[Training] Add datasets version of LCM LoRA SDXL (huggingface#5778)

* add: script to train lcm lora for sdxl with 🤗 datasets * suit up the args. * remove comments. * fix num_update_steps * fix batch unmarshalling * fix num_update_steps_per_epoch * fix; dataloading. * fix microconditions. * unconditional predictions debug * fix batch size. * no need to use use_auth_token * Apply suggestions from code review Co-authored-by: Suraj Patil <[email protected]> * make vae encoding batch size an arg * final serialization in kohya * style * state dict rejigging * feat: no separate teacher unet. * debug * fix state dict serialization * debug * debug * debug * remove prints. * remove kohya utility and make style * fix serialization * fix * add test * add peft dependency. * add: peft * remove peft * autocast device determination from accelerator * autocast * reduce lora rank. * remove unneeded space * Apply suggestions from code review Co-authored-by: Suraj Patil <[email protected]> * style * remove prompt dropout. * also save in native diffusers ckpt format. * debug * debug * debug * better formation of the null embeddings. * remove space. * autocast fixes. * autocast fix. * hacky * remove lora_sayak * Apply suggestions from code review Co-authored-by: Younes Belkada <[email protected]> * style * make log validation leaner. * move back enabled in. * fix: log_validation call. * add: checkpointing tests * taking my chances to see if disabling autocasting has any effect? * start debugging * name * name * name * more debug * more debug * index * remove index. * print length * print length * print length * move unet.train() after add_adapter() * disable some prints. * enable_adapters() manually. * remove prints. * some changes. * fix params_to_optimize * more fixes * debug * debug * remove print * disable grad for certain contexts. * Add support for IPAdapterFull (huggingface#5911) * Add support for IPAdapterFull Co-authored-by: Patrick von Platen <[email protected]> --------- Co-authored-by: YiYi Xu <[email protected]> Co-authored-by: Patrick von Platen <[email protected]> * Fix a bug in `add_noise` function (huggingface#6085) * fix * copies --------- Co-authored-by: yiyixuxu <yixu310@gmail,com> * [Advanced Diffusion Script] Add Widget default text (huggingface#6100) add widget * [Advanced Training Script] Fix pipe example (huggingface#6106) * IP-Adapter for StableDiffusionControlNetImg2ImgPipeline (huggingface#5901) * adapter for StableDiffusionControlNetImg2ImgPipeline * fix-copies * fix-copies --------- Co-authored-by: Sayak Paul <[email protected]> * IP adapter support for most pipelines (huggingface#5900) * support ip-adapter in src/diffusers/pipelines/stable_diffusion/pipeline_stable_diffusion_upscale.py * support ip-adapter in src/diffusers/pipelines/stable_diffusion/pipeline_stable_diffusion_attend_and_excite.py * support ip-adapter in src/diffusers/pipelines/stable_diffusion/pipeline_stable_diffusion_instruct_pix2pix.py * update tests * support ip-adapter in src/diffusers/pipelines/stable_diffusion/pipeline_stable_diffusion_panorama.py * support ip-adapter in src/diffusers/pipelines/stable_diffusion/pipeline_stable_diffusion_sag.py * support ip-adapter in src/diffusers/pipelines/stable_diffusion_safe/pipeline_stable_diffusion_safe.py * support ip-adapter in src/diffusers/pipelines/latent_consistency_models/pipeline_latent_consistency_text2img.py * support ip-adapter in src/diffusers/pipelines/latent_consistency_models/pipeline_latent_consistency_img2img.py * support ip-adapter in src/diffusers/pipelines/stable_diffusion/pipeline_stable_diffusion_ldm3d.py * revert changes to sd_attend_and_excite and sd_upscale * make style * fix broken tests * update ip-adapter implementation to latest * apply suggestions from review --------- Co-authored-by: YiYi Xu <[email protected]> Co-authored-by: Sayak Paul <[email protected]> * fix: lora_alpha * make vae casting conditional/ * param upcasting * propagate comments from huggingface#6145 Co-authored-by: dg845 <[email protected]> * [Peft] fix saving / loading when unet is not "unet" (huggingface#6046) * [Peft] fix saving / loading when unet is not "unet" * Update src/diffusers/loaders/lora.py Co-authored-by: Sayak Paul <[email protected]> * undo stablediffusion-xl changes * use unet_name to get unet for lora helpers * use unet_name --------- Co-authored-by: Sayak Paul <[email protected]> * [Wuerstchen] fix fp16 training and correct lora args (huggingface#6245) fix fp16 training Co-authored-by: Sayak Paul <[email protected]> * [docs] fix: animatediff docs (huggingface#6339) fix: animatediff docs * add: note about the new script in readme_sdxl. * Revert "[Peft] fix saving / loading when unet is not "unet" (huggingface#6046)" This reverts commit 4c7e983. * Revert "[Wuerstchen] fix fp16 training and correct lora args (huggingface#6245)" This reverts commit 0bb9cf0. * Revert "[docs] fix: animatediff docs (huggingface#6339)" This reverts commit 11659a6. * remove tokenize_prompt(). * assistive comments around enable_adapters() and diable_adapters(). --------- Co-authored-by: Suraj Patil <[email protected]> Co-authored-by: Younes Belkada <[email protected]> Co-authored-by: Fabio Rigano <[email protected]> Co-authored-by: YiYi Xu <[email protected]> Co-authored-by: Patrick von Platen <[email protected]> Co-authored-by: yiyixuxu <yixu310@gmail,com> Co-authored-by: apolinário <[email protected]> Co-authored-by: Charchit Sharma <[email protected]> Co-authored-by: Aryan V S <[email protected]> Co-authored-by: dg845 <[email protected]> Co-authored-by: Kashif Rasul <[email protected]>
antoine-scenario · Jan 2, 2024 · 9594df5 · 9594df5
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diff --git a/examples/advanced_diffusion_training/train_dreambooth_lora_sdxl_advanced.py b/examples/advanced_diffusion_training/train_dreambooth_lora_sdxl_advanced.py
@@ -161,6 +161,8 @@ def save_model_card(
 base_model: {base_model}
 instance_prompt: {instance_prompt}
 license: openrail++
+widget:
+    - text: '{validation_prompt if validation_prompt else instance_prompt}'
 ---
 """
 

diff --git a/examples/consistency_distillation/README_sdxl.md b/examples/consistency_distillation/README_sdxl.md
@@ -111,4 +111,38 @@ accelerate launch train_lcm_distill_lora_sdxl_wds.py \
     --report_to=wandb \
     --seed=453645634 \
     --push_to_hub \
-```
+```
+
+We provide another version for LCM LoRA SDXL that follows best practices of `peft` and leverages the `datasets` library for quick experimentation. The script doesn't load two UNets unlike `train_lcm_distill_lora_sdxl_wds.py` which reduces the memory requirements quite a bit. 
+
+Below is an example training command that trains an LCM LoRA on the [Pokemons dataset](https://huggingface.co/datasets/lambdalabs/pokemon-blip-captions):
+
+```bash
+export MODEL_NAME="stabilityai/stable-diffusion-xl-base-1.0"
+export DATASET_NAME="lambdalabs/pokemon-blip-captions"
+export VAE_PATH="madebyollin/sdxl-vae-fp16-fix"
+
+accelerate launch train_lcm_distill_lora_sdxl.py \
+  --pretrained_teacher_model=${MODEL_NAME}  \
+  --pretrained_vae_model_name_or_path=${VAE_PATH} \
+  --output_dir="pokemons-lora-lcm-sdxl" \
+  --mixed_precision="fp16" \
+  --dataset_name=$DATASET_NAME \
+  --resolution=1024 \
+  --train_batch_size=24 \
+  --gradient_accumulation_steps=1 \
+  --gradient_checkpointing \
+  --use_8bit_adam \
+  --lora_rank=64 \
+  --learning_rate=1e-4 \
+  --report_to="wandb" \
+  --lr_scheduler="constant" \
+  --lr_warmup_steps=0 \
+  --max_train_steps=3000 \
+  --checkpointing_steps=500 \
+  --validation_steps=50 \
+  --seed="0" \
+  --report_to="wandb" \
+  --push_to_hub
+```
+
diff --git a/examples/consistency_distillation/test_lcm_lora.py b/examples/consistency_distillation/test_lcm_lora.py
@@ -0,0 +1,112 @@
+# coding=utf-8
+# Copyright 2023 HuggingFace Inc.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+import logging
+import os
+import sys
+import tempfile
+
+import safetensors
+
+
+sys.path.append("..")
+from test_examples_utils import ExamplesTestsAccelerate, run_command  # noqa: E402
+
+
+logging.basicConfig(level=logging.DEBUG)
+
+logger = logging.getLogger()
+stream_handler = logging.StreamHandler(sys.stdout)
+logger.addHandler(stream_handler)
+
+
+class TextToImageLCM(ExamplesTestsAccelerate):
+    def test_text_to_image_lcm_lora_sdxl(self):
+        with tempfile.TemporaryDirectory() as tmpdir:
+            test_args = f"""
+                examples/consistency_distillation/train_lcm_distill_lora_sdxl.py
+                --pretrained_teacher_model hf-internal-testing/tiny-stable-diffusion-xl-pipe
+                --dataset_name hf-internal-testing/dummy_image_text_data
+                --resolution 64
+                --lora_rank 4
+                --train_batch_size 1
+                --gradient_accumulation_steps 1
+                --max_train_steps 2
+                --learning_rate 5.0e-04
+                --scale_lr
+                --lr_scheduler constant
+                --lr_warmup_steps 0
+                --output_dir {tmpdir}
+                """.split()
+
+            run_command(self._launch_args + test_args)
+            # save_pretrained smoke test
+            self.assertTrue(os.path.isfile(os.path.join(tmpdir, "pytorch_lora_weights.safetensors")))
+
+            # make sure the state_dict has the correct naming in the parameters.
+            lora_state_dict = safetensors.torch.load_file(os.path.join(tmpdir, "pytorch_lora_weights.safetensors"))
+            is_lora = all("lora" in k for k in lora_state_dict.keys())
+            self.assertTrue(is_lora)
+
+    def test_text_to_image_lcm_lora_sdxl_checkpointing(self):
+        with tempfile.TemporaryDirectory() as tmpdir:
+            test_args = f"""
+                examples/consistency_distillation/train_lcm_distill_lora_sdxl.py
+                --pretrained_teacher_model hf-internal-testing/tiny-stable-diffusion-xl-pipe
+                --dataset_name hf-internal-testing/dummy_image_text_data
+                --resolution 64
+                --lora_rank 4
+                --train_batch_size 1
+                --gradient_accumulation_steps 1
+                --max_train_steps 7
+                --checkpointing_steps 2
+                --learning_rate 5.0e-04
+                --scale_lr
+                --lr_scheduler constant
+                --lr_warmup_steps 0
+                --output_dir {tmpdir}
+                """.split()
+
+            run_command(self._launch_args + test_args)
+
+            self.assertEqual(
+                {x for x in os.listdir(tmpdir) if "checkpoint" in x},
+                {"checkpoint-2", "checkpoint-4", "checkpoint-6"},
+            )
+
+            test_args = f"""
+                examples/consistency_distillation/train_lcm_distill_lora_sdxl.py
+                --pretrained_teacher_model hf-internal-testing/tiny-stable-diffusion-xl-pipe
+                --dataset_name hf-internal-testing/dummy_image_text_data
+                --resolution 64
+                --lora_rank 4
+                --train_batch_size 1
+                --gradient_accumulation_steps 1
+                --max_train_steps 9
+                --checkpointing_steps 2
+                --resume_from_checkpoint latest
+                --learning_rate 5.0e-04
+                --scale_lr
+                --lr_scheduler constant
+                --lr_warmup_steps 0
+                --output_dir {tmpdir}
+                """.split()
+
+            run_command(self._launch_args + test_args)
+
+            self.assertEqual(
+                {x for x in os.listdir(tmpdir) if "checkpoint" in x},
+                {"checkpoint-2", "checkpoint-4", "checkpoint-6", "checkpoint-8"},
+            )