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Functions506 in github.com/dek924/PerX2CT

⨍ Functions 506◇ Types & classes 129
Methodforward
(self, x)
taming/modules/diffusionmodules/model.py:724
Methodforward
(self, x)
taming/modules/diffusionmodules/model.py:771
Methodforward
Standard forward.
taming/modules/discriminator/model.py:65
Methodforward
Inputs the output of the encoder network z and maps it to a discrete one-hot vector that is the index of the closest embedding vector
taming/modules/vqvae/quantize.py:34
Methodforward
(self, z, temp=None, return_logits=False)
taming/modules/vqvae/quantize.py:171
Methodforward
(self, z, temp=None, rescale_logits=False, return_logits=False)
taming/modules/vqvae/quantize.py:273
Methodforward
(self, embed_id)
taming/modules/vqvae/quantize.py:344
Methodforward
(self, z)
taming/modules/vqvae/quantize.py:409
Methodforward
(self, x, layer_past=None)
taming/modules/transformer/mingpt.py:69
Methodforward
(self, x, layer_past=None, return_present=False)
taming/modules/transformer/mingpt.py:112
Methodforward
(self, idx, embeddings=None, targets=None)
taming/modules/transformer/mingpt.py:160
Methodforward
(self, idx)
taming/modules/transformer/mingpt.py:221
Methodforward
(self, idx, embeddings=None, targets=None)
taming/modules/transformer/mingpt.py:260
Methodforward
(self, x, reverse=False, shape=None)
taming/modules/transformer/mingpt.py:389
Methodforward
(self, x, reverse=False)
taming/modules/transformer/permuter.py:9
Methodforward
(self, x, reverse=False)
taming/modules/transformer/permuter.py:17
Methodforward
(self, x, reverse=False)
taming/modules/transformer/permuter.py:40
Methodforward
(self, x, reverse=False)
taming/modules/transformer/permuter.py:74
Methodforward
(self, x, reverse=False)
taming/modules/transformer/permuter.py:134
Methodforward
(self, x, reverse=False)
taming/modules/transformer/permuter.py:195
Methodforward
(self, x, reverse=False)
taming/modules/transformer/permuter.py:210
Methodforward
(self, x, reverse=False)
taming/modules/transformer/permuter.py:229
Methodforward
(self, codebook_loss, inputs, reconstructions, optimizer_idx, global_step, last_layer=None, co
taming/modules/losses/vqperceptual.py:76
Methodforward
(self, input, target)
taming/modules/losses/lpips.py:41
Methodforward
(self, inp)
taming/modules/losses/lpips.py:63
Methodforward
(self, X)
taming/modules/losses/lpips.py:100
Methodforward
(self, prediction, target)
taming/modules/losses/segmentation.py:6
Methodforward
(self, qloss, target, prediction, split)
taming/modules/losses/segmentation.py:16
Methodfrom_pretrained
(cls, name="vgg_lpips")
x2ct_nerf/modules/losses/lpips.py:33
Methodfrom_pretrained
(cls, name="vgg_lpips")
taming/modules/losses/lpips.py:33
Methodget_additional_input
(self, batch, keys)
x2ct_nerf/models/aegan.py:96
Methodget_block_size
(self)
taming/modules/transformer/mingpt.py:248
Methodget_codebook_entry
(self, indices, shape)
taming/modules/vqvae/quantize.py:92
Methodget_codebook_entry
(self, indices, shape)
taming/modules/vqvae/quantize.py:204
Methodget_codebook_entry
(self, indices, shape)
taming/modules/vqvae/quantize.py:316
Functionget_embedder
(multires, i=0)
x2ct_nerf/modules/nerf/nerf_helpers.py:37
Functionget_rays
transformed_points: (batch_size, args.img_res * args.img_res, args.N_samples, 3) transformed_ray_directions_expanded: (batch_size, args.img_r
x2ct_nerf/modules/volume_rendering.py:13
Functionget_rays_for_no_rendering
trained_ct_res: if trained_ct_res is different from visualize ct_res transformed_points: (batch_size, args.img_res, args.img_res, args.N_samp
x2ct_nerf/modules/volume_rendering.py:42
Functionget_root
(name)
taming/data/utils.py:43
Functionhinge_d_loss
(logits_real, logits_fake)
x2ct_nerf/modules/losses/vqperceptual.py:20
Functionhinge_d_loss
(logits_real, logits_fake)
x2ct_nerf/modules/losses/perceptual.py:20
Functionhinge_d_loss
(logits_real, logits_fake)
taming/modules/losses/vqperceptual.py:20
Functionhook
(b=1, bsize=1, tsize=None)
taming/data/utils.py:35
Methodinitialize
(self, x)
taming/modules/transformer/mingpt.py:370
Methodis_initialized
(self)
taming/modules/transformer/mingpt.py:366
Functionis_prepared
(root)
taming/data/utils.py:50
Functionkaiming_leaky_init
(m)
x2ct_nerf/modules/discriminator/base.py:25
Functionload_scan_dcm
(path)
data_preprocessing/ctxray_utils.py:15
Methodlog_images
(self, batch, **kwargs)
x2ct_nerf/models/zoom_aegan.py:136
Methodlog_images
(self, batch, **kwargs)
x2ct_nerf/models/base.py:124
Methodlog_images
(self, batch, **kwargs)
x2ct_nerf/models/aegan.py:182
Methodlog_images
(self, batch, **kwargs)
x2ct_nerf/models/aegan.py:324
Methodlog_images
(self, batch, **kwargs)
x2ct_nerf/models/aegan.py:485
Methodlog_images
(self, batch, **kwargs)
x2ct_nerf/models/aegan.py:639
Methodlog_images
(self, batch, **kwargs)
x2ct_nerf/models/aegan.py:797
Methodlog_images_from_gt
(self, batch)
x2ct_nerf/models/base.py:260
Methodlog_local
(self, save_dir, split, images, global_step, current_epoch, batch_idx)
main.py:346
Functionmain_test_random_crop
(args)
main_test_zoom.py:438
Functionmark_prepared
(root)
taming/data/utils.py:54
Functionnetwork_query_fn
(inputs, viewdirs, network_fn)
x2ct_nerf/modules/nerf/model_utils.py:75
Methodon_batch_end
Check if we should save a checkpoint after every train batch
main.py:273
Methodon_pretrain_routine_start
(self, trainer, pl_module)
main.py:217
Methodon_train_batch_end
(self, trainer, pl_module, outputs, batch, batch_idx, dataloader_idx)
main.py:402
Methodon_validation_batch_end
(self, trainer, pl_module, outputs, batch, batch_idx, dataloader_idx)
main.py:405
Functionprompt_download
(file_, source, target_dir, content_dir=None)
taming/data/utils.py:58
Functionpsnr
(img_1, img_2, PIXEL_MAX = 255.0)
data_preprocessing/ctxray_utils.py:112
Functionquadratic_crop
bbox is xmin, ymin, xmax, ymax
taming/data/utils.py:96
Methodremap_to_used
(self, inds)
taming/modules/vqvae/quantize.py:385
Functionresize_to_standard
(path)
data_preprocessing/ctxray_utils.py:92
Functionret
(inputs, axis=0)
x2ct_nerf/modules/nerf/model_utils.py:10
Functionsample
take a conditioning sequence of indices in x (of shape (b,t)) and predict the next token in the sequence, feeding the predictions back into t
taming/modules/transformer/mingpt.py:293
Functionsample_pdf
Sample @N_importance samples from @bins with distribution defined by @weights. Inputs: bins: (N_rays, N_samples_+1) where N_samples_
x2ct_nerf/modules/volume_rendering.py:314
Functionsample_with_past
(x, model, steps, temperature=1., sample_logits=True, top_k=None, top_p=None, callback=No
taming/modules/transformer/mingpt.py:324
Functionsave_axis_image
(ct_scan, root_path, prefix, slice_idx=None)
data_preprocessing/3_make_h5_dataset.py:14
Functionsoftplus_d_loss
(opt_idx, logits_real=None, logits_fake=None)
x2ct_nerf/modules/losses/perceptual.py:33
Functionsort_test_data
(config)
main_test_zoom.py:25
Functionsort_test_data
(config)
main_test.py:22
Functionstr2bool
(v)
main.py:32
Functiontensor_back_to_unnormalization
(input_image, mean, std)
utils/logger/TestLogger.py:22
Methodto_8b
(self, x)
x2ct_nerf/models/base.py:146
Methodto_8b
(self, x)
x2ct_nerf/models/aegan.py:204
Functiontorch_dot
Dot product of two tensors.
x2ct_nerf/modules/volume_rendering.py:105
Methodtraining_step
(self, batch, batch_idx, optimizer_idx)
x2ct_nerf/models/zoom_aegan.py:94
Methodtraining_step
(self, batch, batch_idx, optimizer_idx)
x2ct_nerf/models/base.py:84
Methodtraining_step
(self, batch, batch_idx, optimizer_idx)
x2ct_nerf/models/base.py:196
Methodtraining_step
(self, batch, batch_idx, optimizer_idx)
x2ct_nerf/models/aegan.py:125
Methodtraining_step
(self, batch, batch_idx, optimizer_idx)
x2ct_nerf/models/aegan.py:279
Methodtraining_step
(self, batch, batch_idx, optimizer_idx)
x2ct_nerf/models/aegan.py:462
Methodtraining_step
(self, batch, batch_idx, optimizer_idx)
x2ct_nerf/models/aegan.py:597
Methodtraining_step
(self, batch, batch_idx, optimizer_idx)
x2ct_nerf/models/aegan.py:751
Functiontransform_vectors
Left-multiplies MxM @ NxM. Returns NxM.
x2ct_nerf/modules/volume_rendering.py:91
Methodunmap_to_all
(self, inds)
taming/modules/vqvae/quantize.py:399
Functionunpack
(path)
taming/data/utils.py:16
Functionupdate_nerf_params
(cfg)
x2ct_nerf/modules/nerf/model_utils.py:64
Methodvalidation_step
(self, batch, batch_idx)
x2ct_nerf/models/zoom_aegan.py:117
Methodvalidation_step
(self, batch, batch_idx)
x2ct_nerf/models/base.py:105
Methodvalidation_step
(self, batch, batch_idx)
x2ct_nerf/models/base.py:220
Methodvalidation_step
(self, batch, batch_idx)
x2ct_nerf/models/aegan.py:149
Methodvalidation_step
(self, batch, batch_idx)
x2ct_nerf/models/aegan.py:302
Methodvalidation_step
(self, batch, batch_idx)
x2ct_nerf/models/aegan.py:475
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