// RUN: flatbuffer_translate -mlir-to-tflite-flatbuffer %s -o - | flatbuffer_translate --tflite-flatbuffer-to-mlir - -o - | FileCheck %s
// Ensure constants roundtrip exactly

func.func @bool() -> tensor<4xi1> {
  // CHECK-LABEL: @bool
  // CHECK: value = dense<[false, true, true, false]> : tensor<4xi1>
  %0 = "tfl.pseudo_const"() { value = dense<[false, true, true, false]> : tensor<4xi1> } : () -> tensor<4xi1>
  func.return %0 : tensor<4xi1>
}

  // the tensors with known names.
  std::string serialized_quant_stats = "";

  // A bitmask to encode support for reduced precision inference in the model.
  tflite::optimize::ReducedPrecisionSupport support_mask =
      tflite::optimize::ReducedPrecisionSupport::None;

  // Whether to run the passes to propagate the quantization parameters and
  // graph rewrites. Returns false if the inference_type is DT_FLOAT or

// RUN: flatbuffer_translate -mlir-to-tflite-flatbuffer %s -o - | flatbuffer_translate --tflite-flatbuffer-to-mlir - -o - | FileCheck %s
// Ensure lstm roundtrip exactly

#include "tensorflow/compiler/mlir/lite/experimental/common/outline_operations.h"
#include "tensorflow/compiler/mlir/lite/experimental/tac/common/subgraph.h"
#include "tensorflow/compiler/mlir/lite/experimental/tac/common/targets.h"
#include "tensorflow/compiler/mlir/lite/experimental/tac/common/utils.h"
#include "tensorflow/compiler/mlir/lite/experimental/tac/transforms/passes.h"

		t.Errorf("failed to find created record, got error: %v, result: %+v", err, result4)
	}
}

// only sqlite, postgres, sqlserver support returning
func TestUpdateReturning(t *testing.T) {
	if DB.Dialector.Name() != "sqlite" && DB.Dialector.Name() != "postgres" && DB.Dialector.Name() != "sqlserver" {
		return
	}

	users := []*User{
		GetUser("update-returning-1", Config{}),

#include "mlir/Transforms/Passes.h"  // from @llvm-project
#include "tensorflow/compiler/mlir/lite/stablehlo/transforms/legalize_tf_xla_call_module_to_stablehlo_pass.h"
#include "tensorflow/compiler/mlir/lite/stablehlo/transforms/passes.h"
#include "tensorflow/compiler/mlir/lite/stablehlo/transforms/rename_entrypoint_to_main.h"
#include "tensorflow/compiler/mlir/lite/stablehlo/transforms/tf_stablehlo_pass.h"

    } catch (UnsupportedOperationException expected) {
    }
  }

  /**
   * Verifies that an Iterator is unmodifiable.
   *
   * <p>This test only works with iterators that iterate over a finite set.
   */
  public static void assertIteratorIsUnmodifiable(Iterator<?> iterator) {
    while (iterator.hasNext()) {
      iterator.next();
      try {
        iterator.remove();

		t.Errorf("Table with escape character, got %v", r.Statement.SQL.String())
	}

	r = dryDB.Create(&UserWithTable{}).Statement
	if DB.Dialector.Name() != "sqlite" {
		if !regexp.MustCompile(`INSERT INTO .gorm.\..user. (.*name.*) VALUES (.*)`).MatchString(r.Statement.SQL.String()) {
			t.Errorf("Table with escape character, got %v", r.Statement.SQL.String())
		}
	} else {

	return new(Rat).SetFrac64(a, b)
}

// SetFloat64 sets z to exactly f and returns z.
// If f is not finite, SetFloat returns nil.
func (z *Rat) SetFloat64(f float64) *Rat {
	const expMask = 1<<11 - 1
	bits := math.Float64bits(f)
	mantissa := bits & (1<<52 - 1)
	exp := int((bits >> 52) & expMask)
	switch exp {
	case expMask: // non-finite
		return nil
	case 0: // denormal
		exp -= 1022
	default: // normal
		mantissa |= 1 << 52

```

</div>

wird das, da Uvicorn standardmäßig den Port `8000` verwendet, mit der Dokumentation auf dem Port `8008` nicht in Konflikt geraten.

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