def addmm(g, self, mat1, mat2, beta, alpha):
if _try_get_scalar_type(self):
old_type, self, mat1, mat2 = _try_cast_integer_to_float(g, self, mat1, mat2)
return _cast_to_type(
g, g.op("Gemm", mat1, mat2, self,
beta_f=sym_help._scalar(beta), alpha_f=sym_help._scalar(alpha)), old_type)
else:
return g.op("Gemm", mat1, mat2, self, beta_f=sym_help._scalar(beta), alpha_f=sym_help._scalar(alpha))
def addcmul_symbolic(g, self, tensor1, tensor2, value=1, out=None):
from torch.onnx.symbolic_opset9 import add, mul
if out is not None:
sym_help._unimplemented("addcmul",
"Out parameter is not supported for addcmul")
x = mul(g, tensor1, tensor2)
value = sym_help._maybe_get_scalar(value)
if sym_help._scalar(value) != 1:
value = sym_help._if_scalar_type_as(g, value, x)
if not sym_help._is_value(value):
value = g.op("Constant",
value_t=torch.tensor(value, dtype=torch.float32))
x = mul(g, x, value)
return add(g, self, x)
