* limitations under the License.
 */

package org.gradle.api.flow;

import org.gradle.api.Incubating;

/**
 * Marker interface for {@link FlowAction dataflow action} parameters.
 *
 * <p>
 * Parameter types should be interfaces, only declaring getters for {@link org.gradle.api.provider.Property}-like objects.
 * Example:
 * </p>
 * <pre>

import org.gradle.api.file.ArchiveOperations;
import org.gradle.api.file.FileSystemOperations;
import org.gradle.process.ExecOperations;

/**
 * A dataflow action.
 *
 * <p>
 * A parameterized and isolated piece of work that becomes eligible for execution within a
 * {@link FlowScope dataflow scope} as soon as all of its input {@link FlowParameters parameters}
 * become available.
 * </p>
 * <p>

#include <memory>
#include <string>

#include "absl/strings/str_cat.h"
#include "llvm/Support/Casting.h"
#include "mlir/Analysis/DataFlow/ConstantPropagationAnalysis.h"  // from @llvm-project
#include "mlir/Analysis/DataFlow/DeadCodeAnalysis.h"  // from @llvm-project
#include "mlir/Analysis/DataFlowFramework.h"  // from @llvm-project
#include "mlir/Dialect/MLProgram/IR/MLProgram.h"  // from @llvm-project

==============================================================================*/

#include <memory>

#include "llvm/ADT/BitVector.h"
#include "llvm/Support/Casting.h"
#include "mlir/Analysis/DataFlow/ConstantPropagationAnalysis.h"  // from @llvm-project
#include "mlir/Analysis/DataFlow/DeadCodeAnalysis.h"  // from @llvm-project
#include "mlir/Analysis/DataFlowFramework.h"  // from @llvm-project
#include "mlir/Dialect/Func/IR/FuncOps.h"  // from @llvm-project

abstract: TensorFlow is a machine learning system that operates at large scale and in heterogeneous environments. TensorFlow uses dataflow graphs to represent computation, shared state, and the operations that mutate that state. It maps the nodes of a dataflow graph across many machines in a cluster, and within a machine across multiple computational devices, including multicore CPUs, general purpose GPUs, and custom-designed ASICs known as Tensor...

  template <typename T>
  Tensor MakeData(const TensorShape& data_shape) {
    DataType data_type = DataTypeToEnum<T>::v();
    Tensor data(data_type, data_shape);
    auto data_flat = data.flat<T>();
    for (int i = 0; i < data_flat.size(); ++i) {
      data_flat(i) = T(i);
    }
    return data;
  }

  template <typename T>
  void MakeOp(const OpType op_type, const Tensor& x_data, const Input& y_shape,

==============================================================================*/

#include "tensorflow/compiler/mlir/tensorflow/analysis/resource_dataflow.h"

#include "llvm/ADT/STLExtras.h"
#include "mlir/Analysis/DataFlow/SparseAnalysis.h"  // from @llvm-project
#include "mlir/Analysis/DataFlowFramework.h"  // from @llvm-project
#include "mlir/Dialect/Func/IR/FuncOps.h"  // from @llvm-project
#include "mlir/IR/BuiltinOps.h"  // from @llvm-project

#include "llvm/ADT/SmallSet.h"
#include "llvm/ADT/SmallVector.h"
#include "llvm/Support/Casting.h"
#include "mlir/Analysis/DataFlow/ConstantPropagationAnalysis.h"  // from @llvm-project
#include "mlir/Analysis/DataFlow/DeadCodeAnalysis.h"  // from @llvm-project
#include "mlir/Analysis/DataFlow/SparseAnalysis.h"  // from @llvm-project
#include "mlir/Analysis/DataFlowFramework.h"  // from @llvm-project

import org.gradle.internal.service.scopes.Scope;
import org.gradle.internal.service.scopes.ServiceScope;

/**
 * Exposes build lifecycle events as {@link Provider providers} so they can be used as inputs
 * to {@link FlowAction dataflow actions}.
 *
 * @since 8.1
 */
@Incubating
@ServiceScope(Scope.Build.class)
public interface FlowProviders {

    /**

       "If set, quantization passes will run and dump the result before HLO "
       "code generation."},
      {"sanitize_dataflow", &flags->sanitize_dataflow,
       "Enable DataFlow Sanitizer pass."},
      {"sanitize_abilists_dataflow", &flags->sanitize_abilists_dataflow,
       "Comma separated list of ABIList file paths."},
      {"gen_name_to_index", &flags->gen_name_to_index,