}
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Memory after validation end: {
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"memory_allocated": 14.146,
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"memory_reserved": 14.627,
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"max_memory_allocated": 15.527,
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"max_memory_reserved": 17.623
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}
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Memory after epoch 1: {
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"memory_allocated": 14.146,
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"memory_reserved": 14.627,
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"max_memory_allocated": 15.527,
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"max_memory_reserved": 17.623
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}
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Memory after training end: {
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"memory_allocated": 4.461,
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"memory_reserved": 5.014,
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"max_memory_allocated": 15.527,
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"max_memory_reserved": 17.623
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}
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```
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| stage | memory_allocated | max_memory_reserved |
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|:-----------------------:|:----------------:|:-------------------:|
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| before training start | 13.486 | 13.879 |
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| before validation start | 14.146 | 17.623 |
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| after validation end | 14.146 | 17.623 |
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| after epoch 1 | 14.146 | 17.623 |
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| after training end | 4.461 | 17.623 |
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Note: requires about `18` GB of VRAM without precomputation.
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LoRA with rank 128, batch size 1, gradient checkpointing, optimizer adamw, `49x512x768` resolution, **with precomputation**:
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```
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Memory after precomputing conditions: {
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"memory_allocated": 8.88,
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"memory_reserved": 8.895,
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"max_memory_allocated": 8.897,
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"max_memory_reserved": 8.92
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}
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Memory after precomputing latents: {
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"memory_allocated": 9.684,
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"memory_reserved": 9.807,
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"max_memory_allocated": 11.155,
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"max_memory_reserved": 11.613
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}
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Memory before training start: {
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"memory_allocated": 3.809,
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"memory_reserved": 10.01,
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"max_memory_allocated": 9.684,
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"max_memory_reserved": 10.01
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}
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Training configuration: {
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"trainable parameters": 117440512,
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"total samples": 1,
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@@ -221,32 +183,20 @@ Training configuration: {
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"train batch size": 1,
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"gradient accumulation steps": 1
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}
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Memory after epoch 1: {
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"memory_allocated": 4.26,
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"memory_reserved": 10.916,
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"max_memory_allocated": 9.684,
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"max_memory_reserved": 10.916
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}
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Memory before validation start: {
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"memory_allocated": 4.26,
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"memory_reserved": 10.916,
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"max_memory_allocated": 9.684,
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"max_memory_reserved": 10.916
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}
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Memory after validation end: {
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"memory_allocated": 13.924,
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"memory_reserved": 14.209,
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"max_memory_allocated": 15.083,
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"max_memory_reserved": 17.262
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}
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Memory after training end: {
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"memory_allocated": 4.26,
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"memory_reserved": 4.602,
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"max_memory_allocated": 13.923,
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"max_memory_reserved": 14.314
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}
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```
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| stage | memory_allocated | max_memory_reserved |
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|:-----------------------------:|:----------------:|:-------------------:|
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| after precomputing conditions | 8.88 | 8.920 |
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| after precomputing latents | 9.684 | 11.613 |
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| before training start | 3.809 | 10.010 |
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| after epoch 1 | 4.26 | 10.916 |
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| before validation start | 4.26 | 10.916 |
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| after validation end | 13.924 | 17.262 |
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| after training end | 4.26 | 14.314 |
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Note: requires about `17.5` GB of VRAM with precomputation. If validation is not performed, the memory usage is reduced to `11` GB.
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</details>
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<details>
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@@ -380,12 +330,6 @@ export_to_video(output, "output.mp4", fps=15)
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LoRA with rank 128, batch size 1, gradient checkpointing, optimizer adamw, `49x512x768` resolutions, **without precomputation**:
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```
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Memory before training start: {
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"memory_allocated": 38.889,
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"memory_reserved": 39.02,
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"max_memory_allocated": 38.889,
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"max_memory_reserved": 39.02
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}
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Training configuration: {
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"trainable parameters": 163577856,
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"total samples": 69,
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@@ -396,53 +340,21 @@ Training configuration: {
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"train batch size": 1,
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"gradient accumulation steps": 1
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}
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Memory before validation start: {
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"memory_allocated": 39.747,
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"memory_reserved": 56.266,
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"max_memory_allocated": 51.867,
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"max_memory_reserved": 56.266
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}
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Memory after validation end: {
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"memory_allocated": 39.748,
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"memory_reserved": 41.445,
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"max_memory_allocated": 51.867,
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"max_memory_reserved": 58.385
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}
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Memory after epoch 1: {
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"memory_allocated": 39.748,
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"memory_reserved": 40.91,
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"max_memory_allocated": 39.748,
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"max_memory_reserved": 40.91
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}
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Memory after training end: {
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"memory_allocated": 25.288,
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"memory_reserved": 27.783,
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"max_memory_allocated": 39.748,
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"max_memory_reserved": 40.91
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}
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```
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| stage | memory_allocated | max_memory_reserved |
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|:-----------------------:|:----------------:|:-------------------:|
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| before training start | 38.889 | 39.020 |
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| before validation start | 39.747 | 56.266 |
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| after validation end | 39.748 | 58.385 |
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| after epoch 1 | 39.748 | 40.910 |
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| after training end | 25.288 | 40.910 |
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Note: requires about `59` GB of VRAM without precomputation.
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LoRA with rank 128, batch size 1, gradient checkpointing, optimizer adamw, `49x512x768` resolutions, **with precomputation**:
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```
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Memory after precomputing conditions: {
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"memory_allocated": 14.232,
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"memory_reserved": 14.336,
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"max_memory_allocated": 14.395,
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"max_memory_reserved": 14.461
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}
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Memory after precomputing latents: {
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"memory_allocated": 14.717,
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"memory_reserved": 14.762,
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"max_memory_allocated": 16.759,
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"max_memory_reserved": 17.244
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}
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Memory before training start: {
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"memory_allocated": 24.195,
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"memory_reserved": 26.039,
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"max_memory_allocated": 24.195,
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"max_memory_reserved": 26.039
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}
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Training configuration: {
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"trainable parameters": 163577856,
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"total samples": 1,
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@@ -453,33 +365,20 @@ Training configuration: {
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"train batch size": 1,
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"gradient accumulation steps": 1
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}
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Memory after epoch 1: {
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"memory_allocated": 24.83,
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"memory_reserved": 42.387,
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"max_memory_allocated": 36.357,
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"max_memory_reserved": 42.387
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}
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Memory before validation start: {
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"memory_allocated": 24.842,
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"memory_reserved": 42.387,
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"max_memory_allocated": 36.977,
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"max_memory_reserved": 42.387
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}
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Memory after validation end: {
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"memory_allocated": 39.558,
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"memory_reserved": 41.039,
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"max_memory_allocated": 43.226,
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"max_memory_reserved": 46.947
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}
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Memory after training end: {
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"memory_allocated": 24.842,
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"memory_reserved": 26.82,
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"max_memory_allocated": 39.558,
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"max_memory_reserved": 41.039
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}
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```
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| stage | memory_allocated | max_memory_reserved |
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|:-----------------------------:|:----------------:|:-------------------:|
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| after precomputing conditions | 14.232 | 14.461 |
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| after precomputing latents | 14.717 | 17.244 |
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| before training start | 24.195 | 26.039 |
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| after epoch 1 | 24.83 | 42.387 |
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| before validation start | 24.842 | 42.387 |
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| after validation end | 39.558 | 46.947 |
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| after training end | 24.842 | 41.039 |
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Note: requires about `47` GB of VRAM with precomputation. If validation is not performed, the memory usage is reduced to about `42` GB.
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</details>
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If you would like to use a custom dataset, refer to the dataset preparation guide [here](./assets/dataset.md).
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