zero_points[0], q_type.getStorageTypeMin(),
                                     q_type.getStorageTypeMax());
  } else if (auto q_type = dyn_cast<quant::UniformQuantizedPerAxisType>(type)) {
    return quant::UniformQuantizedPerAxisType::get(
        q_type.getFlags(), q_type.getStorageType(), q_type.getExpressedType(),
        scales, zero_points, q_type.getQuantizedDimension(),

        QType::getDefaultMinimumForInteger(/*isSigned=*/true, num_bits);

    auto flags = quant::QuantizationFlags::Signed;
    QType new_qtype;
    if (auto uqtype = qtype.template dyn_cast<quant::UniformQuantizedType>()) {
      new_qtype = quant::UniformQuantizedType::getChecked(
          op.getLoc(), flags, qtype.getStorageType(), qtype.getExpressedType(),
          uqtype.getScale(), uqtype.getZeroPoint() - offset,

}

func TestIssue50646(t *testing.T) {
	anyType := Universe.Lookup("any").Type().Underlying()
	comparableType := Universe.Lookup("comparable").Type()

	if !Comparable(anyType) {
		t.Error("any is not a comparable type")
	}
	if !Comparable(comparableType) {
		t.Error("comparable is not a comparable type")
	}

	if Implements(anyType, comparableType.Underlying().(*Interface)) {

        private final Class<? extends T> type;
        protected final Collector<T> delegate;
        private final ValueCollector<T> valueCollector;

        public TypedCollector(@Nullable Class<? extends T> type, Collector<T> delegate) {
            this.type = type;
            this.delegate = delegate;
            this.valueCollector = ValueSanitizers.collectorFor(type);
        }

        @Nullable

}

// A StorageCast (scast) represents a cast from or to a type based on the
// storage type and a type based on a corresponding quantized type.
//
// This op exists to ensure type coherency for between parts of the computation
// which are operating directly on an underlying storage type and those which
// operate on quantized values.
//
// Examples from storage to quantized type:
//   i8 -> !quant<"uniform[i8:f32]{1.0}">

}

func TestIssue50646(t *testing.T) {
	anyType := Universe.Lookup("any").Type().Underlying()
	comparableType := Universe.Lookup("comparable").Type()

	if !Comparable(anyType) {
		t.Error("any is not a comparable type")
	}
	if !Comparable(comparableType) {
		t.Error("comparable is not a comparable type")
	}

	if Implements(anyType, comparableType.Underlying().(*Interface)) {

	callbackTypeAfterFind    callbackType = "AfterFind"
)

// ErrUnsupportedDataType unsupported data type
var ErrUnsupportedDataType = errors.New("unsupported data type")

type Schema struct {
	Name                      string
	ModelType                 reflect.Type
	Table                     string
	PrioritizedPrimaryField   *Field
	DBNames                   []string
	PrimaryFields             []*Field

	if response != nil {
		w.Write(response)
	}
}

// mimeType represents various MIME type used API responses.
type mimeType string

const (
	// Means no response type.
	mimeNone mimeType = ""
	// Means response type is JSON.
	mimeJSON mimeType = "application/json"
	// Means response type is XML.
	mimeXML mimeType = "application/xml"
)

// RUN: odml-to-stablehlo-opt --compose-uniform-quantized-type \
// RUN:     --split-input-file --verify-diagnostics %s | FileCheck %s

module {
// CHECK-LABEL: quantized_conv_op
// CHECK-SAME: %[[ARG:.*]]: tensor<1x3x3x4xf32>
  func.func @quantized_conv_op(%arg0: tensor<1x3x3x4xf32>) -> tensor<1x3x3x4xf32> {
    %1 = stablehlo.constant dense<1.000000e+03> : tensor<1x1x1x1xf32>  // Input inverse scale.

limitations under the License.
==============================================================================*/
#include "tensorflow/compiler/mlir/lite/experimental/tac/hardwares/target_hardware.h"

#include <algorithm>
#include <cctype>
#include <functional>
#include <memory>
#include <string>
#include <utility>
#include <vector>

#include "llvm/ADT/DenseMap.h"
#include "llvm/Support/raw_ostream.h"