def setUp(self):
x = T.IntVariable(1, 'x')
y = T.IntVariable(1, 'y')
z = T.IntVariable(2, 'z')
f = lambda x, y: x == y
self.op1 = T.BoolBinaryOperator(x, y, '==', '!=', f)
self.op2 = T.BoolBinaryOperator(x, z, '==', '!=', f)
def setUp(self):
x = T.IntVariable(1, 'x')
y = T.IntVariable(1, 'y')
f = lambda x, y: (x, y)
self.op1 = T.IntBinaryOperator(7, x, y, '+', f)
self.op2 = T.IntBinaryOperator(8, x, y, '+', f)
self.op3 = T.IntBinaryOperator(9, x, y, '+', f)
self.op4 = T.IntBinaryOperator(7, x, y, '+', f, True)
self.op5 = T.IntBinaryOperator(8, x, y, '+', f, True)
self.op6 = T.IntBinaryOperator(9, x, y, '+', f, True)
def check_type_forward(self, in_types):
type_check.expect(in_types.size() == 1)
x_type, = in_types
type_check.expect(
x_type.dtype == numpy.float32,
x_type.ndim == 2,
x_type.shape[1] == type_check.IntVariable(self.W.shape[1],
'W.shape[1]'),
)
def check_type_backward(self, in_types, out_types):
type_check.expect(
in_types.size() == 1,
out_types.size() == 1,
)
x_type, = in_types
y_type, = out_types
type_check.expect(
y_type.dtype == numpy.float32,
y_type.ndim == 2,
y_type.shape[0] == x_type.shape[0],
y_type.shape[1] == type_check.IntVariable(self.W.shape[1],
'W.shape[1]'),
)
def check_type_forward(self, in_types):
type_check.expect(in_types.size() > 0)
type_check.expect(
in_types[0].ndim > type_check.IntVariable(self.axis, 'axis'))
ndim = in_types[0].ndim.eval()
for i in range(1, in_types.size().eval()):
type_check.expect(
in_types[0].dtype == in_types[i].dtype,
in_types[0].ndim == in_types[i].ndim,
)
for d in range(0, ndim):
if d == self.axis:
continue
type_check.expect(in_types[0].shape[d] == in_types[i].shape[d])
def setUp(self):
self.x = T.IntVariable(1, 'x')
self.y = T.IntVariable(1, 'y')
def setUp(self):
x = T.IntVariable(1, 'x')
f = lambda x: (x, )
self.op1 = T.IntUnaryOperator(8, x, '-', f)
self.op2 = T.IntUnaryOperator(9, x, '-', f)
def setUp(self):
self.x = T.IntVariable(10, 'x')