// Non-quantizable ops: quantize/dequantize ops
constexpr absl::string_view kModuleCompositeSameScale = R"mlir(
  module {
    func.func @same_scale_after_composite() -> tensor<3x1xf32> {

}

// newSequencer returns a sequencer that allows concurrent tasks up to maxWeight
// and writes tasks' output to out and err.
func newSequencer(maxWeight int64, out, err io.Writer) *sequencer {
	sem := semaphore.NewWeighted(maxWeight)
	prev := make(chan *reporterState, 1)
	prev <- &reporterState{out: out, err: err}
	return &sequencer{
		maxWeight: maxWeight,
		sem:       sem,
		prev:      prev,
	}
}

        """

        librarySourceFile.replace("cout << message", "cout << PREFIX << message")

        def libDefsHeader = file("library/src/main/headers/local_defs.h")
        libDefsHeader << """
            #define PREFIX "LOG: "
        """

        then:
        succeeds installApp
        install.exec().out == "LOG: [info] hello world"

        when:

  constexpr absl::string_view kXlaCallModuleOpWithQuantizationMethodAttr =
      R"mlir(
    func.func @main(%arg0: tensor<1x1x3xf32>, %arg1: tensor<3x4xf32>) -> tensor<1x1x4xf32> {

  %0 = "tf.UniformQuantizedConvolution"(
    %quant_input, %quant_filter, %input_scale, %input_zp,
    %filter_scale, %filter_zp, %accum_scale, %accum_zp
  ) {
    Tin = "tfdtype$DT_QINT8", Tout = "tfdtype$DT_QINT32",
    attr_map = "", batch_group_count = 1 : i64,
    dimension_numbers = "\10\03\1A\02\01\02 \02(\032\02\00\01@\03J\02\01\02",
    explicit_padding = [], feature_group_count = 1 : i64, lhs_dilation = [1, 1],

    %1 = "tf.Identity"(%arg1) {device = ""} : (tensor<100352x10xf32>) -> tensor<100352x10xf32>
    %2 = "tf.XlaCallModule"(%0, %1) <{
        Sout = [#tf_type.shape<?x10>], dim_args_spec = [],
        disabled_checks = [], function_list = [],
        has_token_input_output = false, module = "", platforms = [],
        version = 5 : i64
    }> {

    std::cout << "\tname: '"
              << (output_tensor->name() ? output_tensor->name()->str()
                                        : "<<unnamed>>")
              << "' buffer: " << buffer;
    if (loc) std::cout << llvm::formatv(" {0}", loc(id)).str();
    std::cout << '\n';
  };

  // For every subgraph print out the name (if available), each result's output

	_HW_NCPU       = 3
	_HW_PAGESIZE   = 7
	_HW_NCPUONLINE = 16
)

func sysctlInt(mib []uint32) (int32, bool) {
	var out int32
	nout := unsafe.Sizeof(out)
	ret := sysctl(&mib[0], uint32(len(mib)), (*byte)(unsafe.Pointer(&out)), &nout, nil, 0)
	if ret < 0 {
		return 0, false
	}
	return out, true
}

func getncpu() int32 {
	if n, ok := sysctlInt([]uint32{_CTL_HW, _HW_NCPUONLINE}); ok {
		return int32(n)
	}

            int main () {
              #ifdef ENABLE_GREETING
              std::cout << "Hello!";
              #endif
              return 0;
            }
        """

        when:
        run "mainExecutable"

        then:
        def executable = executable("build/exe/main/main")
        executable.exec().out == "Hello!"
    }

    @ToBeFixedForConfigurationCache

# Développement - Contribuer

Tout d'abord, vous voudrez peut-être voir les moyens de base pour [aider FastAPI et obtenir de l'aide](help-fastapi.md){.internal-link target=_blank}.

## Développement

Si vous avez déjà cloné le dépôt et que vous savez que vous devez vous plonger dans le code, voici quelques directives pour mettre en place votre environnement.

### Environnement virtuel avec `venv`