#include "llvm/ADT/StringMap.h"
#include "mlir/IR/Attributes.h"  // from @llvm-project
#include "mlir/IR/PatternMatch.h"  // from @llvm-project
#include "tensorflow/compiler/mlir/quantization/common/attrs_and_constraints.h"

namespace mlir::quant {

LogicalResult FillAttributesForUniformQuantizedDotOp(
    PatternRewriter& rewriter, Operation* op,
    llvm::StringMap<Attribute>& identifier_to_attr,

}

Attribute GetLhsDilationValue(PatternRewriter& rewriter,
                              llvm::StringMap<Attribute>& identifier_to_attr) {
  return rewriter.getI64ArrayAttr({1, 1});
}

Attribute GetRhsDilationValue(PatternRewriter& rewriter,
                              llvm::StringMap<Attribute>& identifier_to_attr) {
  ArrayAttr dilations =
      mlir::dyn_cast<ArrayAttr>(identifier_to_attr["dilations"]);

        "TPUEmbedding layers");

  op->removeAttr(kTPUEmbeddingAttr);
  return success();
}

LogicalResult FindTPUEmbeddingOps(
    func::FuncOp func_op, llvm::StringMap<Operation*>* enqueue_op_map,
    llvm::StringMap<Operation*>* recv_activation_op_map,
    llvm::StringMap<Operation*>* send_gradient_op_map) {
  auto walk_result = func_op.walk([&](Operation* op) {
    if (llvm::isa<TF::RecvTPUEmbeddingActivationsOp>(op))

  void CountOp(DenseMap<StringRef, llvm::StringMap<int64_t>> &op_count_map,
               StringRef op_name, StringRef dtype);

 private:
  llvm::StringMap<int64_t> op_with_dialect_count_;
  DenseMap<StringRef, llvm::StringMap<int64_t>> op_dtype_count_;
  llvm::StringMap<int64_t> dialect_count_;
  llvm::StringMap<StringRef> dialect_name_of_;
  llvm::StringMap<StringRef> op_name_of_;

#include "tensorflow/compiler/mlir/quantization/tensorflow/utils/tf_to_uniform_attribute_utils.h"

#include <gtest/gtest.h>
#include "absl/strings/string_view.h"
#include "llvm/ADT/StringMap.h"
#include "mlir/IR/AsmState.h"  // from @llvm-project
#include "mlir/IR/Attributes.h"  // from @llvm-project
#include "mlir/IR/Block.h"  // from @llvm-project
#include "mlir/IR/Builders.h"  // from @llvm-project

      SmallVectorImpl<Value>* inputs, NamedAttrList* arg_attrs,
      llvm::StringMap<Attribute>* derived_attrs) const;

  // Uses the collected attribute values to derive all the output types.
  LogicalResult DeriveOutputTypes(Location loc, FunctionType signature,
                                  const llvm::StringMap<Attribute>& attrs,
                                  SmallVectorImpl<Type>* output_types) const;

#define TENSORFLOW_COMPILER_MLIR_OP_OR_ARG_NAME_MAPPER_H_

#include <string>

#include "absl/strings/string_view.h"
#include "llvm/ADT/DenseMap.h"
#include "llvm/ADT/PointerUnion.h"
#include "llvm/ADT/StringMap.h"
#include "llvm/ADT/StringRef.h"
#include "mlir/IR/Operation.h"  // from @llvm-project
#include "mlir/IR/Value.h"  // from @llvm-project

namespace tensorflow {

// PointerUnion for operation and value.

        if (started) {
            started = false
            container.stop()
            monitor.interrupt()
        }
    }

    GradleInContainer withEnv(Map<String, ?> stringMap) {
        Map<String, String> env = [:]
        stringMap.each { k, v -> env[k] = v?.toString() }
        container.withEnv(env)
        this
    }

    ExecutionResult succeeds(String... tasks) {
        executer.withTasks(tasks)

  // match.
  // The `int` in the following two containers are to specify the result index
  // of the given op. -1 indicates all the floating-point results.
  llvm::StringMap<std::pair<int, const QuantParamsEntry>> name_to_info_;
  llvm::StringMap<std::pair<int, const QuantParamsEntry>> regex_to_info_;
};
}  // namespace

bool ImportQuantStatsPass::ParseQuantStats(const std::string &stats_str) {

#ifndef TENSORFLOW_COMPILER_MLIR_TENSORFLOW_IR_TF_STRUCTS_H_
#define TENSORFLOW_COMPILER_MLIR_TENSORFLOW_IR_TF_STRUCTS_H_

#include <optional>

#include "llvm/ADT/StringMap.h"
#include "mlir/IR/BuiltinTypes.h"  // from @llvm-project
#include "mlir/IR/Diagnostics.h"  // from @llvm-project
#include "mlir/IR/Location.h"  // from @llvm-project
#include "mlir/IR/Operation.h"  // from @llvm-project