break;
  }
}

#define DEFINE_TF_GETATTR(func, c_type, cc_type, attr_type, list_field)        \
  void TF_OpKernelConstruction_GetAttr##func(TF_OpKernelConstruction* ctx,     \
                                             const char* attr_name,            \
                                             c_type* val, TF_Status* status) { \

// license that can be found in the LICENSE file.

// Runtime type representation.

package runtime

import (
	"internal/abi"
	"unsafe"
)

type nameOff = abi.NameOff
type typeOff = abi.TypeOff
type textOff = abi.TextOff

type _type = abi.Type

// rtype is a wrapper that allows us to define additional methods.
type rtype struct {
	*abi.Type // embedding is okay here (unlike reflect) because none of this is public

)

// userTypeInfo stores the information associated with a type the user has handed
// to the package. It's computed once and stored in a map keyed by reflection
// type.
type userTypeInfo struct {
	user        reflect.Type // the type the user handed us
	base        reflect.Type // the base type after all indirections
	indir       int          // number of indirections to reach the base type
	externalEnc int          // xGob, xBinary, or xText

                return FILE_COLLECTION.asType();
            case DIRECTORY_PROPERTY:
            case REGULAR_FILE_PROPERTY:
                return Type.getType(File.class);
            case LIST_PROPERTY:
                return Type.getType(List.class);
            case SET_PROPERTY:
                return Type.getType(Set.class);
            case MAP_PROPERTY:
                return Type.getType(Map.class);

	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

              np.random.uniform(size=bias_shape), dtype=dtypes.float32
          )

        self._kernel = np.random.uniform(size=y_shape).astype('f4')
        self._min = (-0.8, -0.8, -0.9)
        self._max = (0.9, 0.9, 1.0)

      @def_function.function(
          input_signature=[
              tensor_spec.TensorSpec(
                  name='x', shape=x_signature, dtype=dtypes.float32
              )
          ]

                throw new IllegalArgumentException(String.format("Cannot set the %s of a property of type %s with key type %s and value type %s " +
                        "using a provider with key type %s and value type %s.", valueKind, Map.class.getName(), keyType.getName(), valueType.getName(),
                    providerKeyType.getName(), providerValueType.getName()));
            }

        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

	//         dates:
	//           type: array
	//           items:
	//             type: string
	//             format: date-time
	//      metadata:
	//        type: object
	//        additionalProperties:
	//          type: object
	//          properties:
	//            key:
	//              type: string
	//            values:
	//              type: array
	//              items: string

// 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.