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Types & classes84 in github.com/bytedance/StyleSSP

↓ 5 callersClassImagePathDataset
evaluation/eval_artfid.py:26
↓ 5 callersClassPerceiverAttention
ip_adapter/resampler_Instruct.py:152
↓ 4 callersClassPerceiverAttention
ip_adapter/resampler_SD3.py:36
↓ 3 callersClassEulerAncestralDiscreteSchedulerOutput
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 callersClassCNAttnProcessor
r""" Default processor for performing attention-related computations.
ip_adapter/attention_processor.py:412
↓ 2 callersClassIPJointAttnProcessor2_0
Attention processor used typically in processing the SD3-like self-attention projections.
ip_adapter/ip_joint_attention.py:18
↓ 2 callersClassJointAttnProcessor2_0
Attention processor used typically in processing the SD3-like self-attention projections.
ip_adapter/ip_joint_attention.py:152
↓ 2 callersClassLCMSchedulerOutput
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 callersClassResampler
ip_adapter/resampler.py:83
↓ 2 callersClassResamplerInstructBigger
ip_adapter/resampler_Instruct.py:271
↓ 1 callersClassAlexNet
src/metrics/lpips.py:67
↓ 1 callersClassAttnProcessor
r""" Default processor for performing attention-related computations.
ip_adapter/attention_processor.py:11
↓ 1 callersClassDDIMSchedulerOutput
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 callersClassIPAdapterInstruct
IP-Adapter with fine-grained features
ip_adapter/ip_adapter_instruct.py:36
↓ 1 callersClassIPAdapterInstructSDXL
ip_adapter/ip_adapter_instruct.py:281
↓ 1 callersClassIPAttnProcessor
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 callersClassImageProjModel
Projection Model
ip_adapter/ip_adapter.py:33
↓ 1 callersClassJointTransformerBlock_IP
ip_adapter/joint_attention_block_modified.py:11
↓ 1 callersClassLPIPS
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 callersClassLinLayers
src/metrics/lpips.py:88
↓ 1 callersClassMLPProjModel
SD model with image prompt
ip_adapter/ip_adapter.py:54
↓ 1 callersClassPerceiverAttention
ip_adapter/resampler.py:36
↓ 1 callersClassResamplerSD3
ip_adapter/resampler_SD3.py:83
↓ 1 callersClassResamplerSD3_Instruct
ip_adapter/resampler_SD3.py:171
↓ 1 callersClassRunConfig
src/config.py:10
↓ 1 callersClassSqueezeNet
src/metrics/lpips.py:56
↓ 1 callersClassVGG16
src/metrics/lpips.py:78
ClassADAIN_Encoder
src/evaluate/net.py:64
ClassADAIN_Encoder
evaluation/net.py:64
ClassAttnProcessor2_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
ClassBaseNet
src/metrics/lpips.py:26
ClassBasicConv2d
src/evaluate/inception.py:394
ClassBasicConv2d
evaluation/inception.py:394
ClassCNAttnProcessor2_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
ClassDecoder
src/evaluate/net.py:117
ClassDecoder
evaluation/net.py:117
ClassGramLoss
src/evaluate/image_metrics.py:135
ClassGramLoss
evaluation/image_metrics.py:135
ClassIPAdapter
ip_adapter/ip_adapter.py:71
ClassIPAdapterFull
IP-Adapter with full features
ip_adapter/ip_adapter.py:323
ClassIPAdapterPlus
IP-Adapter with fine-grained features
ip_adapter/ip_adapter.py:292
ClassIPAdapterPlusXL
SDXL
ip_adapter/ip_adapter.py:334
ClassIPAdapterXL
SDXL
ip_adapter/ip_adapter.py:227
ClassIPAdapter_sd3
ip_adapter/ip_adapter_instruct.py:490
ClassIPAdapter_sd3_Instruct
ip_adapter/ip_adapter_instruct.py:688
ClassIPAttnProcessor2_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
ClassInception3
src/evaluate/inception.py:21
ClassInception3
evaluation/inception.py:21
ClassInceptionA
src/evaluate/inception.py:172
ClassInceptionA
evaluation/inception.py:172
ClassInceptionAux
src/evaluate/inception.py:363
ClassInceptionAux
evaluation/inception.py:363
ClassInceptionB
src/evaluate/inception.py:211
ClassInceptionB
evaluation/inception.py:211
ClassInceptionC
src/evaluate/inception.py:239
ClassInceptionC
evaluation/inception.py:239
ClassInceptionD
src/evaluate/inception.py:285
ClassInceptionD
evaluation/inception.py:285
ClassInceptionE
src/evaluate/inception.py:316
ClassInceptionE
evaluation/inception.py:316
ClassLPIPS
src/evaluate/image_metrics.py:66
ClassLPIPS
evaluation/image_metrics.py:66
ClassLPIPS_vgg
src/evaluate/image_metrics.py:77
ClassLPIPS_vgg
evaluation/image_metrics.py:77
ClassMLP
ip_adapter/resampler_Instruct.py:16
ClassMetric
src/evaluate/image_metrics.py:34
ClassMetric
evaluation/image_metrics.py:34
ClassModel_Type
src/eunms.py:11
ClassMyDDIMScheduler
src/schedulers/ddim_scheduler.py:27
ClassMyEulerAncestralDiscreteScheduler
src/schedulers/euler_scheduler.py:26
ClassMyLCMScheduler
src/schedulers/lcm_scheduler.py:27
ClassPatchSimi
src/evaluate/image_metrics.py:88
ClassPatchSimi
evaluation/image_metrics.py:88
ClassPerceiverAttentionMultiHead
Standard multi-head attention.
ip_adapter/resampler_Instruct.py:104
ClassResamplerInstruct
ip_adapter/resampler_Instruct.py:198
ClassSDDDIMPipeline
src/pipes/sd_inversion_pipeline.py:18
ClassSDXLDDIMPipeline
src/pipes/sdxl_inversion_pipeline.py:19
ClassScheduler_Type
src/eunms.py:6
ClassStableDiffusion3PipelineExtraCFG
r""" Args: transformer ([`SD3Transformer2DModel`]): Conditional Transformer (MMDiT) architecture to denoise the encoded image
ip_adapter/pipeline_stable_diffusion_sd3_extra_cfg.py:135
ClassStableDiffusionPipelineCFG
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
ClassStableDiffusionXLControlNetImg2ImgPipeline
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
ClassStableDiffusionXLControlNetInpaintPipeline
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
ClassStableDiffusionXLImg2ImgPipeline
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
ClassStableDiffusionXLPipelineExtraCFG
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