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)