# Usar los códigos de estado antiguos 403 para errores de autenticación { #use-old-403-authentication-error-status-codes }

Antes de FastAPI versión `0.122.0`, cuando las utilidades de seguridad integradas devolvían un error al cliente después de una autenticación fallida, usaban el código de estado HTTP `403 Forbidden`.

# 响应 - 更改状态码

你可能之前已经了解到，你可以设置默认的[响应状态码](../tutorial/response-status-code.md){.internal-link target=_blank}。

但在某些情况下，你需要返回一个不同于默认值的状态码。

## 使用场景

例如，假设你想默认返回一个HTTP状态码为“OK”`200`。

但如果数据不存在，你想创建它，并返回一个HTTP状态码为“CREATED”`201`。

但你仍然希望能够使用`response_model`过滤和转换你返回的数据。

对于这些情况，你可以使用一个`Response`参数。

## 使用 `Response` 参数

你可以在你的*路径操作函数*中声明一个`Response`类型的参数（就像你可以为cookies和头部做的那样）。

然后你可以在这个*临时*响应对象中设置`status_code`。

      TF_NewStatus(), TF_DeleteStatus);
  int assign = TF_OpIsStateful("AssignAddVariableOp", status.get());
  ASSERT_EQ(TF_OK, TF_GetCode(status.get())) << TF_Message(status.get());
  EXPECT_EQ(assign, 1);
  int id = TF_OpIsStateful("Identity", status.get());
  ASSERT_EQ(TF_OK, TF_GetCode(status.get())) << TF_Message(status.get());
  EXPECT_EQ(id, 0);
}

class ShapeInferenceTest : public ::testing::Test {
 protected:

  if (TF_GetCode(status) != TF_OK) return;
  if (!grad) return;

  status->status = g->graph.AddFunctionDef(grad->record->fdef(),
                                           grad->record->stack_traces());
  if (TF_GetCode(status) != TF_OK) return;

  tensorflow::GradientDef gdef;
  gdef.set_function_name(func->record->fdef().signature().name());
  gdef.set_gradient_func(grad->record->fdef().signature().name());

xmlns="http://s3.amazonaws.com/doc/2006-03-01/"><Role></Role><Rule><Status>Enabled</Status><DeleteMarkerReplication><Status>Disabled</Status></DeleteMarkerReplication><DeleteReplication><Status>Disabled</Status></DeleteReplication><Prefix>key-prefix</Prefix><Destination><Bucket>arn:minio:replication:::destinationbucket</Bucket></Destination></Rule><Rule><Status>Enabled</Status><Priority>3</Priority><DeleteMarkerReplication><Status>Disabled</Status></DeleteMarkerReplication><DeleteReplication><Status>Disab...

}

void TF_TensorFromProto(const TF_Buffer* from, TF_Tensor* to,
                        TF_Status* status) {
  TF_SetStatus(status, TF_OK, "");
  tensorflow::TensorProto from_tensor_proto;
  status->status = BufferToMessage(from, &from_tensor_proto);
  if (!status->status.ok()) {
    return;
  }
  status->status =
      tensorflow::down_cast<tensorflow::TensorInterface*>(to->tensor)
          ->FromProto(from_tensor_proto);

		expStatus: replication.Pending,
	},
	{ // 3. replication status for one target - incorrect format
		name:      "replication status for one target",
		rs:        ReplicationState{ReplicationStatusInternal: "arn1=PENDING"},
		expStatus: replication.StatusType(""),
	},
	{ // 4. replication status for 3 targets, one of them failed
		name: "replication status for 3 targets - one failed",
		rs: ReplicationState{

			stats[arn] = &BucketReplicationStat{
				Failed:          fstats.toMetric(),
				FailStats:       fstats,
				ReplicatedSize:  stat.ReplicatedSize + oldst.ReplicatedSize,
				ReplicatedCount: stat.ReplicatedCount + oldst.ReplicatedCount,
				Latency:         stat.Latency.merge(oldst.Latency),
				XferRateLrg:     &lrg,
				XferRateSml:     &sml,
			}
			totReplicatedSize += stat.ReplicatedSize

xmlns="http://s3.amazonaws.com/doc/2006-03-01/"><Role>arn:aws:iam::AcctID:role/role-name</Role><Rule><Status>Enabled</Status><DeleteMarkerReplication><Status>Disabled</Status></DeleteMarkerReplication><DeleteReplication><Status>Disabled</Status></DeleteReplication><Prefix>key-prefix</Prefix><Destination><Bucket>arn:aws:s3:::destinationbucket</Bucket></Destination><SourceSelectionCriteria><ReplicaModifications><Status>Enabled</Status></ReplicaModifications></SourceSelectionCriteria></Rule></ReplicationConfiguration>`,...

  status->status = c.construction_status();
  if (!status->status.ok()) return;

  if (op_reg_data->shape_inference_fn == nullptr) {
    status->status =
        InvalidArgument("No shape inference function exists for op '",
                        node_def.op(), "', did you forget to define it?");
    return;
  }

  status->status = c.Run(op_reg_data->shape_inference_fn);