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| author | Volpeon <git@volpeon.ink> | 2023-01-14 09:35:42 +0100 |
|---|---|---|
| committer | Volpeon <git@volpeon.ink> | 2023-01-14 09:35:42 +0100 |
| commit | 6c38d0088ece492696a7bc94a5cb43a48289452a (patch) | |
| tree | d84a8fefd52eba5cbf38e64d34962f34dc6d047d /training/common.py | |
| parent | Cleanup (diff) | |
| download | textual-inversion-diff-6c38d0088ece492696a7bc94a5cb43a48289452a.tar.gz textual-inversion-diff-6c38d0088ece492696a7bc94a5cb43a48289452a.tar.bz2 textual-inversion-diff-6c38d0088ece492696a7bc94a5cb43a48289452a.zip | |
Fix
Diffstat (limited to 'training/common.py')
| -rw-r--r-- | training/common.py | 2 |
1 files changed, 1 insertions, 1 deletions
diff --git a/training/common.py b/training/common.py index f5ab326..8083137 100644 --- a/training/common.py +++ b/training/common.py | |||
| @@ -184,7 +184,7 @@ def loss_step( | |||
| 184 | else: | 184 | else: |
| 185 | raise ValueError(f"Unknown prediction type {noise_scheduler.config.prediction_type}") | 185 | raise ValueError(f"Unknown prediction type {noise_scheduler.config.prediction_type}") |
| 186 | 186 | ||
| 187 | if batch["with_prior"]: | 187 | if batch["with_prior"].all(): |
| 188 | # Chunk the noise and model_pred into two parts and compute the loss on each part separately. | 188 | # Chunk the noise and model_pred into two parts and compute the loss on each part separately. |
| 189 | model_pred, model_pred_prior = torch.chunk(model_pred, 2, dim=0) | 189 | model_pred, model_pred_prior = torch.chunk(model_pred, 2, dim=0) |
| 190 | target, target_prior = torch.chunk(target, 2, dim=0) | 190 | target, target_prior = torch.chunk(target, 2, dim=0) |