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| author | Volpeon <git@volpeon.ink> | 2023-01-17 08:13:39 +0100 |
|---|---|---|
| committer | Volpeon <git@volpeon.ink> | 2023-01-17 08:13:39 +0100 |
| commit | 1abbfd5215a99dba9d699e91baec00e6f02a0bd5 (patch) | |
| tree | 670e846b3c08bd8957955ea56d3a4c4b58a8ad6f /training | |
| parent | Update (diff) | |
| download | textual-inversion-diff-1abbfd5215a99dba9d699e91baec00e6f02a0bd5.tar.gz textual-inversion-diff-1abbfd5215a99dba9d699e91baec00e6f02a0bd5.tar.bz2 textual-inversion-diff-1abbfd5215a99dba9d699e91baec00e6f02a0bd5.zip | |
Update
Diffstat (limited to 'training')
| -rw-r--r-- | training/strategy/dreambooth.py | 8 | ||||
| -rw-r--r-- | training/strategy/ti.py | 8 |
2 files changed, 8 insertions, 8 deletions
diff --git a/training/strategy/dreambooth.py b/training/strategy/dreambooth.py index bc26ee6..d813b49 100644 --- a/training/strategy/dreambooth.py +++ b/training/strategy/dreambooth.py | |||
| @@ -88,7 +88,7 @@ def dreambooth_strategy_callbacks( | |||
| 88 | ema_unet = None | 88 | ema_unet = None |
| 89 | 89 | ||
| 90 | def ema_context(): | 90 | def ema_context(): |
| 91 | if use_ema: | 91 | if ema_unet is not None: |
| 92 | return ema_unet.apply_temporary(unet.parameters()) | 92 | return ema_unet.apply_temporary(unet.parameters()) |
| 93 | else: | 93 | else: |
| 94 | return nullcontext() | 94 | return nullcontext() |
| @@ -102,7 +102,7 @@ def dreambooth_strategy_callbacks( | |||
| 102 | text_encoder.text_model.embeddings.persist() | 102 | text_encoder.text_model.embeddings.persist() |
| 103 | text_encoder.text_model.embeddings.temp_token_embedding.requires_grad_(False) | 103 | text_encoder.text_model.embeddings.temp_token_embedding.requires_grad_(False) |
| 104 | 104 | ||
| 105 | if use_ema: | 105 | if ema_unet is not None: |
| 106 | ema_unet.to(accelerator.device) | 106 | ema_unet.to(accelerator.device) |
| 107 | 107 | ||
| 108 | @contextmanager | 108 | @contextmanager |
| @@ -134,11 +134,11 @@ def dreambooth_strategy_callbacks( | |||
| 134 | 134 | ||
| 135 | @torch.no_grad() | 135 | @torch.no_grad() |
| 136 | def on_after_optimize(lr: float): | 136 | def on_after_optimize(lr: float): |
| 137 | if use_ema: | 137 | if ema_unet is not None: |
| 138 | ema_unet.step(unet.parameters()) | 138 | ema_unet.step(unet.parameters()) |
| 139 | 139 | ||
| 140 | def on_log(): | 140 | def on_log(): |
| 141 | if use_ema: | 141 | if ema_unet is not None: |
| 142 | return {"ema_decay": ema_unet.decay} | 142 | return {"ema_decay": ema_unet.decay} |
| 143 | return {} | 143 | return {} |
| 144 | 144 | ||
diff --git a/training/strategy/ti.py b/training/strategy/ti.py index 597abd0..081180f 100644 --- a/training/strategy/ti.py +++ b/training/strategy/ti.py | |||
| @@ -88,7 +88,7 @@ def textual_inversion_strategy_callbacks( | |||
| 88 | ema_embeddings = None | 88 | ema_embeddings = None |
| 89 | 89 | ||
| 90 | def ema_context(): | 90 | def ema_context(): |
| 91 | if use_ema: | 91 | if ema_embeddings is not None: |
| 92 | return ema_embeddings.apply_temporary( | 92 | return ema_embeddings.apply_temporary( |
| 93 | text_encoder.text_model.embeddings.temp_token_embedding.parameters() | 93 | text_encoder.text_model.embeddings.temp_token_embedding.parameters() |
| 94 | ) | 94 | ) |
| @@ -101,7 +101,7 @@ def textual_inversion_strategy_callbacks( | |||
| 101 | def on_prepare(): | 101 | def on_prepare(): |
| 102 | text_encoder.text_model.embeddings.temp_token_embedding.requires_grad_(True) | 102 | text_encoder.text_model.embeddings.temp_token_embedding.requires_grad_(True) |
| 103 | 103 | ||
| 104 | if use_ema: | 104 | if ema_embeddings is not None: |
| 105 | ema_embeddings.to(accelerator.device) | 105 | ema_embeddings.to(accelerator.device) |
| 106 | 106 | ||
| 107 | if gradient_checkpointing: | 107 | if gradient_checkpointing: |
| @@ -120,7 +120,7 @@ def textual_inversion_strategy_callbacks( | |||
| 120 | yield | 120 | yield |
| 121 | 121 | ||
| 122 | def on_after_optimize(lr: float): | 122 | def on_after_optimize(lr: float): |
| 123 | if use_ema: | 123 | if ema_embeddings is not None: |
| 124 | ema_embeddings.step(text_encoder.text_model.embeddings.temp_token_embedding.parameters()) | 124 | ema_embeddings.step(text_encoder.text_model.embeddings.temp_token_embedding.parameters()) |
| 125 | 125 | ||
| 126 | @torch.no_grad() | 126 | @torch.no_grad() |
| @@ -132,7 +132,7 @@ def textual_inversion_strategy_callbacks( | |||
| 132 | ) | 132 | ) |
| 133 | 133 | ||
| 134 | def on_log(): | 134 | def on_log(): |
| 135 | if use_ema: | 135 | if ema_embeddings is not None: |
| 136 | return {"ema_decay": ema_embeddings.decay} | 136 | return {"ema_decay": ema_embeddings.decay} |
| 137 | return {} | 137 | return {} |
| 138 | 138 | ||