source stringclasses 273
values | url stringlengths 47 172 | file_type stringclasses 1
value | chunk stringlengths 1 512 | chunk_id stringlengths 5 9 |
|---|---|---|---|---|
/Users/nielsrogge/Documents/python_projecten/diffusers/docs/source/en/api/attnprocessor.md | https://huggingface.co/docs/diffusers/en/api/attnprocessor/#mochi | .md | MochiAttnProcessor2_0
Attention processor used in Mochi.
MochiVaeAttnProcessor2_0
Attention processor used in Mochi VAE. | 88_15_0 |
/Users/nielsrogge/Documents/python_projecten/diffusers/docs/source/en/api/attnprocessor.md | https://huggingface.co/docs/diffusers/en/api/attnprocessor/#sana | .md | SanaLinearAttnProcessor2_0
Processor for implementing scaled dot-product linear attention.
SanaMultiscaleAttnProcessor2_0
Processor for implementing multiscale quadratic attention.
PAGCFGSanaLinearAttnProcessor2_0
Processor for implementing scaled dot-product linear attention.
PAGIdentitySanaLinearAttnProce... | 88_16_0 |
/Users/nielsrogge/Documents/python_projecten/diffusers/docs/source/en/api/attnprocessor.md | https://huggingface.co/docs/diffusers/en/api/attnprocessor/#stable-audio | .md | StableAudioAttnProcessor2_0
Processor for implementing scaled dot-product attention (enabled by default if you're using PyTorch 2.0). This is
used in the Stable Audio model. It applies rotary embedding on query and key vector, and allows MHA, GQA or MQA. | 88_17_0 |
/Users/nielsrogge/Documents/python_projecten/diffusers/docs/source/en/api/attnprocessor.md | https://huggingface.co/docs/diffusers/en/api/attnprocessor/#slicedattnprocessor | .md | SlicedAttnProcessor
Processor for implementing sliced attention.
Args:
slice_size (`int`, *optional*):
The number of steps to compute attention. Uses as many slices as `attention_head_dim // slice_size`, and
`attention_head_dim` must be a multiple of the `slice_size`.
SlicedAttnAddedKVProcessor
Processor for im... | 88_18_0 |
/Users/nielsrogge/Documents/python_projecten/diffusers/docs/source/en/api/attnprocessor.md | https://huggingface.co/docs/diffusers/en/api/attnprocessor/#slicedattnprocessor | .md | Args:
slice_size (`int`, *optional*):
The number of steps to compute attention. Uses as many slices as `attention_head_dim // slice_size`, and
`attention_head_dim` must be a multiple of the `slice_size`. | 88_18_1 |
/Users/nielsrogge/Documents/python_projecten/diffusers/docs/source/en/api/attnprocessor.md | https://huggingface.co/docs/diffusers/en/api/attnprocessor/#xformersattnprocessor | .md | XFormersAttnProcessor
Processor for implementing memory efficient attention using xFormers.
Args:
attention_op (`Callable`, *optional*, defaults to `None`):
The base
[operator](https://facebookresearch.github.io/xformers/components/ops.html#xformers.ops.AttentionOpBase) to
use as the attention operator. It is recom... | 88_19_0 |
/Users/nielsrogge/Documents/python_projecten/diffusers/docs/source/en/api/attnprocessor.md | https://huggingface.co/docs/diffusers/en/api/attnprocessor/#xformersattnprocessor | .md | operator.
XFormersAttnAddedKVProcessor
Processor for implementing memory efficient attention using xFormers.
Args:
attention_op (`Callable`, *optional*, defaults to `None`):
The base
[operator](https://facebookresearch.github.io/xformers/components/ops.html#xformers.ops.AttentionOpBase) to
use as the attention op... | 88_19_1 |
/Users/nielsrogge/Documents/python_projecten/diffusers/docs/source/en/api/attnprocessor.md | https://huggingface.co/docs/diffusers/en/api/attnprocessor/#xlaflashattnprocessor20 | .md | XLAFlashAttnProcessor2_0
Processor for implementing scaled dot-product attention with pallas flash attention kernel if using `torch_xla`. | 88_20_0 |
/Users/nielsrogge/Documents/python_projecten/diffusers/docs/source/en/api/normalization.md | https://huggingface.co/docs/diffusers/en/api/normalization/ | .md | <!--Copyright 2024 The HuggingFace Team. 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 agr... | 89_0_0 |
/Users/nielsrogge/Documents/python_projecten/diffusers/docs/source/en/api/normalization.md | https://huggingface.co/docs/diffusers/en/api/normalization/ | .md | 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.
--> | 89_0_1 |
/Users/nielsrogge/Documents/python_projecten/diffusers/docs/source/en/api/normalization.md | https://huggingface.co/docs/diffusers/en/api/normalization/#normalization-layers | .md | Customized normalization layers for supporting various models in 🤗 Diffusers. | 89_1_0 |
/Users/nielsrogge/Documents/python_projecten/diffusers/docs/source/en/api/normalization.md | https://huggingface.co/docs/diffusers/en/api/normalization/#adalayernorm | .md | AdaLayerNorm
Norm layer modified to incorporate timestep embeddings.
Parameters:
embedding_dim (`int`): The size of each embedding vector.
num_embeddings (`int`, *optional*): The size of the embeddings dictionary.
output_dim (`int`, *optional*):
norm_elementwise_affine (`bool`, defaults to `False):
norm_eps (`bool`... | 89_2_0 |
/Users/nielsrogge/Documents/python_projecten/diffusers/docs/source/en/api/normalization.md | https://huggingface.co/docs/diffusers/en/api/normalization/#adalayernormzero | .md | AdaLayerNorm
Norm layer modified to incorporate timestep embeddings.
Parameters:
embedding_dim (`int`): The size of each embedding vector.
num_embeddings (`int`, *optional*): The size of the embeddings dictionary.
output_dim (`int`, *optional*):
norm_elementwise_affine (`bool`, defaults to `False):
norm_eps (`bool`... | 89_3_0 |
/Users/nielsrogge/Documents/python_projecten/diffusers/docs/source/en/api/normalization.md | https://huggingface.co/docs/diffusers/en/api/normalization/#adalayernormsingle | .md | AdaLayerNorm
Norm layer modified to incorporate timestep embeddings.
Parameters:
embedding_dim (`int`): The size of each embedding vector.
num_embeddings (`int`, *optional*): The size of the embeddings dictionary.
output_dim (`int`, *optional*):
norm_elementwise_affine (`bool`, defaults to `False):
norm_eps (`bool`... | 89_4_0 |
/Users/nielsrogge/Documents/python_projecten/diffusers/docs/source/en/api/normalization.md | https://huggingface.co/docs/diffusers/en/api/normalization/#adagroupnorm | .md | AdaGroupNorm
GroupNorm layer modified to incorporate timestep embeddings.
Parameters:
embedding_dim (`int`): The size of each embedding vector.
num_embeddings (`int`): The size of the embeddings dictionary.
num_groups (`int`): The number of groups to separate the channels into.
act_fn (`str`, *optional*, defaults t... | 89_5_0 |
/Users/nielsrogge/Documents/python_projecten/diffusers/docs/source/en/api/utilities.md | https://huggingface.co/docs/diffusers/en/api/utilities/ | .md | <!--Copyright 2024 The HuggingFace Team. 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 agr... | 90_0_0 |
/Users/nielsrogge/Documents/python_projecten/diffusers/docs/source/en/api/utilities.md | https://huggingface.co/docs/diffusers/en/api/utilities/ | .md | 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.
--> | 90_0_1 |
/Users/nielsrogge/Documents/python_projecten/diffusers/docs/source/en/api/utilities.md | https://huggingface.co/docs/diffusers/en/api/utilities/#utilities | .md | Utility and helper functions for working with 🤗 Diffusers. | 90_1_0 |
/Users/nielsrogge/Documents/python_projecten/diffusers/docs/source/en/api/utilities.md | https://huggingface.co/docs/diffusers/en/api/utilities/#numpytopil | .md | numpy_to_pil
Convert a numpy image or a batch of images to a PIL image. | 90_2_0 |
/Users/nielsrogge/Documents/python_projecten/diffusers/docs/source/en/api/utilities.md | https://huggingface.co/docs/diffusers/en/api/utilities/#pttopil | .md | pt_to_pil
Convert a torch image to a PIL image. | 90_3_0 |
/Users/nielsrogge/Documents/python_projecten/diffusers/docs/source/en/api/utilities.md | https://huggingface.co/docs/diffusers/en/api/utilities/#loadimage | .md | load_image
Loads `image` to a PIL Image.
Args:
image (`str` or `PIL.Image.Image`):
The image to convert to the PIL Image format.
convert_method (Callable[[PIL.Image.Image], PIL.Image.Image], *optional*):
A conversion method to apply to the image after loading it. When set to `None` the image will be converted
"RGB"... | 90_4_0 |
/Users/nielsrogge/Documents/python_projecten/diffusers/docs/source/en/api/utilities.md | https://huggingface.co/docs/diffusers/en/api/utilities/#exporttogif | .md | export_to_gif | 90_5_0 |
/Users/nielsrogge/Documents/python_projecten/diffusers/docs/source/en/api/utilities.md | https://huggingface.co/docs/diffusers/en/api/utilities/#exporttovideo | .md | export_to_video | 90_6_0 |
/Users/nielsrogge/Documents/python_projecten/diffusers/docs/source/en/api/utilities.md | https://huggingface.co/docs/diffusers/en/api/utilities/#makeimagegrid | .md | make_image_grid
Prepares a single grid of images. Useful for visualization purposes. | 90_7_0 |
/Users/nielsrogge/Documents/python_projecten/diffusers/docs/source/en/api/utilities.md | https://huggingface.co/docs/diffusers/en/api/utilities/#randntensor | .md | randn_tensor
A helper function to create random tensors on the desired `device` with the desired `dtype`. When
passing a list of generators, you can seed each batch size individually. If CPU generators are passed, the tensor
is always created on the CPU. | 90_8_0 |
/Users/nielsrogge/Documents/python_projecten/diffusers/docs/source/en/api/configuration.md | https://huggingface.co/docs/diffusers/en/api/configuration/ | .md | <!--Copyright 2024 The HuggingFace Team. 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 agr... | 91_0_0 |
/Users/nielsrogge/Documents/python_projecten/diffusers/docs/source/en/api/configuration.md | https://huggingface.co/docs/diffusers/en/api/configuration/ | .md | 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.
--> | 91_0_1 |
/Users/nielsrogge/Documents/python_projecten/diffusers/docs/source/en/api/configuration.md | https://huggingface.co/docs/diffusers/en/api/configuration/#configuration | .md | Schedulers from [`~schedulers.scheduling_utils.SchedulerMixin`] and models from [`ModelMixin`] inherit from [`ConfigMixin`] which stores all the parameters that are passed to their respective `__init__` methods in a JSON-configuration file.
<Tip>
To use private or [gated](https://huggingface.co/docs/hub/models-gate... | 91_1_0 |
/Users/nielsrogge/Documents/python_projecten/diffusers/docs/source/en/api/configuration.md | https://huggingface.co/docs/diffusers/en/api/configuration/#configmixin | .md | ConfigMixin
Base class for all configuration classes. All configuration parameters are stored under `self.config`. Also
provides the [`~ConfigMixin.from_config`] and [`~ConfigMixin.save_config`] methods for loading, downloading, and
saving classes that inherit from [`ConfigMixin`].
Class attributes:
- **config_name... | 91_2_0 |
/Users/nielsrogge/Documents/python_projecten/diffusers/docs/source/en/api/configuration.md | https://huggingface.co/docs/diffusers/en/api/configuration/#configmixin | .md | [`~ConfigMixin.save_config`] (should be overridden by parent class).
- **ignore_for_config** (`List[str]`) -- A list of attributes that should not be saved in the config (should be
overridden by subclass).
- **has_compatibles** (`bool`) -- Whether the class has compatible classes (should be overridden by subclass).
- *... | 91_2_1 |
/Users/nielsrogge/Documents/python_projecten/diffusers/docs/source/en/api/configuration.md | https://huggingface.co/docs/diffusers/en/api/configuration/#configmixin | .md | - **_deprecated_kwargs** (`List[str]`) -- Keyword arguments that are deprecated. Note that the `init` function
should only have a `kwargs` argument if at least one argument is deprecated (should be overridden by
subclass).
- load_config
- from_config
- save_config
- to_json_file
- to_json_string | 91_2_2 |
/Users/nielsrogge/Documents/python_projecten/diffusers/docs/source/en/api/internal_classes_overview.md | https://huggingface.co/docs/diffusers/en/api/internal_classes_overview/ | .md | <!--Copyright 2024 The HuggingFace Team. 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 agr... | 92_0_0 |
/Users/nielsrogge/Documents/python_projecten/diffusers/docs/source/en/api/internal_classes_overview.md | https://huggingface.co/docs/diffusers/en/api/internal_classes_overview/ | .md | 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.
--> | 92_0_1 |
/Users/nielsrogge/Documents/python_projecten/diffusers/docs/source/en/api/internal_classes_overview.md | https://huggingface.co/docs/diffusers/en/api/internal_classes_overview/#overview | .md | The APIs in this section are more experimental and prone to breaking changes. Most of them are used internally for development, but they may also be useful to you if you're interested in building a diffusion model with some custom parts or if you're interested in some of our helper utilities for working with 🤗 Diffuse... | 92_1_0 |
/Users/nielsrogge/Documents/python_projecten/diffusers/docs/source/en/api/logging.md | https://huggingface.co/docs/diffusers/en/api/logging/ | .md | <!--Copyright 2024 The HuggingFace Team. 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 agr... | 93_0_0 |
/Users/nielsrogge/Documents/python_projecten/diffusers/docs/source/en/api/logging.md | https://huggingface.co/docs/diffusers/en/api/logging/ | .md | 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.
--> | 93_0_1 |
/Users/nielsrogge/Documents/python_projecten/diffusers/docs/source/en/api/logging.md | https://huggingface.co/docs/diffusers/en/api/logging/#logging | .md | 🤗 Diffusers has a centralized logging system to easily manage the verbosity of the library. The default verbosity is set to `WARNING`.
To change the verbosity level, use one of the direct setters. For instance, to change the verbosity to the `INFO` level.
```python
import diffusers | 93_1_0 |
/Users/nielsrogge/Documents/python_projecten/diffusers/docs/source/en/api/logging.md | https://huggingface.co/docs/diffusers/en/api/logging/#logging | .md | diffusers.logging.set_verbosity_info()
```
You can also use the environment variable `DIFFUSERS_VERBOSITY` to override the default verbosity. You can set it
to one of the following: `debug`, `info`, `warning`, `error`, `critical`. For example:
```bash
DIFFUSERS_VERBOSITY=error ./myprogram.py
```
Additionally, som... | 93_1_1 |
/Users/nielsrogge/Documents/python_projecten/diffusers/docs/source/en/api/logging.md | https://huggingface.co/docs/diffusers/en/api/logging/#logging | .md | `DIFFUSERS_NO_ADVISORY_WARNINGS` to a true value, like `1`. This disables any warning logged by
[`logger.warning_advice`]. For example:
```bash
DIFFUSERS_NO_ADVISORY_WARNINGS=1 ./myprogram.py
```
Here is an example of how to use the same logger as the library in your own module or script:
```python
from diffusers... | 93_1_2 |
/Users/nielsrogge/Documents/python_projecten/diffusers/docs/source/en/api/logging.md | https://huggingface.co/docs/diffusers/en/api/logging/#logging | .md | logging.set_verbosity_info()
logger = logging.get_logger("diffusers")
logger.info("INFO")
logger.warning("WARN")
```
All methods of the logging module are documented below. The main methods are
[`logging.get_verbosity`] to get the current level of verbosity in the logger and
[`logging.set_verbosity`] to set the verbo... | 93_1_3 |
/Users/nielsrogge/Documents/python_projecten/diffusers/docs/source/en/api/logging.md | https://huggingface.co/docs/diffusers/en/api/logging/#logging | .md | In order from the least verbose to the most verbose:
| Method | Integer value | Description |
|----------------------------------------------------------:|--------------:|----------------------------------------------------:|
|... | 93_1_4 |
/Users/nielsrogge/Documents/python_projecten/diffusers/docs/source/en/api/logging.md | https://huggingface.co/docs/diffusers/en/api/logging/#logging | .md | | `diffusers.logging.ERROR` | 40 | only report errors |
| `diffusers.logging.WARNING` or `diffusers.logging.WARN` | 30 | only report errors and warnings (default) |
| `diffusers.logging.IN... | 93_1_5 |
/Users/nielsrogge/Documents/python_projecten/diffusers/docs/source/en/api/logging.md | https://huggingface.co/docs/diffusers/en/api/logging/#logging | .md | | `diffusers.logging.DEBUG` | 10 | report all information |
By default, `tqdm` progress bars are displayed during model download. [`logging.disable_progress_bar`] and [`logging.enable_progress_bar`] are used to enable or disable this behavior. | 93_1_6 |
/Users/nielsrogge/Documents/python_projecten/diffusers/docs/source/en/api/logging.md | https://huggingface.co/docs/diffusers/en/api/logging/#base-setters | .md | set_verbosity_error
Set the verbosity to the `ERROR` level.
set_verbosity_warning
Set the verbosity to the `WARNING` level.
set_verbosity_info
Set the verbosity to the `INFO` level.
set_verbosity_debug
Set the verbosity to the `DEBUG` level. | 93_2_0 |
/Users/nielsrogge/Documents/python_projecten/diffusers/docs/source/en/api/logging.md | https://huggingface.co/docs/diffusers/en/api/logging/#other-functions | .md | get_verbosity
Return the current level for the 🤗 Diffusers' root logger as an `int`.
Returns:
`int`:
Logging level integers which can be one of:
- `50`: `diffusers.logging.CRITICAL` or `diffusers.logging.FATAL`
- `40`: `diffusers.logging.ERROR`
- `30`: `diffusers.logging.WARNING` or `diffusers.logging.WARN`
- `2... | 93_3_0 |
/Users/nielsrogge/Documents/python_projecten/diffusers/docs/source/en/api/logging.md | https://huggingface.co/docs/diffusers/en/api/logging/#other-functions | .md | set_verbosity
Set the verbosity level for the 🤗 Diffusers' root logger.
Args:
verbosity (`int`):
Logging level which can be one of:
- `diffusers.logging.CRITICAL` or `diffusers.logging.FATAL`
- `diffusers.logging.ERROR`
- `diffusers.logging.WARNING` or `diffusers.logging.WARN`
- `diffusers.logging.INFO`
- `diffu... | 93_3_1 |
/Users/nielsrogge/Documents/python_projecten/diffusers/docs/source/en/api/logging.md | https://huggingface.co/docs/diffusers/en/api/logging/#other-functions | .md | This function is not supposed to be directly accessed unless you are writing a custom diffusers module.
enable_default_handler
Enable the default handler of the 🤗 Diffusers' root logger.
disable_default_handler
Disable the default handler of the 🤗 Diffusers' root logger.
enable_explicit_format
Enable explicit... | 93_3_2 |
/Users/nielsrogge/Documents/python_projecten/diffusers/docs/source/en/api/logging.md | https://huggingface.co/docs/diffusers/en/api/logging/#other-functions | .md | ```
[LEVELNAME|FILENAME|LINE NUMBER] TIME >> MESSAGE
```
All handlers currently bound to the root logger are affected by this method.
reset_format
Resets the formatting for 🤗 Diffusers' loggers.
All handlers currently bound to the root logger are affected by this method.
enable_progress_bar
Enable tqdm progres... | 93_3_3 |
/Users/nielsrogge/Documents/python_projecten/diffusers/docs/source/en/api/image_processor.md | https://huggingface.co/docs/diffusers/en/api/image_processor/ | .md | <!--Copyright 2024 The HuggingFace Team. 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 agr... | 94_0_0 |
/Users/nielsrogge/Documents/python_projecten/diffusers/docs/source/en/api/image_processor.md | https://huggingface.co/docs/diffusers/en/api/image_processor/ | .md | 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.
--> | 94_0_1 |
/Users/nielsrogge/Documents/python_projecten/diffusers/docs/source/en/api/image_processor.md | https://huggingface.co/docs/diffusers/en/api/image_processor/#vae-image-processor | .md | The [`VaeImageProcessor`] provides a unified API for [`StableDiffusionPipeline`]s to prepare image inputs for VAE encoding and post-processing outputs once they're decoded. This includes transformations such as resizing, normalization, and conversion between PIL Image, PyTorch, and NumPy arrays. | 94_1_0 |
/Users/nielsrogge/Documents/python_projecten/diffusers/docs/source/en/api/image_processor.md | https://huggingface.co/docs/diffusers/en/api/image_processor/#vae-image-processor | .md | All pipelines with [`VaeImageProcessor`] accept PIL Image, PyTorch tensor, or NumPy arrays as image inputs and return outputs based on the `output_type` argument by the user. You can pass encoded image latents directly to the pipeline and return latents from the pipeline as a specific output with the `output_type` argu... | 94_1_1 |
/Users/nielsrogge/Documents/python_projecten/diffusers/docs/source/en/api/image_processor.md | https://huggingface.co/docs/diffusers/en/api/image_processor/#vae-image-processor | .md | take the generated latents from one pipeline and pass it to another pipeline as input without leaving the latent space. It also makes it much easier to use multiple pipelines together by passing PyTorch tensors directly between different pipelines. | 94_1_2 |
/Users/nielsrogge/Documents/python_projecten/diffusers/docs/source/en/api/image_processor.md | https://huggingface.co/docs/diffusers/en/api/image_processor/#vaeimageprocessor | .md | VaeImageProcessor
Image processor for VAE.
Args:
do_resize (`bool`, *optional*, defaults to `True`):
Whether to downscale the image's (height, width) dimensions to multiples of `vae_scale_factor`. Can accept
`height` and `width` arguments from [`image_processor.VaeImageProcessor.preprocess`] method.
vae_scale_facto... | 94_2_0 |
/Users/nielsrogge/Documents/python_projecten/diffusers/docs/source/en/api/image_processor.md | https://huggingface.co/docs/diffusers/en/api/image_processor/#vaeimageprocessor | .md | VAE scale factor. If `do_resize` is `True`, the image is automatically resized to multiples of this factor.
resample (`str`, *optional*, defaults to `lanczos`):
Resampling filter to use when resizing the image.
do_normalize (`bool`, *optional*, defaults to `True`):
Whether to normalize the image to [-1,1].
do_binarize ... | 94_2_1 |
/Users/nielsrogge/Documents/python_projecten/diffusers/docs/source/en/api/image_processor.md | https://huggingface.co/docs/diffusers/en/api/image_processor/#vaeimageprocessor | .md | do_convert_rgb (`bool`, *optional*, defaults to be `False`):
Whether to convert the images to RGB format.
do_convert_grayscale (`bool`, *optional*, defaults to be `False`):
Whether to convert the images to grayscale format. | 94_2_2 |
/Users/nielsrogge/Documents/python_projecten/diffusers/docs/source/en/api/image_processor.md | https://huggingface.co/docs/diffusers/en/api/image_processor/#vaeimageprocessorldm3d | .md | The [`VaeImageProcessorLDM3D`] accepts RGB and depth inputs and returns RGB and depth outputs.
VaeImageProcessor
Image processor for VAE.
Args:
do_resize (`bool`, *optional*, defaults to `True`):
Whether to downscale the image's (height, width) dimensions to multiples of `vae_scale_factor`. Can accept
`height` an... | 94_3_0 |
/Users/nielsrogge/Documents/python_projecten/diffusers/docs/source/en/api/image_processor.md | https://huggingface.co/docs/diffusers/en/api/image_processor/#vaeimageprocessorldm3d | .md | vae_scale_factor (`int`, *optional*, defaults to `8`):
VAE scale factor. If `do_resize` is `True`, the image is automatically resized to multiples of this factor.
resample (`str`, *optional*, defaults to `lanczos`):
Resampling filter to use when resizing the image.
do_normalize (`bool`, *optional*, defaults to `True`):... | 94_3_1 |
/Users/nielsrogge/Documents/python_projecten/diffusers/docs/source/en/api/image_processor.md | https://huggingface.co/docs/diffusers/en/api/image_processor/#vaeimageprocessorldm3d | .md | do_binarize (`bool`, *optional*, defaults to `False`):
Whether to binarize the image to 0/1.
do_convert_rgb (`bool`, *optional*, defaults to be `False`):
Whether to convert the images to RGB format.
do_convert_grayscale (`bool`, *optional*, defaults to be `False`):
Whether to convert the images to grayscale format.
LDM... | 94_3_2 |
/Users/nielsrogge/Documents/python_projecten/diffusers/docs/source/en/api/image_processor.md | https://huggingface.co/docs/diffusers/en/api/image_processor/#pixartimageprocessor | .md | PixArtImageProcessor
Image processor for PixArt image resize and crop.
Args:
do_resize (`bool`, *optional*, defaults to `True`):
Whether to downscale the image's (height, width) dimensions to multiples of `vae_scale_factor`. Can accept
`height` and `width` arguments from [`image_processor.VaeImageProcessor.preproce... | 94_4_0 |
/Users/nielsrogge/Documents/python_projecten/diffusers/docs/source/en/api/image_processor.md | https://huggingface.co/docs/diffusers/en/api/image_processor/#pixartimageprocessor | .md | VAE scale factor. If `do_resize` is `True`, the image is automatically resized to multiples of this factor.
resample (`str`, *optional*, defaults to `lanczos`):
Resampling filter to use when resizing the image.
do_normalize (`bool`, *optional*, defaults to `True`):
Whether to normalize the image to [-1,1].
do_binarize ... | 94_4_1 |
/Users/nielsrogge/Documents/python_projecten/diffusers/docs/source/en/api/image_processor.md | https://huggingface.co/docs/diffusers/en/api/image_processor/#pixartimageprocessor | .md | do_convert_rgb (`bool`, *optional*, defaults to be `False`):
Whether to convert the images to RGB format.
do_convert_grayscale (`bool`, *optional*, defaults to be `False`):
Whether to convert the images to grayscale format. | 94_4_2 |
/Users/nielsrogge/Documents/python_projecten/diffusers/docs/source/en/api/image_processor.md | https://huggingface.co/docs/diffusers/en/api/image_processor/#ipadaptermaskprocessor | .md | IPAdapterMaskProcessor
Image processor for IP Adapter image masks.
Args:
do_resize (`bool`, *optional*, defaults to `True`):
Whether to downscale the image's (height, width) dimensions to multiples of `vae_scale_factor`.
vae_scale_factor (`int`, *optional*, defaults to `8`):
VAE scale factor. If `do_resize` is `Tru... | 94_5_0 |
/Users/nielsrogge/Documents/python_projecten/diffusers/docs/source/en/api/image_processor.md | https://huggingface.co/docs/diffusers/en/api/image_processor/#ipadaptermaskprocessor | .md | resample (`str`, *optional*, defaults to `lanczos`):
Resampling filter to use when resizing the image.
do_normalize (`bool`, *optional*, defaults to `False`):
Whether to normalize the image to [-1,1].
do_binarize (`bool`, *optional*, defaults to `True`):
Whether to binarize the image to 0/1.
do_convert_grayscale (`bool... | 94_5_1 |
/Users/nielsrogge/Documents/python_projecten/diffusers/docs/source/en/api/quantization.md | https://huggingface.co/docs/diffusers/en/api/quantization/ | .md | <!--Copyright 2024 The HuggingFace Team. 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 agr... | 95_0_0 |
/Users/nielsrogge/Documents/python_projecten/diffusers/docs/source/en/api/quantization.md | https://huggingface.co/docs/diffusers/en/api/quantization/ | .md | 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.
--> | 95_0_1 |
/Users/nielsrogge/Documents/python_projecten/diffusers/docs/source/en/api/quantization.md | https://huggingface.co/docs/diffusers/en/api/quantization/#quantization | .md | Quantization techniques reduce memory and computational costs by representing weights and activations with lower-precision data types like 8-bit integers (int8). This enables loading larger models you normally wouldn't be able to fit into memory, and speeding up inference. Diffusers supports 8-bit and 4-bit quantizatio... | 95_1_0 |
/Users/nielsrogge/Documents/python_projecten/diffusers/docs/source/en/api/quantization.md | https://huggingface.co/docs/diffusers/en/api/quantization/#quantization | .md | Quantization techniques that aren't supported in Transformers can be added with the [`DiffusersQuantizer`] class.
<Tip>
Learn how to quantize models in the [Quantization](../quantization/overview) guide.
</Tip> | 95_1_1 |
/Users/nielsrogge/Documents/python_projecten/diffusers/docs/source/en/api/quantization.md | https://huggingface.co/docs/diffusers/en/api/quantization/#bitsandbytesconfig | .md | BitsAndBytesConfig
This is a wrapper class about all possible attributes and features that you can play with a model that has been
loaded using `bitsandbytes`.
This replaces `load_in_8bit` or `load_in_4bit`therefore both options are mutually exclusive.
Currently only supports `LLM.int8()`, `FP4`, and `NF4` quanti... | 95_2_0 |
/Users/nielsrogge/Documents/python_projecten/diffusers/docs/source/en/api/quantization.md | https://huggingface.co/docs/diffusers/en/api/quantization/#bitsandbytesconfig | .md | then more arguments will be added to this class.
Args:
load_in_8bit (`bool`, *optional*, defaults to `False`):
This flag is used to enable 8-bit quantization with LLM.int8().
load_in_4bit (`bool`, *optional*, defaults to `False`):
This flag is used to enable 4-bit quantization by replacing the Linear layers with FP4/... | 95_2_1 |
/Users/nielsrogge/Documents/python_projecten/diffusers/docs/source/en/api/quantization.md | https://huggingface.co/docs/diffusers/en/api/quantization/#bitsandbytesconfig | .md | `bitsandbytes`.
llm_int8_threshold (`float`, *optional*, defaults to 6.0):
This corresponds to the outlier threshold for outlier detection as described in `LLM.int8() : 8-bit Matrix
Multiplication for Transformers at Scale` paper: https://arxiv.org/abs/2208.07339 Any hidden states value
that is above this threshold wil... | 95_2_2 |
/Users/nielsrogge/Documents/python_projecten/diffusers/docs/source/en/api/quantization.md | https://huggingface.co/docs/diffusers/en/api/quantization/#bitsandbytesconfig | .md | in fp16. Values are usually normally distributed, that is, most values are in the range [-3.5, 3.5], but
there are some exceptional systematic outliers that are very differently distributed for large models.
These outliers are often in the interval [-60, -6] or [6, 60]. Int8 quantization works well for values of
magnit... | 95_2_3 |
/Users/nielsrogge/Documents/python_projecten/diffusers/docs/source/en/api/quantization.md | https://huggingface.co/docs/diffusers/en/api/quantization/#bitsandbytesconfig | .md | but a lower threshold might be needed for more unstable models (small models, fine-tuning).
llm_int8_skip_modules (`List[str]`, *optional*):
An explicit list of the modules that we do not want to convert in 8-bit. This is useful for models such as
Jukebox that has several heads in different places and not necessarily a... | 95_2_4 |
/Users/nielsrogge/Documents/python_projecten/diffusers/docs/source/en/api/quantization.md | https://huggingface.co/docs/diffusers/en/api/quantization/#bitsandbytesconfig | .md | for `CausalLM` models, the last `lm_head` is typically kept in its original `dtype`.
llm_int8_enable_fp32_cpu_offload (`bool`, *optional*, defaults to `False`):
This flag is used for advanced use cases and users that are aware of this feature. If you want to split
your model in different parts and run some parts in int... | 95_2_5 |
/Users/nielsrogge/Documents/python_projecten/diffusers/docs/source/en/api/quantization.md | https://huggingface.co/docs/diffusers/en/api/quantization/#bitsandbytesconfig | .md | operations will not be run on CPU.
llm_int8_has_fp16_weight (`bool`, *optional*, defaults to `False`):
This flag runs LLM.int8() with 16-bit main weights. This is useful for fine-tuning as the weights do not
have to be converted back and forth for the backward pass.
bnb_4bit_compute_dtype (`torch.dtype` or str, *option... | 95_2_6 |
/Users/nielsrogge/Documents/python_projecten/diffusers/docs/source/en/api/quantization.md | https://huggingface.co/docs/diffusers/en/api/quantization/#bitsandbytesconfig | .md | This sets the computational type which might be different than the input type. For example, inputs might be
fp32, but computation can be set to bf16 for speedups.
bnb_4bit_quant_type (`str`, *optional*, defaults to `"fp4"`):
This sets the quantization data type in the bnb.nn.Linear4Bit layers. Options are FP4 and NF4 ... | 95_2_7 |
/Users/nielsrogge/Documents/python_projecten/diffusers/docs/source/en/api/quantization.md | https://huggingface.co/docs/diffusers/en/api/quantization/#bitsandbytesconfig | .md | which are specified by `fp4` or `nf4`.
bnb_4bit_use_double_quant (`bool`, *optional*, defaults to `False`):
This flag is used for nested quantization where the quantization constants from the first quantization are
quantized again.
bnb_4bit_quant_storage (`torch.dtype` or str, *optional*, defaults to `torch.uint8`):
Th... | 95_2_8 |
/Users/nielsrogge/Documents/python_projecten/diffusers/docs/source/en/api/quantization.md | https://huggingface.co/docs/diffusers/en/api/quantization/#ggufquantizationconfig | .md | GGUFQuantizationConfig
This is a config class for GGUF Quantization techniques.
Args:
compute_dtype: (`torch.dtype`, defaults to `torch.float32`):
This sets the computational type which might be different than the input type. For example, inputs might be
fp32, but computation can be set to bf16 for speedups. | 95_3_0 |
/Users/nielsrogge/Documents/python_projecten/diffusers/docs/source/en/api/quantization.md | https://huggingface.co/docs/diffusers/en/api/quantization/#torchaoconfig | .md | TorchAoConfig
This is a config class for torchao quantization/sparsity techniques.
Args:
quant_type (`str`):
The type of quantization we want to use, currently supporting:
- **Integer quantization:**
- Full function names: `int4_weight_only`, `int8_dynamic_activation_int4_weight`,
`int8_weight_only`, `int8_dynamic_ac... | 95_4_0 |
/Users/nielsrogge/Documents/python_projecten/diffusers/docs/source/en/api/quantization.md | https://huggingface.co/docs/diffusers/en/api/quantization/#torchaoconfig | .md | - Shorthands: `int4wo`, `int4dq`, `int8wo`, `int8dq`
- **Floating point 8-bit quantization:**
- Full function names: `float8_weight_only`, `float8_dynamic_activation_float8_weight`,
`float8_static_activation_float8_weight`
- Shorthands: `float8wo`, `float8wo_e5m2`, `float8wo_e4m3`, `float8dq`, `float8dq_e4m3`,
`float... | 95_4_1 |
/Users/nielsrogge/Documents/python_projecten/diffusers/docs/source/en/api/quantization.md | https://huggingface.co/docs/diffusers/en/api/quantization/#torchaoconfig | .md | `float8_e4m3_tensor`, `float8_e4m3_row`,
- **Floating point X-bit quantization:**
- Full function names: `fpx_weight_only`
- Shorthands: `fpX_eAwB`, where `X` is the number of bits (between `1` to `7`), `A` is the number
of exponent bits and `B` is the number of mantissa bits. The constraint of `X == A + B + 1` must
... | 95_4_2 |
/Users/nielsrogge/Documents/python_projecten/diffusers/docs/source/en/api/quantization.md | https://huggingface.co/docs/diffusers/en/api/quantization/#torchaoconfig | .md | be satisfied for a given shorthand notation.
- **Unsigned Integer quantization:**
- Full function names: `uintx_weight_only`
- Shorthands: `uint1wo`, `uint2wo`, `uint3wo`, `uint4wo`, `uint5wo`, `uint6wo`, `uint7wo`
modules_to_not_convert (`List[str]`, *optional*, default to `None`):
The list of modules to not quantiz... | 95_4_3 |
/Users/nielsrogge/Documents/python_projecten/diffusers/docs/source/en/api/quantization.md | https://huggingface.co/docs/diffusers/en/api/quantization/#torchaoconfig | .md | modules left in their original precision.
kwargs (`Dict[str, Any]`, *optional*):
The keyword arguments for the chosen type of quantization, for example, int4_weight_only quantization
supports two keyword arguments `group_size` and `inner_k_tiles` currently. More API examples and
documentation of arguments can be found ... | 95_4_4 |
/Users/nielsrogge/Documents/python_projecten/diffusers/docs/source/en/api/quantization.md | https://huggingface.co/docs/diffusers/en/api/quantization/#torchaoconfig | .md | quantization_config = TorchAoConfig("int8wo")
transformer = FluxTransformer2DModel.from_pretrained(
"black-forest-labs/Flux.1-Dev",
subfolder="transformer",
quantization_config=quantization_config,
torch_dtype=torch.bfloat16,
)
``` | 95_4_5 |
/Users/nielsrogge/Documents/python_projecten/diffusers/docs/source/en/api/quantization.md | https://huggingface.co/docs/diffusers/en/api/quantization/#diffusersquantizer | .md | DiffusersQuantizer
Abstract class of the HuggingFace quantizer. Supports for now quantizing HF diffusers models for inference and/or
quantization. This class is used only for diffusers.models.modeling_utils.ModelMixin.from_pretrained and cannot be
easily used outside the scope of that method yet.
Attributes
quantiz... | 95_5_0 |
/Users/nielsrogge/Documents/python_projecten/diffusers/docs/source/en/api/quantization.md | https://huggingface.co/docs/diffusers/en/api/quantization/#diffusersquantizer | .md | The quantization config that defines the quantization parameters of your model that you want to quantize.
modules_to_not_convert (`List[str]`, *optional*):
The list of module names to not convert when quantizing the model.
required_packages (`List[str]`, *optional*):
The list of required pip packages to install prior t... | 95_5_1 |
/Users/nielsrogge/Documents/python_projecten/diffusers/docs/source/en/api/video_processor.md | https://huggingface.co/docs/diffusers/en/api/video_processor/ | .md | <!--Copyright 2024 The HuggingFace Team. 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 agr... | 96_0_0 |
/Users/nielsrogge/Documents/python_projecten/diffusers/docs/source/en/api/video_processor.md | https://huggingface.co/docs/diffusers/en/api/video_processor/ | .md | 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.
--> | 96_0_1 |
/Users/nielsrogge/Documents/python_projecten/diffusers/docs/source/en/api/video_processor.md | https://huggingface.co/docs/diffusers/en/api/video_processor/#video-processor | .md | The [`VideoProcessor`] provides a unified API for video pipelines to prepare inputs for VAE encoding and post-processing outputs once they're decoded. The class inherits [`VaeImageProcessor`] so it includes transformations such as resizing, normalization, and conversion between PIL Image, PyTorch, and NumPy arrays. | 96_1_0 |
/Users/nielsrogge/Documents/python_projecten/diffusers/docs/source/en/api/video_processor.md | https://huggingface.co/docs/diffusers/en/api/video_processor/#videoprocessor | .md | [[autodoc]] preprocess_video: No module named 'diffusers.video_processor.VideoProcessor'; 'diffusers.video_processor' is not a package
[[autodoc]] postprocess_video: No module named 'diffusers.video_processor.VideoProcessor'; 'diffusers.video_processor' is not a package | 96_2_0 |
/Users/nielsrogge/Documents/python_projecten/diffusers/docs/source/en/api/activations.md | https://huggingface.co/docs/diffusers/en/api/activations/ | .md | <!--Copyright 2024 The HuggingFace Team. 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 agr... | 97_0_0 |
/Users/nielsrogge/Documents/python_projecten/diffusers/docs/source/en/api/activations.md | https://huggingface.co/docs/diffusers/en/api/activations/ | .md | 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.
--> | 97_0_1 |
/Users/nielsrogge/Documents/python_projecten/diffusers/docs/source/en/api/activations.md | https://huggingface.co/docs/diffusers/en/api/activations/#activation-functions | .md | Customized activation functions for supporting various models in 🤗 Diffusers. | 97_1_0 |
/Users/nielsrogge/Documents/python_projecten/diffusers/docs/source/en/api/activations.md | https://huggingface.co/docs/diffusers/en/api/activations/#gelu | .md | GELU
GELU activation function with tanh approximation support with `approximate="tanh"`.
Parameters:
dim_in (`int`): The number of channels in the input.
dim_out (`int`): The number of channels in the output.
approximate (`str`, *optional*, defaults to `"none"`): If `"tanh"`, use tanh approximation.
bias (`bool`, d... | 97_2_0 |
/Users/nielsrogge/Documents/python_projecten/diffusers/docs/source/en/api/activations.md | https://huggingface.co/docs/diffusers/en/api/activations/#geglu | .md | GEGLU
A [variant](https://arxiv.org/abs/2002.05202) of the gated linear unit activation function.
Parameters:
dim_in (`int`): The number of channels in the input.
dim_out (`int`): The number of channels in the output.
bias (`bool`, defaults to True): Whether to use a bias in the linear layer. | 97_3_0 |
/Users/nielsrogge/Documents/python_projecten/diffusers/docs/source/en/api/activations.md | https://huggingface.co/docs/diffusers/en/api/activations/#approximategelu | .md | ApproximateGELU
The approximate form of the Gaussian Error Linear Unit (GELU). For more details, see section 2 of this
[paper](https://arxiv.org/abs/1606.08415).
Parameters:
dim_in (`int`): The number of channels in the input.
dim_out (`int`): The number of channels in the output.
bias (`bool`, defaults to True): W... | 97_4_0 |
/Users/nielsrogge/Documents/python_projecten/diffusers/docs/source/en/api/pipelines/stable_unclip.md | https://huggingface.co/docs/diffusers/en/api/pipelines/stable_unclip/ | .md | <!--Copyright 2024 The HuggingFace Team. 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 agr... | 98_0_0 |
/Users/nielsrogge/Documents/python_projecten/diffusers/docs/source/en/api/pipelines/stable_unclip.md | https://huggingface.co/docs/diffusers/en/api/pipelines/stable_unclip/ | .md | 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.
--> | 98_0_1 |
/Users/nielsrogge/Documents/python_projecten/diffusers/docs/source/en/api/pipelines/stable_unclip.md | https://huggingface.co/docs/diffusers/en/api/pipelines/stable_unclip/#stable-unclip | .md | Stable unCLIP checkpoints are finetuned from [Stable Diffusion 2.1](./stable_diffusion/stable_diffusion_2) checkpoints to condition on CLIP image embeddings.
Stable unCLIP still conditions on text embeddings. Given the two separate conditionings, stable unCLIP can be used
for text guided image variation. When combined ... | 98_1_0 |
/Users/nielsrogge/Documents/python_projecten/diffusers/docs/source/en/api/pipelines/stable_unclip.md | https://huggingface.co/docs/diffusers/en/api/pipelines/stable_unclip/#stable-unclip | .md | *Contrastive models like CLIP have been shown to learn robust representations of images that capture both semantics and style. To leverage these representations for image generation, we propose a two-stage model: a prior that generates a CLIP image embedding given a text caption, and a decoder that generates an image c... | 98_1_1 |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.