update

[docs] Fix missing API function (#6604 )
fix?
2024-01-18 10:14:04 +00:00 · 2024-01-17 13:59:09 -08:00 · 2024-01-17 20:11:45 +05:30 · 2024-01-17 19:25:30 +05:30
3 changed files with 21 additions and 13 deletions
@@ -33,6 +33,9 @@ model = AutoencoderKL.from_single_file(url)
 ## AutoencoderKL

 [[autodoc]] AutoencoderKL
+    - decode
+    - encode
+    - all

 ## AutoencoderKLOutput

@@ -1279,7 +1279,7 @@ def main(args):
        for name, param in text_encoder_one.named_parameters():
            if "token_embedding" in name:
                # ensure that dtype is float32, even if rest of the model that isn't trained is loaded in fp16
-                param = param.to(dtype=torch.float32)
+                param.data = param.to(dtype=torch.float32)
                param.requires_grad = True
                text_lora_parameters_one.append(param)
            else:
@@ -1288,7 +1288,7 @@ def main(args):
        for name, param in text_encoder_two.named_parameters():
            if "token_embedding" in name:
                # ensure that dtype is float32, even if rest of the model that isn't trained is loaded in fp16
-                param = param.to(dtype=torch.float32)
+                param.data = param.to(dtype=torch.float32)
                param.requires_grad = True
                text_lora_parameters_two.append(param)
            else:
@@ -1725,19 +1725,19 @@ def main(args):
        num_train_epochs_text_encoder = int(args.train_text_encoder_frac * args.num_train_epochs)
    elif args.train_text_encoder_ti:  # args.train_text_encoder_ti
        num_train_epochs_text_encoder = int(args.train_text_encoder_ti_frac * args.num_train_epochs)
-
+    # flag used for textual inversion
+    pivoted = False
    for epoch in range(first_epoch, args.num_train_epochs):
        # if performing any kind of optimization of text_encoder params
        if args.train_text_encoder or args.train_text_encoder_ti:
            if epoch == num_train_epochs_text_encoder:
                print("PIVOT HALFWAY", epoch)
                # stopping optimization of text_encoder params
-                # re setting the optimizer to optimize only on unet params
-                optimizer.param_groups[1]["lr"] = 0.0
-                optimizer.param_groups[2]["lr"] = 0.0
+                # this flag is used to reset the optimizer to optimize only on unet params
+                pivoted = True

            else:
-                # still optimizng the text encoder
+                # still optimizing the text encoder
                text_encoder_one.train()
                text_encoder_two.train()
                # set top parameter requires_grad = True for gradient checkpointing works
@@ -1747,6 +1747,12 @@ def main(args):

        unet.train()
        for step, batch in enumerate(train_dataloader):
+            if pivoted:
+                # stopping optimization of text_encoder params
+                # re setting the optimizer to optimize only on unet params
+                optimizer.param_groups[1]["lr"] = 0.0
+                optimizer.param_groups[2]["lr"] = 0.0
+
            with accelerator.accumulate(unet):
                prompts = batch["prompts"]
                # encode batch prompts when custom prompts are provided for each image -
@@ -1885,8 +1891,7 @@ def main(args):

                # every step, we reset the embeddings to the original embeddings.
                if args.train_text_encoder_ti:
-                    for idx, text_encoder in enumerate(text_encoders):
-                        embedding_handler.retract_embeddings()
+                    embedding_handler.retract_embeddings()

            # Checks if the accelerator has performed an optimization step behind the scenes
            if accelerator.sync_gradients:
@@ -519,10 +519,10 @@ def export_to_video(video_frames: List[np.ndarray], output_video_path: str = Non


 def load_hf_numpy(path) -> np.ndarray:
-    if not path.startswith("http://") or path.startswith("https://"):
-        path = Path(
-            "https://huggingface.co/datasets/fusing/diffusers-testing/resolve/main", urllib.parse.quote(path)
-        ).as_posix()
+    base_url = "https://huggingface.co/datasets/fusing/diffusers-testing/resolve/main"
+
+    if not path.startswith("http://") and not path.startswith("https://"):
+        path = os.path.join(base_url, urllib.parse.quote(path))

    return load_numpy(path)
Author	SHA1	Message	Date
Dhruv Nair	50a96ca719	update	2024-01-18 10:14:04 +00:00
Steven Liu	5ca062e011	[docs] Fix missing API function (#6604 ) fix?	2024-01-17 13:59:09 -08:00
Linoy Tsaban	619e3ab6f6	[bug fix] advanced dreambooth lora sdxl - fixes bugs described in #6486 (#6599 ) * fixes bugs: 1. redundant retraction 2. param clone 3. stopping optimization of text encoder params * param upscaling * style	2024-01-17 20:11:45 +05:30
Patrick von Platen	9e2804f720	Update pr_test_peft_backend.yml to use 1 process for testing (#6613 )	2024-01-17 19:25:30 +05:30