ImageUrl string
	}

	DB.Migrator().DropTable(&HNPost{}, &EngadgetPost{})
	if err := DB.Migrator().AutoMigrate(&HNPost{}, &EngadgetPost{}); err != nil {
		t.Fatalf("failed to auto migrate, got error: %v", err)
	}

	for _, name := range []string{"author_id", "author_name", "author_email"} {
		if !DB.Migrator().HasColumn(&EngadgetPost{}, name) {
			t.Errorf("should has prefixed column %v", name)
		}

Era `upper`? O era `uppercase`? `first_uppercase`? `capitalize`?

Luego lo intentas con el viejo amigo de los programadores, el auto-completado del editor.

Escribes el primer parámetro de la función `first_name`, luego un punto (`.`) y luego presionas `Ctrl+Space` para iniciar el auto-completado.

Tristemente, no obtienes nada útil:

<img src="https://fastapi.tiangolo.com/img/python-types/image01.png">

### Añade tipos

        new BundleReader(Env::Default(), filename /* prefix to a V2 ckpt */));
    if (!v2_reader_->status().ok()) {
      tsl::Set_TF_Status_from_Status(status, v2_reader_->status());
      return;
    }
    auto result = BuildV2VarMaps();
    var_to_shape_map_.swap(result.first);
    var_to_data_type_map_.swap(result.second);
  } else {
    reader_.reset(new TensorSliceReader(filename));
    if (!reader_->status().ok()) {

    }

	}

	if name := DB.Dialector.Name(); name == "postgres" {
		t.Skip("skip postgres due to it only allow unique constraint matching given keys")
	}

	DB.Migrator().DropTable(&Blog{}, &Tag{}, "blog_tags", "locale_blog_tags", "shared_blog_tags")
	if err := DB.AutoMigrate(&Blog{}, &Tag{}); err != nil {
		t.Fatalf("Failed to auto migrate, got error: %v", err)
	}

                        top: containerTop,
                        right: 'auto',
                        left: 9
                    });
                } else {
                    this.container.css({
                        top: containerTop,
                        right: containerRight,
                        left: 'auto'
                    });
                }

//
// The code under test will have created streamz counters like this:
// auto* streamz = tensorflow::monitoring::Counter<1>::New("name",
// "description", "label");
// and then incremented that counter for various values of label:
// streamz->GetCell("label-value")->IncrementBy(1);
//
// The test code can then read and test the value of that counter:
//
// auto* reader = TFE_MonitoringNewCounterReader("name");
// test();

Sie könnten beispielsweise ein „Auto“ oder einen „Blog-Beitrag“ identifizieren.

Anschließend könnten Sie Berechtigungen für diese Entität hinzufügen, etwa „Fahren“ (für das Auto) oder „Bearbeiten“ (für den Blog).

  *result = outputs[0];
  return absl::OkStatus();
}
}  // namespace

absl::Status GradientRegistry::Register(
    const string& op_name, GradientFunctionFactory gradient_function_factory) {
  auto iter = registry_.find(op_name);
  if (iter != registry_.end()) {
    const string error_msg = "Gradient already exists for op: " + op_name + ".";
    return errors::AlreadyExists(error_msg);
  }

  if (dlMTensor->deleter != nullptr) {
    dlMTensor->deleter(dlMTensor);
  }
}

void* TFE_HandleToDLPack(TFE_TensorHandle* h, TF_Status* status) {
  auto tf_dlm_context = GetDlContext(h, status);
  if (!status->status.ok()) {
    return nullptr;
  }

  auto* tf_dlm_data = TFE_TensorHandleDevicePointer(h, status);
  if (!status->status.ok()) {
    return nullptr;
  }