zirain <******@****.***> 1657592759 +0800

zirain <******@****.***> 1657592759 +0800

    sub: Optional[SubItem] = None
    if PYDANTIC_V2:
        model_config = {"json_schema_serialization_defaults_required": True}


def get_app_client(separate_input_output_schemas: bool = True) -> TestClient:
    app = FastAPI(separate_input_output_schemas=separate_input_output_schemas)

    @app.post("/items/")
    def create_item(item: Item):
        return item

    @app.post("/items-list/")
    def create_item_list(item: List[Item]):

    AbstractTensorHandle* conj_output;
    std::string name = "Conj_Exp_Grad";
    TF_RETURN_IF_ERROR(SafeConj(ctx, exp_.get(), &conj_output, name.c_str()));
    AbstractTensorHandlePtr conj_output_releaser(conj_output);

    name = "Mul_Exp_Grad";
    TF_RETURN_IF_ERROR(
        Mul(ctx, conj_output, grad_outputs[0], &grad_inputs[0], name.c_str()));
    return absl::OkStatus();
  }

	// Output: true
}

func ExampleFields() {
	fmt.Printf("Fields are: %q", bytes.Fields([]byte("  foo bar  baz   ")))
	// Output: Fields are: ["foo" "bar" "baz"]
}

func ExampleFieldsFunc() {
	f := func(c rune) bool {
		return !unicode.IsLetter(c) && !unicode.IsNumber(c)
	}
	fmt.Printf("Fields are: %q", bytes.FieldsFunc([]byte("  foo1;bar2,baz3..."), f))
	// Output: Fields are: ["foo1" "bar2" "baz3"]

auto& kUnknownRank = shape_inference::InferenceContext::kUnknownRank;

// GraphTensor wraps a `TF_Output`, i.e. a pointer to TF_Operation and the index
// into the list of outputs for the operation.
class GraphTensor : public TracingTensorHandle {
 public:
  explicit GraphTensor(TF_Output output, TF_Graph* graph)
      : TracingTensorHandle(kGraph), output_(output), graph_(graph) {}

  tensorflow::DataType DataType() const override {

  sources.reserve(output_tensors.size());
  for (const TapeTensor& output_tensor : output_tensors) {
    // Ownership of `aid` transferred to CallBackwardFunction below.
    Gradient* aid;
    if (output_tensor.GetDType() == tensorflow::DT_VARIANT) {
      // Note: Needs to be zeros rather than ones since there's currently no
      // ones_like for variants.
      aid = output_tensor.ZerosLike();
    } else {

      output_names_vec.push_back(string(output_names[i]));
    }
  }

  // Process control output names.
  std::vector<string> control_output_names_vec;
  if (control_output_names) {
    control_output_names_vec.reserve(ncontrol_outputs);
    for (int i = 0; i < ncontrol_outputs; ++i) {
      control_output_names_vec.push_back(string(control_output_names[i]));
    }
  }

  // Compute body nodes.

				return configWriter.PrintClusterDump(filter, outputFormat)
			default:
				return fmt.Errorf("output format %q not supported", outputFormat)
			}
		},
		ValidArgsFunction: completion.ValidPodsNameArgs(ctx),
	}

	clusterConfigCmd.PersistentFlags().StringVarP(&outputFormat, "output", "o", summaryOutput, "Output format: one of json|yaml|short")

		for len(output) > 0 && (output[0] < want || output[0] != want && len(output[0]) >= 5 && output[0][:5] == want[:5]) {
			if len(output[0]) >= 5 && output[0][:5] == want[:5] {
				t.Errorf("mismatched output:\nhave %s\nwant %s", output[0], want)
				output = output[1:]
				continue Diff
			}
			t.Errorf("unexpected output: %q", output[0])
			output = output[1:]
		}