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fix typo #34

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fix typo #34

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2 changes: 1 addition & 1 deletion dezero/functions.py
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Original file line number Diff line number Diff line change
Expand Up @@ -595,7 +595,7 @@ def backward(self, gy):
return gx, ggamma, gbeta


def batch_nrom(x, gamma, beta, mean, var, decay=0.9, eps=2e-5):
def batch_norm(x, gamma, beta, mean, var, decay=0.9, eps=2e-5):
return BatchNorm(mean, var, decay, eps)(x, gamma, beta)


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2 changes: 1 addition & 1 deletion dezero/layers.py
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Original file line number Diff line number Diff line change
Expand Up @@ -327,5 +327,5 @@ def _init_params(self, x):
def __call__(self, x):
if self.avg_mean.data is None:
self._init_params(x)
return F.batch_nrom(x, self.gamma, self.beta, self.avg_mean.data,
return F.batch_norm(x, self.gamma, self.beta, self.avg_mean.data,
self.avg_var.data)
32 changes: 16 additions & 16 deletions tests/gpu/gpu_test_batchnorm.py
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Original file line number Diff line number Diff line change
Expand Up @@ -26,39 +26,39 @@ def test_type1(self):
N, C = 8, 3
x, gamma, beta, mean, var = get_params(N, C)
with dezero.test_mode():
y = F.batch_nrom(x, gamma, beta, mean, var)
y = F.batch_norm(x, gamma, beta, mean, var)
self.assertTrue(y.data.dtype == np.float32)

def test_forward1(self):
N, C = 8, 1
x, gamma, beta, mean, var = get_params(N, C)
cy = CF.fixed_batch_normalization(x, gamma, beta, mean, var)
with dezero.test_mode():
y = F.batch_nrom(x, gamma, beta, mean, var)
y = F.batch_norm(x, gamma, beta, mean, var)
self.assertTrue(array_allclose(y.data, cy.data))

def test_forward2(self):
N, C = 1, 10
x, gamma, beta, mean, var = get_params(N, C)
cy = CF.fixed_batch_normalization(x, gamma, beta, mean, var)
with dezero.test_mode():
y = F.batch_nrom(x, gamma, beta, mean, var)
y = F.batch_norm(x, gamma, beta, mean, var)
self.assertTrue(array_allclose(y.data, cy.data))

def test_forward3(self):
N, C = 20, 10
x, gamma, beta, mean, var = get_params(N, C)
cy = CF.fixed_batch_normalization(x, gamma, beta, mean, var)
with dezero.test_mode():
y = F.batch_nrom(x, gamma, beta, mean, var)
y = F.batch_norm(x, gamma, beta, mean, var)
self.assertTrue(array_allclose(y.data, cy.data))

def test_forward4(self):
N, C, H, W = 20, 10, 5, 5
x, gamma, beta, mean, var = get_params(N, C, H, W)
cy = CF.fixed_batch_normalization(x, gamma, beta, mean, var)
with dezero.test_mode():
y = F.batch_nrom(x, gamma, beta, mean, var)
y = F.batch_norm(x, gamma, beta, mean, var)
self.assertTrue(array_allclose(y.data, cy.data))


Expand All @@ -69,71 +69,71 @@ class TestBatchNorm(unittest.TestCase):
def test_type1(self):
N, C = 8, 3
x, gamma, beta, mean, var = get_params(N, C)
y = F.batch_nrom(x, gamma, beta, mean, var)
y = F.batch_norm(x, gamma, beta, mean, var)
self.assertTrue(y.data.dtype == np.float32)

def test_forward1(self):
N, C = 8, 1
x, gamma, beta, mean, var = get_params(N, C)
cy = CF.batch_normalization(x, gamma, beta, running_mean=mean, running_var=var)
y = F.batch_nrom(x, gamma, beta, mean, var)
y = F.batch_norm(x, gamma, beta, mean, var)
self.assertTrue(array_allclose(y.data, cy.data))

def test_forward2(self):
N, C = 1, 10
x, gamma, beta, mean, var = get_params(N, C)
cy = CF.batch_normalization(x, gamma, beta)
y = F.batch_nrom(x, gamma, beta, mean, var)
y = F.batch_norm(x, gamma, beta, mean, var)
self.assertTrue(array_allclose(y.data, cy.data))

def test_forward3(self):
N, C = 20, 10
x, gamma, beta, mean, var = get_params(N, C)
cy = CF.batch_normalization(x, gamma, beta)
y = F.batch_nrom(x, gamma, beta, mean, var)
y = F.batch_norm(x, gamma, beta, mean, var)
self.assertTrue(array_allclose(y.data, cy.data))

def test_forward4(self):
N, C, H, W = 20, 10, 5, 5
x, gamma, beta, mean, var = get_params(N, C, H, W)
cy = CF.batch_normalization(x, gamma, beta)
y = F.batch_nrom(x, gamma, beta, mean, var)
y = F.batch_norm(x, gamma, beta, mean, var)
self.assertTrue(array_allclose(y.data, cy.data))

def test_backward1(self):
N, C = 8, 3
x, gamma, beta, mean, var = get_params(N, C, dtype=np.float64)
f = lambda x: F.batch_nrom(x, gamma, beta, mean, var)
f = lambda x: F.batch_norm(x, gamma, beta, mean, var)
self.assertTrue(gradient_check(f, x))

def test_backward2(self):
N, C = 8, 3
x, gamma, beta, mean, var = get_params(N, C, dtype=np.float64)
f = lambda gamma: F.batch_nrom(x, gamma, beta, mean, var)
f = lambda gamma: F.batch_norm(x, gamma, beta, mean, var)
self.assertTrue(gradient_check(f, gamma))

def test_backward3(self):
N, C = 8, 3
x, gamma, beta, mean, var = get_params(N, C, dtype=np.float64)
f = lambda beta: F.batch_nrom(x, gamma, beta, mean, var)
f = lambda beta: F.batch_norm(x, gamma, beta, mean, var)
self.assertTrue(gradient_check(f, beta))

def test_backward4(self):
params = 10, 20, 5, 5
x, gamma, beta, mean, var = get_params(*params, dtype=np.float64)
f = lambda x: F.batch_nrom(x, gamma, beta, mean, var)
f = lambda x: F.batch_norm(x, gamma, beta, mean, var)
self.assertTrue(gradient_check(f, x))

def test_backward5(self):
params = 10, 20, 5, 5
x, gamma, beta, mean, var = get_params(*params, dtype=np.float64)
f = lambda gamma: F.batch_nrom(x, gamma, beta, mean, var)
f = lambda gamma: F.batch_norm(x, gamma, beta, mean, var)
self.assertTrue(gradient_check(f, gamma))

def test_backward6(self):
params = 10, 20, 5, 5
x, gamma, beta, mean, var = get_params(*params, dtype=np.float64)
f = lambda beta: F.batch_nrom(x, gamma, beta, mean, var)
f = lambda beta: F.batch_norm(x, gamma, beta, mean, var)
self.assertTrue(gradient_check(f, beta))


Expand Down
32 changes: 16 additions & 16 deletions tests/test_batchnorm.py
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Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -26,39 +26,39 @@ def test_type1(self):
N, C = 8, 3
x, gamma, beta, mean, var = get_params(N, C)
with dezero.test_mode():
y = F.batch_nrom(x, gamma, beta, mean, var)
y = F.batch_norm(x, gamma, beta, mean, var)
self.assertTrue(y.data.dtype == np.float32)

def test_forward1(self):
N, C = 8, 1
x, gamma, beta, mean, var = get_params(N, C)
cy = CF.fixed_batch_normalization(x, gamma, beta, mean, var)
with dezero.test_mode():
y = F.batch_nrom(x, gamma, beta, mean, var)
y = F.batch_norm(x, gamma, beta, mean, var)
self.assertTrue(array_allclose(y.data, cy.data))

def test_forward2(self):
N, C = 1, 10
x, gamma, beta, mean, var = get_params(N, C)
cy = CF.fixed_batch_normalization(x, gamma, beta, mean, var)
with dezero.test_mode():
y = F.batch_nrom(x, gamma, beta, mean, var)
y = F.batch_norm(x, gamma, beta, mean, var)
self.assertTrue(array_allclose(y.data, cy.data))

def test_forward3(self):
N, C = 20, 10
x, gamma, beta, mean, var = get_params(N, C)
cy = CF.fixed_batch_normalization(x, gamma, beta, mean, var)
with dezero.test_mode():
y = F.batch_nrom(x, gamma, beta, mean, var)
y = F.batch_norm(x, gamma, beta, mean, var)
self.assertTrue(array_allclose(y.data, cy.data))

def test_forward4(self):
N, C, H, W = 20, 10, 5, 5
x, gamma, beta, mean, var = get_params(N, C, H, W)
cy = CF.fixed_batch_normalization(x, gamma, beta, mean, var)
with dezero.test_mode():
y = F.batch_nrom(x, gamma, beta, mean, var)
y = F.batch_norm(x, gamma, beta, mean, var)
self.assertTrue(array_allclose(y.data, cy.data))


Expand All @@ -69,35 +69,35 @@ class TestBatchNorm(unittest.TestCase):
def test_type1(self):
N, C = 8, 3
x, gamma, beta, mean, var = get_params(N, C)
y = F.batch_nrom(x, gamma, beta, mean, var)
y = F.batch_norm(x, gamma, beta, mean, var)
self.assertTrue(y.data.dtype == np.float32)

def test_forward1(self):
N, C = 8, 1
x, gamma, beta, mean, var = get_params(N, C)
cy = CF.batch_normalization(x, gamma, beta, running_mean=mean, running_var=var)
y = F.batch_nrom(x, gamma, beta, mean, var)
y = F.batch_norm(x, gamma, beta, mean, var)
self.assertTrue(array_allclose(y.data, cy.data))

def test_forward2(self):
N, C = 1, 10
x, gamma, beta, mean, var = get_params(N, C)
cy = CF.batch_normalization(x, gamma, beta)
y = F.batch_nrom(x, gamma, beta, mean, var)
y = F.batch_norm(x, gamma, beta, mean, var)
self.assertTrue(array_allclose(y.data, cy.data))

def test_forward3(self):
N, C = 20, 10
x, gamma, beta, mean, var = get_params(N, C)
cy = CF.batch_normalization(x, gamma, beta)
y = F.batch_nrom(x, gamma, beta, mean, var)
y = F.batch_norm(x, gamma, beta, mean, var)
self.assertTrue(array_allclose(y.data, cy.data))

def test_forward4(self):
N, C, H, W = 20, 10, 5, 5
x, gamma, beta, mean, var = get_params(N, C, H, W)
cy = CF.batch_normalization(x, gamma, beta)
y = F.batch_nrom(x, gamma, beta, mean, var)
y = F.batch_norm(x, gamma, beta, mean, var)
self.assertTrue(array_allclose(y.data, cy.data))

def test_forward5(self):
Expand Down Expand Up @@ -130,37 +130,37 @@ def test_forward6(self):
def test_backward1(self):
N, C = 8, 3
x, gamma, beta, mean, var = get_params(N, C, dtype=np.float64)
f = lambda x: F.batch_nrom(x, gamma, beta, mean, var)
f = lambda x: F.batch_norm(x, gamma, beta, mean, var)
self.assertTrue(gradient_check(f, x))

def test_backward2(self):
N, C = 8, 3
x, gamma, beta, mean, var = get_params(N, C, dtype=np.float64)
f = lambda gamma: F.batch_nrom(x, gamma, beta, mean, var)
f = lambda gamma: F.batch_norm(x, gamma, beta, mean, var)
self.assertTrue(gradient_check(f, gamma))

def test_backward3(self):
N, C = 8, 3
x, gamma, beta, mean, var = get_params(N, C, dtype=np.float64)
f = lambda beta: F.batch_nrom(x, gamma, beta, mean, var)
f = lambda beta: F.batch_norm(x, gamma, beta, mean, var)
self.assertTrue(gradient_check(f, beta))

def test_backward4(self):
params = 10, 20, 5, 5
x, gamma, beta, mean, var = get_params(*params, dtype=np.float64)
f = lambda x: F.batch_nrom(x, gamma, beta, mean, var)
f = lambda x: F.batch_norm(x, gamma, beta, mean, var)
self.assertTrue(gradient_check(f, x))

def test_backward5(self):
params = 10, 20, 5, 5
x, gamma, beta, mean, var = get_params(*params, dtype=np.float64)
f = lambda gamma: F.batch_nrom(x, gamma, beta, mean, var)
f = lambda gamma: F.batch_norm(x, gamma, beta, mean, var)
self.assertTrue(gradient_check(f, gamma))

def test_backward6(self):
params = 10, 20, 5, 5
x, gamma, beta, mean, var = get_params(*params, dtype=np.float64)
f = lambda beta: F.batch_nrom(x, gamma, beta, mean, var)
f = lambda beta: F.batch_norm(x, gamma, beta, mean, var)
self.assertTrue(gradient_check(f, beta))


Expand Down