def test_relu_speed(self):
import time
from EggNetExtension import relu4D
from EggNet import relu
n_runs = 100
# Get large image data set
I, _ = get_uniform_test_image_and_kernel((10, 28, 28, 6),
(3, 3, 6, 12))
print("Code Time")
t_start = time.time()
for i in range(n_runs):
_ = relu4D(I)
t_end = time.time()
t_cext = (t_end - t_start) / n_runs
print("C-Ext ", t_cext)
t_start = time.time()
for i in range(n_runs):
_ = relu(I)
t_end = time.time()
t_py = (t_end - t_start) / n_runs
print("Python ", t_py)
# Speedup is ~2
print("Speedup: ", t_py / t_cext)
def test_relu_ndim(self):
from EggNet import relu
import EggNetExtension
sizes_to_test = [
(100, 100),
(10, 100, 100),
(10, 100, 100, 10),
]
for size in sizes_to_test:
x = np.random.rand(*size).astype(np.float32)
x_relu1 = x.copy()
x_relu2 = relu(x)
if x.ndim == 2:
EggNetExtension.relu2D(x_relu1)
elif x.ndim == 3:
EggNetExtension.relu3D(x_relu1)
elif x.ndim == 4:
EggNetExtension.relu4D(x_relu1)
else:
raise ValueError()
self.assertTrue(
np.allclose(x_relu1, x_relu2, atol=self.NUMERIC_EPS))
def test_int(self):
from EggNet import relu
import EggNetExtension
x1 = np.random.rand(100).astype(dtype=np.int16) * 10 - 5
x2 = x1.copy()
EggNetExtension.relu_int16_t_inplace(x1)
x2 = relu(x2)
np.allclose(x1, x2, atol=self.NUMERIC_EPS)
def __call__(self, *args, **kwargs):
# use the '@' sign to refer to a tensor dot
# calculate z = xW + b
x = args[0]
z = np.matmul(x, self.W) + self.b
if self.activation is None:
return z
elif self.activation is "relu":
# return np.apply_over_axis(relu, z, 1)
return relu(z)
elif self.activation is "softmax":
# return np.apply_over_axis(softmax, z, 1)
return softmax(z)
else:
raise ValueError("Activation of {} is not valid".format(
self.activation))
def __call__(self, input, *args, **kwargs):
x = input
try:
z = conv2d_fast(x, self.kernel, stride=1)
except ImportError as imerror:
print(
"[ERROR]: The Fast C-Extension could not be loaded? Is it installed? Fallback to default python "
"implementation: ", imerror)
z = conv2d(x, self.kernel, stride=1)
if self.use_bias:
z += self.b
if self.activation is None:
return z
elif self.activation is "relu":
return relu(z)
else:
raise ValueError("Activation of {} is not valid".format(
self.activation))