Python disentangle_feature_axis_by_idx Examples

Example #1

 def set_feature_lock(self, event, idx_feature, set_to=None):
     if set_to is None:
         self.feature_lock_status[idx_feature] = np.logical_not(self.feature_lock_status[idx_feature])
     else:
         self.feature_lock_status[idx_feature] = set_to
     self.feature_directoion_disentangled = feature_axis.disentangle_feature_axis_by_idx(
         self.feature_direction, idx_base=np.flatnonzero(self.feature_lock_status))

Example #2

 def __init__(self):
     self.latents = z_sample
     self.feature_direction = feature_direction
     self.feature_lock_status = np.zeros(num_feature).astype('bool')
     self.feature_directoion_disentangled = feature_axis.disentangle_feature_axis_by_idx(
         self.feature_direction,
         idx_base=np.flatnonzero(self.feature_lock_status))

Example #3

File: script_generation_interactive.py Project: mahmud83/transparent_latent_gan

 def __init__(self):
     self.latents = np.random.randn(1, *Gs.input_shapes[0][1:])
     self.feature_direction = feature_direction
     self.feature_lock_status = np.zeros(num_feature).astype('bool')
     self.feature_directoion_disentangled = feature_axis.disentangle_feature_axis_by_idx(
         self.feature_direction, idx_base=np.flatnonzero(self.feature_lock_status))
     img_cur = gen_image(self.latents)
     h_img.set_data(img_cur)
     plt.draw()

Example #4

if not os.path.exists(path_feature_direction):
    os.mkdir(path_feature_direction)

pathfile_feature_direction = os.path.join(
    path_feature_direction,
    'feature_direction_{}.pkl'.format(misc.gen_time_str()))
dict_to_save = {'direction': feature_direction, 'name': y_name}
with open(pathfile_feature_direction, 'wb') as f:
    pickle.dump(dict_to_save, f)

##
""" disentangle correlated feature axis """
pathfile_feature_direction = glob.glob(
    os.path.join(path_feature_direction, 'feature_direction_*.pkl'))[-1]

with open(pathfile_feature_direction, 'rb') as f:
    feature_direction_name = pickle.load(f)

feature_direction = feature_direction_name['direction']
feature_name = np.array(feature_direction_name['name'])

len_z, len_y = feature_direction.shape

feature_direction_disentangled = feature_axis.disentangle_feature_axis_by_idx(
    feature_direction, idx_base=range(len_y // 4), idx_target=None)

feature_axis.plot_feature_cos_sim(feature_direction_disentangled,
                                  feature_name=feature_name)

##

Example #5

File: test_feature_axis_orthogonalize.py Project: mahmud83/transparent_latent_gan

import importlib
import numpy as np
import src.tf_gan.feature_axis as feature_axis

importlib.reload(feature_axis)

vectors = np.random.rand(10, 4)

print(np.sum(vectors**2, axis=0))

vectors_normalized = feature_axis.normalize_feature_axis(vectors)

print(np.sum(vectors_normalized**2, axis=0))

print(
    feature_axis.orthogonalize_one_vector(np.array([1, 0, 0]),
                                          np.array([1, 1, 1])))

print(vectors_normalized)

vectors_orthogonal = feature_axis.orthogonalize_vectors(vectors_normalized)
vectors_disentangled = feature_axis.disentangle_feature_axis_by_idx(
    vectors, idx_base=[0], idx_target=[2, 3])

print(np.dot(vectors_normalized[:, -2], vectors_normalized[:, -1]))
print(np.dot(vectors_orthogonal[:, -2], vectors_orthogonal[:, -1]))

feature_axis.plot_feature_cos_sim(vectors)
feature_axis.plot_feature_cos_sim(vectors_orthogonal)
feature_axis.plot_feature_cos_sim(vectors_disentangled)