def cat(g, tensor_list, dim, scale=None, zero_point=None):
tensors = symbolic_helper._unpack_list(tensor_list)
input = tensors[0]
if input not in symbolic_helper._quantized_ops:
return opset9.cat(g, tensor_list, dim)
dim = symbolic_helper._parse_arg(dim, "i")
kwargs = {
"Y_scale_f": tensors[0].node()["Y_scale"],
"Y_zero_point_i": tensors[0].node()["Y_zero_point"],
}
output = g.op("_caffe2::Int8Concat", *tensors, axis_i=dim, **kwargs)
symbolic_helper._quantized_ops.add(output)
return output
def cat(g, tensor_list, dim):
if symbolic_helper._is_packed_list(tensor_list):
return opset9.cat(g, tensor_list, dim)
else:
dim = symbolic_helper._get_const(dim, "i", "dim")
return g.op("ConcatFromSequence", tensor_list, axis_i=dim)