rng.uniform(low=0.0, high=1.0, size=static_input_shape).astype(
            np.float32
        )
    )

    def data_gen() -> repr_dataset.RepresentativeDataset:
      for _ in range(100):
        yield {
            'input_tensor': rng.uniform(
                low=0.0, high=1.0, size=static_input_shape
            ).astype(np.float32)
        }

import org.gradle.plugins.signing.signatory.SignatoryProvider;
import org.gradle.security.internal.BaseSignatoryProvider;
import org.gradle.util.internal.ConfigureUtil;

import static org.codehaus.groovy.runtime.DefaultGroovyMethods.asType;

public interface ConfigurableSignatoryProvider<T extends Signatory> extends BaseSignatoryProvider<T>, SignatoryProvider<T> {
    @Override
    default void configure(SigningExtension settings, Closure closure) {

    def data_gen():
      for _ in range(255):
        yield {
            'x': ops.convert_to_tensor(
                np.random.uniform(size=(10)).astype('f4')
            ),
            'y': ops.convert_to_tensor(
                np.random.uniform(size=(10)).astype('f4')
            ),
        }

    root = ModelWithAdd()

    temp_path = self.create_tempdir().full_path
    saved_model_save.save(

        return Type.getMethodDescriptor(
            extractReturnType(methodElement),
            methodElement.getParameters().stream().map(it -> extractType(it.asType())).toArray(Type[]::new)
        );
    }

            if (leftValue.isMissing()) {
                return leftValue.asType();
            }
            Value<? extends B> rightValue = right.calculateValue(consumer);
            if (rightValue.isMissing()) {
                return rightValue.asType();
            }

    MAP_PROPERTY("org.gradle.api.provider.MapProperty"),
    PROPERTY("org.gradle.api.provider.Property"),
    UNSUPPORTED((Type) null) {
        @Override
        public Type asType() {
            throw new UnsupportedOperationException("Unsupported type");
        }
    };

    @SuppressWarnings("ImmutableEnumChecker")
    private final Type type;

    GradleLazyType(String name) {

        static <T> Value<T> ofNullable(@Nullable T value) {
            if (value == null) {
                return MISSING.asType();
            }
            return new Present<>(value);
        }

        static <T> Value<T> missing() {
            return MISSING.asType();
        }

        static <T> Value<T> of(T value) {
            if (value == null) {

            Value<? extends V> value = providerOfValue.calculateValue(consumer);
            if (value.isMissing()) {
                return value.asType();
            }
            collector.add(key, value.getWithoutSideEffect(), dest);
            return Value.present().withSideEffect(SideEffect.fixedFrom(value));
        }

        @Override

        """Initializes a SimpleGatherAndConvModel."""
        self.embedding_w = np.random.randn(1024, 3, 4, 3).astype('f4')
        self.embedding_w = np.minimum(np.maximum(self.embedding_w, -4), 4)

        self.conv_filters = np.random.uniform(
            low=-10, high=10, size=filter_shape
        ).astype('f4')

        second_conv_filter_shape = (3, 3, filter_shape[-1], 1)

        MethodHandle decorated = MethodHandles.insertArguments(INTERCEPTOR, 0, this, spreader, flags, caller.lookupClass().getName());
        return decorated.asCollector(Object[].class, original.type().parameterCount()).asType(original.type());
    }

    private Object interceptMethodHandle(MethodHandle original, int flags, String consumer, Object[] args) throws Throwable {
        boolean isSpread = (flags & IndyInterface.SPREAD_CALL) != 0;