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Functions210 in github.com/ChangyuanWang17/APQ-DM

⨍ Functions 210◇ Types & classes 29
↓ 34 callersFunctionprint
(*args, **kwargs)
util.py:179
↓ 10 callersMethodmax
(self)
util.py:64
↓ 9 callersMethodload_state_dict
(self, state_dict)
models/ema.py:48
↓ 7 callersMethodstate_dict
(self)
models/ema.py:45
↓ 6 callersFunctioncompute_alpha
(beta, t)
functions/denoising.py:7
↓ 5 callersFunctionnonlinearity
(x)
models/diffusion.py:29
↓ 4 callersFunctionNormalize
(in_channels)
models/diffusion.py:34
↓ 4 callersMethod__init__
Build pretrained InceptionV3 Parameters ---------- output_blocks : list of int Indices of blocks to return featur
pytorch-fid-master/src/pytorch_fid/inception.py:31
↓ 4 callersMethod__init__
(self, config, quantization=False, sequence=None, args=None)
models/diffusion.py:224
↓ 4 callersFunctionasymmetric_linear_quantization_params
Compute the scaling factor and zeropoint with the given quantization range. saturation_min: lower bound for quantization range saturation
utils/quantization_utils/quant_utils.py:109
↓ 4 callersFunctioninverse_data_transform
(config, X)
datasets/__init__.py:206
↓ 4 callersMethodsample_image
(self, x, model, last=True)
runners/diffusion.py:534
↓ 4 callersMethodset_calibrate
(self, calibrate=True)
utils/quant_util.py:177
↓ 4 callersFunctiontqdm
(x)
pytorch-fid-master/src/pytorch_fid/fid_score.py:49
↓ 4 callersMethodupdate
(self, **kwargs)
util.py:85
↓ 3 callersFunctioncheck_integrity
(fpath, md5=None)
datasets/utils.py:20
↓ 3 callersFunctioncompute_statistics_of_path
(path, model, batch_size, dims, device, num_workers=1)
pytorch-fid-master/src/pytorch_fid/fid_score.py:234
↓ 3 callersFunctionis_dist_avail_and_initialized
()
util.py:187
↓ 2 callersFunctionGroupWise_Quantizaion
(x, dim=128, group_n=8, maxmin='max')
utils/quant_util.py:399
↓ 2 callersMethod__init__
(self, range_left=-6, range_right=6, dim=128, device=None)
utils/quant_util.py:48
↓ 2 callersMethod__repr__
(self)
datasets/vision.py:34
↓ 2 callersMethod_check_integrity
(self)
datasets/celeba.py:108
↓ 2 callersMethod_format_transform_repr
(self, transform, head)
datasets/vision.py:49
↓ 2 callersMethod_format_transform_repr
(self, transform, head)
datasets/vision.py:70
↓ 2 callersFunction_inception_v3
Wraps `torchvision.models.inception_v3`
pytorch-fid-master/src/pytorch_fid/inception.py:166
↓ 2 callersFunctionaccuracy
Computes the precision@k for the specified values of k
utils/compute.py:53
↓ 2 callersMethodbackward
(ctx, grad_outputs)
utils/quant_util.py:343
↓ 2 callersMethodcalibrate_quantization
(self, inputs, init_min, init_max)
utils/quant_util.py:186
↓ 2 callersFunctiongen_bar_updater
()
datasets/utils.py:8
↓ 2 callersFunctiongeneralized_steps
(x, seq, model, b, **kwargs)
functions/denoising.py:15
↓ 2 callersFunctionlinear_dequantize
Map integer input tensor to fixed point float point with given scaling factor and zeropoint. input: integer input tensor to be mapped sca
utils/quantization_utils/quant_utils.py:86
↓ 2 callersFunctionlinear_quantize
Quantize single-precision input tensor to integers with the given scaling factor and zeropoint. input: single-precision input tensor to be qu
utils/quantization_utils/quant_utils.py:62
↓ 2 callersFunctionmakedir_exist_ok
Python2 support for os.makedirs(.., exist_ok=True)
datasets/utils.py:36
↓ 2 callersFunctionmd5_hash
(path)
functions/ckpt_util.py:49
↓ 2 callersFunctionread
(rel_path)
pytorch-fid-master/setup.py:6
↓ 2 callersMethodtrain
(self)
runners/diffusion.py:103
↓ 2 callersMethodupdate
(self, value, n=1)
util.py:31
↓ 1 callersMethod__init__
(self, root, classes="train", transform=None, target_transform=None)
datasets/lsun.py:75
↓ 1 callersMethod__len__
(self)
datasets/vision.py:31
↓ 1 callersFunction_get_confirm_token
(response)
datasets/utils.py:169
↓ 1 callersMethod_quantize
(self, inputs, weight, bias)
utils/quant_util.py:319
↓ 1 callersMethod_quantize_activation
(self, inputs)
utils/quant_util.py:226
↓ 1 callersMethod_quantize_weight
(self, weight)
utils/quant_util.py:284
↓ 1 callersFunction_save_response_content
(response, destination, chunk_size=32768)
datasets/utils.py:177
↓ 1 callersMethod_verify_classes
(self, classes)
datasets/lsun.py:96
↓ 1 callersFunctioncal_entropy
(attn)
functions/denoising.py:12
↓ 1 callersMethodcal_entropy
(self, attn)
runners/diffusion.py:198
↓ 1 callersFunctioncalculate_activation_statistics
Calculation of the statistics used by the FID. Params: -- files : List of image files paths -- model : Instance of inception m
pytorch-fid-master/src/pytorch_fid/fid_score.py:209
↓ 1 callersFunctioncalculate_fid_given_paths
Calculates the FID of two paths
pytorch-fid-master/src/pytorch_fid/fid_score.py:249
↓ 1 callersFunctioncalculate_frechet_distance
Numpy implementation of the Frechet Distance. The Frechet distance between two multivariate Gaussians X_1 ~ N(mu_1, C_1) and X_2 ~ N(mu_2, C_2
pytorch-fid-master/src/pytorch_fid/fid_score.py:152
↓ 1 callersMethodcalibrate_loss
(self, model, image, device, batchsize)
runners/diffusion.py:600
↓ 1 callersFunctiondata_transform
(config, X)
datasets/__init__.py:189
↓ 1 callersFunctionddpm_steps
(x, seq, model, b, **kwargs)
functions/denoising.py:105
↓ 1 callersFunctiondict2namespace
(config)
main.py:220
↓ 1 callersFunctiondownload
(url, local_path, chunk_size=1024)
functions/ckpt_util.py:37
↓ 1 callersMethoddownload
(self)
datasets/celeba.py:120
↓ 1 callersFunctiondownload_file_from_google_drive
Download a Google Drive file from and place it in root. Args: file_id (str): id of file to be downloaded root (str): Directory t
datasets/utils.py:134
↓ 1 callersMethodema
(self, module)
models/ema.py:24
↓ 1 callersMethodextra_repr
(self)
datasets/vision.py:54
↓ 1 callersFunctionfid_inception_v3
Build pretrained Inception model for FID computation The Inception model for FID computation uses a different set of weights and has a slight
pytorch-fid-master/src/pytorch_fid/inception.py:197
↓ 1 callersMethodfirst_calibrate
(self, calibrate=True)
utils/quant_util.py:180
↓ 1 callersFunctiongeneralized_steps_loss
(x, seq, model, b, optimizer, t_mode, **kwargs)
functions/denoising.py:61
↓ 1 callersMethodgenerate_calibrate_set
(self, fpmodel, model, t_mode, num_calibrate_set)
runners/diffusion.py:201
↓ 1 callersFunctionget_activations
Calculates the activations of the pool_3 layer for all images. Params: -- files : List of image files paths -- model : Instan
pytorch-fid-master/src/pytorch_fid/fid_score.py:93
↓ 1 callersFunctionget_beta_schedule
(beta_schedule, *, beta_start, beta_end, num_diffusion_timesteps)
runners/diffusion.py:33
↓ 1 callersFunctionget_ckpt_path
(name, root=None, check=False)
functions/ckpt_util.py:55
↓ 1 callersFunctionget_dataset
(args, config)
datasets/__init__.py:30
↓ 1 callersFunctionget_optimizer
(config, parameters)
functions/__init__.py:4
↓ 1 callersFunctionget_rank
()
util.py:201
↓ 1 callersFunctionget_timestep_embedding
This matches the implementation in Denoising Diffusion Probabilistic Models: From Fairseq. Build sinusoidal embeddings. This matches
models/diffusion.py:8
↓ 1 callersFunctionget_version
(rel_path)
pytorch-fid-master/setup.py:12
↓ 1 callersFunctionis_main_process
()
util.py:207
↓ 1 callersFunctionlogit_transform
(image, lam=1e-6)
datasets/__init__.py:184
↓ 1 callersFunctionlp_loss
loss function measured in L_p Norm
utils/quant_util.py:37
↓ 1 callersFunctionmain
()
main.py:231
↓ 1 callersFunctionmain
()
pytorch-fid-master/src/pytorch_fid/fid_score.py:288
↓ 1 callersFunctionnoise_estimation_loss
(model, x0: torch.Tensor, t: torch.LongTensor,
functions/denoising.py:44
↓ 1 callersFunctionparse_args_and_config
()
main.py:17
↓ 1 callersMethodregister
(self, module)
models/ema.py:9
↓ 1 callersMethodreset
reset all parameters
utils/compute.py:76
↓ 1 callersMethodreset_parameters
(self)
utils/quant_util.py:372
↓ 1 callersMethodsample
(self)
runners/diffusion.py:270
↓ 1 callersMethodsample_fid
(self, model)
runners/diffusion.py:432
↓ 1 callersMethodsample_interpolation
(self, model)
runners/diffusion.py:494
↓ 1 callersMethodsample_sequence
(self, model)
runners/diffusion.py:471
↓ 1 callersFunctionsave_fid_stats
Calculates the FID of two paths
pytorch-fid-master/src/pytorch_fid/fid_score.py:268
↓ 1 callersFunctionsetup_for_distributed
This function disables printing when not in master process
util.py:172
↓ 1 callersFunctionsigmoid
(x)
runners/diffusion.py:34
↓ 1 callersMethodtest
(self)
runners/diffusion.py:581
↓ 1 callersMethodupdate
(self, module)
models/ema.py:16
Method__call__
(self, input, target)
datasets/vision.py:63
Method__call__
(self, img)
datasets/__init__.py:21
Method__getattr__
(self, attr)
util.py:92
Method__getitem__
(self, idx)
utils/data_utils.py:37
Method__getitem__
(self, i)
pytorch-fid-master/src/pytorch_fid/fid_score.py:85
Method__getitem__
(self, index)
datasets/ffhq.py:31
Method__getitem__
(self, index)
datasets/vision.py:28
Method__getitem__
(self, index)
datasets/lsun.py:38
Method__getitem__
Args: index (int): Index Returns: tuple: Tuple (image, target) where target is the index of the target categ
datasets/lsun.py:146
Method__getitem__
(self, index)
datasets/celeba.py:133
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