// CHECK: %[[quant:.*]] = "tf.Cast"(%[[round]]) : (tensor<1x3x4x3xf32>) -> tensor<1x3x4x3xi8>
// CHECK: %[[pad:.*]] = "tf.PadV2"(%[[quant]]
// CHECK: %[[xlaconv:.*]] = "tf.XlaConvV2"(%[[pad]]
// CHECK: %[[sub:.*]] = "tf.Sub"(%[[xlaconv]]
// CHECK: %[[cast:.*]] = "tf.Cast"(%[[sub]]) <{Truncate = false}> : (tensor<1x3x2x2xi32>) -> tensor<1x3x2x2xf32>
// CHECK: %[[dequant1:.*]] = "tf.Mul"(%[[cast]]
// CHECK: %[[relu:.*]] = "tf.Relu"(%[[dequant1]]

        if( RO == null || RO.length() == 0 ) {

            /* No resolveOrder has been specified, use the
             * default which is LMHOSTS,DNS,WINS,BCAST
             * LMHOSTS,BCAST,DNS if jcifs.smb1.netbios.wins has not
             * been specified.
             */

            if( NbtAddress.getWINSAddress() == null ) {
                resolveOrder = new int[2];

            details == 'redundant cast to java.lang.String'
            solutions.empty
            verifyAll(getSingleLocation(ReceivedProblem.ReceivedFileLocation)) {
                it.path == fooFileLocation.absolutePath
            }
            additionalData.asMap ["formatted"] == """\
$fooFileLocation:5: warning: [cast] redundant cast to $expectedType
        String s = (String)"Hello World";

      new_unit.set_node_name(name_loc_id.str());
    }
  };

  ArrayRef<Location> locations = mlir::cast<FusedLoc>(loc).getLocations();
  if (IsImportLocPattern(mlir::cast<FusedLoc>(loc))) {
    QuantizationUnit new_unit;
    // Op type is a NameLoc with the ":" suffix.
    StringRef op_type_with_suffix =
        mlir::cast<NameLoc>(locations.front()).getName().strref();
    StringRef op_type =

    }

    @Nullable
    @Override
    public <S> S coerce(Class<S> type) {
        if (type.isInstance(value)) {
            return type.cast(value);
        }
        if (type.isEnum() && type.getName().equals(value.getDeclaringClass().getName())) {
            return type.cast(Enum.valueOf(Cast.uncheckedNonnullCast(type.asSubclass(Enum.class)), value.name()));
        }
        return null;
    }

    if (!mlir::cast<ShapedType>(lhs.getType()).hasStaticShape() ||
        !mlir::cast<ShapedType>(rhs.getType()).hasStaticShape() ||
        !mlir::cast<ShapedType>(cond.getType()).hasStaticShape()) {
      return rewriteOpWithDynamicInput(op, rewriter);
    }

    auto lhs_shape = mlir::cast<ShapedType>(lhs.getType()).getShape();
    auto rhs_shape = mlir::cast<ShapedType>(rhs.getType()).getShape();

  for (int i : llvm::seq<int>(1, num_dims - 1)) {
    Value input_size_i = GetDimValue(builder, loc, input_shape_value, i);
    const int stride_i = mlir::cast<IntegerAttr>(strides[i]).getInt();
    const int dilation_i = mlir::cast<IntegerAttr>(dilations[i]).getInt();
    const int filter_i = filter_shape.getDimSize(i - 1);
    Value pad_i_low, pad_i_high;
    GetSamePaddingValues(builder, loc, input_size_i, filter_i, dilation_i,

            return this;
        }
        if (action instanceof SingletonSet) {
            SingletonSet<T> singletonSet = Cast.uncheckedNonnullCast(action);
            return addOne(singletonSet.singleAction);
        }
        if (action instanceof SetWithFewActions) {
            SetWithFewActions<T> compositeSet = Cast.uncheckedNonnullCast(action);
            return addAll(compositeSet);
        }

  TF_ASSERT_OK_AND_ASSIGN(tf::libtf::Dictionary node,
                          Cast<tf::libtf::Dictionary>(objects.front()));

  // The next three nodes of data-structure-model are lists.
  for (unsigned int i = 1; i < 4; i++) {
    TF_ASSERT_OK_AND_ASSIGN(tf::libtf::List node,
                            Cast<tf::libtf::List>(objects.at(i)));
  }
  // The last three nodes of data-structure-model are dictionaries.

import groovy.lang.Closure;
import org.gradle.api.specs.AndSpec;
import org.gradle.api.specs.CompositeSpec;
import org.gradle.api.specs.Spec;
import org.gradle.api.specs.internal.ClosureSpec;
import org.gradle.internal.Cast;

import javax.annotation.Nullable;

/**
 * A {@link CompositeSpec} that requires all component specs to provide a description.
 * The aggregation is based on an {@link AndSpec}.
 *