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Functions4,150 in github.com/Adamdad/hash3D

⨍ Functions 4,150◇ Types & classes 914↳ Endpoints 2
↓ 11 callersFunctionget_rank
()
threestudio-hash3d/threestudio/utils/misc.py:18
↓ 11 callersFunctionlog_txt_as_img
(wh, xc, size=10)
threestudio-hash3d/extern/ldm_zero123/util.py:35
↓ 11 callersMethodmeshgrid
(self, h, w)
threestudio-hash3d/extern/ldm_zero123/models/diffusion/ddpm.py:792
↓ 11 callersMethodsample
(self, batch_size=16, return_intermediates=False)
threestudio-hash3d/extern/ldm_zero123/models/diffusion/ddpm.py:417
↓ 10 callersFunctionC
(value: Any, epoch: int, global_step: int)
gaussiandreamer-hash3d/threestudio/utils/misc.py:65
↓ 10 callersMethod__init__
(self, dim_in: int, dim_out: int, config: dict)
threestudio-hash3d/threestudio/models/networks.py:215
↓ 10 callersFunctionconfig_to_primitive
(config, resolve: bool = True)
gaussiandreamer-hash3d/threestudio/utils/config.py:112
↓ 10 callersMethodfrom_pretrained
r""" Instantiate a PyTorch diffusion pipeline from pretrained pipeline weights. The pipeline is set in evaluation mode (`model.eval()
threestudio-hash3d/DeepCache/sd/pipeline_utils.py:769
↓ 10 callersMethodget_learned_conditioning
(self, c)
threestudio-hash3d/extern/ldm_zero123/models/diffusion/ddpm.py:777
↓ 10 callersFunctionget_rank
()
gaussiandreamer-hash3d/threestudio/utils/misc.py:17
↓ 10 callersFunctionnonlinearity
(x)
gaussiandreamer-hash3d/threestudio/utils/GAN/vae.py:35
↓ 10 callersFunctionnonlinearity
(x)
threestudio-hash3d/extern/ldm_zero123/modules/diffusionmodules/model.py:34
↓ 10 callersFunctionnonlinearity
(x)
threestudio-hash3d/threestudio/utils/GAN/vae.py:35
↓ 9 callersFunctionNormalize
(in_channels, num_groups=32)
gaussiandreamer-hash3d/threestudio/utils/GAN/vae.py:40
↓ 9 callersFunctionNormalize
(in_channels, num_groups=32)
threestudio-hash3d/extern/ldm_zero123/modules/diffusionmodules/model.py:39
↓ 9 callersFunctionNormalize
(in_channels, num_groups=32)
threestudio-hash3d/threestudio/utils/GAN/vae.py:40
↓ 9 callersMethod__init__
(self, dim_in: int, dim_out: int, config: dict)
gaussiandreamer-hash3d/threestudio/models/networks.py:151
↓ 9 callersMethod__init__
(self, channels, use_conv, dims=2, out_channels=None, padding=1)
threestudio-hash3d/extern/ldm_zero123/modules/diffusionmodules/openaimodel.py:104
↓ 9 callersMethodenable_attention_slicing
r""" Enable sliced attention computation. When this option is enabled, the attention module splits the input tensor in slices to compu
threestudio-hash3d/DeepCache/sd/pipeline_utils.py:1783
↓ 9 callersMethodget_first_stage_encoding
(self, encoder_posterior)
threestudio-hash3d/extern/ldm_zero123/models/diffusion/ddpm.py:766
↓ 9 callersFunctionperpendicular_component
(x: Float[Tensor, "B C H W"], y: Float[Tensor, "B C H W"])
threestudio-hash3d/threestudio/utils/ops.py:498
↓ 9 callersFunctionshift_azimuth_deg
(azimuth: Float[Tensor, "..."])
gaussiandreamer-hash3d/threestudio/models/prompt_processors/base.py:168
↓ 9 callersFunctionshift_azimuth_deg
(azimuth: Float[Tensor, "..."])
threestudio-hash3d/threestudio/models/prompt_processors/base.py:170
↓ 8 callersMethod_get_signature_keys
(obj)
dreamgaussian-hash3d/DeepCache/zero123/pipeline_utils.py:1654
↓ 8 callersMethod_get_signature_keys
(obj)
dreamgaussian-hash3d/DeepCache/sdxl/pipeline_utils.py:1654
↓ 8 callersMethod_get_signature_keys
(obj)
dreamgaussian-hash3d/DeepCache/sd/pipeline_utils.py:1654
↓ 8 callersMethod_get_signature_keys
(obj)
gaussiandreamer-hash3d/DeepCache/zero123/pipeline_utils.py:1654
↓ 8 callersMethod_get_signature_keys
(obj)
gaussiandreamer-hash3d/DeepCache/sdxl/pipeline_utils.py:1654
↓ 8 callersMethod_get_signature_keys
(obj)
gaussiandreamer-hash3d/DeepCache/sd/pipeline_utils.py:1654
↓ 8 callersMethod_get_signature_keys
(obj)
threestudio-hash3d/DeepCache/zero123/pipeline_utils.py:1654
↓ 8 callersMethod_get_signature_keys
(obj)
threestudio-hash3d/DeepCache/sdxl/pipeline_utils.py:1654
↓ 8 callersMethod_get_signature_keys
(obj)
threestudio-hash3d/DeepCache/sd/pipeline_utils.py:1654
↓ 8 callersMethoddevice
r""" Returns: `torch.device`: The torch device on which the pipeline is located.
dreamgaussian-hash3d/DeepCache/zero123/pipeline_utils.py:753
↓ 8 callersMethoddevice
r""" Returns: `torch.device`: The torch device on which the pipeline is located.
gaussiandreamer-hash3d/DeepCache/zero123/pipeline_utils.py:753
↓ 8 callersMethoddevice
r""" Returns: `torch.device`: The torch device on which the pipeline is located.
threestudio-hash3d/DeepCache/zero123/pipeline_utils.py:753
↓ 8 callersMethoddo_update_step
( self, epoch: int, global_step: int, on_load_weights: bool = False )
gaussiandreamer-hash3d/threestudio/utils/base.py:22
↓ 8 callersMethoddo_update_step
( self, epoch: int, global_step: int, on_load_weights: bool = False )
threestudio-hash3d/threestudio/utils/base.py:22
↓ 8 callersMethodenable_sequential_cpu_offload
r""" Offloads all models to CPU using accelerate, significantly reducing memory usage. When called, unet, text_encoder, vae and safety
threestudio-hash3d/extern/zero123.py:180
↓ 8 callersMethodenable_xformers_memory_efficient_attention
r""" Enable memory efficient attention from [xFormers](https://facebookresearch.github.io/xformers/). When this option is enabled, you
threestudio-hash3d/DeepCache/sd/pipeline_utils.py:1722
↓ 8 callersMethodfrom_pretrained
r""" Instantiate a PyTorch diffusion pipeline from pretrained pipeline weights. The pipeline is set in evaluation mode (`model.eval()
dreamgaussian-hash3d/DeepCache/sd/pipeline_utils.py:769
↓ 8 callersFunctionget_ray_directions
Get ray directions for all pixels in camera coordinate. Reference: https://www.scratchapixel.com/lessons/3d-basic-rendering/ r
gaussiandreamer-hash3d/threestudio/utils/ops.py:179
↓ 8 callersFunctionget_ray_directions
Get ray directions for all pixels in camera coordinate. Reference: https://www.scratchapixel.com/lessons/3d-basic-rendering/ r
threestudio-hash3d/threestudio/utils/ops.py:180
↓ 8 callersFunctionnormalization
Make a standard normalization layer. :param channels: number of input channels. :return: an nn.Module for normalization.
threestudio-hash3d/extern/ldm_zero123/modules/diffusionmodules/util.py:226
↓ 8 callersFunctionparse_version
(ver: str)
gaussiandreamer-hash3d/threestudio/utils/misc.py:13
↓ 8 callersFunctionperpendicular_component
(x: Float[Tensor, "B C H W"], y: Float[Tensor, "B C H W"])
gaussiandreamer-hash3d/threestudio/utils/ops.py:431
↓ 8 callersMethodrefine
(self, pred_rgb, elevation, azimuth, radius, guidance_scale=5, steps=50, strength=0.8, default
dreamgaussian-hash3d/guidance/zero123_utils.py:76
↓ 8 callersMethodsample
(self)
threestudio-hash3d/extern/ldm_zero123/modules/distributions/distributions.py:17
↓ 8 callersMethodsample
( self, prompt_utils: PromptProcessorOutput, elevation: Float[Tensor, "B"], az
threestudio-hash3d/threestudio/models/guidance/stable_diffusion_vsd_guidance.py:327
↓ 8 callersMethodwrite
(self, x)
gaussiandreamer-hash3d/gaussiansplatting/utils/general_utils.py:118
↓ 7 callersMethod__init__
( self, unet_config, timesteps=1000, beta_schedule="linear", loss_type
threestudio-hash3d/extern/ldm_zero123/models/diffusion/ddpm.py:67
↓ 7 callersMethoddecode_latents
( self, latents: Float[Tensor, "B 4 H W"], )
threestudio-hash3d/threestudio/models/guidance/zero123_guidance.py:195
↓ 7 callersMethodencode
(self, c)
gaussiandreamer-hash3d/threestudio/utils/GAN/discriminator.py:114
↓ 7 callersMethodencode
(self, text)
threestudio-hash3d/extern/ldm_zero123/modules/encoders/modules.py:210
↓ 7 callersMethodexport
(self, *args, **kwargs)
threestudio-hash3d/threestudio/models/geometry/base.py:50
↓ 7 callersMethodforward_density
(self, points: Float[Tensor, "*N Di"])
gaussiandreamer-hash3d/threestudio/models/geometry/volume_grid.py:148
↓ 7 callersFunctionget_encoding
(n_input_dims: int, config)
gaussiandreamer-hash3d/threestudio/models/networks.py:132
↓ 7 callersFunctionget_encoding
(n_input_dims: int, config)
threestudio-hash3d/threestudio/models/networks.py:194
↓ 7 callersFunctionget_rays
( directions: Float[Tensor, "... 3"], c2w: Float[Tensor, "... 4 4"], keepdim=False, noise_scal
threestudio-hash3d/threestudio/utils/ops.py:220
↓ 7 callersFunctionload_img
(img_name, size=None)
threestudio-hash3d/extern/ldm_zero123/modules/evaluate/evaluate_perceptualsim.py:322
↓ 7 callersFunctionmake_attn
(in_channels, attn_type="vanilla")
gaussiandreamer-hash3d/threestudio/utils/GAN/vae.py:193
↓ 7 callersFunctionmake_attn
(in_channels, attn_type="vanilla")
threestudio-hash3d/extern/ldm_zero123/modules/diffusionmodules/model.py:194
↓ 7 callersFunctionmake_attn
(in_channels, attn_type="vanilla")
threestudio-hash3d/threestudio/utils/GAN/vae.py:193
↓ 7 callersMethodto_rgb
(self, x)
threestudio-hash3d/extern/ldm_zero123/models/diffusion/ddpm.py:1917
↓ 6 callersMethod__init__
(self, dim_in, dim_out)
gaussiandreamer-hash3d/threestudio/utils/GAN/attention.py:39
↓ 6 callersMethod__init__
(self, dim_in, dim_out)
threestudio-hash3d/extern/ldm_zero123/modules/attention.py:39
↓ 6 callersMethod__init__
(self, dim_in, dim_out)
threestudio-hash3d/threestudio/utils/GAN/attention.py:39
↓ 6 callersFunctionadd_JPEG_noise
(img)
threestudio-hash3d/extern/ldm_zero123/modules/image_degradation/bsrgan.py:452
↓ 6 callersFunctionadd_blur
(img, sf=4)
threestudio-hash3d/extern/ldm_zero123/modules/image_degradation/bsrgan.py:335
↓ 6 callersMethodbackward
(ctx, g)
threestudio-hash3d/threestudio/utils/ops.py:52
↓ 6 callersFunctiondefault
(val, d)
threestudio-hash3d/extern/ldm_zero123/util.py:77
↓ 6 callersFunctiondefault
(val, d)
threestudio-hash3d/extern/ldm_zero123/modules/x_transformer.py:57
↓ 6 callersMethodeval
(self)
gaussiandreamer-hash3d/threestudio/models/renderers/patch_renderer.py:105
↓ 6 callersMethodextract
(self, args)
gaussiandreamer-hash3d/gaussiansplatting/arguments/__init__.py:40
↓ 6 callersFunctionfocal2fov
(focal, pixels)
gaussiandreamer-hash3d/gaussiansplatting/utils/graphics_utils.py:98
↓ 6 callersMethodforward_unet
Forward pass for the U-Net based diffusion model. Args: latents (Tensor): Input latent tensors representing the model's
gaussiandreamer-hash3d/threestudio/models/guidance/stable_diffusion_guidance_cache.py:168
↓ 6 callersMethodforward_unet
( self, latents: Float[Tensor, "..."], t: Float[Tensor, "..."], encoder_hidden
gaussiandreamer-hash3d/threestudio/models/guidance/stable_diffusion_guidance.py:146
↓ 6 callersMethodforward_unet
Forward pass for the U-Net based diffusion model. Args: latents (Tensor): Input latent tensors representing the model's
threestudio-hash3d/threestudio/models/guidance/stable_diffusion_guidance_cache.py:168
↓ 6 callersMethodforward_unet
( self, latents: Float[Tensor, "..."], t: Float[Tensor, "..."], encoder_hidden
threestudio-hash3d/threestudio/models/guidance/stable_diffusion_guidance.py:147
↓ 6 callersMethodgeometry
(self)
gaussiandreamer-hash3d/threestudio/models/renderers/base.py:54
↓ 6 callersMethodget_save_dir
(self)
threestudio-hash3d/threestudio/utils/saving.py:29
↓ 6 callersMethodget_text_embeddings_perp_neg
( self, elevation: Float[Tensor, "B"], azimuth: Float[Tensor, "B"], camera_dis
threestudio-hash3d/threestudio/models/prompt_processors/base.py:82
↓ 6 callersFunctionismap
(x)
threestudio-hash3d/extern/ldm_zero123/util.py:61
↓ 6 callersMethodnormal_consistency
(self)
threestudio-hash3d/threestudio/models/mesh.py:269
↓ 6 callersMethodrender
(self)
dreamgaussian-hash3d/main_hash.py:894
↓ 6 callersMethodrender
(self)
dreamgaussian-hash3d/main.py:879
↓ 6 callersFunctionrenew_resnet_paths
Updates paths inside resnets to the new naming scheme (local renaming)
gaussiandreamer-hash3d/scripts/convert_zero123_to_diffusers.py:216
↓ 6 callersFunctionrenew_resnet_paths
Updates paths inside resnets to the new naming scheme (local renaming)
threestudio-hash3d/scripts/convert_zero123_to_diffusers.py:216
↓ 6 callersFunctionsafe_normalize
(x, eps=1e-20)
dreamgaussian-hash3d/cam_utils.py:20
↓ 6 callersFunctionscale_tensor
( dat: Num[Tensor, "... D"], inp_scale: ValidScale, tgt_scale: ValidScale )
gaussiandreamer-hash3d/threestudio/utils/ops.py:26
↓ 6 callersFunctionscale_tensor
( dat: Num[Tensor, "... D"], inp_scale: ValidScale, tgt_scale: ValidScale )
threestudio-hash3d/threestudio/utils/ops.py:27
↓ 5 callersMethod__init__
(self, inplace=True)
gaussiandreamer-hash3d/threestudio/utils/GAN/mobilenet.py:34
↓ 5 callersMethod__init__
(self, inplace=True)
threestudio-hash3d/threestudio/utils/GAN/mobilenet.py:34
↓ 5 callersMethod_get_denoise_row_from_list
( self, samples, desc="", force_no_decoder_quantization=False )
threestudio-hash3d/extern/ldm_zero123/models/diffusion/ddpm.py:749
↓ 5 callersFunctionadjust_lora_scale_text_encoder
(text_encoder, lora_scale: float = 1.0)
dreamgaussian-hash3d/DeepCache/sd/lora.py:70
↓ 5 callersFunctionadjust_lora_scale_text_encoder
(text_encoder, lora_scale: float = 1.0)
gaussiandreamer-hash3d/DeepCache/sd/lora.py:70
↓ 5 callersFunctionadjust_lora_scale_text_encoder
(text_encoder, lora_scale: float = 1.0)
threestudio-hash3d/DeepCache/sd/lora.py:70
↓ 5 callersMethodcompute_hash_index
Computes the hash index for a given key. Args: key (torch.Tensor): Key tensor of the form [c1, c2, c3, t]. Retu
gaussiandreamer-hash3d/threestudio/utils/hash_table.py:43
↓ 5 callersMethodcompute_hash_index
Computes the hash index for a given key. Args: key (torch.Tensor): Key tensor of the form [c1, c2, c3, t]. Retu
threestudio-hash3d/threestudio/utils/hash_table.py:46
↓ 5 callersMethoddecode_latents
( self, latents: Float[Tensor, "B 4 H W"], latent_height: int = 64, latent_wid
threestudio-hash3d/threestudio/models/guidance/stable_diffusion_guidance.py:171
↓ 5 callersMethoddevice
r""" Returns: `torch.device`: The torch device on which the pipeline is located.
dreamgaussian-hash3d/DeepCache/sdxl/pipeline_utils.py:753
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