我们从Python开源项目中，提取了以下7个代码示例，用于说明如何使用chainer.utils.type_check.eval()。
def check_type_forward(self, in_types): n_in = in_types.size() type_check.expect(3 <= n_in, n_in <= 4) x_type = in_types[0] v_type = in_types[1] g_type = in_types[2] type_check.expect( x_type.dtype.kind == "f", v_type.dtype.kind == "f", g_type.dtype.kind == "f", x_type.ndim == 4, v_type.ndim == 4, g_type.ndim == 4, x_type.shape[1] == v_type.shape[1], ) if type_check.eval(n_in) == 4: b_type = in_types[3] type_check.expect( b_type.dtype == x_type.dtype, b_type.ndim == 1, b_type.shape[0] == v_type.shape[0], )
def check_type_forward(self, in_types): n_in = in_types.size() type_check.expect(2 <= n_in, n_in <= 4) x_type = in_types[0] v_type = in_types[1] g_type = in_types[1] type_check.expect( x_type.dtype.kind == "f", v_type.dtype.kind == "f", g_type.dtype.kind == "f", x_type.ndim == self.ndim + 2, v_type.ndim == self.ndim + 2, g_type.ndim == self.ndim + 2, x_type.shape[1] == v_type.shape[1], ) if type_check.eval(n_in) == 4: b_type = in_types[3] type_check.expect( b_type.dtype == x_type.dtype, b_type.ndim == 1, b_type.shape[0] == v_type.shape[0], )
def check_type_forward(self, in_types): n_in = type_check.eval(in_types.size()) if n_in != 3 and n_in != 5: raise type_check.InvalidType( '%s or %s' % (in_types.size() == 3, in_types.size() == 5), '%s == %s' % (in_types.size(), n_in)) x_type, gamma_type, beta_type = in_types[:3] M = type_check.eval(gamma_type.ndim) type_check.expect( x_type.dtype.kind == 'f', x_type.ndim >= gamma_type.ndim + 1, x_type.shape[1:1 + M] == gamma_type.shape, # TODO(beam2d): Check shape gamma_type.dtype == x_type.dtype, beta_type.dtype == x_type.dtype, gamma_type.shape == beta_type.shape, ) if len(in_types) == 5: mean_type, var_type = in_types[3:] type_check.expect( mean_type.dtype == x_type.dtype, mean_type.shape == gamma_type.shape, var_type.dtype == x_type.dtype, var_type.shape == gamma_type.shape, )
def check_type_forward(self, in_types): n_in = in_types.size() type_check.expect(2 <= n_in, n_in <= 3) x_type = in_types[0] w_type = in_types[1] type_check.expect( x_type.dtype.kind == 'f', w_type.dtype.kind == 'f', x_type.ndim == 4, w_type.ndim == 5, x_type.shape[1] == w_type.shape[0] * w_type.shape[2], ) if type_check.eval(n_in) == 3: b_type = in_types[2] type_check.expect( b_type.dtype == x_type.dtype, b_type.ndim == 2, b_type.shape[0] == w_type.shape[0], b_type.shape[1] == w_type.shape[1], )
def check_type_forward(self, in_types): n_in = type_check.eval(in_types.size()) if n_in != 3: raise type_check.InvalidType( '%s == %s' % (in_types.size(), n_in)) x_type, gamma_type, beta_type = in_types[:3] M = type_check.eval(gamma_type.ndim) type_check.expect( x_type.dtype.kind == 'f', x_type.ndim >= gamma_type.ndim + 1, x_type.shape[1:1 + M] == gamma_type.shape, gamma_type.dtype == x_type.dtype, beta_type.dtype == x_type.dtype, gamma_type.shape == beta_type.shape, )
def check_type_forward(self, in_types): n_in = in_types.size() type_check.expect(4 <= n_in, n_in <= 5) x_type = in_types[0] w_type = in_types[1] b_type = in_types[2] ct_type = in_types[3] type_check.expect( x_type.dtype.kind == "f", w_type.dtype.kind == "f", b_type.dtype.kind == "f", x_type.ndim == 3, w_type.ndim == 2, b_type.ndim == 1, b_type.shape[0] * 3 == w_type.shape[0] * 2, ct_type.dtype == x_type.dtype, ct_type.ndim == 2, ct_type.shape[1] == x_type.shape[1], ) if type_check.eval(n_in) == 5: mask_x_type = in_types[4] type_check.expect( mask_x_type.dtype == x_type.dtype, mask_x_type.ndim == 2, mask_x_type.shape[1] == x_type.shape[1], ) # x: (batchsize, feature_dimension, seq_length)
