GetIndicesForElement(index, buffer, builder, loc)})
      .getOutput();
}

TensorType GetSizeType(OpBuilder builder) {
  return tensorflow::GetTypeFromTFTensorShape({1}, builder.getIntegerType(32));
}

Value ReshapeScalarToSizeType(OpBuilder builder, Value scalar, Location loc) {
  auto size_type = GetSizeType(builder);
  return builder.create<TF::ReshapeOp>(
      loc, ArrayRef<Type>{size_type},

          return null;
        }
      };

  /**
   * Returns a builder for creating simple, fast escapers. A builder instance can be reused and each
   * escaper that is created will be a snapshot of the current builder state. Builders are not
   * thread safe.
   *
   * <p>The initial state of the builder is such that:
   *
   * <ul>
   *   <li>There are no replacement mappings

/**
 * Executes the given [builder] against this object's [GroovyBuilderScope].
 *
 * @see [GroovyBuilderScope]
 */
inline fun <T> Any.withGroovyBuilder(builder: GroovyBuilderScope.() -> T): T =
    GroovyBuilderScope.of(this).builder()


/**
 * Provides a dynamic dispatching DSL with Groovy semantics for better integration with
 * plugins that rely on Groovy builders such as the core `maven` plugin.
 *

    }

    private def createExternalJar() {
        ArtifactBuilder builder = artifactBuilder()
        builder.sourceFile('org/gradle/test/BuildClass.java') << '''
            package org.gradle.test;
            public class BuildClass { }
'''
        builder.buildJar(file("repo/test-1.3.jar"))
    }

  Value scattered_start_indices = builder.create<TF::TensorScatterUpdateOp>(
      loc, empty_start_indices,
      /*indices=*/
      builder.create<TF::ReshapeOp>(
          loc, RankedTensorType::get({index_map_size, 1}, builder.getI64Type()),
          Create1DConstValue<int64_t>(builder, loc, indices),
          Create1DConstValue<int64_t>(builder, loc, {index_map_size, 1})),
      /*value=*/

    // the resource, and we use it to just look up.
    // See core/kernels/data/iterator_ops.cc.)
    resource_op = builder.create<TF::IteratorOp>(
        op->getLoc(), resource.getType(), shared_name, container,
        it.getOutputTypes(), it.getOutputShapes());
  } else {
    resource_op = builder.create<TF::VarHandleOp>(
        op->getLoc(), resource.getType(), container, shared_name);
  }

                                  OpBuilder* builder) {
  return builder->create<TF::TPUGetLayoutOp>(
      compile_launch.getLoc(),
      llvm::ArrayRef<Type>{RankedTensorType::get({ShapedType::kDynamic},
                                                 builder->getIntegerType(64))},
      llvm::ArrayRef<Value>{compilation_key},
      llvm::ArrayRef<NamedAttribute>{
          builder->getNamedAttr("index",

      mlir::emitError(loc, "non-broadcastable operands");
    } else {
      return UnrankedTensorType::get(builder->getI1Type());
    }
  }

  auto ranked_type = mlir::dyn_cast<RankedTensorType>(result_type);
  if (!ranked_type) return UnrankedTensorType::get(builder->getI1Type());

  return RankedTensorType::get(ranked_type.getShape(), builder->getI1Type());
}

Type InferReductionOpType(Value input, Value reduction_indices,

  OpBuilder builder(module_op.getContext());
  builder.setInsertionPointAfter(session_init_op);

  const Location loc = builder.getUnknownLoc();
  const auto func_type = builder.getFunctionType(/*inputs=*/{}, /*results=*/{});

  auto init_func = builder.create<func::FuncOp>(
      loc, /*sym_name=*/"init_func_restore_op", func_type);

      func.emitError("we cannot get hardware info for this function.");
      signalPassFailure();
    }

    float total_cost = GetCostForFunc(&func, *target);
    OpBuilder builder(func);
    UpdateCost(func, total_cost, &builder);
  }
}

}  // namespace

std::unique_ptr<OperationPass<ModuleOp>> CreateComputeCostPass() {
  return std::make_unique<ComputeCostPass>();
}