* java.util.function.Function java.util.function.Function}.
 *
 * <p>The {@link Functions} class provides common functions and related utilities.
 *
 * <p>See the Guava User Guide article on <a
 * href="https://github.com/google/guava/wiki/FunctionalExplained">the use of {@code Function}</a>.
 *
 * <h3>For Java 8+ users</h3>
 *

  auto cleanup_tensors = absl::MakeCleanup([outs]() {
    for (auto t : outs) {
      t->Unref();
    }
  });
  return Unflatten(outs, concrete_fn.output_signature);
}

StatusOr<Function::ConcreteFunction> Function::GetConcreteFunction(
    TaggedValue value) const {
  if (concrete_fns_.empty()) {
    return tensorflow::errors::FailedPrecondition(
        "No registered ConcreteFunctions.");
  }

See the License for the specific language governing permissions and
limitations under the License.
==============================================================================*/

#include "tensorflow/compiler/mlir/tfrt/function/function.h"

#include "absl/log/log.h"
#include "absl/strings/match.h"
#include "mlir/IR/OperationSupport.h"  // from @llvm-project
#include "mlir/Pass/PassManager.h"  // from @llvm-project

  // to proactively transfer the result to host since the consumer op (or
  // function) of the result may still be on TPU.
  // TODO(b/194081364): remove this option once we unify servo TPU serving
  // result transfer behavior.
  bool tpu_transfer_result_to_host = false;
};

// Compile MLIR generated by tf.function in TF dialect into BEF.
Status CompileTFMLIRToBEF(const TfrtFunctionCompileOptions& options,

  attr {
    key: "_disable_call_shape_inference"
    value {
      b: true
    }
  }
  attr {
    key: "_tpu_replicate"
    value {
      s: "cluster"
    }
  }
}
library {
  function {
    signature {
      name: "test_func_name"
      input_arg {
        name: "a_0"
        type: DT_INT32
      }
      output_arg {
        name: "a"
        type: DT_INT32
      }
    }

    signature {
      name: "foo3"
    }
  }
  function {
    signature {
      name: "foo4"
    }
  }
  function {
    signature {
      name: "foo5"
    }
  }
  function {
    signature {
      name: "foo6"
    }
  }
  function {
    signature {
      name: "foo7"
    }
  }
  function {
    signature {
      name: "foo8"
    }
  }
  function {
    signature {

  }
}
node {
  name: "func_call"
  op: "test_func_name"
  input: "x"
  input: "x"
  attr {
    key: "_disable_call_shape_inference"
    value {
      b: true
    }
  }
}
library {
  function {
    signature {
      name: "test_func_name"
      input_arg {
        name: "a_0"
        type: DT_RESOURCE
      }
      input_arg {
        name: "a_1"
        type: DT_RESOURCE
      }

            var used = 0

            if (kFunction.instanceParameter != null && kFunction.extensionReceiverParameter != null)
                error("member-extension functions are not supported")

            kFunction.instanceParameter?.let { put(it, receiver) }
            kFunction.parameters.forEach { param ->
                val paramName = param.name
                when {

            propertyOriginalTypes.getOrPut(kClass) { mutableMapOf() }[property.name] = originalType
        }

        fun claimFunction(kClass: KClass<*>, kFunction: KFunction<*>) {
            claimedFunctions.getOrPut(kClass) { mutableSetOf() }.add(kFunction)
        }

        val types: Iterable<KClass<*>>
            get() = properties.keys

        fun hasType(kClass: KClass<*>): Boolean = kClass in properties

import org.gradle.declarative.dsl.schema.FqName
import kotlin.reflect.KCallable
import kotlin.reflect.KClass
import kotlin.reflect.KFunction
import kotlin.reflect.KVisibility


fun schemaFromTypes(
    topLevelReceiver: KClass<*>,
    types: Iterable<KClass<*>>,
    externalFunctions: List<KFunction<*>> = emptyList(),
    externalObjects: Map<FqName, KClass<*>> = emptyMap(),
    defaultImports: List<FqName> = emptyList(),