repo stringlengths 7 90 | file_url stringlengths 81 315 | file_path stringlengths 4 228 | content stringlengths 0 32.8k | language stringclasses 1
value | license stringclasses 7
values | commit_sha stringlengths 40 40 | retrieved_at stringdate 2026-01-04 14:38:15 2026-01-05 02:33:18 | truncated bool 2
classes |
|---|---|---|---|---|---|---|---|---|
yaxingwang/MineGAN | https://github.com/yaxingwang/MineGAN/blob/a810f2d77f36ea9cf6993dede958b6f5d458f4b6/MNISTtf/MNISTtf_old/conditional_continue/off_manifold/tflib/ops/conv2d.py | MNISTtf/MNISTtf_old/conditional_continue/off_manifold/tflib/ops/conv2d.py | import tflib as lib
import numpy as np
import tensorflow as tf
_default_weightnorm = False
def enable_default_weightnorm():
global _default_weightnorm
_default_weightnorm = True
_weights_stdev = None
def set_weights_stdev(weights_stdev):
global _weights_stdev
_weights_stdev = weights_stdev
def unset... | python | MIT | a810f2d77f36ea9cf6993dede958b6f5d458f4b6 | 2026-01-05T07:08:28.063149Z | false |
yaxingwang/MineGAN | https://github.com/yaxingwang/MineGAN/blob/a810f2d77f36ea9cf6993dede958b6f5d458f4b6/MNISTtf/MNISTtf_old/conditional_continue/off_manifold/tflib/ops/batchnorm.py | MNISTtf/MNISTtf_old/conditional_continue/off_manifold/tflib/ops/batchnorm.py | import tflib as lib
import numpy as np
import tensorflow as tf
def Batchnorm(name, axes, inputs, is_training=None, stats_iter=None, update_moving_stats=True, fused=True):
if ((axes == [0,2,3]) or (axes == [0,2])) and fused==True:
if axes==[0,2]:
inputs = tf.expand_dims(inputs, 3)
# Old... | python | MIT | a810f2d77f36ea9cf6993dede958b6f5d458f4b6 | 2026-01-05T07:08:28.063149Z | false |
yaxingwang/MineGAN | https://github.com/yaxingwang/MineGAN/blob/a810f2d77f36ea9cf6993dede958b6f5d458f4b6/MNISTtf/MNISTtf_old/conditional_continue/off_manifold/tflib/ops/cond_batchnorm.py | MNISTtf/MNISTtf_old/conditional_continue/off_manifold/tflib/ops/cond_batchnorm.py | import tflib as lib
import numpy as np
import tensorflow as tf
def Batchnorm(name, axes, inputs, is_training=None, stats_iter=None, update_moving_stats=True, fused=True, labels=None, n_labels=None):
"""conditional batchnorm (dumoulin et al 2016) for BCHW conv filtermaps"""
if axes != [0,2,3]:
raise Ex... | python | MIT | a810f2d77f36ea9cf6993dede958b6f5d458f4b6 | 2026-01-05T07:08:28.063149Z | false |
yaxingwang/MineGAN | https://github.com/yaxingwang/MineGAN/blob/a810f2d77f36ea9cf6993dede958b6f5d458f4b6/MNISTtf/MNISTtf_old/conditional_continue/off_manifold/tflib/ops/linear.py | MNISTtf/MNISTtf_old/conditional_continue/off_manifold/tflib/ops/linear.py | import tflib as lib
import numpy as np
import tensorflow as tf
_default_weightnorm = False
def enable_default_weightnorm():
global _default_weightnorm
_default_weightnorm = True
def disable_default_weightnorm():
global _default_weightnorm
_default_weightnorm = False
_weights_stdev = None
def set_wei... | python | MIT | a810f2d77f36ea9cf6993dede958b6f5d458f4b6 | 2026-01-05T07:08:28.063149Z | false |
yaxingwang/MineGAN | https://github.com/yaxingwang/MineGAN/blob/a810f2d77f36ea9cf6993dede958b6f5d458f4b6/MNISTtf/MNISTtf_old/conditional_continue/on_manifold/teacher_output_d.py | MNISTtf/MNISTtf_old/conditional_continue/on_manifold/teacher_output_d.py |
import os, sys
sys.path.append(os.getcwd())
import numpy as np
import tensorflow as tf
import tflib as lib
import tflib.ops.linear
import tflib.ops.conv2d
import tflib.ops.batchnorm
import tflib.ops.deconv2d
import tflib.save_images
import tflib.mnist
import tflib.plot
import pdb
def teacher_model(noise, fake_dat... | python | MIT | a810f2d77f36ea9cf6993dede958b6f5d458f4b6 | 2026-01-05T07:08:28.063149Z | false |
yaxingwang/MineGAN | https://github.com/yaxingwang/MineGAN/blob/a810f2d77f36ea9cf6993dede958b6f5d458f4b6/MNISTtf/MNISTtf_old/conditional_continue/on_manifold/cgan_super_g_d_two_class_unbalance_one_D.py | MNISTtf/MNISTtf_old/conditional_continue/on_manifold/cgan_super_g_d_two_class_unbalance_one_D.py | import os, sys
sys.path.append(os.getcwd())
import time
import matplotlib
matplotlib.use('Agg')
import matplotlib.pyplot as plt
import numpy as np
import sklearn.datasets
import tensorflow as tf
import tflib as lib
import tflib.ops.linear
import tflib.ops.conv2d
import tflib.ops.batchnorm
import tflib.ops.deconv2d
i... | python | MIT | a810f2d77f36ea9cf6993dede958b6f5d458f4b6 | 2026-01-05T07:08:28.063149Z | false |
yaxingwang/MineGAN | https://github.com/yaxingwang/MineGAN/blob/a810f2d77f36ea9cf6993dede958b6f5d458f4b6/MNISTtf/MNISTtf_old/conditional_continue/on_manifold/teacher.py | MNISTtf/MNISTtf_old/conditional_continue/on_manifold/teacher.py |
import os, sys
sys.path.append(os.getcwd())
import numpy as np
import tensorflow as tf
import tflib as lib
import tflib.ops.linear
import tflib.ops.conv2d
import tflib.ops.batchnorm
import tflib.ops.deconv2d
import tflib.save_images
import tflib.mnist
import tflib.plot
import pdb
def teacher_model(noise, fake_data... | python | MIT | a810f2d77f36ea9cf6993dede958b6f5d458f4b6 | 2026-01-05T07:08:28.063149Z | false |
yaxingwang/MineGAN | https://github.com/yaxingwang/MineGAN/blob/a810f2d77f36ea9cf6993dede958b6f5d458f4b6/MNISTtf/MNISTtf_old/conditional_continue/on_manifold/cgan_mnist_knowledge_distillation_adaptor_step1.py | MNISTtf/MNISTtf_old/conditional_continue/on_manifold/cgan_mnist_knowledge_distillation_adaptor_step1.py | import os, sys
sys.path.append(os.getcwd())
import time
import matplotlib
matplotlib.use('Agg')
import matplotlib.pyplot as plt
import numpy as np
import sklearn.datasets
import tensorflow as tf
import tflib as lib
import tflib.ops.linear
import tflib.ops.conv2d
import tflib.ops.batchnorm
import tflib.ops.deconv2d
i... | python | MIT | a810f2d77f36ea9cf6993dede958b6f5d458f4b6 | 2026-01-05T07:08:28.063149Z | false |
yaxingwang/MineGAN | https://github.com/yaxingwang/MineGAN/blob/a810f2d77f36ea9cf6993dede958b6f5d458f4b6/MNISTtf/MNISTtf_old/conditional_continue/on_manifold/cgan_super_g_d_two_class_unbalance_one_D_no_share_latent.py | MNISTtf/MNISTtf_old/conditional_continue/on_manifold/cgan_super_g_d_two_class_unbalance_one_D_no_share_latent.py | import os, sys
sys.path.append(os.getcwd())
import time
import matplotlib
matplotlib.use('Agg')
import matplotlib.pyplot as plt
import numpy as np
import sklearn.datasets
import tensorflow as tf
import tflib as lib
import tflib.ops.linear
import tflib.ops.conv2d
import tflib.ops.batchnorm
import tflib.ops.deconv2d
i... | python | MIT | a810f2d77f36ea9cf6993dede958b6f5d458f4b6 | 2026-01-05T07:08:28.063149Z | false |
yaxingwang/MineGAN | https://github.com/yaxingwang/MineGAN/blob/a810f2d77f36ea9cf6993dede958b6f5d458f4b6/MNISTtf/MNISTtf_old/conditional_continue/on_manifold/tflib/lsun_label.py | MNISTtf/MNISTtf_old/conditional_continue/on_manifold/tflib/lsun_label.py |
from os import listdir
import numpy as np
import scipy.misc
import time
import pdb
Label={'bedroom':0,
'kitchen':1,
'dining_room':2,
'conference_room':3,
'living_room':4,
'bridge':5,
'tower':6,
'classroom':7,
'church_outdoor':8,
'restaurant':9}
def make_g... | python | MIT | a810f2d77f36ea9cf6993dede958b6f5d458f4b6 | 2026-01-05T07:08:28.063149Z | false |
yaxingwang/MineGAN | https://github.com/yaxingwang/MineGAN/blob/a810f2d77f36ea9cf6993dede958b6f5d458f4b6/MNISTtf/MNISTtf_old/conditional_continue/on_manifold/tflib/plot.py | MNISTtf/MNISTtf_old/conditional_continue/on_manifold/tflib/plot.py | import matplotlib
matplotlib.use('Agg')
import matplotlib.pyplot as plt
import numpy as np
import collections
import time
import cPickle as pickle
_since_beginning = collections.defaultdict(lambda: {})
_since_last_flush = collections.defaultdict(lambda: {})
_iter = [0]
def tick():
_iter[0] += 1
def plot(name, valu... | python | MIT | a810f2d77f36ea9cf6993dede958b6f5d458f4b6 | 2026-01-05T07:08:28.063149Z | false |
yaxingwang/MineGAN | https://github.com/yaxingwang/MineGAN/blob/a810f2d77f36ea9cf6993dede958b6f5d458f4b6/MNISTtf/MNISTtf_old/conditional_continue/on_manifold/tflib/mnist_step1.py | MNISTtf/MNISTtf_old/conditional_continue/on_manifold/tflib/mnist_step1.py | import numpy
import os
import urllib
import gzip
import cPickle as pickle
import pdb
def mnist_generator(data, batch_size, n_labelled, limit=None, selecting_label = None, bias = None):
images, targets = data
if bias is not None :
images = images[targets!=bias]
targets = targets[targets!=bias]... | python | MIT | a810f2d77f36ea9cf6993dede958b6f5d458f4b6 | 2026-01-05T07:08:28.063149Z | false |
yaxingwang/MineGAN | https://github.com/yaxingwang/MineGAN/blob/a810f2d77f36ea9cf6993dede958b6f5d458f4b6/MNISTtf/MNISTtf_old/conditional_continue/on_manifold/tflib/mnist.py | MNISTtf/MNISTtf_old/conditional_continue/on_manifold/tflib/mnist.py | import numpy
import os
import urllib
import gzip
import cPickle as pickle
import pdb
def mnist_generator(data, batch_size, n_labelled, limit=None, selecting_label = None, bias = None):
images, targets = data
if bias is not None :
images = images[targets!=bias]
targets = targets[targets!=bias]... | python | MIT | a810f2d77f36ea9cf6993dede958b6f5d458f4b6 | 2026-01-05T07:08:28.063149Z | false |
yaxingwang/MineGAN | https://github.com/yaxingwang/MineGAN/blob/a810f2d77f36ea9cf6993dede958b6f5d458f4b6/MNISTtf/MNISTtf_old/conditional_continue/on_manifold/tflib/__init__.py | MNISTtf/MNISTtf_old/conditional_continue/on_manifold/tflib/__init__.py | import numpy as np
import tensorflow as tf
#import locale
#locale.setlocale(locale.LC_ALL, '')
_params = {}
_param_aliases = {}
def param(name, *args, **kwargs):
"""
A wrapper for `tf.Variable` which enables parameter sharing in models.
Creates and returns theano shared variables similarly to `tf.Va... | python | MIT | a810f2d77f36ea9cf6993dede958b6f5d458f4b6 | 2026-01-05T07:08:28.063149Z | false |
yaxingwang/MineGAN | https://github.com/yaxingwang/MineGAN/blob/a810f2d77f36ea9cf6993dede958b6f5d458f4b6/MNISTtf/MNISTtf_old/conditional_continue/on_manifold/tflib/lsun.py | MNISTtf/MNISTtf_old/conditional_continue/on_manifold/tflib/lsun.py | import numpy as np
import scipy.misc
import time
import cv2
from os import listdir
def make_generator(path, n_files, batch_size, image_size):
epoch_count = [1]
images_name = listdir(path)
if n_files == 0:
n_files = len(images_name)
else:
n_files = n_files
def get_epoch():
... | python | MIT | a810f2d77f36ea9cf6993dede958b6f5d458f4b6 | 2026-01-05T07:08:28.063149Z | false |
yaxingwang/MineGAN | https://github.com/yaxingwang/MineGAN/blob/a810f2d77f36ea9cf6993dede958b6f5d458f4b6/MNISTtf/MNISTtf_old/conditional_continue/on_manifold/tflib/save_images.py | MNISTtf/MNISTtf_old/conditional_continue/on_manifold/tflib/save_images.py | """
Image grid saver, based on color_grid_vis from github.com/Newmu
"""
import numpy as np
import scipy.misc
from scipy.misc import imsave
def save_images(X, save_path):
# [0, 1] -> [0,255]
if isinstance(X.flatten()[0], np.floating):
X = (255.99*X).astype('uint8')
n_samples = X.shape[0]
rows ... | python | MIT | a810f2d77f36ea9cf6993dede958b6f5d458f4b6 | 2026-01-05T07:08:28.063149Z | false |
yaxingwang/MineGAN | https://github.com/yaxingwang/MineGAN/blob/a810f2d77f36ea9cf6993dede958b6f5d458f4b6/MNISTtf/MNISTtf_old/conditional_continue/on_manifold/tflib/mnist_mask_digit.py | MNISTtf/MNISTtf_old/conditional_continue/on_manifold/tflib/mnist_mask_digit.py |
import numpy
import os
import urllib
import gzip
import cPickle as pickle
import pdb
def mnist_generator(data, batch_size, n_labelled, limit=None, selecting_label = None):
images, targets = data
# if selecting_label is None:
# rng_state = numpy.random.get_state()
# numpy.random.shuffle(images)
... | python | MIT | a810f2d77f36ea9cf6993dede958b6f5d458f4b6 | 2026-01-05T07:08:28.063149Z | false |
yaxingwang/MineGAN | https://github.com/yaxingwang/MineGAN/blob/a810f2d77f36ea9cf6993dede958b6f5d458f4b6/MNISTtf/MNISTtf_old/conditional_continue/on_manifold/tflib/ops/layernorm.py | MNISTtf/MNISTtf_old/conditional_continue/on_manifold/tflib/ops/layernorm.py | import tflib as lib
import numpy as np
import tensorflow as tf
def Layernorm(name, norm_axes, inputs):
mean, var = tf.nn.moments(inputs, norm_axes, keep_dims=True)
# Assume the 'neurons' axis is the first of norm_axes. This is the case for fully-connected and BCHW conv layers.
n_neurons = inputs.get_shap... | python | MIT | a810f2d77f36ea9cf6993dede958b6f5d458f4b6 | 2026-01-05T07:08:28.063149Z | false |
yaxingwang/MineGAN | https://github.com/yaxingwang/MineGAN/blob/a810f2d77f36ea9cf6993dede958b6f5d458f4b6/MNISTtf/MNISTtf_old/conditional_continue/on_manifold/tflib/ops/deconv2d.py | MNISTtf/MNISTtf_old/conditional_continue/on_manifold/tflib/ops/deconv2d.py | import tflib as lib
import numpy as np
import tensorflow as tf
_default_weightnorm = False
def enable_default_weightnorm():
global _default_weightnorm
_default_weightnorm = True
_weights_stdev = None
def set_weights_stdev(weights_stdev):
global _weights_stdev
_weights_stdev = weights_stdev
def unset... | python | MIT | a810f2d77f36ea9cf6993dede958b6f5d458f4b6 | 2026-01-05T07:08:28.063149Z | false |
yaxingwang/MineGAN | https://github.com/yaxingwang/MineGAN/blob/a810f2d77f36ea9cf6993dede958b6f5d458f4b6/MNISTtf/MNISTtf_old/conditional_continue/on_manifold/tflib/ops/__init__.py | MNISTtf/MNISTtf_old/conditional_continue/on_manifold/tflib/ops/__init__.py | python | MIT | a810f2d77f36ea9cf6993dede958b6f5d458f4b6 | 2026-01-05T07:08:28.063149Z | false | |
yaxingwang/MineGAN | https://github.com/yaxingwang/MineGAN/blob/a810f2d77f36ea9cf6993dede958b6f5d458f4b6/MNISTtf/MNISTtf_old/conditional_continue/on_manifold/tflib/ops/conv1d.py | MNISTtf/MNISTtf_old/conditional_continue/on_manifold/tflib/ops/conv1d.py | import tflib as lib
import numpy as np
import tensorflow as tf
_default_weightnorm = False
def enable_default_weightnorm():
global _default_weightnorm
_default_weightnorm = True
def Conv1D(name, input_dim, output_dim, filter_size, inputs, he_init=True, mask_type=None, stride=1, weightnorm=None, biases=True, ... | python | MIT | a810f2d77f36ea9cf6993dede958b6f5d458f4b6 | 2026-01-05T07:08:28.063149Z | false |
yaxingwang/MineGAN | https://github.com/yaxingwang/MineGAN/blob/a810f2d77f36ea9cf6993dede958b6f5d458f4b6/MNISTtf/MNISTtf_old/conditional_continue/on_manifold/tflib/ops/conv2d.py | MNISTtf/MNISTtf_old/conditional_continue/on_manifold/tflib/ops/conv2d.py | import tflib as lib
import numpy as np
import tensorflow as tf
_default_weightnorm = False
def enable_default_weightnorm():
global _default_weightnorm
_default_weightnorm = True
_weights_stdev = None
def set_weights_stdev(weights_stdev):
global _weights_stdev
_weights_stdev = weights_stdev
def unset... | python | MIT | a810f2d77f36ea9cf6993dede958b6f5d458f4b6 | 2026-01-05T07:08:28.063149Z | false |
yaxingwang/MineGAN | https://github.com/yaxingwang/MineGAN/blob/a810f2d77f36ea9cf6993dede958b6f5d458f4b6/MNISTtf/MNISTtf_old/conditional_continue/on_manifold/tflib/ops/batchnorm.py | MNISTtf/MNISTtf_old/conditional_continue/on_manifold/tflib/ops/batchnorm.py | import tflib as lib
import numpy as np
import tensorflow as tf
def Batchnorm(name, axes, inputs, is_training=None, stats_iter=None, update_moving_stats=True, fused=True):
if ((axes == [0,2,3]) or (axes == [0,2])) and fused==True:
if axes==[0,2]:
inputs = tf.expand_dims(inputs, 3)
# Old... | python | MIT | a810f2d77f36ea9cf6993dede958b6f5d458f4b6 | 2026-01-05T07:08:28.063149Z | false |
yaxingwang/MineGAN | https://github.com/yaxingwang/MineGAN/blob/a810f2d77f36ea9cf6993dede958b6f5d458f4b6/MNISTtf/MNISTtf_old/conditional_continue/on_manifold/tflib/ops/cond_batchnorm.py | MNISTtf/MNISTtf_old/conditional_continue/on_manifold/tflib/ops/cond_batchnorm.py | import tflib as lib
import numpy as np
import tensorflow as tf
def Batchnorm(name, axes, inputs, is_training=None, stats_iter=None, update_moving_stats=True, fused=True, labels=None, n_labels=None):
"""conditional batchnorm (dumoulin et al 2016) for BCHW conv filtermaps"""
if axes != [0,2,3]:
raise Ex... | python | MIT | a810f2d77f36ea9cf6993dede958b6f5d458f4b6 | 2026-01-05T07:08:28.063149Z | false |
yaxingwang/MineGAN | https://github.com/yaxingwang/MineGAN/blob/a810f2d77f36ea9cf6993dede958b6f5d458f4b6/MNISTtf/MNISTtf_old/conditional_continue/on_manifold/tflib/ops/linear.py | MNISTtf/MNISTtf_old/conditional_continue/on_manifold/tflib/ops/linear.py | import tflib as lib
import numpy as np
import tensorflow as tf
_default_weightnorm = False
def enable_default_weightnorm():
global _default_weightnorm
_default_weightnorm = True
def disable_default_weightnorm():
global _default_weightnorm
_default_weightnorm = False
_weights_stdev = None
def set_wei... | python | MIT | a810f2d77f36ea9cf6993dede958b6f5d458f4b6 | 2026-01-05T07:08:28.063149Z | false |
yaxingwang/MineGAN | https://github.com/yaxingwang/MineGAN/blob/a810f2d77f36ea9cf6993dede958b6f5d458f4b6/MNISTtf/MNISTtf_old/unconditioanal/off_manifold/gan_mnist_knowledge_distillation_adaptor_step4.py | MNISTtf/MNISTtf_old/unconditioanal/off_manifold/gan_mnist_knowledge_distillation_adaptor_step4.py | import os, sys
sys.path.append(os.getcwd())
import time
import matplotlib
matplotlib.use('Agg')
import matplotlib.pyplot as plt
import numpy as np
import sklearn.datasets
import tensorflow as tf
import tflib as lib
import tflib.ops.linear
import tflib.ops.conv2d
import tflib.ops.batchnorm
import tflib.ops.deconv2d
i... | python | MIT | a810f2d77f36ea9cf6993dede958b6f5d458f4b6 | 2026-01-05T07:08:28.063149Z | false |
yaxingwang/MineGAN | https://github.com/yaxingwang/MineGAN/blob/a810f2d77f36ea9cf6993dede958b6f5d458f4b6/MNISTtf/MNISTtf_old/unconditioanal/off_manifold/gan_mnist_knowledge_distillation_adaptor_step2.py | MNISTtf/MNISTtf_old/unconditioanal/off_manifold/gan_mnist_knowledge_distillation_adaptor_step2.py | import os, sys
sys.path.append(os.getcwd())
import time
import matplotlib
matplotlib.use('Agg')
import matplotlib.pyplot as plt
import numpy as np
import sklearn.datasets
import tensorflow as tf
import tflib as lib
import tflib.ops.linear
import tflib.ops.conv2d
import tflib.ops.batchnorm
import tflib.ops.deconv2d
i... | python | MIT | a810f2d77f36ea9cf6993dede958b6f5d458f4b6 | 2026-01-05T07:08:28.063149Z | false |
yaxingwang/MineGAN | https://github.com/yaxingwang/MineGAN/blob/a810f2d77f36ea9cf6993dede958b6f5d458f4b6/MNISTtf/MNISTtf_old/unconditioanal/off_manifold/teacher.py | MNISTtf/MNISTtf_old/unconditioanal/off_manifold/teacher.py |
import os, sys
sys.path.append(os.getcwd())
import numpy as np
import tensorflow as tf
import tflib as lib
import tflib.ops.linear
import tflib.ops.conv2d
import tflib.ops.batchnorm
import tflib.ops.deconv2d
import tflib.save_images
import tflib.mnist
import tflib.plot
import pdb
def teacher_model(noise, fake_data... | python | MIT | a810f2d77f36ea9cf6993dede958b6f5d458f4b6 | 2026-01-05T07:08:28.063149Z | false |
yaxingwang/MineGAN | https://github.com/yaxingwang/MineGAN/blob/a810f2d77f36ea9cf6993dede958b6f5d458f4b6/MNISTtf/MNISTtf_old/unconditioanal/off_manifold/gan_mnist_knowledge_distillation_baseline.py | MNISTtf/MNISTtf_old/unconditioanal/off_manifold/gan_mnist_knowledge_distillation_baseline.py | import os, sys
sys.path.append(os.getcwd())
import time
import matplotlib
matplotlib.use('Agg')
import matplotlib.pyplot as plt
import numpy as np
import sklearn.datasets
import tensorflow as tf
import tflib as lib
import tflib.ops.linear
import tflib.ops.conv2d
import tflib.ops.batchnorm
import tflib.ops.deconv2d
i... | python | MIT | a810f2d77f36ea9cf6993dede958b6f5d458f4b6 | 2026-01-05T07:08:28.063149Z | false |
yaxingwang/MineGAN | https://github.com/yaxingwang/MineGAN/blob/a810f2d77f36ea9cf6993dede958b6f5d458f4b6/MNISTtf/MNISTtf_old/unconditioanal/off_manifold/gan_mnist_knowledge_distillation_adaptor_step1.py | MNISTtf/MNISTtf_old/unconditioanal/off_manifold/gan_mnist_knowledge_distillation_adaptor_step1.py | import os, sys
sys.path.append(os.getcwd())
import time
import matplotlib
matplotlib.use('Agg')
import matplotlib.pyplot as plt
import numpy as np
import sklearn.datasets
import tensorflow as tf
import tflib as lib
import tflib.ops.linear
import tflib.ops.conv2d
import tflib.ops.batchnorm
import tflib.ops.deconv2d
i... | python | MIT | a810f2d77f36ea9cf6993dede958b6f5d458f4b6 | 2026-01-05T07:08:28.063149Z | false |
yaxingwang/MineGAN | https://github.com/yaxingwang/MineGAN/blob/a810f2d77f36ea9cf6993dede958b6f5d458f4b6/MNISTtf/MNISTtf_old/unconditioanal/off_manifold/gan_mnist_knowledge_distillation_adaptor_step3.py | MNISTtf/MNISTtf_old/unconditioanal/off_manifold/gan_mnist_knowledge_distillation_adaptor_step3.py | import os, sys
sys.path.append(os.getcwd())
import time
import matplotlib
matplotlib.use('Agg')
import matplotlib.pyplot as plt
import numpy as np
import sklearn.datasets
import tensorflow as tf
import tflib as lib
import tflib.ops.linear
import tflib.ops.conv2d
import tflib.ops.batchnorm
import tflib.ops.deconv2d
i... | python | MIT | a810f2d77f36ea9cf6993dede958b6f5d458f4b6 | 2026-01-05T07:08:28.063149Z | false |
yaxingwang/MineGAN | https://github.com/yaxingwang/MineGAN/blob/a810f2d77f36ea9cf6993dede958b6f5d458f4b6/MNISTtf/MNISTtf_old/unconditioanal/off_manifold/tflib/lsun_label.py | MNISTtf/MNISTtf_old/unconditioanal/off_manifold/tflib/lsun_label.py |
from os import listdir
import numpy as np
import scipy.misc
import time
import pdb
Label={'bedroom':0,
'kitchen':1,
'dining_room':2,
'conference_room':3,
'living_room':4,
'bridge':5,
'tower':6,
'classroom':7,
'church_outdoor':8,
'restaurant':9}
def make_g... | python | MIT | a810f2d77f36ea9cf6993dede958b6f5d458f4b6 | 2026-01-05T07:08:28.063149Z | false |
yaxingwang/MineGAN | https://github.com/yaxingwang/MineGAN/blob/a810f2d77f36ea9cf6993dede958b6f5d458f4b6/MNISTtf/MNISTtf_old/unconditioanal/off_manifold/tflib/plot.py | MNISTtf/MNISTtf_old/unconditioanal/off_manifold/tflib/plot.py | import matplotlib
matplotlib.use('Agg')
import matplotlib.pyplot as plt
import numpy as np
import collections
import time
import cPickle as pickle
_since_beginning = collections.defaultdict(lambda: {})
_since_last_flush = collections.defaultdict(lambda: {})
_iter = [0]
def tick():
_iter[0] += 1
def plot(name, valu... | python | MIT | a810f2d77f36ea9cf6993dede958b6f5d458f4b6 | 2026-01-05T07:08:28.063149Z | false |
yaxingwang/MineGAN | https://github.com/yaxingwang/MineGAN/blob/a810f2d77f36ea9cf6993dede958b6f5d458f4b6/MNISTtf/MNISTtf_old/unconditioanal/off_manifold/tflib/mnist_step1.py | MNISTtf/MNISTtf_old/unconditioanal/off_manifold/tflib/mnist_step1.py | import numpy
import os
import urllib
import gzip
import cPickle as pickle
import pdb
def mnist_generator(data, batch_size, n_labelled, limit=None, selecting_label = None, bias = None):
images, targets = data
if bias is not None :
images = images[targets!=bias]
targets = targets[targets!=bias]... | python | MIT | a810f2d77f36ea9cf6993dede958b6f5d458f4b6 | 2026-01-05T07:08:28.063149Z | false |
yaxingwang/MineGAN | https://github.com/yaxingwang/MineGAN/blob/a810f2d77f36ea9cf6993dede958b6f5d458f4b6/MNISTtf/MNISTtf_old/unconditioanal/off_manifold/tflib/mnist_step2.py | MNISTtf/MNISTtf_old/unconditioanal/off_manifold/tflib/mnist_step2.py | import numpy
import os
import urllib
import gzip
import cPickle as pickle
import pdb
import os
from scipy.misc import imsave
def mnist_generator(data, batch_size, n_labelled, limit=None, selecting_label = None):
images, targets = data
#for index, i in enumerate(targets):
# if not os.path.exists('datase... | python | MIT | a810f2d77f36ea9cf6993dede958b6f5d458f4b6 | 2026-01-05T07:08:28.063149Z | false |
yaxingwang/MineGAN | https://github.com/yaxingwang/MineGAN/blob/a810f2d77f36ea9cf6993dede958b6f5d458f4b6/MNISTtf/MNISTtf_old/unconditioanal/off_manifold/tflib/mnist.py | MNISTtf/MNISTtf_old/unconditioanal/off_manifold/tflib/mnist.py | import numpy
import os
import urllib
import gzip
import cPickle as pickle
import pdb
def mnist_generator(data, batch_size, n_labelled, limit=None, selecting_label = None, bias = None):
images, targets = data
if bias is not None :
images = images[targets!=bias]
targets = targets[targets!=bias]... | python | MIT | a810f2d77f36ea9cf6993dede958b6f5d458f4b6 | 2026-01-05T07:08:28.063149Z | false |
yaxingwang/MineGAN | https://github.com/yaxingwang/MineGAN/blob/a810f2d77f36ea9cf6993dede958b6f5d458f4b6/MNISTtf/MNISTtf_old/unconditioanal/off_manifold/tflib/__init__.py | MNISTtf/MNISTtf_old/unconditioanal/off_manifold/tflib/__init__.py | import numpy as np
import tensorflow as tf
#import locale
#locale.setlocale(locale.LC_ALL, '')
_params = {}
_param_aliases = {}
def param(name, *args, **kwargs):
"""
A wrapper for `tf.Variable` which enables parameter sharing in models.
Creates and returns theano shared variables similarly to `tf.Va... | python | MIT | a810f2d77f36ea9cf6993dede958b6f5d458f4b6 | 2026-01-05T07:08:28.063149Z | false |
yaxingwang/MineGAN | https://github.com/yaxingwang/MineGAN/blob/a810f2d77f36ea9cf6993dede958b6f5d458f4b6/MNISTtf/MNISTtf_old/unconditioanal/off_manifold/tflib/lsun.py | MNISTtf/MNISTtf_old/unconditioanal/off_manifold/tflib/lsun.py | import numpy as np
import scipy.misc
import time
import cv2
from os import listdir
def make_generator(path, n_files, batch_size, image_size):
epoch_count = [1]
images_name = listdir(path)
if n_files == 0:
n_files = len(images_name)
else:
n_files = n_files
def get_epoch():
... | python | MIT | a810f2d77f36ea9cf6993dede958b6f5d458f4b6 | 2026-01-05T07:08:28.063149Z | false |
yaxingwang/MineGAN | https://github.com/yaxingwang/MineGAN/blob/a810f2d77f36ea9cf6993dede958b6f5d458f4b6/MNISTtf/MNISTtf_old/unconditioanal/off_manifold/tflib/save_images.py | MNISTtf/MNISTtf_old/unconditioanal/off_manifold/tflib/save_images.py | """
Image grid saver, based on color_grid_vis from github.com/Newmu
"""
import numpy as np
import scipy.misc
from scipy.misc import imsave
def save_images(X, save_path):
# [0, 1] -> [0,255]
if isinstance(X.flatten()[0], np.floating):
X = (255.99*X).astype('uint8')
n_samples = X.shape[0]
rows ... | python | MIT | a810f2d77f36ea9cf6993dede958b6f5d458f4b6 | 2026-01-05T07:08:28.063149Z | false |
yaxingwang/MineGAN | https://github.com/yaxingwang/MineGAN/blob/a810f2d77f36ea9cf6993dede958b6f5d458f4b6/MNISTtf/MNISTtf_old/unconditioanal/off_manifold/tflib/ops/layernorm.py | MNISTtf/MNISTtf_old/unconditioanal/off_manifold/tflib/ops/layernorm.py | import tflib as lib
import numpy as np
import tensorflow as tf
def Layernorm(name, norm_axes, inputs):
mean, var = tf.nn.moments(inputs, norm_axes, keep_dims=True)
# Assume the 'neurons' axis is the first of norm_axes. This is the case for fully-connected and BCHW conv layers.
n_neurons = inputs.get_shap... | python | MIT | a810f2d77f36ea9cf6993dede958b6f5d458f4b6 | 2026-01-05T07:08:28.063149Z | false |
yaxingwang/MineGAN | https://github.com/yaxingwang/MineGAN/blob/a810f2d77f36ea9cf6993dede958b6f5d458f4b6/MNISTtf/MNISTtf_old/unconditioanal/off_manifold/tflib/ops/deconv2d.py | MNISTtf/MNISTtf_old/unconditioanal/off_manifold/tflib/ops/deconv2d.py | import tflib as lib
import numpy as np
import tensorflow as tf
_default_weightnorm = False
def enable_default_weightnorm():
global _default_weightnorm
_default_weightnorm = True
_weights_stdev = None
def set_weights_stdev(weights_stdev):
global _weights_stdev
_weights_stdev = weights_stdev
def unset... | python | MIT | a810f2d77f36ea9cf6993dede958b6f5d458f4b6 | 2026-01-05T07:08:28.063149Z | false |
yaxingwang/MineGAN | https://github.com/yaxingwang/MineGAN/blob/a810f2d77f36ea9cf6993dede958b6f5d458f4b6/MNISTtf/MNISTtf_old/unconditioanal/off_manifold/tflib/ops/__init__.py | MNISTtf/MNISTtf_old/unconditioanal/off_manifold/tflib/ops/__init__.py | python | MIT | a810f2d77f36ea9cf6993dede958b6f5d458f4b6 | 2026-01-05T07:08:28.063149Z | false | |
yaxingwang/MineGAN | https://github.com/yaxingwang/MineGAN/blob/a810f2d77f36ea9cf6993dede958b6f5d458f4b6/MNISTtf/MNISTtf_old/unconditioanal/off_manifold/tflib/ops/conv1d.py | MNISTtf/MNISTtf_old/unconditioanal/off_manifold/tflib/ops/conv1d.py | import tflib as lib
import numpy as np
import tensorflow as tf
_default_weightnorm = False
def enable_default_weightnorm():
global _default_weightnorm
_default_weightnorm = True
def Conv1D(name, input_dim, output_dim, filter_size, inputs, he_init=True, mask_type=None, stride=1, weightnorm=None, biases=True, ... | python | MIT | a810f2d77f36ea9cf6993dede958b6f5d458f4b6 | 2026-01-05T07:08:28.063149Z | false |
yaxingwang/MineGAN | https://github.com/yaxingwang/MineGAN/blob/a810f2d77f36ea9cf6993dede958b6f5d458f4b6/MNISTtf/MNISTtf_old/unconditioanal/off_manifold/tflib/ops/conv2d.py | MNISTtf/MNISTtf_old/unconditioanal/off_manifold/tflib/ops/conv2d.py | import tflib as lib
import numpy as np
import tensorflow as tf
_default_weightnorm = False
def enable_default_weightnorm():
global _default_weightnorm
_default_weightnorm = True
_weights_stdev = None
def set_weights_stdev(weights_stdev):
global _weights_stdev
_weights_stdev = weights_stdev
def unset... | python | MIT | a810f2d77f36ea9cf6993dede958b6f5d458f4b6 | 2026-01-05T07:08:28.063149Z | false |
yaxingwang/MineGAN | https://github.com/yaxingwang/MineGAN/blob/a810f2d77f36ea9cf6993dede958b6f5d458f4b6/MNISTtf/MNISTtf_old/unconditioanal/off_manifold/tflib/ops/batchnorm.py | MNISTtf/MNISTtf_old/unconditioanal/off_manifold/tflib/ops/batchnorm.py | import tflib as lib
import numpy as np
import tensorflow as tf
def Batchnorm(name, axes, inputs, is_training=None, stats_iter=None, update_moving_stats=True, fused=True):
if ((axes == [0,2,3]) or (axes == [0,2])) and fused==True:
if axes==[0,2]:
inputs = tf.expand_dims(inputs, 3)
# Old... | python | MIT | a810f2d77f36ea9cf6993dede958b6f5d458f4b6 | 2026-01-05T07:08:28.063149Z | false |
yaxingwang/MineGAN | https://github.com/yaxingwang/MineGAN/blob/a810f2d77f36ea9cf6993dede958b6f5d458f4b6/MNISTtf/MNISTtf_old/unconditioanal/off_manifold/tflib/ops/cond_batchnorm.py | MNISTtf/MNISTtf_old/unconditioanal/off_manifold/tflib/ops/cond_batchnorm.py | import tflib as lib
import numpy as np
import tensorflow as tf
def Batchnorm(name, axes, inputs, is_training=None, stats_iter=None, update_moving_stats=True, fused=True, labels=None, n_labels=None):
"""conditional batchnorm (dumoulin et al 2016) for BCHW conv filtermaps"""
if axes != [0,2,3]:
raise Ex... | python | MIT | a810f2d77f36ea9cf6993dede958b6f5d458f4b6 | 2026-01-05T07:08:28.063149Z | false |
yaxingwang/MineGAN | https://github.com/yaxingwang/MineGAN/blob/a810f2d77f36ea9cf6993dede958b6f5d458f4b6/MNISTtf/MNISTtf_old/unconditioanal/off_manifold/tflib/ops/linear.py | MNISTtf/MNISTtf_old/unconditioanal/off_manifold/tflib/ops/linear.py | import tflib as lib
import numpy as np
import tensorflow as tf
_default_weightnorm = False
def enable_default_weightnorm():
global _default_weightnorm
_default_weightnorm = True
def disable_default_weightnorm():
global _default_weightnorm
_default_weightnorm = False
_weights_stdev = None
def set_wei... | python | MIT | a810f2d77f36ea9cf6993dede958b6f5d458f4b6 | 2026-01-05T07:08:28.063149Z | false |
yaxingwang/MineGAN | https://github.com/yaxingwang/MineGAN/blob/a810f2d77f36ea9cf6993dede958b6f5d458f4b6/MNISTtf/MNISTtf_old/unconditioanal/on_manifold/gan_mnist_knowledge_distillation_adaptor_step4.py | MNISTtf/MNISTtf_old/unconditioanal/on_manifold/gan_mnist_knowledge_distillation_adaptor_step4.py | import os, sys
sys.path.append(os.getcwd())
import time
import matplotlib
matplotlib.use('Agg')
import matplotlib.pyplot as plt
import numpy as np
import sklearn.datasets
import tensorflow as tf
import tflib as lib
import tflib.ops.linear
import tflib.ops.conv2d
import tflib.ops.batchnorm
import tflib.ops.deconv2d
i... | python | MIT | a810f2d77f36ea9cf6993dede958b6f5d458f4b6 | 2026-01-05T07:08:28.063149Z | false |
yaxingwang/MineGAN | https://github.com/yaxingwang/MineGAN/blob/a810f2d77f36ea9cf6993dede958b6f5d458f4b6/MNISTtf/MNISTtf_old/unconditioanal/on_manifold/gan_mnist_knowledge_distillation_adaptor_step2.py | MNISTtf/MNISTtf_old/unconditioanal/on_manifold/gan_mnist_knowledge_distillation_adaptor_step2.py | import os, sys
sys.path.append(os.getcwd())
import time
import matplotlib
matplotlib.use('Agg')
import matplotlib.pyplot as plt
import numpy as np
import sklearn.datasets
import tensorflow as tf
import tflib as lib
import tflib.ops.linear
import tflib.ops.conv2d
import tflib.ops.batchnorm
import tflib.ops.deconv2d
i... | python | MIT | a810f2d77f36ea9cf6993dede958b6f5d458f4b6 | 2026-01-05T07:08:28.063149Z | false |
yaxingwang/MineGAN | https://github.com/yaxingwang/MineGAN/blob/a810f2d77f36ea9cf6993dede958b6f5d458f4b6/MNISTtf/MNISTtf_old/unconditioanal/on_manifold/teacher.py | MNISTtf/MNISTtf_old/unconditioanal/on_manifold/teacher.py |
import os, sys
sys.path.append(os.getcwd())
import numpy as np
import tensorflow as tf
import tflib as lib
import tflib.ops.linear
import tflib.ops.conv2d
import tflib.ops.batchnorm
import tflib.ops.deconv2d
import tflib.save_images
import tflib.mnist
import tflib.plot
import pdb
def teacher_model(noise, fake_data... | python | MIT | a810f2d77f36ea9cf6993dede958b6f5d458f4b6 | 2026-01-05T07:08:28.063149Z | false |
yaxingwang/MineGAN | https://github.com/yaxingwang/MineGAN/blob/a810f2d77f36ea9cf6993dede958b6f5d458f4b6/MNISTtf/MNISTtf_old/unconditioanal/on_manifold/gan_mnist_knowledge_distillation_baseline.py | MNISTtf/MNISTtf_old/unconditioanal/on_manifold/gan_mnist_knowledge_distillation_baseline.py | import os, sys
sys.path.append(os.getcwd())
import time
import matplotlib
matplotlib.use('Agg')
import matplotlib.pyplot as plt
import numpy as np
import sklearn.datasets
import tensorflow as tf
import tflib as lib
import tflib.ops.linear
import tflib.ops.conv2d
import tflib.ops.batchnorm
import tflib.ops.deconv2d
i... | python | MIT | a810f2d77f36ea9cf6993dede958b6f5d458f4b6 | 2026-01-05T07:08:28.063149Z | false |
yaxingwang/MineGAN | https://github.com/yaxingwang/MineGAN/blob/a810f2d77f36ea9cf6993dede958b6f5d458f4b6/MNISTtf/MNISTtf_old/unconditioanal/on_manifold/gan_mnist_knowledge_distillation_adaptor_step1.py | MNISTtf/MNISTtf_old/unconditioanal/on_manifold/gan_mnist_knowledge_distillation_adaptor_step1.py | import os, sys
sys.path.append(os.getcwd())
import time
import matplotlib
matplotlib.use('Agg')
import matplotlib.pyplot as plt
import numpy as np
import sklearn.datasets
import tensorflow as tf
import tflib as lib
import tflib.ops.linear
import tflib.ops.conv2d
import tflib.ops.batchnorm
import tflib.ops.deconv2d
i... | python | MIT | a810f2d77f36ea9cf6993dede958b6f5d458f4b6 | 2026-01-05T07:08:28.063149Z | false |
yaxingwang/MineGAN | https://github.com/yaxingwang/MineGAN/blob/a810f2d77f36ea9cf6993dede958b6f5d458f4b6/MNISTtf/MNISTtf_old/unconditioanal/on_manifold/gan_mnist_knowledge_distillation_adaptor_step3.py | MNISTtf/MNISTtf_old/unconditioanal/on_manifold/gan_mnist_knowledge_distillation_adaptor_step3.py | import os, sys
sys.path.append(os.getcwd())
import time
import matplotlib
matplotlib.use('Agg')
import matplotlib.pyplot as plt
import numpy as np
import sklearn.datasets
import tensorflow as tf
import tflib as lib
import tflib.ops.linear
import tflib.ops.conv2d
import tflib.ops.batchnorm
import tflib.ops.deconv2d
i... | python | MIT | a810f2d77f36ea9cf6993dede958b6f5d458f4b6 | 2026-01-05T07:08:28.063149Z | false |
yaxingwang/MineGAN | https://github.com/yaxingwang/MineGAN/blob/a810f2d77f36ea9cf6993dede958b6f5d458f4b6/MNISTtf/MNISTtf_old/unconditioanal/on_manifold/tflib/lsun_label.py | MNISTtf/MNISTtf_old/unconditioanal/on_manifold/tflib/lsun_label.py |
from os import listdir
import numpy as np
import scipy.misc
import time
import pdb
Label={'bedroom':0,
'kitchen':1,
'dining_room':2,
'conference_room':3,
'living_room':4,
'bridge':5,
'tower':6,
'classroom':7,
'church_outdoor':8,
'restaurant':9}
def make_g... | python | MIT | a810f2d77f36ea9cf6993dede958b6f5d458f4b6 | 2026-01-05T07:08:28.063149Z | false |
yaxingwang/MineGAN | https://github.com/yaxingwang/MineGAN/blob/a810f2d77f36ea9cf6993dede958b6f5d458f4b6/MNISTtf/MNISTtf_old/unconditioanal/on_manifold/tflib/plot.py | MNISTtf/MNISTtf_old/unconditioanal/on_manifold/tflib/plot.py | import matplotlib
matplotlib.use('Agg')
import matplotlib.pyplot as plt
import numpy as np
import collections
import time
import cPickle as pickle
_since_beginning = collections.defaultdict(lambda: {})
_since_last_flush = collections.defaultdict(lambda: {})
_iter = [0]
def tick():
_iter[0] += 1
def plot(name, valu... | python | MIT | a810f2d77f36ea9cf6993dede958b6f5d458f4b6 | 2026-01-05T07:08:28.063149Z | false |
yaxingwang/MineGAN | https://github.com/yaxingwang/MineGAN/blob/a810f2d77f36ea9cf6993dede958b6f5d458f4b6/MNISTtf/MNISTtf_old/unconditioanal/on_manifold/tflib/mnist.py | MNISTtf/MNISTtf_old/unconditioanal/on_manifold/tflib/mnist.py | import numpy
import os
import urllib
import gzip
import cPickle as pickle
import pdb
import os
from scipy.misc import imsave
def mnist_generator(data, batch_size, n_labelled, limit=None, selecting_label = None):
images, targets = data
#for index, i in enumerate(targets):
# if not os.path.exists('datase... | python | MIT | a810f2d77f36ea9cf6993dede958b6f5d458f4b6 | 2026-01-05T07:08:28.063149Z | false |
yaxingwang/MineGAN | https://github.com/yaxingwang/MineGAN/blob/a810f2d77f36ea9cf6993dede958b6f5d458f4b6/MNISTtf/MNISTtf_old/unconditioanal/on_manifold/tflib/__init__.py | MNISTtf/MNISTtf_old/unconditioanal/on_manifold/tflib/__init__.py | import numpy as np
import tensorflow as tf
#import locale
#locale.setlocale(locale.LC_ALL, '')
_params = {}
_param_aliases = {}
def param(name, *args, **kwargs):
"""
A wrapper for `tf.Variable` which enables parameter sharing in models.
Creates and returns theano shared variables similarly to `tf.Va... | python | MIT | a810f2d77f36ea9cf6993dede958b6f5d458f4b6 | 2026-01-05T07:08:28.063149Z | false |
yaxingwang/MineGAN | https://github.com/yaxingwang/MineGAN/blob/a810f2d77f36ea9cf6993dede958b6f5d458f4b6/MNISTtf/MNISTtf_old/unconditioanal/on_manifold/tflib/lsun.py | MNISTtf/MNISTtf_old/unconditioanal/on_manifold/tflib/lsun.py | import numpy as np
import scipy.misc
import time
import cv2
from os import listdir
def make_generator(path, n_files, batch_size, image_size):
epoch_count = [1]
images_name = listdir(path)
if n_files == 0:
n_files = len(images_name)
else:
n_files = n_files
def get_epoch():
... | python | MIT | a810f2d77f36ea9cf6993dede958b6f5d458f4b6 | 2026-01-05T07:08:28.063149Z | false |
yaxingwang/MineGAN | https://github.com/yaxingwang/MineGAN/blob/a810f2d77f36ea9cf6993dede958b6f5d458f4b6/MNISTtf/MNISTtf_old/unconditioanal/on_manifold/tflib/save_images.py | MNISTtf/MNISTtf_old/unconditioanal/on_manifold/tflib/save_images.py | """
Image grid saver, based on color_grid_vis from github.com/Newmu
"""
import numpy as np
import scipy.misc
from scipy.misc import imsave
def save_images(X, save_path):
# [0, 1] -> [0,255]
if isinstance(X.flatten()[0], np.floating):
X = (255.99*X).astype('uint8')
n_samples = X.shape[0]
rows ... | python | MIT | a810f2d77f36ea9cf6993dede958b6f5d458f4b6 | 2026-01-05T07:08:28.063149Z | false |
yaxingwang/MineGAN | https://github.com/yaxingwang/MineGAN/blob/a810f2d77f36ea9cf6993dede958b6f5d458f4b6/MNISTtf/MNISTtf_old/unconditioanal/on_manifold/tflib/ops/layernorm.py | MNISTtf/MNISTtf_old/unconditioanal/on_manifold/tflib/ops/layernorm.py | import tflib as lib
import numpy as np
import tensorflow as tf
def Layernorm(name, norm_axes, inputs):
mean, var = tf.nn.moments(inputs, norm_axes, keep_dims=True)
# Assume the 'neurons' axis is the first of norm_axes. This is the case for fully-connected and BCHW conv layers.
n_neurons = inputs.get_shap... | python | MIT | a810f2d77f36ea9cf6993dede958b6f5d458f4b6 | 2026-01-05T07:08:28.063149Z | false |
yaxingwang/MineGAN | https://github.com/yaxingwang/MineGAN/blob/a810f2d77f36ea9cf6993dede958b6f5d458f4b6/MNISTtf/MNISTtf_old/unconditioanal/on_manifold/tflib/ops/deconv2d.py | MNISTtf/MNISTtf_old/unconditioanal/on_manifold/tflib/ops/deconv2d.py | import tflib as lib
import numpy as np
import tensorflow as tf
_default_weightnorm = False
def enable_default_weightnorm():
global _default_weightnorm
_default_weightnorm = True
_weights_stdev = None
def set_weights_stdev(weights_stdev):
global _weights_stdev
_weights_stdev = weights_stdev
def unset... | python | MIT | a810f2d77f36ea9cf6993dede958b6f5d458f4b6 | 2026-01-05T07:08:28.063149Z | false |
yaxingwang/MineGAN | https://github.com/yaxingwang/MineGAN/blob/a810f2d77f36ea9cf6993dede958b6f5d458f4b6/MNISTtf/MNISTtf_old/unconditioanal/on_manifold/tflib/ops/__init__.py | MNISTtf/MNISTtf_old/unconditioanal/on_manifold/tflib/ops/__init__.py | python | MIT | a810f2d77f36ea9cf6993dede958b6f5d458f4b6 | 2026-01-05T07:08:28.063149Z | false | |
yaxingwang/MineGAN | https://github.com/yaxingwang/MineGAN/blob/a810f2d77f36ea9cf6993dede958b6f5d458f4b6/MNISTtf/MNISTtf_old/unconditioanal/on_manifold/tflib/ops/conv1d.py | MNISTtf/MNISTtf_old/unconditioanal/on_manifold/tflib/ops/conv1d.py | import tflib as lib
import numpy as np
import tensorflow as tf
_default_weightnorm = False
def enable_default_weightnorm():
global _default_weightnorm
_default_weightnorm = True
def Conv1D(name, input_dim, output_dim, filter_size, inputs, he_init=True, mask_type=None, stride=1, weightnorm=None, biases=True, ... | python | MIT | a810f2d77f36ea9cf6993dede958b6f5d458f4b6 | 2026-01-05T07:08:28.063149Z | false |
yaxingwang/MineGAN | https://github.com/yaxingwang/MineGAN/blob/a810f2d77f36ea9cf6993dede958b6f5d458f4b6/MNISTtf/MNISTtf_old/unconditioanal/on_manifold/tflib/ops/conv2d.py | MNISTtf/MNISTtf_old/unconditioanal/on_manifold/tflib/ops/conv2d.py | import tflib as lib
import numpy as np
import tensorflow as tf
_default_weightnorm = False
def enable_default_weightnorm():
global _default_weightnorm
_default_weightnorm = True
_weights_stdev = None
def set_weights_stdev(weights_stdev):
global _weights_stdev
_weights_stdev = weights_stdev
def unset... | python | MIT | a810f2d77f36ea9cf6993dede958b6f5d458f4b6 | 2026-01-05T07:08:28.063149Z | false |
yaxingwang/MineGAN | https://github.com/yaxingwang/MineGAN/blob/a810f2d77f36ea9cf6993dede958b6f5d458f4b6/MNISTtf/MNISTtf_old/unconditioanal/on_manifold/tflib/ops/batchnorm.py | MNISTtf/MNISTtf_old/unconditioanal/on_manifold/tflib/ops/batchnorm.py | import tflib as lib
import numpy as np
import tensorflow as tf
def Batchnorm(name, axes, inputs, is_training=None, stats_iter=None, update_moving_stats=True, fused=True):
if ((axes == [0,2,3]) or (axes == [0,2])) and fused==True:
if axes==[0,2]:
inputs = tf.expand_dims(inputs, 3)
# Old... | python | MIT | a810f2d77f36ea9cf6993dede958b6f5d458f4b6 | 2026-01-05T07:08:28.063149Z | false |
yaxingwang/MineGAN | https://github.com/yaxingwang/MineGAN/blob/a810f2d77f36ea9cf6993dede958b6f5d458f4b6/MNISTtf/MNISTtf_old/unconditioanal/on_manifold/tflib/ops/cond_batchnorm.py | MNISTtf/MNISTtf_old/unconditioanal/on_manifold/tflib/ops/cond_batchnorm.py | import tflib as lib
import numpy as np
import tensorflow as tf
def Batchnorm(name, axes, inputs, is_training=None, stats_iter=None, update_moving_stats=True, fused=True, labels=None, n_labels=None):
"""conditional batchnorm (dumoulin et al 2016) for BCHW conv filtermaps"""
if axes != [0,2,3]:
raise Ex... | python | MIT | a810f2d77f36ea9cf6993dede958b6f5d458f4b6 | 2026-01-05T07:08:28.063149Z | false |
yaxingwang/MineGAN | https://github.com/yaxingwang/MineGAN/blob/a810f2d77f36ea9cf6993dede958b6f5d458f4b6/MNISTtf/MNISTtf_old/unconditioanal/on_manifold/tflib/ops/linear.py | MNISTtf/MNISTtf_old/unconditioanal/on_manifold/tflib/ops/linear.py | import tflib as lib
import numpy as np
import tensorflow as tf
_default_weightnorm = False
def enable_default_weightnorm():
global _default_weightnorm
_default_weightnorm = True
def disable_default_weightnorm():
global _default_weightnorm
_default_weightnorm = False
_weights_stdev = None
def set_wei... | python | MIT | a810f2d77f36ea9cf6993dede958b6f5d458f4b6 | 2026-01-05T07:08:28.063149Z | false |
yaxingwang/MineGAN | https://github.com/yaxingwang/MineGAN/blob/a810f2d77f36ea9cf6993dede958b6f5d458f4b6/MNISTtf/MNISTtf_old/conditional_one_hot/off_manifold/useless.py | MNISTtf/MNISTtf_old/conditional_one_hot/off_manifold/useless.py | import os, sys
sys.path.append(os.getcwd())
import time
import matplotlib
matplotlib.use('Agg')
import matplotlib.pyplot as plt
import numpy as np
import sklearn.datasets
import tensorflow as tf
import tflib as lib
import tflib.ops.linear
import tflib.ops.conv2d
import tflib.ops.batchnorm
import tflib.ops.deconv2d
i... | python | MIT | a810f2d77f36ea9cf6993dede958b6f5d458f4b6 | 2026-01-05T07:08:28.063149Z | false |
yaxingwang/MineGAN | https://github.com/yaxingwang/MineGAN/blob/a810f2d77f36ea9cf6993dede958b6f5d458f4b6/MNISTtf/MNISTtf_old/conditional_one_hot/off_manifold/teacher_output_d.py | MNISTtf/MNISTtf_old/conditional_one_hot/off_manifold/teacher_output_d.py |
import os, sys
sys.path.append(os.getcwd())
import numpy as np
import tensorflow as tf
import tflib as lib
import tflib.ops.linear
import tflib.ops.conv2d
import tflib.ops.batchnorm
import tflib.ops.deconv2d
import tflib.save_images
import tflib.mnist
import tflib.plot
import pdb
def teacher_model(noise, fake_dat... | python | MIT | a810f2d77f36ea9cf6993dede958b6f5d458f4b6 | 2026-01-05T07:08:28.063149Z | false |
yaxingwang/MineGAN | https://github.com/yaxingwang/MineGAN/blob/a810f2d77f36ea9cf6993dede958b6f5d458f4b6/MNISTtf/MNISTtf_old/conditional_one_hot/off_manifold/cgan_super_g_d_two_class_unbalance_one_D.py | MNISTtf/MNISTtf_old/conditional_one_hot/off_manifold/cgan_super_g_d_two_class_unbalance_one_D.py | import os, sys
sys.path.append(os.getcwd())
import time
import matplotlib
matplotlib.use('Agg')
import matplotlib.pyplot as plt
import numpy as np
import sklearn.datasets
import tensorflow as tf
import tflib as lib
import tflib.ops.linear
import tflib.ops.conv2d
import tflib.ops.batchnorm
import tflib.ops.deconv2d
i... | python | MIT | a810f2d77f36ea9cf6993dede958b6f5d458f4b6 | 2026-01-05T07:08:28.063149Z | false |
yaxingwang/MineGAN | https://github.com/yaxingwang/MineGAN/blob/a810f2d77f36ea9cf6993dede958b6f5d458f4b6/MNISTtf/MNISTtf_old/conditional_one_hot/off_manifold/teacher.py | MNISTtf/MNISTtf_old/conditional_one_hot/off_manifold/teacher.py |
import os, sys
sys.path.append(os.getcwd())
import numpy as np
import tensorflow as tf
import tflib as lib
import tflib.ops.linear
import tflib.ops.conv2d
import tflib.ops.batchnorm
import tflib.ops.deconv2d
import tflib.save_images
import tflib.mnist
import tflib.plot
import pdb
def teacher_model(noise, fake_data... | python | MIT | a810f2d77f36ea9cf6993dede958b6f5d458f4b6 | 2026-01-05T07:08:28.063149Z | false |
yaxingwang/MineGAN | https://github.com/yaxingwang/MineGAN/blob/a810f2d77f36ea9cf6993dede958b6f5d458f4b6/MNISTtf/MNISTtf_old/conditional_one_hot/off_manifold/cgan_mnist_knowledge_distillation_adaptor_step1.py | MNISTtf/MNISTtf_old/conditional_one_hot/off_manifold/cgan_mnist_knowledge_distillation_adaptor_step1.py | import os, sys
sys.path.append(os.getcwd())
import time
import matplotlib
matplotlib.use('Agg')
import matplotlib.pyplot as plt
import numpy as np
import sklearn.datasets
import tensorflow as tf
import tflib as lib
import tflib.ops.linear
import tflib.ops.conv2d
import tflib.ops.batchnorm
import tflib.ops.deconv2d
i... | python | MIT | a810f2d77f36ea9cf6993dede958b6f5d458f4b6 | 2026-01-05T07:08:28.063149Z | false |
yaxingwang/MineGAN | https://github.com/yaxingwang/MineGAN/blob/a810f2d77f36ea9cf6993dede958b6f5d458f4b6/MNISTtf/MNISTtf_old/conditional_one_hot/off_manifold/cgan_super_g_d_two_class_unbalance_one_D_no_share_latent.py | MNISTtf/MNISTtf_old/conditional_one_hot/off_manifold/cgan_super_g_d_two_class_unbalance_one_D_no_share_latent.py | import os, sys
sys.path.append(os.getcwd())
import time
import matplotlib
matplotlib.use('Agg')
import matplotlib.pyplot as plt
import numpy as np
import sklearn.datasets
import tensorflow as tf
import tflib as lib
import tflib.ops.linear
import tflib.ops.conv2d
import tflib.ops.batchnorm
import tflib.ops.deconv2d
i... | python | MIT | a810f2d77f36ea9cf6993dede958b6f5d458f4b6 | 2026-01-05T07:08:28.063149Z | false |
yaxingwang/MineGAN | https://github.com/yaxingwang/MineGAN/blob/a810f2d77f36ea9cf6993dede958b6f5d458f4b6/MNISTtf/MNISTtf_old/conditional_one_hot/off_manifold/tflib/lsun_label.py | MNISTtf/MNISTtf_old/conditional_one_hot/off_manifold/tflib/lsun_label.py |
from os import listdir
import numpy as np
import scipy.misc
import time
import pdb
Label={'bedroom':0,
'kitchen':1,
'dining_room':2,
'conference_room':3,
'living_room':4,
'bridge':5,
'tower':6,
'classroom':7,
'church_outdoor':8,
'restaurant':9}
def make_g... | python | MIT | a810f2d77f36ea9cf6993dede958b6f5d458f4b6 | 2026-01-05T07:08:28.063149Z | false |
yaxingwang/MineGAN | https://github.com/yaxingwang/MineGAN/blob/a810f2d77f36ea9cf6993dede958b6f5d458f4b6/MNISTtf/MNISTtf_old/conditional_one_hot/off_manifold/tflib/plot.py | MNISTtf/MNISTtf_old/conditional_one_hot/off_manifold/tflib/plot.py | import matplotlib
matplotlib.use('Agg')
import matplotlib.pyplot as plt
import numpy as np
import collections
import time
import cPickle as pickle
_since_beginning = collections.defaultdict(lambda: {})
_since_last_flush = collections.defaultdict(lambda: {})
_iter = [0]
def tick():
_iter[0] += 1
def plot(name, valu... | python | MIT | a810f2d77f36ea9cf6993dede958b6f5d458f4b6 | 2026-01-05T07:08:28.063149Z | false |
yaxingwang/MineGAN | https://github.com/yaxingwang/MineGAN/blob/a810f2d77f36ea9cf6993dede958b6f5d458f4b6/MNISTtf/MNISTtf_old/conditional_one_hot/off_manifold/tflib/mnist_step1.py | MNISTtf/MNISTtf_old/conditional_one_hot/off_manifold/tflib/mnist_step1.py | import numpy
import os
import urllib
import gzip
import cPickle as pickle
import pdb
def mnist_generator(data, batch_size, n_labelled, limit=None, selecting_label = None, bias = None):
images, targets = data
if bias is not None :
images = images[targets!=bias]
targets = targets[targets!=bias]... | python | MIT | a810f2d77f36ea9cf6993dede958b6f5d458f4b6 | 2026-01-05T07:08:28.063149Z | false |
yaxingwang/MineGAN | https://github.com/yaxingwang/MineGAN/blob/a810f2d77f36ea9cf6993dede958b6f5d458f4b6/MNISTtf/MNISTtf_old/conditional_one_hot/off_manifold/tflib/mnist_step2.py | MNISTtf/MNISTtf_old/conditional_one_hot/off_manifold/tflib/mnist_step2.py | import numpy
import os
import urllib
import gzip
import cPickle as pickle
import pdb
import os
from scipy.misc import imsave
def mnist_generator(data, batch_size, n_labelled, limit=None, selecting_label = None):
images, targets = data
#for index, i in enumerate(targets):
# if not os.path.exists('datase... | python | MIT | a810f2d77f36ea9cf6993dede958b6f5d458f4b6 | 2026-01-05T07:08:28.063149Z | false |
yaxingwang/MineGAN | https://github.com/yaxingwang/MineGAN/blob/a810f2d77f36ea9cf6993dede958b6f5d458f4b6/MNISTtf/MNISTtf_old/conditional_one_hot/off_manifold/tflib/mnist.py | MNISTtf/MNISTtf_old/conditional_one_hot/off_manifold/tflib/mnist.py | import numpy
import os
import urllib
import gzip
import cPickle as pickle
import pdb
def mnist_generator(data, batch_size, n_labelled, limit=None, selecting_label = None, bias = None):
images, targets = data
if bias is not None :
images = images[targets!=bias]
targets = targets[targets!=bias]... | python | MIT | a810f2d77f36ea9cf6993dede958b6f5d458f4b6 | 2026-01-05T07:08:28.063149Z | false |
yaxingwang/MineGAN | https://github.com/yaxingwang/MineGAN/blob/a810f2d77f36ea9cf6993dede958b6f5d458f4b6/MNISTtf/MNISTtf_old/conditional_one_hot/off_manifold/tflib/__init__.py | MNISTtf/MNISTtf_old/conditional_one_hot/off_manifold/tflib/__init__.py | import numpy as np
import tensorflow as tf
#import locale
#locale.setlocale(locale.LC_ALL, '')
_params = {}
_param_aliases = {}
def param(name, *args, **kwargs):
"""
A wrapper for `tf.Variable` which enables parameter sharing in models.
Creates and returns theano shared variables similarly to `tf.Va... | python | MIT | a810f2d77f36ea9cf6993dede958b6f5d458f4b6 | 2026-01-05T07:08:28.063149Z | false |
yaxingwang/MineGAN | https://github.com/yaxingwang/MineGAN/blob/a810f2d77f36ea9cf6993dede958b6f5d458f4b6/MNISTtf/MNISTtf_old/conditional_one_hot/off_manifold/tflib/lsun.py | MNISTtf/MNISTtf_old/conditional_one_hot/off_manifold/tflib/lsun.py | import numpy as np
import scipy.misc
import time
import cv2
from os import listdir
def make_generator(path, n_files, batch_size, image_size):
epoch_count = [1]
images_name = listdir(path)
if n_files == 0:
n_files = len(images_name)
else:
n_files = n_files
def get_epoch():
... | python | MIT | a810f2d77f36ea9cf6993dede958b6f5d458f4b6 | 2026-01-05T07:08:28.063149Z | false |
yaxingwang/MineGAN | https://github.com/yaxingwang/MineGAN/blob/a810f2d77f36ea9cf6993dede958b6f5d458f4b6/MNISTtf/MNISTtf_old/conditional_one_hot/off_manifold/tflib/save_images.py | MNISTtf/MNISTtf_old/conditional_one_hot/off_manifold/tflib/save_images.py | """
Image grid saver, based on color_grid_vis from github.com/Newmu
"""
import numpy as np
import scipy.misc
from scipy.misc import imsave
def save_images(X, save_path):
# [0, 1] -> [0,255]
if isinstance(X.flatten()[0], np.floating):
X = (255.99*X).astype('uint8')
n_samples = X.shape[0]
rows ... | python | MIT | a810f2d77f36ea9cf6993dede958b6f5d458f4b6 | 2026-01-05T07:08:28.063149Z | false |
yaxingwang/MineGAN | https://github.com/yaxingwang/MineGAN/blob/a810f2d77f36ea9cf6993dede958b6f5d458f4b6/MNISTtf/MNISTtf_old/conditional_one_hot/off_manifold/tflib/mnist_mask_digit.py | MNISTtf/MNISTtf_old/conditional_one_hot/off_manifold/tflib/mnist_mask_digit.py |
import numpy
import os
import urllib
import gzip
import cPickle as pickle
import pdb
def mnist_generator(data, batch_size, n_labelled, limit=None, selecting_label = None):
images, targets = data
# if selecting_label is None:
# rng_state = numpy.random.get_state()
# numpy.random.shuffle(images)
... | python | MIT | a810f2d77f36ea9cf6993dede958b6f5d458f4b6 | 2026-01-05T07:08:28.063149Z | false |
yaxingwang/MineGAN | https://github.com/yaxingwang/MineGAN/blob/a810f2d77f36ea9cf6993dede958b6f5d458f4b6/MNISTtf/MNISTtf_old/conditional_one_hot/off_manifold/tflib/ops/layernorm.py | MNISTtf/MNISTtf_old/conditional_one_hot/off_manifold/tflib/ops/layernorm.py | import tflib as lib
import numpy as np
import tensorflow as tf
def Layernorm(name, norm_axes, inputs):
mean, var = tf.nn.moments(inputs, norm_axes, keep_dims=True)
# Assume the 'neurons' axis is the first of norm_axes. This is the case for fully-connected and BCHW conv layers.
n_neurons = inputs.get_shap... | python | MIT | a810f2d77f36ea9cf6993dede958b6f5d458f4b6 | 2026-01-05T07:08:28.063149Z | false |
yaxingwang/MineGAN | https://github.com/yaxingwang/MineGAN/blob/a810f2d77f36ea9cf6993dede958b6f5d458f4b6/MNISTtf/MNISTtf_old/conditional_one_hot/off_manifold/tflib/ops/deconv2d.py | MNISTtf/MNISTtf_old/conditional_one_hot/off_manifold/tflib/ops/deconv2d.py | import tflib as lib
import numpy as np
import tensorflow as tf
_default_weightnorm = False
def enable_default_weightnorm():
global _default_weightnorm
_default_weightnorm = True
_weights_stdev = None
def set_weights_stdev(weights_stdev):
global _weights_stdev
_weights_stdev = weights_stdev
def unset... | python | MIT | a810f2d77f36ea9cf6993dede958b6f5d458f4b6 | 2026-01-05T07:08:28.063149Z | false |
yaxingwang/MineGAN | https://github.com/yaxingwang/MineGAN/blob/a810f2d77f36ea9cf6993dede958b6f5d458f4b6/MNISTtf/MNISTtf_old/conditional_one_hot/off_manifold/tflib/ops/__init__.py | MNISTtf/MNISTtf_old/conditional_one_hot/off_manifold/tflib/ops/__init__.py | python | MIT | a810f2d77f36ea9cf6993dede958b6f5d458f4b6 | 2026-01-05T07:08:28.063149Z | false | |
yaxingwang/MineGAN | https://github.com/yaxingwang/MineGAN/blob/a810f2d77f36ea9cf6993dede958b6f5d458f4b6/MNISTtf/MNISTtf_old/conditional_one_hot/off_manifold/tflib/ops/conv1d.py | MNISTtf/MNISTtf_old/conditional_one_hot/off_manifold/tflib/ops/conv1d.py | import tflib as lib
import numpy as np
import tensorflow as tf
_default_weightnorm = False
def enable_default_weightnorm():
global _default_weightnorm
_default_weightnorm = True
def Conv1D(name, input_dim, output_dim, filter_size, inputs, he_init=True, mask_type=None, stride=1, weightnorm=None, biases=True, ... | python | MIT | a810f2d77f36ea9cf6993dede958b6f5d458f4b6 | 2026-01-05T07:08:28.063149Z | false |
yaxingwang/MineGAN | https://github.com/yaxingwang/MineGAN/blob/a810f2d77f36ea9cf6993dede958b6f5d458f4b6/MNISTtf/MNISTtf_old/conditional_one_hot/off_manifold/tflib/ops/conv2d.py | MNISTtf/MNISTtf_old/conditional_one_hot/off_manifold/tflib/ops/conv2d.py | import tflib as lib
import numpy as np
import tensorflow as tf
_default_weightnorm = False
def enable_default_weightnorm():
global _default_weightnorm
_default_weightnorm = True
_weights_stdev = None
def set_weights_stdev(weights_stdev):
global _weights_stdev
_weights_stdev = weights_stdev
def unset... | python | MIT | a810f2d77f36ea9cf6993dede958b6f5d458f4b6 | 2026-01-05T07:08:28.063149Z | false |
yaxingwang/MineGAN | https://github.com/yaxingwang/MineGAN/blob/a810f2d77f36ea9cf6993dede958b6f5d458f4b6/MNISTtf/MNISTtf_old/conditional_one_hot/off_manifold/tflib/ops/batchnorm.py | MNISTtf/MNISTtf_old/conditional_one_hot/off_manifold/tflib/ops/batchnorm.py | import tflib as lib
import numpy as np
import tensorflow as tf
def Batchnorm(name, axes, inputs, is_training=None, stats_iter=None, update_moving_stats=True, fused=True):
if ((axes == [0,2,3]) or (axes == [0,2])) and fused==True:
if axes==[0,2]:
inputs = tf.expand_dims(inputs, 3)
# Old... | python | MIT | a810f2d77f36ea9cf6993dede958b6f5d458f4b6 | 2026-01-05T07:08:28.063149Z | false |
yaxingwang/MineGAN | https://github.com/yaxingwang/MineGAN/blob/a810f2d77f36ea9cf6993dede958b6f5d458f4b6/MNISTtf/MNISTtf_old/conditional_one_hot/off_manifold/tflib/ops/cond_batchnorm.py | MNISTtf/MNISTtf_old/conditional_one_hot/off_manifold/tflib/ops/cond_batchnorm.py | import tflib as lib
import numpy as np
import tensorflow as tf
def Batchnorm(name, axes, inputs, is_training=None, stats_iter=None, update_moving_stats=True, fused=True, labels=None, n_labels=None):
"""conditional batchnorm (dumoulin et al 2016) for BCHW conv filtermaps"""
if axes != [0,2,3]:
raise Ex... | python | MIT | a810f2d77f36ea9cf6993dede958b6f5d458f4b6 | 2026-01-05T07:08:28.063149Z | false |
yaxingwang/MineGAN | https://github.com/yaxingwang/MineGAN/blob/a810f2d77f36ea9cf6993dede958b6f5d458f4b6/MNISTtf/MNISTtf_old/conditional_one_hot/off_manifold/tflib/ops/linear.py | MNISTtf/MNISTtf_old/conditional_one_hot/off_manifold/tflib/ops/linear.py | import tflib as lib
import numpy as np
import tensorflow as tf
_default_weightnorm = False
def enable_default_weightnorm():
global _default_weightnorm
_default_weightnorm = True
def disable_default_weightnorm():
global _default_weightnorm
_default_weightnorm = False
_weights_stdev = None
def set_wei... | python | MIT | a810f2d77f36ea9cf6993dede958b6f5d458f4b6 | 2026-01-05T07:08:28.063149Z | false |
yaxingwang/MineGAN | https://github.com/yaxingwang/MineGAN/blob/a810f2d77f36ea9cf6993dede958b6f5d458f4b6/MNISTtf/MNISTtf_old/conditional_one_hot/miner/useless.py | MNISTtf/MNISTtf_old/conditional_one_hot/miner/useless.py | import os, sys
sys.path.append(os.getcwd())
import time
import matplotlib
matplotlib.use('Agg')
import matplotlib.pyplot as plt
import numpy as np
import sklearn.datasets
import tensorflow as tf
import tflib as lib
import tflib.ops.linear
import tflib.ops.conv2d
import tflib.ops.batchnorm
import tflib.ops.deconv2d
i... | python | MIT | a810f2d77f36ea9cf6993dede958b6f5d458f4b6 | 2026-01-05T07:08:28.063149Z | false |
yaxingwang/MineGAN | https://github.com/yaxingwang/MineGAN/blob/a810f2d77f36ea9cf6993dede958b6f5d458f4b6/MNISTtf/MNISTtf_old/conditional_one_hot/miner/teacher_output_d.py | MNISTtf/MNISTtf_old/conditional_one_hot/miner/teacher_output_d.py |
import os, sys
sys.path.append(os.getcwd())
import numpy as np
import tensorflow as tf
import tflib as lib
import tflib.ops.linear
import tflib.ops.conv2d
import tflib.ops.batchnorm
import tflib.ops.deconv2d
import tflib.save_images
import tflib.mnist
import tflib.plot
import pdb
def teacher_model(noise, fake_dat... | python | MIT | a810f2d77f36ea9cf6993dede958b6f5d458f4b6 | 2026-01-05T07:08:28.063149Z | false |
yaxingwang/MineGAN | https://github.com/yaxingwang/MineGAN/blob/a810f2d77f36ea9cf6993dede958b6f5d458f4b6/MNISTtf/MNISTtf_old/conditional_one_hot/miner/cgan_super_g_d_two_class_unbalance_one_D.py | MNISTtf/MNISTtf_old/conditional_one_hot/miner/cgan_super_g_d_two_class_unbalance_one_D.py | import os, sys
sys.path.append(os.getcwd())
import time
import matplotlib
matplotlib.use('Agg')
import matplotlib.pyplot as plt
import numpy as np
import sklearn.datasets
import tensorflow as tf
import tflib as lib
import tflib.ops.linear
import tflib.ops.conv2d
import tflib.ops.batchnorm
import tflib.ops.deconv2d
i... | python | MIT | a810f2d77f36ea9cf6993dede958b6f5d458f4b6 | 2026-01-05T07:08:28.063149Z | false |
yaxingwang/MineGAN | https://github.com/yaxingwang/MineGAN/blob/a810f2d77f36ea9cf6993dede958b6f5d458f4b6/MNISTtf/MNISTtf_old/conditional_one_hot/miner/teacher.py | MNISTtf/MNISTtf_old/conditional_one_hot/miner/teacher.py |
import os, sys
sys.path.append(os.getcwd())
import numpy as np
import tensorflow as tf
import tflib as lib
import tflib.ops.linear
import tflib.ops.conv2d
import tflib.ops.batchnorm
import tflib.ops.deconv2d
import tflib.save_images
import tflib.mnist
import tflib.plot
import pdb
def teacher_model(noise, fake_data... | python | MIT | a810f2d77f36ea9cf6993dede958b6f5d458f4b6 | 2026-01-05T07:08:28.063149Z | false |
yaxingwang/MineGAN | https://github.com/yaxingwang/MineGAN/blob/a810f2d77f36ea9cf6993dede958b6f5d458f4b6/MNISTtf/MNISTtf_old/conditional_one_hot/miner/cgan_mnist_knowledge_distillation_adaptor_step1.py | MNISTtf/MNISTtf_old/conditional_one_hot/miner/cgan_mnist_knowledge_distillation_adaptor_step1.py | import os, sys
sys.path.append(os.getcwd())
import time
import matplotlib
matplotlib.use('Agg')
import matplotlib.pyplot as plt
import numpy as np
import sklearn.datasets
import tensorflow as tf
import tflib as lib
import tflib.ops.linear
import tflib.ops.conv2d
import tflib.ops.batchnorm
import tflib.ops.deconv2d
i... | python | MIT | a810f2d77f36ea9cf6993dede958b6f5d458f4b6 | 2026-01-05T07:08:28.063149Z | false |
yaxingwang/MineGAN | https://github.com/yaxingwang/MineGAN/blob/a810f2d77f36ea9cf6993dede958b6f5d458f4b6/MNISTtf/MNISTtf_old/conditional_one_hot/miner/cgan_super_g_d_two_class_unbalance_one_D_no_share_latent.py | MNISTtf/MNISTtf_old/conditional_one_hot/miner/cgan_super_g_d_two_class_unbalance_one_D_no_share_latent.py | import os, sys
sys.path.append(os.getcwd())
import time
import matplotlib
matplotlib.use('Agg')
import matplotlib.pyplot as plt
import numpy as np
import sklearn.datasets
import tensorflow as tf
import tflib as lib
import tflib.ops.linear
import tflib.ops.conv2d
import tflib.ops.batchnorm
import tflib.ops.deconv2d
i... | python | MIT | a810f2d77f36ea9cf6993dede958b6f5d458f4b6 | 2026-01-05T07:08:28.063149Z | false |
yaxingwang/MineGAN | https://github.com/yaxingwang/MineGAN/blob/a810f2d77f36ea9cf6993dede958b6f5d458f4b6/MNISTtf/MNISTtf_old/conditional_one_hot/miner/tflib/lsun_label.py | MNISTtf/MNISTtf_old/conditional_one_hot/miner/tflib/lsun_label.py |
from os import listdir
import numpy as np
import scipy.misc
import time
import pdb
Label={'bedroom':0,
'kitchen':1,
'dining_room':2,
'conference_room':3,
'living_room':4,
'bridge':5,
'tower':6,
'classroom':7,
'church_outdoor':8,
'restaurant':9}
def make_g... | python | MIT | a810f2d77f36ea9cf6993dede958b6f5d458f4b6 | 2026-01-05T07:08:28.063149Z | false |
yaxingwang/MineGAN | https://github.com/yaxingwang/MineGAN/blob/a810f2d77f36ea9cf6993dede958b6f5d458f4b6/MNISTtf/MNISTtf_old/conditional_one_hot/miner/tflib/plot.py | MNISTtf/MNISTtf_old/conditional_one_hot/miner/tflib/plot.py | import matplotlib
matplotlib.use('Agg')
import matplotlib.pyplot as plt
import numpy as np
import collections
import time
import cPickle as pickle
_since_beginning = collections.defaultdict(lambda: {})
_since_last_flush = collections.defaultdict(lambda: {})
_iter = [0]
def tick():
_iter[0] += 1
def plot(name, valu... | python | MIT | a810f2d77f36ea9cf6993dede958b6f5d458f4b6 | 2026-01-05T07:08:28.063149Z | false |
yaxingwang/MineGAN | https://github.com/yaxingwang/MineGAN/blob/a810f2d77f36ea9cf6993dede958b6f5d458f4b6/MNISTtf/MNISTtf_old/conditional_one_hot/miner/tflib/mnist_step1.py | MNISTtf/MNISTtf_old/conditional_one_hot/miner/tflib/mnist_step1.py | import numpy
import os
import urllib
import gzip
import cPickle as pickle
import pdb
def mnist_generator(data, batch_size, n_labelled, limit=None, selecting_label = None, bias = None):
images, targets = data
if bias is not None :
images = images[targets!=bias]
targets = targets[targets!=bias]... | python | MIT | a810f2d77f36ea9cf6993dede958b6f5d458f4b6 | 2026-01-05T07:08:28.063149Z | false |
yaxingwang/MineGAN | https://github.com/yaxingwang/MineGAN/blob/a810f2d77f36ea9cf6993dede958b6f5d458f4b6/MNISTtf/MNISTtf_old/conditional_one_hot/miner/tflib/mnist_step2.py | MNISTtf/MNISTtf_old/conditional_one_hot/miner/tflib/mnist_step2.py | import numpy
import os
import urllib
import gzip
import cPickle as pickle
import pdb
import os
from scipy.misc import imsave
def mnist_generator(data, batch_size, n_labelled, limit=None, selecting_label = None):
images, targets = data
#for index, i in enumerate(targets):
# if not os.path.exists('datase... | python | MIT | a810f2d77f36ea9cf6993dede958b6f5d458f4b6 | 2026-01-05T07:08:28.063149Z | false |
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