Compare commits
6 Commits
| Author | SHA1 | Date | |
|---|---|---|---|
 patil-suraj
|
ea238e821b | ||
|
patil-suraj
|
b6d1d670fc | ||
|
Dhruv Nair
|
4330a747d4 | ||
|
Sayak Paul
|
76de6a09fb | ||
|
Sayak Paul
|
25caf24ef9 | ||
|
Abubakar Abid
|
8db3c9bc9f |
@@ -52,7 +52,9 @@ jobs:
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- name: Install dependencies
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run: |
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python -m pip install --upgrade pip
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pip install -U setuptools wheel twine torch
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pip install -U setuptools wheel twine
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pip install -U torch --index-url https://download.pytorch.org/whl/cpu
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pip install -U transformers
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- name: Build the dist files
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run: python setup.py bdist_wheel && python setup.py sdist
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@@ -400,14 +400,14 @@
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title: DPMSolverSDEScheduler
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- local: api/schedulers/singlestep_dpm_solver
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title: DPMSolverSinglestepScheduler
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- local: api/schedulers/edm_multistep_dpm_solver
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title: EDMDPMSolverMultistepScheduler
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- local: api/schedulers/edm_euler
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title: EDMEulerScheduler
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- local: api/schedulers/euler_ancestral
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title: EulerAncestralDiscreteScheduler
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- local: api/schedulers/euler
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title: EulerDiscreteScheduler
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- local: api/schedulers/edm_euler
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title: EDMEulerScheduler
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- local: api/schedulers/edm_multistep_dpm_solver
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title: EDMDPMSolverMultistepScheduler
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- local: api/schedulers/heun
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title: HeunDiscreteScheduler
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- local: api/schedulers/ipndm
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@@ -172,3 +172,41 @@ inpaint = StableDiffusionInpaintPipeline(**text2img.components)
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# now you can use text2img(...), img2img(...), inpaint(...) just like the call methods of each respective pipeline
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```
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### Create web demos using `gradio`
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The Stable Diffusion pipelines are automatically supported in [Gradio](https://github.com/gradio-app/gradio/), a library that makes creating beautiful and user-friendly machine learning apps on the web a breeze. First, make sure you have Gradio installed:
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```
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pip install -U gradio
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```
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Then, create a web demo around any Stable Diffusion-based pipeline. For example, you can create an image generation pipeline in a single line of code with Gradio's [`Interface.from_pipeline`](https://www.gradio.app/docs/interface#interface-from-pipeline) function:
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```py
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from diffusers import StableDiffusionPipeline
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import gradio as gr
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pipe = StableDiffusionPipeline.from_pretrained("CompVis/stable-diffusion-v1-4")
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gr.Interface.from_pipeline(pipe).launch()
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```
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which opens an intuitive drag-and-drop interface in your browser:
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Similarly, you could create a demo for an image-to-image pipeline with:
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```py
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from diffusers import StableDiffusionImg2ImgPipeline
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import gradio as gr
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pipe = StableDiffusionImg2ImgPipeline.from_pretrained("runwayml/stable-diffusion-v1-5")
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gr.Interface.from_pipeline(pipe).launch()
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```
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By default, the web demo runs on a local server. If you'd like to share it with others, you can generate a temporary public
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link by setting `share=True` in `launch()`. Or, you can host your demo on [Hugging Face Spaces](https://huggingface.co/spaces)https://huggingface.co/spaces for a permanent link.
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@@ -70,7 +70,7 @@ from diffusers.utils.import_utils import is_xformers_available
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# Will error if the minimal version of diffusers is not installed. Remove at your own risks.
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check_min_version("0.27.0.dev0")
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check_min_version("0.28.0.dev0")
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logger = get_logger(__name__)
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@@ -78,7 +78,7 @@ from diffusers.utils.torch_utils import is_compiled_module
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# Will error if the minimal version of diffusers is not installed. Remove at your own risks.
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check_min_version("0.27.0.dev0")
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check_min_version("0.28.0.dev0")
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logger = get_logger(__name__)
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@@ -40,7 +40,7 @@ from diffusers.utils import BaseOutput, check_min_version
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# Will error if the minimal version of diffusers is not installed. Remove at your own risks.
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check_min_version("0.27.0.dev0")
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check_min_version("0.28.0.dev0")
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class MarigoldDepthOutput(BaseOutput):
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@@ -72,7 +72,7 @@ if is_wandb_available():
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import wandb
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# Will error if the minimal version of diffusers is not installed. Remove at your own risks.
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check_min_version("0.27.0.dev0")
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check_min_version("0.28.0.dev0")
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logger = get_logger(__name__)
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@@ -65,7 +65,7 @@ if is_wandb_available():
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import wandb
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# Will error if the minimal version of diffusers is not installed. Remove at your own risks.
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check_min_version("0.27.0.dev0")
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check_min_version("0.28.0.dev0")
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logger = get_logger(__name__)
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@@ -78,7 +78,7 @@ if is_wandb_available():
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import wandb
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# Will error if the minimal version of diffusers is not installed. Remove at your own risks.
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check_min_version("0.27.0.dev0")
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check_min_version("0.28.0.dev0")
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logger = get_logger(__name__)
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@@ -71,7 +71,7 @@ if is_wandb_available():
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import wandb
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# Will error if the minimal version of diffusers is not installed. Remove at your own risks.
|
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check_min_version("0.27.0.dev0")
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check_min_version("0.28.0.dev0")
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|
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logger = get_logger(__name__)
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@@ -77,7 +77,7 @@ if is_wandb_available():
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import wandb
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# Will error if the minimal version of diffusers is not installed. Remove at your own risks.
|
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check_min_version("0.27.0.dev0")
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check_min_version("0.28.0.dev0")
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logger = get_logger(__name__)
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@@ -60,7 +60,7 @@ if is_wandb_available():
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import wandb
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|
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# Will error if the minimal version of diffusers is not installed. Remove at your own risks.
|
||||
check_min_version("0.27.0.dev0")
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check_min_version("0.28.0.dev0")
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||||
|
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logger = get_logger(__name__)
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|
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|
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@@ -60,7 +60,7 @@ if is_wandb_available():
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import wandb
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|
||||
# Will error if the minimal version of diffusers is not installed. Remove at your own risks.
|
||||
check_min_version("0.27.0.dev0")
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||||
check_min_version("0.28.0.dev0")
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||||
|
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logger = logging.getLogger(__name__)
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|
||||
|
||||
@@ -61,7 +61,7 @@ if is_wandb_available():
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||||
import wandb
|
||||
|
||||
# Will error if the minimal version of diffusers is not installed. Remove at your own risks.
|
||||
check_min_version("0.27.0.dev0")
|
||||
check_min_version("0.28.0.dev0")
|
||||
|
||||
logger = get_logger(__name__)
|
||||
|
||||
|
||||
@@ -63,7 +63,7 @@ from diffusers.utils.import_utils import is_xformers_available
|
||||
|
||||
|
||||
# Will error if the minimal version of diffusers is not installed. Remove at your own risks.
|
||||
check_min_version("0.27.0.dev0")
|
||||
check_min_version("0.28.0.dev0")
|
||||
|
||||
logger = get_logger(__name__)
|
||||
|
||||
|
||||
@@ -63,7 +63,7 @@ if is_wandb_available():
|
||||
import wandb
|
||||
|
||||
# Will error if the minimal version of diffusers is not installed. Remove at your own risks.
|
||||
check_min_version("0.27.0.dev0")
|
||||
check_min_version("0.28.0.dev0")
|
||||
|
||||
logger = get_logger(__name__)
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||||
|
||||
|
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@@ -35,7 +35,7 @@ from diffusers.utils import check_min_version
|
||||
|
||||
|
||||
# Will error if the minimal version of diffusers is not installed. Remove at your own risks.
|
||||
check_min_version("0.27.0.dev0")
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||||
check_min_version("0.28.0.dev0")
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|
||||
# Cache compiled models across invocations of this script.
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||||
cc.initialize_cache(os.path.expanduser("~/.cache/jax/compilation_cache"))
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@@ -70,7 +70,7 @@ if is_wandb_available():
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||||
import wandb
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||||
|
||||
# Will error if the minimal version of diffusers is not installed. Remove at your own risks.
|
||||
check_min_version("0.27.0.dev0")
|
||||
check_min_version("0.28.0.dev0")
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||||
|
||||
logger = get_logger(__name__)
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|
||||
|
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@@ -75,7 +75,7 @@ if is_wandb_available():
|
||||
import wandb
|
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|
||||
# Will error if the minimal version of diffusers is not installed. Remove at your own risks.
|
||||
check_min_version("0.27.0.dev0")
|
||||
check_min_version("0.28.0.dev0")
|
||||
|
||||
logger = get_logger(__name__)
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||||
|
||||
|
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@@ -53,7 +53,7 @@ from diffusers.utils.torch_utils import is_compiled_module
|
||||
|
||||
|
||||
# Will error if the minimal version of diffusers is not installed. Remove at your own risks.
|
||||
check_min_version("0.27.0.dev0")
|
||||
check_min_version("0.28.0.dev0")
|
||||
|
||||
logger = get_logger(__name__, log_level="INFO")
|
||||
|
||||
|
||||
@@ -59,7 +59,7 @@ if is_wandb_available():
|
||||
import wandb
|
||||
|
||||
# Will error if the minimal version of diffusers is not installed. Remove at your own risks.
|
||||
check_min_version("0.27.0.dev0")
|
||||
check_min_version("0.28.0.dev0")
|
||||
|
||||
logger = get_logger(__name__, log_level="INFO")
|
||||
|
||||
|
||||
@@ -52,7 +52,7 @@ if is_wandb_available():
|
||||
|
||||
|
||||
# Will error if the minimal version of diffusers is not installed. Remove at your own risks.
|
||||
check_min_version("0.27.0.dev0")
|
||||
check_min_version("0.28.0.dev0")
|
||||
|
||||
logger = get_logger(__name__, log_level="INFO")
|
||||
|
||||
|
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@@ -46,7 +46,7 @@ from diffusers.utils import check_min_version, is_wandb_available
|
||||
|
||||
|
||||
# Will error if the minimal version of diffusers is not installed. Remove at your own risks.
|
||||
check_min_version("0.27.0.dev0")
|
||||
check_min_version("0.28.0.dev0")
|
||||
|
||||
logger = get_logger(__name__, log_level="INFO")
|
||||
|
||||
|
||||
@@ -46,7 +46,7 @@ from diffusers.utils import check_min_version, is_wandb_available
|
||||
|
||||
|
||||
# Will error if the minimal version of diffusers is not installed. Remove at your own risks.
|
||||
check_min_version("0.27.0.dev0")
|
||||
check_min_version("0.28.0.dev0")
|
||||
|
||||
logger = get_logger(__name__, log_level="INFO")
|
||||
|
||||
|
||||
@@ -51,7 +51,7 @@ if is_wandb_available():
|
||||
|
||||
|
||||
# Will error if the minimal version of diffusers is not installed. Remove at your own risks.
|
||||
check_min_version("0.27.0.dev0")
|
||||
check_min_version("0.28.0.dev0")
|
||||
|
||||
logger = get_logger(__name__, log_level="INFO")
|
||||
|
||||
|
||||
@@ -60,7 +60,7 @@ if is_wandb_available():
|
||||
import wandb
|
||||
|
||||
# Will error if the minimal version of diffusers is not installed. Remove at your own risks.
|
||||
check_min_version("0.27.0.dev0")
|
||||
check_min_version("0.28.0.dev0")
|
||||
|
||||
logger = get_logger(__name__)
|
||||
|
||||
|
||||
@@ -56,7 +56,7 @@ if is_wandb_available():
|
||||
|
||||
|
||||
# Will error if the minimal version of diffusers is not installed. Remove at your own risks.
|
||||
check_min_version("0.27.0.dev0")
|
||||
check_min_version("0.28.0.dev0")
|
||||
|
||||
logger = get_logger(__name__, log_level="INFO")
|
||||
|
||||
|
||||
@@ -49,7 +49,7 @@ from diffusers.utils import check_min_version
|
||||
|
||||
|
||||
# Will error if the minimal version of diffusers is not installed. Remove at your own risks.
|
||||
check_min_version("0.27.0.dev0")
|
||||
check_min_version("0.28.0.dev0")
|
||||
|
||||
logger = logging.getLogger(__name__)
|
||||
|
||||
|
||||
@@ -52,7 +52,7 @@ from diffusers.utils.torch_utils import is_compiled_module
|
||||
|
||||
|
||||
# Will error if the minimal version of diffusers is not installed. Remove at your own risks.
|
||||
check_min_version("0.27.0.dev0")
|
||||
check_min_version("0.28.0.dev0")
|
||||
|
||||
logger = get_logger(__name__, log_level="INFO")
|
||||
|
||||
|
||||
@@ -64,7 +64,7 @@ from diffusers.utils.torch_utils import is_compiled_module
|
||||
|
||||
|
||||
# Will error if the minimal version of diffusers is not installed. Remove at your own risks.
|
||||
check_min_version("0.27.0.dev0")
|
||||
check_min_version("0.28.0.dev0")
|
||||
|
||||
logger = get_logger(__name__)
|
||||
|
||||
|
||||
@@ -54,7 +54,7 @@ from diffusers.utils.torch_utils import is_compiled_module
|
||||
|
||||
|
||||
# Will error if the minimal version of diffusers is not installed. Remove at your own risks.
|
||||
check_min_version("0.27.0.dev0")
|
||||
check_min_version("0.28.0.dev0")
|
||||
|
||||
logger = get_logger(__name__)
|
||||
|
||||
|
||||
@@ -80,7 +80,7 @@ else:
|
||||
|
||||
|
||||
# Will error if the minimal version of diffusers is not installed. Remove at your own risks.
|
||||
check_min_version("0.27.0.dev0")
|
||||
check_min_version("0.28.0.dev0")
|
||||
|
||||
logger = get_logger(__name__)
|
||||
|
||||
|
||||
@@ -56,7 +56,7 @@ else:
|
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# ------------------------------------------------------------------------------
|
||||
|
||||
# Will error if the minimal version of diffusers is not installed. Remove at your own risks.
|
||||
check_min_version("0.27.0.dev0")
|
||||
check_min_version("0.28.0.dev0")
|
||||
|
||||
logger = logging.getLogger(__name__)
|
||||
|
||||
|
||||
@@ -76,7 +76,7 @@ else:
|
||||
|
||||
|
||||
# Will error if the minimal version of diffusers is not installed. Remove at your own risks.
|
||||
check_min_version("0.27.0.dev0")
|
||||
check_min_version("0.28.0.dev0")
|
||||
|
||||
logger = get_logger(__name__)
|
||||
|
||||
|
||||
@@ -29,7 +29,7 @@ from diffusers.utils.import_utils import is_xformers_available
|
||||
|
||||
|
||||
# Will error if the minimal version of diffusers is not installed. Remove at your own risks.
|
||||
check_min_version("0.27.0.dev0")
|
||||
check_min_version("0.28.0.dev0")
|
||||
|
||||
logger = get_logger(__name__, log_level="INFO")
|
||||
|
||||
|
||||
@@ -50,7 +50,7 @@ if is_wandb_available():
|
||||
|
||||
|
||||
# Will error if the minimal version of diffusers is not installed. Remove at your own risks.
|
||||
check_min_version("0.27.0.dev0")
|
||||
check_min_version("0.28.0.dev0")
|
||||
|
||||
logger = get_logger(__name__, log_level="INFO")
|
||||
|
||||
|
||||
@@ -51,7 +51,7 @@ if is_wandb_available():
|
||||
|
||||
|
||||
# Will error if the minimal version of diffusers is not installed. Remove at your own risks.
|
||||
check_min_version("0.27.0.dev0")
|
||||
check_min_version("0.28.0.dev0")
|
||||
|
||||
logger = get_logger(__name__, log_level="INFO")
|
||||
|
||||
|
||||
@@ -249,7 +249,7 @@ version_range_max = max(sys.version_info[1], 10) + 1
|
||||
|
||||
setup(
|
||||
name="diffusers",
|
||||
version="0.27.0.dev0", # expected format is one of x.y.z.dev0, or x.y.z.rc1 or x.y.z (no to dashes, yes to dots)
|
||||
version="0.28.0.dev0", # expected format is one of x.y.z.dev0, or x.y.z.rc1 or x.y.z (no to dashes, yes to dots)
|
||||
description="State-of-the-art diffusion in PyTorch and JAX.",
|
||||
long_description=open("README.md", "r", encoding="utf-8").read(),
|
||||
long_description_content_type="text/markdown",
|
||||
|
||||
@@ -1,4 +1,4 @@
|
||||
__version__ = "0.27.0.dev0"
|
||||
__version__ = "0.28.0.dev0"
|
||||
|
||||
from typing import TYPE_CHECKING
|
||||
|
||||
|
||||
@@ -767,7 +767,18 @@ class AttnProcessor:
|
||||
query = attn.to_q(hidden_states)
|
||||
|
||||
if encoder_hidden_states is None:
|
||||
encoder_hidden_states = hidden_states
|
||||
# encoder_hidden_states = hidden_states
|
||||
batch, seq, dim = hidden_states.shape
|
||||
height = width = seq**0.5
|
||||
# reshape to (batch, height, width, dim)
|
||||
encoder_hidden_states = hidden_states.view(batch, height, width, dim)
|
||||
# reshape to (batch, dim, height, width)
|
||||
encoder_hidden_states = encoder_hidden_states.permute(0, 3, 1, 2)
|
||||
encoder_hidden_states = torch.nn.functional.avg_pool2d(hidden_states, kernel_size=4)
|
||||
# reshape to (batch, dim, seq)
|
||||
encoder_hidden_states = encoder_hidden_states.view(batch, dim, -1)
|
||||
# reshape to (batch, seq, dim)
|
||||
encoder_hidden_states = encoder_hidden_states.permute(0, 2, 1)
|
||||
elif attn.norm_cross:
|
||||
encoder_hidden_states = attn.norm_encoder_hidden_states(encoder_hidden_states)
|
||||
|
||||
@@ -1259,7 +1270,18 @@ class AttnProcessor2_0:
|
||||
query = attn.to_q(hidden_states)
|
||||
|
||||
if encoder_hidden_states is None:
|
||||
encoder_hidden_states = hidden_states
|
||||
# encoder_hidden_states = hidden_states
|
||||
batch, seq, dim = hidden_states.shape
|
||||
height = width = seq**0.5
|
||||
# reshape to (batch, height, width, dim)
|
||||
encoder_hidden_states = hidden_states.view(batch, height, width, dim)
|
||||
# reshape to (batch, dim, height, width)
|
||||
encoder_hidden_states = encoder_hidden_states.permute(0, 3, 1, 2)
|
||||
encoder_hidden_states = torch.nn.functional.avg_pool2d(hidden_states, kernel_size=4)
|
||||
# reshape to (batch, dim, seq)
|
||||
encoder_hidden_states = encoder_hidden_states.view(batch, dim, -1)
|
||||
# reshape to (batch, seq, dim)
|
||||
encoder_hidden_states = encoder_hidden_states.permute(0, 2, 1)
|
||||
elif attn.norm_cross:
|
||||
encoder_hidden_states = attn.norm_encoder_hidden_states(encoder_hidden_states)
|
||||
|
||||
|
||||
@@ -1092,6 +1092,13 @@ class ControlNetPipelineSlowTests(unittest.TestCase):
|
||||
for param_name, param_value in single_file_pipe.controlnet.config.items():
|
||||
if param_name in PARAMS_TO_IGNORE:
|
||||
continue
|
||||
|
||||
# This parameter doesn't appear to be loaded from the config.
|
||||
# So when it is registered to config, it remains a tuple as this is the default in the class definition
|
||||
# from_pretrained, does load from config and converts to a list when registering to config
|
||||
if param_name == "conditioning_embedding_out_channels" and isinstance(param_value, tuple):
|
||||
param_value = list(param_value)
|
||||
|
||||
assert (
|
||||
pipe.controlnet.config[param_name] == param_value
|
||||
), f"{param_name} differs between single file loading and pretrained loading"
|
||||
|
||||
@@ -1002,6 +1002,11 @@ class ControlNetSDXLPipelineSlowTests(unittest.TestCase):
|
||||
for param_name, param_value in single_file_pipe.unet.config.items():
|
||||
if param_name in PARAMS_TO_IGNORE:
|
||||
continue
|
||||
|
||||
# Upcast attention might be set to None in a config file, which is incorrect. It should default to False in the model
|
||||
if param_name == "upcast_attention" and pipe.unet.config[param_name] is None:
|
||||
pipe.unet.config[param_name] = False
|
||||
|
||||
assert (
|
||||
pipe.unet.config[param_name] == param_value
|
||||
), f"{param_name} differs between single file loading and pretrained loading"
|
||||
|
||||
Reference in New Issue
Block a user