#include <Python.h>

#include <fstream>
#include <memory>
#include <optional>
#include <string>
#include <vector>

#include "absl/container/flat_hash_set.h"
#include "absl/status/status.h"
#include "absl/strings/string_view.h"
#include "flatbuffers/flatbuffer_builder.h"  // from @flatbuffers
#include "tensorflow/c/kernels.h"
#include "tensorflow/c/tf_status.h"

      return false;
    }
  }

  return true;
}

// TODO: b/289744814 - Refactor to have a single source of truth of TF Quant
// specs.
absl::flat_hash_set<int> GetQuantizableOperands(Operation* op) {
  absl::flat_hash_set<int> quantizable_operands;
  if (isa<TF::DepthwiseConv2dNativeOp, TF::Conv2DOp, TF::Conv3DOp, TF::MatMulOp,
          TF::BatchMatMulOp>(op)) {
    quantizable_operands.insert(1);

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

#ifndef TENSORFLOW_COMPILER_MLIR_TF2XLA_API_V2_TF_EXECUTOR_TO_GRAPH_H_
#define TENSORFLOW_COMPILER_MLIR_TF2XLA_API_V2_TF_EXECUTOR_TO_GRAPH_H_

#include "absl/container/flat_hash_set.h"
#include "llvm/ADT/StringRef.h"
#include "mlir/Dialect/Func/IR/FuncOps.h"  // from @llvm-project
#include "mlir/IR/BuiltinOps.h"  // from @llvm-project

// to satisfy the API of MLIR pass registration. In order to do this, the
// command-line option header is pulled in.

#include <memory>
#include <utility>

#include "absl/container/flat_hash_set.h"
#include "mlir/IR/BuiltinOps.h"  // from @llvm-project
#include "mlir/Tools/mlir-translate/Translation.h"  // from @llvm-project
#include "tensorflow/compiler/mlir/tensorflow/dialect_registration.h"

#define TENSORFLOW_COMPILER_MLIR_LITE_SPARSITY_SPARSIFY_MODEL_H_

#include "absl/status/status.h"
#include "flatbuffers/flatbuffer_builder.h"  // from @flatbuffers
#include "tensorflow/compiler/mlir/lite/schema/schema_generated.h"

namespace mlir {
namespace lite {

// Sparsify the `input_model` and write the result to a flatbuffer `builder`.
absl::Status SparsifyModel(const tflite::ModelT& input_model,

        "//tensorflow/compiler/mlir/lite:tensorflow_lite",
        "//tensorflow/compiler/mlir/quantization/common/quantization_lib",
        "@com_google_absl//absl/container:flat_hash_map",
        "@com_google_absl//absl/log",
        "@com_google_absl//absl/strings",
        "@com_google_absl//absl/strings:str_format",
        "@llvm-project//llvm:Support",
        "@llvm-project//mlir:IR",
        "@llvm-project//mlir:Pass",

#define TENSORFLOW_COMPILER_MLIR_LITE_QUANTIZATION_LITE_QUANTIZE_WEIGHTS_H_

#include <memory>
#include <string>
#include <unordered_map>
#include <unordered_set>
#include <vector>

#include "absl/container/flat_hash_set.h"
#include "flatbuffers/flatbuffer_builder.h"  // from @flatbuffers
#include "tensorflow/compiler/mlir/lite/schema/schema_generated.h"
#include "tensorflow/lite/c/c_api_types.h"

string ArgTypeView::TypeName() const {
  if (arg_type_.is_read_only()) {
    if (arg_type_.is_list()) {
      return "absl::Span<AbstractTensorHandle* const>";
    } else {
      return "AbstractTensorHandle* const";
    }
  } else {
    if (arg_type_.is_list()) {
      return "absl::Span<AbstractTensorHandle*>";
    } else {
      return "AbstractTensorHandle**";
    }
  }
}

}  // namespace cpp

#include "tensorflow/compiler/mlir/tensorflow/ir/tf_ops.h"  // IWYU pragma: keep
#include "tsl/platform/path.h"

namespace mlir::quant::stablehlo {
namespace {

std::string GetOutputFilePath(absl::string_view calibration_data_dir,
                              absl::string_view func_name,
                              int32_t output_file_idx) {
  return tsl::io::JoinPath(calibration_data_dir,
                           llvm::Twine(func_name)

limitations under the License.
==============================================================================*/

#include <algorithm>
#include <numeric>
#include <string>

#include "absl/algorithm/container.h"
#include "absl/strings/str_format.h"
#include "llvm/ADT/ArrayRef.h"
#include "mlir/Support/LLVM.h"  // from @llvm-project
#include "tensorflow/compiler/mlir/quantization/common/attrs_and_constraints.h"