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Functions867 in github.com/Fanghua-Yu/SUPIR

⨍ Functions 867◇ Types & classes 180↳ Endpoints 12

( self, weighting_config, scaling_config, num_idx, discretization_conf

sgm/modules/diffusionmodules/denoiser.py:32

(self, diffusion_model, compile_model: bool = False)

sgm/modules/diffusionmodules/wrappers.py:12

(self, *args, **kwargs)

sgm/modules/diffusionmodules/wrappers.py:41

(self, in_channels, with_conv)

sgm/modules/diffusionmodules/model.py:56

(self, in_channels, with_conv)

sgm/modules/diffusionmodules/model.py:72

( self, *, in_channels, out_channels=None, conv_shortcut=False,

sgm/modules/diffusionmodules/model.py:92

(self, in_channels)

sgm/modules/diffusionmodules/model.py:154

(self, in_channels)

sgm/modules/diffusionmodules/model.py:159

(self, in_channels)

sgm/modules/diffusionmodules/model.py:209

( self, *, ch, out_ch, ch_mult=(1, 2, 4, 8), num_res_blocks,

sgm/modules/diffusionmodules/model.py:483

( self, *, ch, out_ch, ch_mult=(1, 2, 4, 8), num_res_blocks,

sgm/modules/diffusionmodules/model.py:600

(self, scale, dyn_thresh_config=None)

sgm/modules/diffusionmodules/guiders.py:13

(self, scale, scale_min=None, dyn_thresh_config=None)

sgm/modules/diffusionmodules/guiders.py:45

(self, sample: bool = True)

sgm/modules/autoencoding/regularizers/__init__.py:24

( self, num_features, logdet=False, affine=True, allow_reverse_init=False )

sgm/modules/autoencoding/lpips/util.py:46

Construct a PatchGAN discriminator Parameters: input_nc (int) -- the number of channels in input images ndf (int)

sgm/modules/autoencoding/lpips/model/model.py:22

sgm/modules/autoencoding/lpips/loss/lpips.py:68

(self, chn_in, chn_out=1, use_dropout=False)

sgm/modules/autoencoding/lpips/loss/lpips.py:84

(self, requires_grad=False, pretrained=True)

sgm/modules/autoencoding/lpips/loss/lpips.py:100

( self, disc_start: int, logvar_init: float = 0.0, pixelloss_weight=1.0,

sgm/modules/autoencoding/losses/__init__.py:88

sgm/modules/distributions/distributions.py:14

(self, parameters, deterministic=False)

sgm/modules/distributions/distributions.py:25

sgm/modules/encoders/modules.py:38

(self, emb_models: Union[List, ListConfig])

sgm/modules/encoders/modules.py:85

(self, cond_pth, un_cond_pth=None)

sgm/modules/encoders/modules.py:247

(self, embed_dim, n_classes=1000, add_sequence_dim=False)

sgm/modules/encoders/modules.py:329

( self, version="google/t5-v1_1-xxl", device="cuda", max_length=77, freeze=True )

sgm/modules/encoders/modules.py:365

( self, version="google/byt5-base", device="cuda", max_length=77, freeze=True )

sgm/modules/encoders/modules.py:408

( self, version="openai/clip-vit-large-patch14", device="cuda", max_length=77,

sgm/modules/encoders/modules.py:450

( self, arch="ViT-H-14", version="laion2b_s32b_b79k", device="cuda", m

sgm/modules/encoders/modules.py:517

( self, arch="ViT-H-14", version="laion2b_s32b_b79k", device="cuda", m

sgm/modules/encoders/modules.py:619

( self, arch="ViT-H-14", version="laion2b_s32b_b79k", device="cuda", m

sgm/modules/encoders/modules.py:689

( self, clip_version="openai/clip-vit-large-patch14", t5_version="google/t5-v1_1-xl",

sgm/modules/encoders/modules.py:845

( self, n_stages=1, method="bilinear", multiplier=0.5, in_channels=3,

sgm/modules/encoders/modules.py:873

( self, model_config, linear_start, linear_end, timesteps=1000,

sgm/modules/encoders/modules.py:933

sgm/modules/encoders/modules.py:1030

( self, weight: float = 1.0, flatten_output: bool = True, *args, **kwargs )

sgm/modules/encoders/modules.py:1047

( self, network_config, denoiser_config, first_stage_config, condition

sgm/models/diffusion.py:23

( self, ema_decay: Union[None, float] = None, monitor: Union[None, str] = None,

sgm/models/autoencoder.py:25

( self, *args, encoder_config: Dict, decoder_config: Dict, loss_config

sgm/models/autoencoder.py:123

(self, *args, **kwargs)

sgm/models/autoencoder.py:325

llava/train/llava_trainer.py:124

llava/eval/model_vqa_loader.py:60

llava/train/train.py:640

llava/train/llava_trainer.py:121

Function_build_alibi_tensor

(self: BloomModel, batch_size: int, query_length: int, key_length: int, dtype: torch.dtype, device: torch.devi

llava/model/language_model/mpt/hf_prefixlm_converter.py:140

Function_bwd_kernel

(Q, K, V, Bias, DO, DQ, DK, DV, LSE, D, softmax_scale, stride_qb, stride_qh, stride_qm, stride_kb, stride_kh,

llava/model/language_model/mpt/flash_attn_triton.py:306

Function_bwd_preprocess_do_o_dot

(Out, DO, Delta, stride_ob, stride_oh, stride_om, stride_dob, stride_doh, stride_dom, nheads, seqlen_q, seqlen

llava/model/language_model/mpt/flash_attn_triton.py:155

( self, x, context=None, additional_tokens=None, n_times_crossframe_attn_in_self=0 )

sgm/modules/attention.py:465

(self, x, context=None)

sgm/modules/attention.py:527

sgm/modules/diffusionmodules/openaimodel.py:330

sgm/modules/diffusionmodules/openaimodel.py:402

Function_fwd_kernel

(Q, K, V, Bias, Out, Lse, TMP, softmax_scale, stride_qb, stride_qh, stride_qm, stride_kb, stride_kh, stride_kn

llava/model/language_model/mpt/flash_attn_triton.py:51

Method_get_train_sampler

llava/train/llava_trainer.py:134

Function_prepare_attn_mask

(self: BloomModel, attention_mask: torch.Tensor, bidirectional_mask: Optional[torch.Tensor], input_shape: Tupl

llava/model/language_model/mpt/hf_prefixlm_converter.py:126

Function_prepare_decoder_attention_mask

(self, attention_mask, input_shape, inputs_embeds, past_key_values_length)

llava/model/language_model/mpt/hf_prefixlm_converter.py:285

Function_prepare_decoder_attention_mask

( self, attention_mask, input_shape, inputs_embeds, past_key_values_length )

llava/train/llama_flash_attn_monkey_patch.py:98

Method_reorder_cache

Used by HuggingFace generate when using beam search with kv-caching. See https://github.com/huggingface/transformers/blob/3ec7a47664ebe40c40f

llava/model/language_model/mpt/modeling_mpt.py:322

Method_save_checkpoint

(self, model, trial, metrics=None)

llava/train/llava_trainer.py:150

Method_set_gradient_checkpointing

(self, module, value=False)

llava/model/language_model/llava_mpt.py:68

Methodactivation_checkpointing_fn

llava/model/language_model/mpt/modeling_mpt.py:229

Methodactivation_checkpointing_fn

llava/model/language_model/mpt/modeling_mpt.py:298

Functionadain_color_fix

(target: Image, source: Image)

SUPIR/utils/colorfix.py:14

Functionadd_bidirectional_mask_if_missing

Attempts to add bidirectional_mask to batch if missing. Raises: KeyError if bidirectional_mask is missing and can't be inferred

llava/model/language_model/mpt/hf_prefixlm_converter.py:401

Functionadd_text

(state, text, image, image_process_mode, request: gr.Request)

llava/serve/gradio_web_server.py:129

Functionattn_forward_new_xformers

(self, hidden_states)

SUPIR/utils/tilevae.py:232

Functionautocast

(disable=False)

SUPIR/utils/devices.py:92

Functionautocast

(f, enabled=True)

llava/model/language_model/mpt/flash_attn_triton.py:419

llava/model/language_model/mpt/flash_attn_triton.py:446

llava/model/language_model/mpt/flash_attn_triton.py:475

(ctx, *output_grads)

sgm/modules/diffusionmodules/util.py:119

(ctx, *output_grads)

sgm/modules/diffusionmodules/util.py:186

Functionbaseline_param_init_fn_

(module: nn.Module, init_std: float, n_layers: int, d_model: Optional[int]=None, init_div_is_residual: Union[i

llava/model/language_model/mpt/param_init_fns.py:131

Functionclear_history

(request: gr.Request)

llava/serve/gradio_web_server.py:123

Functioncond_cast_float

SUPIR/utils/devices.py:79

Functioncond_cast_unet

SUPIR/utils/devices.py:75

llava/model/multimodal_projector/builder.py:14

llava/model/multimodal_encoder/clip_encoder.py:72

Methodconfigure_optimizers

sgm/models/diffusion.py:196

Methodconfigure_optimizers

sgm/models/autoencoder.py:112

Methodconfigure_optimizers

sgm/models/autoencoder.py:254

Functionconvert_caps

llava/eval/eval_science_qa_gpt4.py:19

Functionconvert_caps

llava/eval/eval_science_qa.py:19

Functionconvert_caps

llava/eval/eval_science_qa_gpt4_requery.py:21

Functionconvert_hf_causal_lm_to_prefix_lm

Converts a HuggingFace Causal LM to a Prefix LM. Supported HuggingFace model classes: - `GPT2LMHeadModel` - `GPTNeoForCausalLM`

llava/model/language_model/mpt/hf_prefixlm_converter.py:335

Functionconvert_module_to_f16

SUPIR/modules/SUPIR_v0.py:37

Functionconvert_module_to_f16

sgm/modules/diffusionmodules/openaimodel.py:28

Functionconvert_module_to_f32

SUPIR/modules/SUPIR_v0.py:41

Functionconvert_module_to_f32

sgm/modules/diffusionmodules/openaimodel.py:32

Methodconvert_to_fp16

Convert the torso of the model to float16.

SUPIR/modules/SUPIR_v0.py:485

Methodconvert_to_fp16

Convert the torso of the model to float16.

sgm/modules/diffusionmodules/openaimodel.py:963

Methodconvert_to_fp16

Convert the torso of the model to float16.

sgm/modules/diffusionmodules/openaimodel.py:1201

Methodconvert_to_fp32

Convert the torso of the model to float32.

SUPIR/modules/SUPIR_v0.py:492

Methodconvert_to_fp32

Convert the torso of the model to float32.

sgm/modules/diffusionmodules/openaimodel.py:971

Methodconvert_to_fp32

Convert the torso of the model to float32.

sgm/modules/diffusionmodules/openaimodel.py:1208

Methodcount_flops

sgm/modules/diffusionmodules/openaimodel.py:459

Methodcount_flops

sgm/modules/diffusionmodules/openaimodel.py:493

Functioncustom_forward

llava/model/language_model/mpt/hf_prefixlm_converter.py:209

(self, *args, **kwargs)

sgm/models/autoencoder.py:103

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