def check_type_forward(self, in_types):
n_in = in_types.size()
type_check.expect(2 <= n_in, n_in <= 3)
x_type, w_type = in_types[:2]
type_check.expect(
x_type.dtype.kind == 'f',
w_type.dtype.kind == 'f',
x_type.ndim >= 2,
w_type.ndim == 2,
type_check.prod(x_type.shape[1:]) == w_type.shape[1],
)
if n_in.eval() == 3:
b_type = in_types[2]
type_check.expect(
b_type.dtype == x_type.dtype,
b_type.ndim == 1,
b_type.shape[0] == w_type.shape[0],
)
python类prod()的实例源码
def check_type_forward(self, in_types):
n_in = in_types.size()
type_check.expect(2 <= n_in, n_in <= 3)
x_type, w_type = in_types[:2]
type_check.expect(
x_type.dtype == numpy.float32,
w_type.dtype == numpy.float32,
x_type.ndim >= 2,
w_type.ndim == 2,
type_check.prod(x_type.shape[1:]) == w_type.shape[1],
)
if n_in.eval() == 3:
b_type = in_types[2]
type_check.expect(
b_type.dtype == numpy.float32,
b_type.ndim == 1,
b_type.shape[0] == w_type.shape[0],
)
def check_type_forward(self, in_types):
type_check.expect(
in_types.size() == 1,
)
x_type, = in_types
cnt = _count_unknown_dims(self.shape)
if cnt == 0:
type_check.expect(
type_check.prod(x_type.shape) == type_check.prod(self.shape))
else:
known_size = 1
for s in self.shape:
if s > 0:
known_size *= s
size_var = type_check.Variable(known_size,
'known_size(=%d)' % known_size)
type_check.expect(
type_check.prod(x_type.shape) % size_var == 0)
def check_type_forward(self, in_types):
n_in = in_types.size()
type_check.expect(2 <= n_in, n_in <= 3)
x_type, w_type = in_types[:2]
type_check.expect(
x_type.dtype == numpy.float32,
w_type.dtype == numpy.float32,
x_type.ndim >= 2,
w_type.ndim == 2,
type_check.prod(x_type.shape[1:]) == w_type.shape[1],
)
if n_in.eval() == 3:
b_type = in_types[2]
type_check.expect(
b_type.dtype == numpy.float32,
b_type.ndim == 1,
b_type.shape[0] == w_type.shape[0],
)
def check_type_forward(self, in_types):
n_in = in_types.size()
type_check.expect(2 <= n_in, n_in <= 3)
x_type, w_type = in_types[:2]
type_check.expect(
x_type.dtype == numpy.float32,
w_type.dtype == numpy.float32,
x_type.ndim >= 2,
w_type.ndim == 2,
type_check.prod(x_type.shape[1:]) == w_type.shape[1],
)
if n_in.eval() == 3:
b_type = in_types[2]
type_check.expect(
b_type.dtype == numpy.float32,
b_type.ndim == 1,
b_type.shape[0] == w_type.shape[0],
)
def check_type_forward(self, in_types):
n_in = in_types.size()
type_check.expect(2 <= n_in, n_in <= 3)
x_type, w_type = in_types[:2]
type_check.expect(
x_type.dtype == numpy.float32,
w_type.dtype == numpy.float32,
x_type.ndim >= 2,
w_type.ndim == 2,
type_check.prod(x_type.shape[1:]) == w_type.shape[1],
)
if n_in.eval() == 3:
b_type = in_types[2]
type_check.expect(
b_type.dtype == numpy.float32,
b_type.ndim == 1,
b_type.shape[0] == w_type.shape[0],
)
def check_type_forward(self, in_types):
n_in = in_types.size()
type_check.expect(3 <= n_in, n_in <= 4)
x_type, w_type, g_type = in_types[:3]
type_check.expect(
x_type.dtype.kind == "f",
w_type.dtype.kind == "f",
g_type.dtype.kind == "f",
x_type.ndim >= 2,
w_type.ndim == 2,
g_type.ndim == 2,
type_check.prod(x_type.shape[1:]) == w_type.shape[1],
)
if n_in.eval() == 4:
b_type = in_types[3]
type_check.expect(
b_type.dtype == x_type.dtype,
b_type.ndim == 1,
b_type.shape[0] == w_type.shape[0],
)
def check_type_forward(self, in_types):
n_in = in_types.size()
type_check.expect(2 <= n_in, n_in <= 3)
x_type, w_type = in_types[:2]
type_check.expect(
x_type.dtype == numpy.float32,
w_type.dtype == numpy.float32,
x_type.ndim >= 2,
w_type.ndim == 2,
type_check.prod(x_type.shape[1:]) == w_type.shape[1],
)
if n_in.eval() == 3:
b_type = in_types[2]
type_check.expect(
b_type.dtype == numpy.float32,
b_type.ndim == 1,
b_type.shape[0] == w_type.shape[0],
)
function_binary_linear.py 文件源码
项目：BinaryNetConvolution
作者: rarilurelo
项目源码
文件源码
阅读 31
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def check_type_forward(self, in_types):
n_in = in_types.size()
type_check.expect(2 <= n_in, n_in <= 3)
x_type, w_type = in_types[:2]
type_check.expect(
x_type.dtype == numpy.float32,
w_type.dtype == numpy.float32,
x_type.ndim >= 2,
w_type.ndim == 2,
type_check.prod(x_type.shape[1:]) == w_type.shape[1],
)
if n_in.eval() == 3:
b_type = in_types[2]
type_check.expect(
b_type.dtype == numpy.float32,
b_type.ndim == 1,
b_type.shape[0] == w_type.shape[0],
)
def check_type_forward(self, in_types):
n_in = in_types.size()
type_check.expect(3 <= n_in, n_in <= 4)
x_type, w_type, g_type = in_types[:3]
type_check.expect(
x_type.dtype.kind == "f",
w_type.dtype.kind == "f",
g_type.dtype.kind == "f",
x_type.ndim >= 2,
w_type.ndim == 2,
g_type.ndim == 2,
type_check.prod(x_type.shape[1:]) == w_type.shape[1],
)
if n_in.eval() == 4:
b_type = in_types[3]
type_check.expect(
b_type.dtype == x_type.dtype,
b_type.ndim == 1,
b_type.shape[0] == w_type.shape[0],
)
def check_type_forward(self, in_types):
n_in = in_types.size()
type_check.expect(3 <= n_in, n_in <= 4)
x_type, w_type, g_type = in_types[:3]
type_check.expect(
x_type.dtype.kind == "f",
w_type.dtype.kind == "f",
g_type.dtype.kind == "f",
x_type.ndim >= 2,
w_type.ndim == 2,
g_type.ndim == 2,
type_check.prod(x_type.shape[1:]) == w_type.shape[1],
)
if n_in.eval() == 4:
b_type = in_types[3]
type_check.expect(
b_type.dtype == x_type.dtype,
b_type.ndim == 1,
b_type.shape[0] == w_type.shape[0],
)
def check_type_forward(self, in_types):
n_in = in_types.size()
type_check.expect(2 <= n_in, n_in <= 3)
x_type, w_type = in_types[:2]
type_check.expect(
x_type.dtype == np.float32,
w_type.dtype == np.float32,
x_type.ndim >= 2,
w_type.ndim == 2,
type_check.prod(x_type.shape[1:]) == w_type.shape[1],
)
if n_in.eval() == 3:
b_type = in_types[2]
type_check.expect(
b_type.dtype == np.float32,
b_type.ndim == 1,
b_type.shape[0] == w_type.shape[0],
)
def check_type_forward(self, in_types):
n_in = in_types.size()
type_check.expect(3 <= n_in, n_in <= 4)
x_type, w_type, g_type = in_types[:3]
type_check.expect(
x_type.dtype.kind == "f",
w_type.dtype.kind == "f",
g_type.dtype.kind == "f",
x_type.ndim >= 2,
w_type.ndim == 2,
g_type.ndim == 2,
type_check.prod(x_type.shape[1:]) == w_type.shape[1],
)
if n_in.eval() == 4:
b_type = in_types[3]
type_check.expect(
b_type.dtype == x_type.dtype,
b_type.ndim == 1,
b_type.shape[0] == w_type.shape[0],
)
