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Functions55 in github.com/Team-TUD/CTAB-GAN-Plus

⨍ Functions 55◇ Types & classes 10
↓ 13 callersMethodtransform
(self, data, ispositive = False, positive_list = None)
model/synthesizer/transformer.py:143
↓ 8 callersMethodinverse_transform
(self, data)
model/synthesizer/transformer.py:301
↓ 7 callersMethodfit
(self)
model/synthesizer/transformer.py:59
↓ 5 callersFunctionapply_activate
(data, output_info)
model/synthesizer/ctabgan_synthesizer.py:55
↓ 5 callersMethodsample
(self, batch)
model/synthesizer/ctabgan_synthesizer.py:167
↓ 4 callersMethod__init__
(self, data, output_info)
model/synthesizer/ctabgan_synthesizer.py:109
↓ 4 callersFunction_log_add
Add two numbers in the log space.
model/privacy_utils/rdp_accountant.py:17
↓ 2 callersFunction_compute_rdp
Compute RDP of the Sampled Gaussian mechanism at order alpha. Args: q: The sampling rate. sigma: The std of the additive Gaussian noise.
model/privacy_utils/rdp_accountant.py:184
↓ 2 callersFunction_log_erfc
Compute log(erfc(x)) with high accuracy for large x.
model/privacy_utils/rdp_accountant.py:113
↓ 2 callersFunction_log_sub
Subtract two numbers in the log space. Answer must be non-negative.
model/privacy_utils/rdp_accountant.py:26
↓ 2 callersMethodsample_train
(self, batch)
model/synthesizer/ctabgan_synthesizer.py:151
↓ 2 callersFunctionsupervised_model_training
(x_train, y_train, x_test, y_test, model_name,problem_type)
model/eval/evaluation.py:17
↓ 1 callersFunction_compute_delta
Compute delta given a list of RDP values and target epsilon. Args: orders: An array (or a scalar) of orders. rdp: A list (or a scalar) of R
model/privacy_utils/rdp_accountant.py:131
↓ 1 callersFunction_compute_eps
Compute epsilon given a list of RDP values and target delta. Args: orders: An array (or a scalar) of orders. rdp: A list (or a scalar) of R
model/privacy_utils/rdp_accountant.py:157
↓ 1 callersFunction_compute_log_a
Compute log(A_alpha) for any positive finite alpha.
model/privacy_utils/rdp_accountant.py:105
↓ 1 callersFunction_compute_log_a_frac
Compute log(A_alpha) for fractional alpha. 0 < q < 1.
model/privacy_utils/rdp_accountant.py:68
↓ 1 callersFunction_compute_log_a_int
Compute log(A_alpha) for integer alpha. 0 < q < 1.
model/privacy_utils/rdp_accountant.py:50
↓ 1 callersFunctioncalc_gradient_penalty_slerp
(netD, real_data, fake_data, transformer, device='cpu', lambda_=10)
model/synthesizer/ctabgan_synthesizer.py:314
↓ 1 callersFunctioncompute_rdp
Compute RDP of the Sampled Gaussian Mechanism. Args: q: The sampling rate. noise_multiplier: The ratio of the standard deviation of the Gau
model/privacy_utils/rdp_accountant.py:207
↓ 1 callersFunctioncond_loss
(data, output_info, c, m)
model/synthesizer/ctabgan_synthesizer.py:182
↓ 1 callersFunctiondetermine_layers_disc
(side, num_channels)
model/synthesizer/ctabgan_synthesizer.py:253
↓ 1 callersFunctiondetermine_layers_gen
(side, random_dim, num_channels)
model/synthesizer/ctabgan_synthesizer.py:282
↓ 1 callersMethodget_metadata
(self)
model/synthesizer/transformer.py:18
↓ 1 callersFunctionget_st_ed
(target_col_index,output_info)
model/synthesizer/ctabgan_synthesizer.py:69
↓ 1 callersMethodinverse_prep
(self, data, eps=1)
model/pipeline/data_preparation.py:107
↓ 1 callersFunctionmaximum_interval
(output_info)
model/synthesizer/ctabgan_synthesizer.py:102
↓ 1 callersFunctionrandom_choice_prob_index
(a, axis=1)
model/synthesizer/ctabgan_synthesizer.py:98
↓ 1 callersFunctionrandom_choice_prob_index_sampling
(probs,col_idx)
model/synthesizer/ctabgan_synthesizer.py:90
↓ 1 callersMethodsample
(self, n, col, opt)
model/synthesizer/ctabgan_synthesizer.py:224
↓ 1 callersFunctionslerp
(val, low, high)
model/synthesizer/ctabgan_synthesizer.py:305
Method__init__
(self, raw_csv_path = "Real_Datasets/Adult.csv", test_ratio = 0.20,
model/ctabgan.py:16
Method__init__
(self,input_dim, dis_dims,st_ed)
model/synthesizer/ctabgan_synthesizer.py:16
Method__init__
(self, data, output_info)
model/synthesizer/ctabgan_synthesizer.py:206
Method__init__
(self, side, layers)
model/synthesizer/ctabgan_synthesizer.py:234
Method__init__
(self, side, layers)
model/synthesizer/ctabgan_synthesizer.py:245
Method__init__
(self, class_dim=(256, 256, 256, 256), random_dim=100, num_
model/synthesizer/ctabgan_synthesizer.py:343
Method__init__
(self, train_data=pd.DataFrame, categorical_list=[], mixed_dict={}, general_list=[], non_categorical_list=[],
model/synthesizer/transformer.py:8
Method__init__
(self, side)
model/synthesizer/transformer.py:410
Method__init__
(self, raw_df: pd.DataFrame, categorical: list, log:list, mixed:dict, general:list, non_categorical:list, inte
model/pipeline/data_preparation.py:8
Function_log_print
Pretty print.
model/privacy_utils/rdp_accountant.py:42
Functioncompute_rdp_from_ledger
Compute RDP of Sampled Gaussian Mechanism from ledger. Args: ledger: A formatted privacy ledger. orders: An array (or a scalar) of RDP orde
model/privacy_utils/rdp_accountant.py:262
Methodfit
(self)
model/ctabgan.py:40
Methodfit
(self, train_data=pd.DataFrame, categorical=[], mixed={}, general=[], non_categorical=[], type={})
model/synthesizer/ctabgan_synthesizer.py:362
Methodforward
(self, input)
model/synthesizer/ctabgan_synthesizer.py:39
Methodforward
(self, input)
model/synthesizer/ctabgan_synthesizer.py:241
Methodforward
(self, input_)
model/synthesizer/ctabgan_synthesizer.py:250
Methodgenerate_samples
(self)
model/ctabgan.py:50
Functionget_privacy_spent
Compute delta (or eps) for given eps (or delta) from RDP values. Args: orders: An array (or a scalar) of RDP orders. rdp: An array of RDP v
model/privacy_utils/rdp_accountant.py:229
Functionget_utility_metrics
(real_path,fake_paths,scaler="MinMax",type={"Classification":["lr","dt","rf","mlp"]},test_ratio=.20)
model/eval/evaluation.py:64
Methodinverse_transform
(self, data)
model/synthesizer/transformer.py:423
Functionprivacy_metrics
(real_path,fake_path,data_percent=15)
model/eval/evaluation.py:182
Methodsample
(self, n)
model/synthesizer/ctabgan_synthesizer.py:551
Functionstat_sim
(real_path,fake_path,cat_cols=None)
model/eval/evaluation.py:128
Methodtransform
(self, data)
model/synthesizer/transformer.py:414
Functionweights_init
(m)
model/synthesizer/ctabgan_synthesizer.py:332