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Functions77 in github.com/CausalLearning/MultiRobustness

⨍ Functions 77◇ Types & classes 15
↓ 9 callersFunctionget_ckpt
(model_dir, epoch)
scripts/utils.py:3
↓ 7 callersFunction_stride_arr
Map a stride scalar to the stride array for tf.nn.conv2d.
cleverhans_models.py:103
↓ 7 callersMethod_stride_arr
Map a stride scalar to the stride array for tf.nn.conv2d.
cifar10_model.py:20
↓ 6 callersFunctioncompute_grad
(model)
pgd_attack.py:128
↓ 6 callersFunctionevaluate
(model, eval_attacks, sess, config, plot=False, summary_writer=None, eval_train=False, eval_validation=False,
eval.py:55
↓ 5 callersMethodperturb
(self, x_nat, y, sess, x_nat_no_aug=None)
pgd_attack.py:163
↓ 4 callersFunction_batch_norm
Batch normalization.
cleverhans_models.py:223
↓ 4 callersMethod_batch_norm
Batch normalization.
cifar10_model.py:108
↓ 4 callersFunction_relu
Relu, with optional leaky support.
cleverhans_models.py:291
↓ 4 callersMethod_relu
Relu, with optional leaky support.
cifar10_model.py:171
↓ 4 callersFunctionevaluate_ch
(model, config, sess, norm='l1', bound=None, verbose=True)
eval_ch.py:25
↓ 4 callersFunctionevaluate_fb
(model, config, x_min, x_max, norm='l1', bound=None, verbose=True)
eval_fb.py:18
↓ 3 callersFunction_conv
Convolution.
cleverhans_models.py:280
↓ 3 callersMethod_conv
Convolution.
cifar10_model.py:161
↓ 3 callersFunctionget_model
(config)
eval_ch.py:88
↓ 3 callersFunctionget_saver
(config)
eval_ch.py:100
↓ 2 callersMethod__init__
(self)
cleverhans_models.py:110
↓ 2 callersMethod_fprop
(self, x, set_ref=False)
cleverhans_models.py:88
↓ 2 callersMethod_load_datafile
(filename)
cifar10_input.py:69
↓ 2 callersMethodbuild
(self, layers, input_shape)
cleverhans_models.py:55
↓ 2 callersMethodfprop
(self, x)
cleverhans_models.py:125
↓ 2 callersMethodget_next_batch
(self, batch_size, multiple_passes=False, reshuffle_after_pass=True)
cifar10_input.py:125
↓ 2 callersMethodmake_vars
(self)
cleverhans_models.py:208
↓ 2 callersMethodnorm_perturb
(self, x_nat, y, sess, norm_attacks, norm_weights, trans=None)
pgd_attack.py:277
↓ 1 callersMethod_bias_variable
(shape)
model.py:76
↓ 1 callersMethod_build_model
Build the core model within the graph.
cifar10_model.py:24
↓ 1 callersMethod_decay
L2 weight decay loss.
cifar10_model.py:153
↓ 1 callersMethod_fully_connected
FullyConnected layer for final output.
cifar10_model.py:175
↓ 1 callersFunction_global_avg_pool
(x)
cleverhans_models.py:296
↓ 1 callersMethod_global_avg_pool
(self, x)
cifar10_model.py:189
↓ 1 callersMethod_weight_variable
(shape)
model.py:71
↓ 1 callersFunctiondelta_update
(old_delta, g, x_adv, attack, x_min, x_max, weight, seed=None, t=None)
pgd_attack.py:44
↓ 1 callersMethodfprop
(self, x)
cleverhans_models.py:156
↓ 1 callersMethodget_output_shape
(self)
cleverhans_models.py:16
↓ 1 callersMethodgrid_perturb
(self, x_nat, y, sess, attack_config, weight, norm_attacks, norm_weights)
pgd_attack.py:219
↓ 1 callersFunctioninit_delta
(x, attack, weight)
pgd_attack.py:23
↓ 1 callersFunctionmake_wresnet
(nb_classes=10, input_shape=(None, 32, 32, 3), scope=None, filters=None)
cleverhans_models.py:331
↓ 1 callersFunctionname
(attack)
pgd_attack.py:140
↓ 1 callersFunctionone_hot
(a, n_classes)
eval_ch.py:19
↓ 1 callersMethodset_input_shape
(self, input_shape)
cleverhans_models.py:113
↓ 1 callersFunctionuniform_weights
(n_attacks, n_samples)
pgd_attack.py:17
Method__init__
Attack parameter initialization. The attack performs k steps of size a, while always staying within epsilon from the initial p
pgd_attack.py:145
Method__init__
ResNet constructor.
cifar10_model.py:12
Method__init__
(self, path)
cifar10_input.py:40
Method__init__
(self, raw_cifar10data, sess)
cifar10_input.py:90
Method__init__
(self, xs, ys)
cifar10_input.py:118
Method__init__
(self, raw_datasubset, sess, x_input_placeholder, augmented)
cifar10_input.py:156
Method__init__
ResNet constructor. :param layers: a list of layers in CleverHans format each with set_input_shape() and fprop() methods. :param input_s
cleverhans_models.py:23
Method__init__
(self, filters)
cleverhans_models.py:134
Method__init__
(self, num_hid)
cleverhans_models.py:198
Method__init__
(self)
cleverhans_models.py:303
Method__init__
(self)
cleverhans_models.py:316
Method__init__
self.conv1 = tf.layers.Conv2D(32, (5, 5), activation='relu', padding='same', name='conv1') self.pool1 = tf.layers.MaxPooling2D((2, 2)
cleverhans_models.py:344
Method__init__
(self, config)
model.py:14
Method_conv2d
(x, W)
model.py:81
Function_decay
L2 weight decay loss.
cleverhans_models.py:271
Method_max_pool_2x2
( x)
model.py:85
Function_residual
Residual unit with 2 sub layers.
cleverhans_models.py:236
Method_residual
Residual unit with 2 sub layers.
cifar10_model.py:120
Methodadd_internal_summaries
(self)
cifar10_model.py:17
Methodadd_internal_summaries
(self)
cleverhans_models.py:99
Methodfprop
(self, x, set_ref=False)
cleverhans_models.py:81
Methodfprop
(self, x)
cleverhans_models.py:218
Methodfprop
(self, x)
cleverhans_models.py:310
Methodfprop
(self, x)
cleverhans_models.py:327
Methodfprop
(self, x)
cleverhans_models.py:371
Methodget_next_batch
(self, batch_size, multiple_passes=False, reshuffle_after_pass=True)
cifar10_input.py:163
Methodget_vars
(self)
cleverhans_models.py:50
Methodmake_input_placeholder
(self)
cleverhans_models.py:75
Methodmake_label_placeholder
(self)
cleverhans_models.py:78
Methodset_input_shape
(self, input_shape)
cleverhans_models.py:141
Methodset_input_shape
(self, input_shape)
cleverhans_models.py:201
Methodset_input_shape
(self, shape)
cleverhans_models.py:306
Methodset_input_shape
(self, shape)
cleverhans_models.py:319
Functionshow_images
Display a list of images in a single figure with matplotlib. Parameters --------- images: List of np.arrays compatible with plt.imsho
eval.py:27
Functionworker
((model_dir, epoch))
scripts/eval_mnist_lps.py:46
Functionworker
((model_dir, epoch))
scripts/eval_cifar_lps.py:59