def test_moments(self):
input_shape = (10, 10, 10, 10)
x_0 = np.zeros(input_shape)
x_1 = np.ones(input_shape)
x_random = np.random.random(input_shape)
th_axes = [0, 2, 3]
tf_axes = [0, 1, 2]
for ip in [x_0, x_1, x_random]:
for axes in [th_axes, tf_axes]:
for keep_dims in [True, False]:
ip_th = KTH.variable(ip)
th_mean, th_var = KCTH.moments(ip_th, axes, keep_dims=keep_dims)
ip_tf = KTF.variable(ip)
tf_mean, tf_var = KCTF.moments(ip_tf, axes, keep_dims=keep_dims)
ip_cntk = KCTK.variable(ip)
cntk_mean, cntk_var = KCNTK.moments(ip_cntk, axes, keep_dims=keep_dims)
th_mean_val = KTH.eval(th_mean)
tf_mean_val = KTF.eval(tf_mean)
cntk_mean_val = KCTK.eval(cntk_mean)
th_var_val = KTH.eval(th_var)
tf_var_val = KTF.eval(tf_var)
cntk_var_val = KCTK.eval(cntk_var)
# absolute tolerance needed when working with zeros
assert_allclose(th_mean_val, tf_mean_val, rtol=1e-4, atol=1e-10)
assert_allclose(th_var_val, tf_var_val, rtol=1e-4, atol=1e-10)
assert_allclose(th_mean_val, cntk_mean_val, rtol=1e-4, atol=1e-10)
assert_allclose(th_var_val, cntk_var_val, rtol=1e-4, atol=1e-10)
def test_moments(self):
input_shape = (10, 10, 10, 10)
x_0 = np.zeros(input_shape)
x_1 = np.ones(input_shape)
x_random = np.random.random(input_shape)
th_axes = [0, 2, 3]
tf_axes = [0, 1, 2]
for ip in [x_0, x_1, x_random]:
for axes in [th_axes, tf_axes]:
for keep_dims in [True, False]:
ip_th = KTH.variable(ip)
th_mean, th_var = KCTH.moments(ip_th,
axes,
keep_dims=keep_dims)
ip_tf = KTF.variable(ip)
tf_mean, tf_var = KCTF.moments(ip_tf,
axes,
keep_dims=keep_dims)
th_mean_val = KTH.eval(th_mean)
tf_mean_val = KTF.eval(tf_mean)
th_var_val = KTH.eval(th_var)
tf_var_val = KTF.eval(tf_var)
assert_allclose(th_mean_val, tf_mean_val, rtol=1e-4)
assert_allclose(th_var_val, tf_var_val, rtol=1e-4)