Code
Hub
Workspaces
Following
Trending
Connect
MCP
copy
Create free account
hub
/
github.com/bytedance/StyleSSP
/ types & classes
Types & classes
84 in github.com/bytedance/StyleSSP
⨍
Functions
440
◇
Types & classes
84
↓ 5 callers
Class
ImagePathDataset
evaluation/eval_artfid.py:26
↓ 5 callers
Class
PerceiverAttention
ip_adapter/resampler_Instruct.py:152
↓ 4 callers
Class
PerceiverAttention
ip_adapter/resampler_SD3.py:36
↓ 3 callers
Class
EulerAncestralDiscreteSchedulerOutput
Output class for the scheduler's `step` function output. Args: prev_sample (`torch.FloatTensor` of shape `(batch_size, num_channels,
src/schedulers/euler_scheduler.py:10
↓ 2 callers
Class
CNAttnProcessor
r""" Default processor for performing attention-related computations.
ip_adapter/attention_processor.py:412
↓ 2 callers
Class
IPJointAttnProcessor2_0
Attention processor used typically in processing the SD3-like self-attention projections.
ip_adapter/ip_joint_attention.py:18
↓ 2 callers
Class
JointAttnProcessor2_0
Attention processor used typically in processing the SD3-like self-attention projections.
ip_adapter/ip_joint_attention.py:152
↓ 2 callers
Class
LCMSchedulerOutput
Output class for the scheduler's `step` function output. Args: prev_sample (`torch.FloatTensor` of shape `(batch_size, num_channels,
src/schedulers/lcm_scheduler.py:11
↓ 2 callers
Class
Resampler
ip_adapter/resampler.py:83
↓ 2 callers
Class
ResamplerInstructBigger
ip_adapter/resampler_Instruct.py:271
↓ 1 callers
Class
AlexNet
src/metrics/lpips.py:67
↓ 1 callers
Class
AttnProcessor
r""" Default processor for performing attention-related computations.
ip_adapter/attention_processor.py:11
↓ 1 callers
Class
DDIMSchedulerOutput
Output class for the scheduler's `step` function output. Args: prev_sample (`torch.FloatTensor` of shape `(batch_size, num_channels,
src/schedulers/ddim_scheduler.py:11
↓ 1 callers
Class
IPAdapterInstruct
IP-Adapter with fine-grained features
ip_adapter/ip_adapter_instruct.py:36
↓ 1 callers
Class
IPAdapterInstructSDXL
ip_adapter/ip_adapter_instruct.py:281
↓ 1 callers
Class
IPAttnProcessor
r""" Attention processor for IP-Adapater. Args: hidden_size (`int`): The hidden size of the attention layer. cross
ip_adapter/attention_processor.py:84
↓ 1 callers
Class
ImageProjModel
Projection Model
ip_adapter/ip_adapter.py:33
↓ 1 callers
Class
JointTransformerBlock_IP
ip_adapter/joint_attention_block_modified.py:11
↓ 1 callers
Class
LPIPS
r"""Creates a criterion that measures Learned Perceptual Image Patch Similarity (LPIPS). Arguments: net_type (str): the network type t
src/metrics/lpips.py:122
↓ 1 callers
Class
LinLayers
src/metrics/lpips.py:88
↓ 1 callers
Class
MLPProjModel
SD model with image prompt
ip_adapter/ip_adapter.py:54
↓ 1 callers
Class
PerceiverAttention
ip_adapter/resampler.py:36
↓ 1 callers
Class
ResamplerSD3
ip_adapter/resampler_SD3.py:83
↓ 1 callers
Class
ResamplerSD3_Instruct
ip_adapter/resampler_SD3.py:171
↓ 1 callers
Class
RunConfig
src/config.py:10
↓ 1 callers
Class
SqueezeNet
src/metrics/lpips.py:56
↓ 1 callers
Class
VGG16
src/metrics/lpips.py:78
Class
ADAIN_Encoder
src/evaluate/net.py:64
Class
ADAIN_Encoder
evaluation/net.py:64
Class
AttnProcessor2_0
r""" Processor for implementing scaled dot-product attention (enabled by default if you're using PyTorch 2.0).
ip_adapter/attention_processor.py:191
Class
BaseNet
src/metrics/lpips.py:26
Class
BasicConv2d
src/evaluate/inception.py:394
Class
BasicConv2d
evaluation/inception.py:394
Class
CNAttnProcessor2_0
r""" Processor for implementing scaled dot-product attention (enabled by default if you're using PyTorch 2.0).
ip_adapter/attention_processor.py:477
Class
Decoder
src/evaluate/net.py:117
Class
Decoder
evaluation/net.py:117
Class
GramLoss
src/evaluate/image_metrics.py:135
Class
GramLoss
evaluation/image_metrics.py:135
Class
IPAdapter
ip_adapter/ip_adapter.py:71
Class
IPAdapterFull
IP-Adapter with full features
ip_adapter/ip_adapter.py:323
Class
IPAdapterPlus
IP-Adapter with fine-grained features
ip_adapter/ip_adapter.py:292
Class
IPAdapterPlusXL
SDXL
ip_adapter/ip_adapter.py:334
Class
IPAdapterXL
SDXL
ip_adapter/ip_adapter.py:227
Class
IPAdapter_sd3
ip_adapter/ip_adapter_instruct.py:490
Class
IPAdapter_sd3_Instruct
ip_adapter/ip_adapter_instruct.py:688
Class
IPAttnProcessor2_0
r""" Attention processor for IP-Adapater for PyTorch 2.0. Args: hidden_size (`int`): The hidden size of the attention laye
ip_adapter/attention_processor.py:280
Class
Inception3
src/evaluate/inception.py:21
Class
Inception3
evaluation/inception.py:21
Class
InceptionA
src/evaluate/inception.py:172
Class
InceptionA
evaluation/inception.py:172
Class
InceptionAux
src/evaluate/inception.py:363
Class
InceptionAux
evaluation/inception.py:363
Class
InceptionB
src/evaluate/inception.py:211
Class
InceptionB
evaluation/inception.py:211
Class
InceptionC
src/evaluate/inception.py:239
Class
InceptionC
evaluation/inception.py:239
Class
InceptionD
src/evaluate/inception.py:285
Class
InceptionD
evaluation/inception.py:285
Class
InceptionE
src/evaluate/inception.py:316
Class
InceptionE
evaluation/inception.py:316
Class
LPIPS
src/evaluate/image_metrics.py:66
Class
LPIPS
evaluation/image_metrics.py:66
Class
LPIPS_vgg
src/evaluate/image_metrics.py:77
Class
LPIPS_vgg
evaluation/image_metrics.py:77
Class
MLP
ip_adapter/resampler_Instruct.py:16
Class
Metric
src/evaluate/image_metrics.py:34
Class
Metric
evaluation/image_metrics.py:34
Class
Model_Type
src/eunms.py:11
Class
MyDDIMScheduler
src/schedulers/ddim_scheduler.py:27
Class
MyEulerAncestralDiscreteScheduler
src/schedulers/euler_scheduler.py:26
Class
MyLCMScheduler
src/schedulers/lcm_scheduler.py:27
Class
PatchSimi
src/evaluate/image_metrics.py:88
Class
PatchSimi
evaluation/image_metrics.py:88
Class
PerceiverAttentionMultiHead
Standard multi-head attention.
ip_adapter/resampler_Instruct.py:104
Class
ResamplerInstruct
ip_adapter/resampler_Instruct.py:198
Class
SDDDIMPipeline
src/pipes/sd_inversion_pipeline.py:18
Class
SDXLDDIMPipeline
src/pipes/sdxl_inversion_pipeline.py:19
Class
Scheduler_Type
src/eunms.py:6
Class
StableDiffusion3PipelineExtraCFG
r""" Args: transformer ([`SD3Transformer2DModel`]): Conditional Transformer (MMDiT) architecture to denoise the encoded image
ip_adapter/pipeline_stable_diffusion_sd3_extra_cfg.py:135
Class
StableDiffusionPipelineCFG
r""" Pipeline for text-to-image generation using Stable Diffusion. This model inherits from [`DiffusionPipeline`]. Check the superclass docum
ip_adapter/pipeline_stable_diffusion_extra_cfg.py:135
Class
StableDiffusionXLControlNetImg2ImgPipeline
r""" Pipeline for image-to-image generation using Stable Diffusion XL with ControlNet guidance. This model inherits from [`DiffusionPipeline`
pipeline_controlnet_sd_xl_img2img_plus.py:175
Class
StableDiffusionXLControlNetInpaintPipeline
r""" Pipeline for text-to-image generation using Stable Diffusion XL. This model inherits from [`DiffusionPipeline`]. Check the superclass do
pipeline_controlnet_inpaint_sd_xl.py:168
Class
StableDiffusionXLImg2ImgPipeline
r""" Pipeline for text-to-image generation using Stable Diffusion XL. This model inherits from [`DiffusionPipeline`]. Check the superclass do
pipeline_controlnet_sd_xl_img2img.py:184
Class
StableDiffusionXLPipelineExtraCFG
r""" Pipeline for text-to-image generation using Stable Diffusion XL. This model inherits from [`DiffusionPipeline`]. Check the superclass do
ip_adapter/pipeline_stable_diffusion_sdxl_extra_cfg.py:159