diff --git a/ppdiffusers/README.md b/ppdiffusers/README.md
index 11b31f2ce..7141e5d3e 100644
--- a/ppdiffusers/README.md
+++ b/ppdiffusers/README.md
@@ -20,6 +20,8 @@
**PPDiffusers**是一款支持多种模态（如文本图像跨模态、图像、语音）扩散模型（Diffusion Model）训练和推理的国产化工具箱，依托于[**PaddlePaddle**](https://www.paddlepaddle.org.cn/)框架和[**PaddleNLP**](https://github.com/PaddlePaddle/PaddleNLP)自然语言处理开发库。
## News 📢
+* 🔥 **2024.10.18 发布 0.29.0 版本，新增图像生成模型[Stable Diffusion 3 (SD3)](https://github.com/PaddlePaddle/PaddleMIX/blob/develop/ppdiffusers/examples/text_to_image/README_sd3.md)，支持DreamBooth训练及高性能推理；SD3、SDXL适配昇腾910B，提供国产计算芯片上的训推能力；DIT支持[高性能推理](https://github.com/PaddlePaddle/PaddleMIX/blob/develop/ppdiffusers/examples/class_conditional_image_generation/DiT/README.md#23-paddle-inference-%E9%AB%98%E6%80%A7%E8%83%BD%E6%8E%A8%E7%90%86)；支持PaddleNLP 3.0 beta版本。**
+
* 🔥 **2024.07.15 发布 0.24.1 版本，新增[Open-Sora](https://github.com/PaddlePaddle/PaddleMIX/tree/develop/ppdiffusers/examples/Open-Sora)，支持模型训练和推理；全面支持Paddle 3.0。**
* 🔥 **2024.04.17 发布 0.24.0 版本，支持[Sora相关技术](https://github.com/PaddlePaddle/PaddleMIX/tree/develop/ppdiffusers/examples/sora)，支持[DiT](https://github.com/PaddlePaddle/PaddleMIX/tree/develop/ppdiffusers/examples/class_conditional_image_generation/DiT)、[SiT](https://github.com/PaddlePaddle/PaddleMIX/tree/develop/ppdiffusers/examples/class_conditional_image_generation/DiT#exploring-flow-and-diffusion-based-generative-models-with-scalable-interpolant-transformers-sit)、[UViT](https://github.com/PaddlePaddle/PaddleMIX/tree/develop/ppdiffusers/examples/text_to_image_mscoco_uvit)训练推理，新增[NaViT](https://github.com/PaddlePaddle/PaddleMIX/tree/develop/ppdiffusers/examples/navit)、[MAGVIT-v2](https://github.com/PaddlePaddle/PaddleMIX/tree/develop/ppdiffusers/examples/video_tokenizer/magvit2)模型；
@@ -38,11 +40,6 @@ Stable Diffusion支持[BF16 O2训练](https://github.com/PaddlePaddle/PaddleMIX/
[LoRA加载升级](#加载HF-LoRA权重)，支持加载SDXL的LoRA权重；
[Controlnet](https://github.com/PaddlePaddle/PaddleMIX/tree/develop/ppdiffusers/ppdiffusers/pipelines/controlnet)升级，支持ControlNetImg2Img、ControlNetInpaint、StableDiffusionXLControlNet等。**
-* 🔥 **2023.06.20 发布 0.16.1 版本，新增[T2I-Adapter](https://github.com/PaddlePaddle/PaddleMIX/tree/develop/ppdiffusers/examples/t2i-adapter)，支持训练与推理；ControlNet升级，支持[reference only推理](https://github.com/PaddlePaddle/PaddleMIX/tree/develop/ppdiffusers/examples/community#controlnet-reference-only)；新增[WebUIStableDiffusionPipeline](https://github.com/PaddlePaddle/PaddleMIX/tree/develop/ppdiffusers/examples/community#automatic1111-webui-stable-diffusion)，
-支持通过prompt的方式动态加载lora、textual_inversion权重；
-新增[StableDiffusionHiresFixPipeline](https://github.com/PaddlePaddle/PaddleMIX/tree/develop/ppdiffusers/examples/community#stable-diffusion-with-high-resolution-fixing)，支持高分辨率修复；
-新增关键点控制生成任务评价指标[COCOeval](https://github.com/PaddlePaddle/PaddleMIX/tree/develop/ppdiffusers/scripts/cocoeval_keypoints_score)；
-新增多种模态扩散模型Pipeline，包括视频生成（[Text-to-Video-Synth](#文本视频多模)、[Text-to-Video-Zero](#文本视频多模)）、音频生成（[AudioLDM](#文本音频多模)、[Spectrogram Diffusion](#音频)）；新增文图生成模型[IF](#文本图像多模)。**
diff --git a/ppdiffusers/VERSION b/ppdiffusers/VERSION
index 1fee94775..beb3a3f6f 100644
--- a/ppdiffusers/VERSION
+++ b/ppdiffusers/VERSION
@@ -1 +1 @@
-0.24.1
\ No newline at end of file
+0.29.0
\ No newline at end of file
diff --git a/ppdiffusers/deploy/sd3/README.md b/ppdiffusers/deploy/sd3/README.md
index 7e883dd59..b3d7f19b2 100644
--- a/ppdiffusers/deploy/sd3/README.md
+++ b/ppdiffusers/deploy/sd3/README.md
@@ -52,6 +52,7 @@ python -m paddle.distributed.launch --gpus 0,1 text_to_image_generation-stable_d
```
## 在 NVIDIA A800-SXM4-80GB 上测试的性能如下：
-| Paddle batch parallel | Paddle Single Card | PyTorch | Paddle 动态图 |
-| --------------------- | ------------------ | --------- | ------------ |
-| 0.86 s | 1.2 s | 1.78 s | 4.202 s |
+
+| Paddle batch parallel | Paddle Single Card | PyTorch | TensorRT | Paddle 动态图 |
+| --------------------- | ------------------ | --------- | -------- | ------------ |
+| 0.86 s | 1.2 s | 1.78 s | 1.16 s | 4.202 s |⬤
\ No newline at end of file
diff --git a/ppdiffusers/deploy/sd3/text_to_image_generation-stable_diffusion_3.py b/ppdiffusers/deploy/sd3/text_to_image_generation-stable_diffusion_3.py
new file mode 100644
index 000000000..982e341b8
--- /dev/null
+++ b/ppdiffusers/deploy/sd3/text_to_image_generation-stable_diffusion_3.py
@@ -0,0 +1,145 @@
+# Copyright (c) 2024 PaddlePaddle Authors. All Rights Reserved.
+#
+# 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 os
+import argparse
+import paddle
+def parse_args():
+ parser = argparse.ArgumentParser(
+ description=" Use PaddleMIX to accelerate the Stable Diffusion3 image generation model."
+ )
+ parser.add_argument(
+ "--benchmark",
+ type=(lambda x: str(x).lower() in ["true", "1", "yes"]),
+ default=False,
+ help="if set to True, measure inference performance",
+ )
+ parser.add_argument(
+ "--inference_optimize",
+ type=(lambda x: str(x).lower() in ["true", "1", "yes"]),
+ default=False,
+ help="If set to True, all optimizations except Triton are enabled.",
+ )
+ parser.add_argument(
+ "--inference_optimize_bp",
+ type=(lambda x: str(x).lower() in ["true", "1", "yes"]),
+ default=False,
+ help="If set to True, batch parallel is enabled in DIT and dual-GPU acceleration is used.",
+ )
+ parser.add_argument("--height", type=int, default=512, help="Height of the generated image.")
+ parser.add_argument("--width", type=int, default=512, help="Width of the generated image.")
+ parser.add_argument("--num-inference-steps", type=int, default=50, help="Number of inference steps.")
+ parser.add_argument("--dtype", type=str, default="float32", help="Inference data types.")
+
+ return parser.parse_args()
+
+
+args = parse_args()
+
+if args.inference_optimize:
+ os.environ["INFERENCE_OPTIMIZE"] = "True"
+ os.environ["INFERENCE_OPTIMIZE_TRITON"] = "True"
+if args.inference_optimize_bp:
+ os.environ["INFERENCE_OPTIMIZE_BP"] = "True"
+if args.dtype == "float32":
+ inference_dtype = paddle.float32
+elif args.dtype == "float16":
+ inference_dtype = paddle.float16
+
+
+if args.inference_optimize_bp:
+ from paddle.distributed import fleet
+ from paddle.distributed.fleet.utils import recompute
+ import numpy as np
+ import random
+ import paddle.distributed as dist
+ import paddle.distributed.fleet as fleet
+ strategy = fleet.DistributedStrategy()
+ model_parallel_size = 2
+ data_parallel_size = 1
+ strategy.hybrid_configs = {
+ "dp_degree": data_parallel_size,
+ "mp_degree": model_parallel_size,
+ "pp_degree": 1
+ }
+ fleet.init(is_collective=True, strategy=strategy)
+ hcg = fleet.get_hybrid_communicate_group()
+ mp_id = hcg.get_model_parallel_rank()
+ rank_id = dist.get_rank()
+
+import datetime
+from ppdiffusers import StableDiffusion3Pipeline
+
+
+pipe = StableDiffusion3Pipeline.from_pretrained(
+ "stabilityai/stable-diffusion-3-medium-diffusers",
+ paddle_dtype=inference_dtype,
+)
+
+pipe.transformer = paddle.incubate.jit.inference(
+ pipe.transformer,
+ save_model_dir="./tmp/sd3",
+ enable_new_ir=True,
+ cache_static_model=True,
+ # V100环境下，需设置exp_enable_use_cutlass=False,
+ exp_enable_use_cutlass=True,
+ delete_pass_lists=["add_norm_fuse_pass"],
+)
+
+generator = paddle.Generator().manual_seed(42)
+prompt = "A cat holding a sign that says hello world"
+
+
+image = pipe(
+ prompt, num_inference_steps=args.num_inference_steps, width=args.width, height=args.height, generator=generator
+).images[0]
+
+if args.benchmark:
+ # warmup
+ for i in range(3):
+ image = pipe(
+ prompt,
+ num_inference_steps=args.num_inference_steps,
+ width=args.width,
+ height=args.height,
+ generator=generator,
+ ).images[0]
+
+ repeat_times = 10
+ sumtime = 0.0
+ for i in range(repeat_times):
+ paddle.device.synchronize()
+ starttime = datetime.datetime.now()
+ image = pipe(
+ prompt,
+ num_inference_steps=args.num_inference_steps,
+ width=args.width,
+ height=args.height,
+ generator=generator,
+ ).images[0]
+ paddle.device.synchronize()
+ endtime = datetime.datetime.now()
+ duringtime = endtime - starttime
+ duringtime = duringtime.seconds * 1000 + duringtime.microseconds / 1000.0
+ sumtime += duringtime
+ print("SD3 end to end time : ", duringtime, "ms")
+
+ print("SD3 ave end to end time : ", sumtime / repeat_times, "ms")
+ cuda_mem_after_used = paddle.device.cuda.max_memory_allocated() / (1024**3)
+ print(f"Max used CUDA memory : {cuda_mem_after_used:.3f} GiB")
+
+if args.inference_optimize_bp:
+ if rank_id == 0:
+ image.save("text_to_image_generation-stable_diffusion_3-result.png")
+else:
+ image.save("text_to_image_generation-stable_diffusion_3-result.png")
diff --git a/ppdiffusers/examples/controlnet/requirements.txt b/ppdiffusers/examples/controlnet/requirements.txt
index e4077be2b..72397cb3f 100644
--- a/ppdiffusers/examples/controlnet/requirements.txt
+++ b/ppdiffusers/examples/controlnet/requirements.txt
@@ -4,3 +4,5 @@ paddlenlp>=2.7.2
opencv-python
ppdiffusers>=0.24.0
cchardet
+gradio==3.16.2
+basicsr==1.4.2
diff --git a/ppdiffusers/examples/dreambooth/README_sd3.md b/ppdiffusers/examples/dreambooth/README_sd3.md
index d0b9a725b..5f4e57475 100644
--- a/ppdiffusers/examples/dreambooth/README_sd3.md
+++ b/ppdiffusers/examples/dreambooth/README_sd3.md
@@ -131,7 +131,7 @@ import paddle
pipe = StableDiffusion3Pipeline.from_pretrained(
"stabilityai/stable-diffusion-3-medium-diffusers", paddle_dtype=paddle.float16
)
-pipeline.load_lora_weights('your-lora-checkpoint')
+pipe.load_lora_weights('your-lora-checkpoint')
image = pipe("A picture of a sks dog in a bucket", num_inference_steps=25).images[0]
image.save("sks_dog_dreambooth_lora.png")
diff --git a/ppdiffusers/examples/inference/image_to_image_text_guided_generation-stable_diffusion_3.py b/ppdiffusers/examples/inference/image_to_image_text_guided_generation-stable_diffusion_3.py
index 58607d502..13b749a98 100644
--- a/ppdiffusers/examples/inference/image_to_image_text_guided_generation-stable_diffusion_3.py
+++ b/ppdiffusers/examples/inference/image_to_image_text_guided_generation-stable_diffusion_3.py
@@ -20,6 +20,6 @@
url = "https://paddlenlp.bj.bcebos.com/models/community/CompVis/stable-diffusion-v1-4/sketch-mountains-input.png"
init_image = load_image(url).resize((512, 512))
prompt = "cat wizard, gandalf, lord of the rings, detailed, fantasy, cute, adorable, Pixar, Disney, 8k"
-images = pipe(prompt=prompt, image=init_image, strength=0.95, guidance_scale=7.5).images[0]
+image = pipe(prompt=prompt, image=init_image, strength=0.95, guidance_scale=7.5).images[0]
image.save("image_to_image_text_guided_generation-stable_diffusion_3-result.png")
diff --git a/ppdiffusers/examples/inference/text_to_image_generation-stable_diffusion_3.py b/ppdiffusers/examples/inference/text_to_image_generation-stable_diffusion_3.py
index fd1784f8f..1bbf8d6a0 100644
--- a/ppdiffusers/examples/inference/text_to_image_generation-stable_diffusion_3.py
+++ b/ppdiffusers/examples/inference/text_to_image_generation-stable_diffusion_3.py
@@ -1,4 +1,4 @@
-# Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
+# Copyright (c) 2024 PaddlePaddle Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
@@ -11,134 +11,13 @@
# 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 os
-import argparse
-import paddle
-def parse_args():
- parser = argparse.ArgumentParser(
- description=" Use PaddleMIX to accelerate the Stable Diffusion3 image generation model."
- )
- parser.add_argument(
- "--benchmark",
- type=(lambda x: str(x).lower() in ["true", "1", "yes"]),
- default=False,
- help="if set to True, measure inference performance",
- )
- parser.add_argument(
- "--inference_optimize",
- type=(lambda x: str(x).lower() in ["true", "1", "yes"]),
- default=False,
- help="If set to True, all optimizations except Triton are enabled.",
- )
- parser.add_argument(
- "--inference_optimize_bp",
- type=(lambda x: str(x).lower() in ["true", "1", "yes"]),
- default=False,
- help="If set to True, batch parallel is enabled in DIT and dual-GPU acceleration is used.",
- )
- parser.add_argument("--height", type=int, default=512, help="Height of the generated image.")
- parser.add_argument("--width", type=int, default=512, help="Width of the generated image.")
- parser.add_argument("--num-inference-steps", type=int, default=50, help="Number of inference steps.")
- parser.add_argument("--dtype", type=str, default="float32", help="Inference data types.")
-
- return parser.parse_args()
-
-
-args = parse_args()
-
-if args.inference_optimize:
- os.environ["INFERENCE_OPTIMIZE"] = "True"
- os.environ["INFERENCE_OPTIMIZE_TRITON"] = "True"
-if args.inference_optimize_bp:
- os.environ["INFERENCE_OPTIMIZE_BP"] = "True"
-if args.dtype == "float32":
- inference_dtype = paddle.float32
-elif args.dtype == "float16":
- inference_dtype = paddle.float16
-
-if args.inference_optimize_bp:
- from paddle.distributed import fleet
- from paddle.distributed.fleet.utils import recompute
- import numpy as np
- import random
- import paddle.distributed as dist
- import paddle.distributed.fleet as fleet
- strategy = fleet.DistributedStrategy()
- model_parallel_size = 2
- data_parallel_size = 1
- strategy.hybrid_configs = {
- "dp_degree": data_parallel_size,
- "mp_degree": model_parallel_size,
- "pp_degree": 1
- }
- fleet.init(is_collective=True, strategy=strategy)
- hcg = fleet.get_hybrid_communicate_group()
- mp_id = hcg.get_model_parallel_rank()
- rank_id = dist.get_rank()
-
-import datetime
+import paddle
from ppdiffusers import StableDiffusion3Pipeline
-
-
pipe = StableDiffusion3Pipeline.from_pretrained(
- "stabilityai/stable-diffusion-3-medium-diffusers",
- paddle_dtype=inference_dtype,
+ "stabilityai/stable-diffusion-3-medium-diffusers", paddle_dtype=paddle.float16
)
-
-pipe.transformer = paddle.incubate.jit.inference(
- pipe.transformer,
- save_model_dir="./tmp/sd3",
- enable_new_ir=True,
- cache_static_model=True,
- exp_enable_use_cutlass=True,
- delete_pass_lists=["add_norm_fuse_pass"],
-)
-
generator = paddle.Generator().manual_seed(42)
prompt = "A cat holding a sign that says hello world"
-
-
-image = pipe(
- prompt, num_inference_steps=args.num_inference_steps, width=args.width, height=args.height, generator=generator
-).images[0]
-
-if args.benchmark:
- # warmup
- for i in range(3):
- image = pipe(
- prompt,
- num_inference_steps=args.num_inference_steps,
- width=args.width,
- height=args.height,
- generator=generator,
- ).images[0]
-
- repeat_times = 10
- sumtime = 0.0
- for i in range(repeat_times):
- paddle.device.synchronize()
- starttime = datetime.datetime.now()
- image = pipe(
- prompt,
- num_inference_steps=args.num_inference_steps,
- width=args.width,
- height=args.height,
- generator=generator,
- ).images[0]
- paddle.device.synchronize()
- endtime = datetime.datetime.now()
- duringtime = endtime - starttime
- duringtime = duringtime.seconds * 1000 + duringtime.microseconds / 1000.0
- sumtime += duringtime
- print("SD3 end to end time : ", duringtime, "ms")
-
- print("SD3 ave end to end time : ", sumtime / repeat_times, "ms")
- cuda_mem_after_used = paddle.device.cuda.max_memory_allocated() / (1024**3)
- print(f"Max used CUDA memory : {cuda_mem_after_used:.3f} GiB")
-
-if args.inference_optimize_bp:
- if rank_id == 0:
- image.save("text_to_image_generation-stable_diffusion_3-result.png")
-else:
- image.save("text_to_image_generation-stable_diffusion_3-result.png")
+image = pipe(prompt, generator=generator).images[0]
+image.save("text_to_image_generation-stable_diffusion_3-result.png")
\ No newline at end of file
diff --git a/ppdiffusers/examples/inference/sd15_infer_demo.py b/ppdiffusers/examples/inference/text_to_image_generation-stable_diffusion_paddle_inference.py
similarity index 100%
rename from ppdiffusers/examples/inference/sd15_infer_demo.py
rename to ppdiffusers/examples/inference/text_to_image_generation-stable_diffusion_paddle_inference.py
diff --git a/ppdiffusers/examples/kandinsky2_2/text_to_image/README.md b/ppdiffusers/examples/kandinsky2_2/text_to_image/README.md
index dd7584bfc..dbb0b87b5 100644
--- a/ppdiffusers/examples/kandinsky2_2/text_to_image/README.md
+++ b/ppdiffusers/examples/kandinsky2_2/text_to_image/README.md
@@ -124,7 +124,7 @@ prior_components = {"prior_" + k: v for k,v in pipe_prior.components.items()}
pipe = KandinskyV22CombinedPipeline.from_pretrained("kandinsky-community/kandinsky-2-2-decoder", **prior_components)
prompt='A robot pokemon, 4k photo'
-images = pipe(prompt=prompt, negative_prompt=negative_prompt).images
+images = pipe(prompt=prompt).images
images[0]
```
diff --git a/ppdiffusers/examples/text_to_image/README_sd3.md b/ppdiffusers/examples/text_to_image/README_sd3.md
new file mode 100644
index 000000000..426fe61fc
--- /dev/null
+++ b/ppdiffusers/examples/text_to_image/README_sd3.md
@@ -0,0 +1,41 @@
+# Stable Diffusion 3 (SD3)
+
+Stable Diffusion 3（SD3）是一种多模态扩散Transformer（MMDiT）文本生成图像模型，具有显著提升的图像质量、排版能力、复杂提示理解能力和资源效率。该模型能够根据文本提示生成高质量的图像。
+
+
+
+与之前的版本相比，SD3 进行了以下两项重大改进：
+
+1. **训练目标优化**：采用整流（rectified flow）替代原先DDPM中的训练目标，提升了训练效果。
+2. **去噪模型升级**：将去噪模型从U-Net更换为更适合处理多模态信息的MM-DiT，增强了模型的多模态处理能力。
+
+此外，SD3 在模型结构和训练目标上还进行了多项细微优化，包括调整训练噪声采样分布，并采用了三个固定的预训练文本编码器（OpenCLIP-ViT/G、CLIP-ViT/L 和 T5-xxl）。
+
+
+ 
+
+SD3模型结构图
+
+## 快速体验
+
+想要快速体验 SD3 模型，可以参考以下推理示例：
+
+- **文本生成图像**：[SD3 文本生成图像推理示例](https://github.com/PaddlePaddle/PaddleMIX/blob/develop/ppdiffusers/examples/inference/text_to_image_generation-stable_diffusion_3.py)
+- **图像生成图像**：[SD3 图像生成图像推理示例](https://github.com/PaddlePaddle/PaddleMIX/blob/develop/ppdiffusers/examples/inference/image_to_image_text_guided_generation-stable_diffusion_3.py)
+
+## 个性化微调
+
+PPDiffusers 提供了 SD3 的个性化微调训练示例，仅需少量主题图像即可定制专属的 SD3 模型。支持以下微调方式：
+
+- **DreamBooth LoRA 微调**
+- **DreamBooth 全参数微调**
+
+同时，支持在 NPU 硬件上进行训练。具体示例请参考：[DreamBooth 训练示例：Stable Diffusion 3 (SD3)](https://github.com/PaddlePaddle/PaddleMIX/blob/develop/ppdiffusers/examples/dreambooth/README_sd3.md)。
+
+## 高性能推理
+
+在推理方面，SD3 提供了高性能的推理实现，支持多卡并行推理。与竞品 TensorRT 相比，性能提升了 25.9%。具体内容请参考：[Stable Diffusion 3 高性能推理](https://github.com/PaddlePaddle/PaddleMIX/tree/develop/ppdiffusers/deploy/sd3)。
+
+---
+
+欢迎使用 Stable Diffusion 3，期待您的反馈与贡献！
\ No newline at end of file
diff --git a/ppdiffusers/ppdiffusers/version.py b/ppdiffusers/ppdiffusers/version.py
index 618e5abbb..4d0c3aa1e 100644
--- a/ppdiffusers/ppdiffusers/version.py
+++ b/ppdiffusers/ppdiffusers/version.py
@@ -14,4 +14,4 @@
# this file will be generated by tools
# please not modify it.
-VERSION = "0.24.1"
\ No newline at end of file
+VERSION = "0.29.0"
\ No newline at end of file
diff --git a/ppdiffusers/tests/pipelines/stable_diffusion_2/test_stable_diffusion_diffedit.py b/ppdiffusers/tests/pipelines/stable_diffusion_2/test_stable_diffusion_diffedit.py
index 57ebbe39d..88ab7d6d1 100644
--- a/ppdiffusers/tests/pipelines/stable_diffusion_2/test_stable_diffusion_diffedit.py
+++ b/ppdiffusers/tests/pipelines/stable_diffusion_2/test_stable_diffusion_diffedit.py
@@ -264,7 +264,7 @@ def setUpClass(cls):
def test_stable_diffusion_diffedit_full(self):
generator = paddle.Generator().manual_seed(seed=0)
pipe = StableDiffusionDiffEditPipeline.from_pretrained(
- "stabilityai/stable-diffusion-2", safety_checker=None, paddle_dtype="float16"
+ "stabilityai/stable-diffusion-2", safety_checker=None, paddle_dtype=paddle.float16
)
pipe.scheduler = DDIMScheduler.from_config(pipe.scheduler.config)
pipe.inverse_scheduler = DDIMInverseScheduler.from_config(pipe.scheduler.config)
@@ -299,7 +299,7 @@ def test_stable_diffusion_diffedit_full(self):
def test_stable_diffusion_diffedit_dpm(self):
generator = paddle.Generator().manual_seed(seed=0)
pipe = StableDiffusionDiffEditPipeline.from_pretrained(
- "stabilityai/stable-diffusion-2", safety_checker=None, torch_dtype="float16"
+ "stabilityai/stable-diffusion-2", safety_checker=None, paddle_dtype=paddle.float16
)
pipe.scheduler = DPMSolverMultistepScheduler.from_config(pipe.scheduler.config)
pipe.inverse_scheduler = DPMSolverMultistepInverseScheduler.from_config(pipe.scheduler.config)