def accuracy(y, t):
y, t = as_variable(y), as_variable(t)
pred = y.data.argmax(axis=1).reshape(t.shape)
result = (pred == t.data)
acc = result.mean()
return Variable(as_array(acc))
def dropout(x, dropout_ratio=0.5):
x = as_variable(x)
if kdezero.Config.train:
xp = cuda.get_array_module(x)
mask = xp.random.rand(*x.shape) > dropout_ratio
scale = xp.array(1.0 - dropout_ratio).astype(x.dtype)
y = x * mask / scale
return y
else:
return x
def reshape(x, shape):
if x.shape == shape:
return as_variable(x)
return Reshape(shape)(x)
def broadcast_to(x, shape):
if x.shape == shape:
return as_variable(x)
return BroadcastTo(shape)(x)
def sum_to(x, shape):
if x.shape == shape:
return as_variable(x)
return SumTo(shape)(x)