def _validate(self, machine, n=10):
N = n * n
z = np.random.uniform(-np.pi, np.pi, size=[n, self.arch['z_dim']])
z = np.cos(z)
z = np.concatenate([z] * n, axis=1)
z = np.reshape(z, [N, -1]).astype(np.float32) # consecutive rows
# y = np.random.randint(1, arch['y_dim'], size=[N, 2])
y = np.asarray(
[
[5, 0, 0], # 5
[9, 0, 0], # 9
[12, 0, 0], # 2
[17, 0, 0], # 7
[19, 0, 0],
[161, 0, 0],
[170, 0, 0],
[170, 16, 0],
[161, 9, 4],
[19, 24, 50]
],
dtype=np.int64)
y = np.concatenate([y] * n, axis=0)
Z = tf.constant(z)
Y = tf.constant(y)
Xh = machine.generate(Z, Y) # 100, 64, 64, 3
Xh = make_png_thumbnail(Xh, n)
return Xh
def _validate(self, machine, n=10):
N = n * n
z = np.random.uniform(-np.pi, np.pi, size=[n, self.arch['z_dim']])
z = np.cos(z)
z = np.concatenate([z] * n, axis=1)
z = np.reshape(z, [N, -1]).astype(np.float32) # consecutive rows
# y = np.random.randint(1, arch['y_dim'], size=[N, 2])
y = np.asarray(
[[5, 0, 0 ], # 5
[9, 0, 0 ], # 9
[12, 0, 0 ], # 2
[17, 0, 0 ], # 7
[19, 0, 0 ],
[161, 0, 0 ],
[170, 0, 0 ],
[170, 16, 0 ],
[161, 9, 4 ],
[19, 24, 50]],
dtype=np.int64)
y = np.concatenate([y] * n, axis=0)
Z = tf.constant(z)
Y = tf.constant(y)
Xh = machine.generate(Z, Y) # 100, 64, 64, 3
Xh = make_png_thumbnail(Xh, n)
return Xh
def _validate(self, machine, n=10):
N = n * n
# same row same z
z = tf.random_normal(shape=[n, self.arch['z_dim']])
z = tf.tile(z, [1, n])
z = tf.reshape(z, [N, -1])
z = tf.Variable(z, trainable=False, dtype=tf.float32)
# same column same y
y = tf.range(0, 10, 1, dtype=tf.int64)
y = tf.reshape(y, [-1,])
y = tf.tile(y, [n,])
Xh = machine.generate(z, y) # 100, 64, 64, 3
Xh = make_png_thumbnail(Xh, n)
return Xh
def _validate(self, machine, n=10):
N = n * n
# same row same z
z = tf.random_normal(shape=[n, self.arch['z_dim']])
z = tf.tile(z, [1, n])
z = tf.reshape(z, [N, -1])
z = tf.Variable(z, trainable=False, dtype=tf.float32)
# same column same y
y = tf.range(0, 10, 1, dtype=tf.int64)
y = tf.reshape(y, [
-1,
])
y = tf.tile(y, [
n,
])
Xh = machine.generate(z, y) # 100, 64, 64, 3
Xh = make_png_thumbnail(Xh, n)
return Xh