// of the tensor dimension.
bool FloatValueEquals(const Attribute& attr, const double value) {
  const auto fp_attr = mlir::dyn_cast_or_null<DenseFPElementsAttr>(attr);
  if (!fp_attr) return false;

  if (fp_attr.isSplat()) {
    return fp_attr.getSplatValue<APFloat>().isExactlyValue(value);
  }
  return llvm::all_of(fp_attr.getValues<APFloat>(), [value](const APFloat& f) {
    return f.isExactlyValue(value);
  });
}

def LegalizeMin : Pat<
  (TF_MinOp $arg0, $axes, BoolAttr:$arg2),
  (TFL_ReduceMinOp $arg0, (CreateTFCastToInt32Op $axes), $arg2)>;

def LegalizeMax : Pat<
  (TF_MaxOp $arg0, $axes, BoolAttr:$arg2),
  (TFL_ReduceMaxOp $arg0, (CreateTFCastToInt32Op $axes), $arg2)>;

def LegalizeProd : Pat<
  (TF_ProdOp $arg0, $axes, BoolAttr:$arg2),
  (TFL_ReduceProdOp $arg0, (CreateTFCastToInt32Op $axes), $arg2)>;

Type DeduceEqualCmpOpType(Builder *builder, Location loc, Value x, Value y,
                          BoolAttr incompatible_shape_error);

Type InferReductionOpType(Value input, Value reduction_indices,
                          BoolAttr keep_dims);

// Verifies that the given types are cast compatible. If not, emits appropriate

static bool FloatValueEquals(const Attribute &attr, double value) {
  auto fp_attr = mlir::dyn_cast_or_null<DenseFPElementsAttr>(attr);
  if (fp_attr == nullptr) return false;

  if (fp_attr.isSplat()) {
    return fp_attr.getSplatValue<APFloat>().isExactlyValue(value);
  }
  return llvm::all_of(fp_attr.getValues<APFloat>(), [value](const APFloat &f) {
    return f.isExactlyValue(value);
  });
}

    I64Attr:$num_bits,
    // Quantization range starts from 0 or 1; starts from 1 if true.
    DefaultValuedOptionalAttr<BoolAttr, "false">:$narrow_range,
    // The sign of the quantization.
    DefaultValuedOptionalAttr<BoolAttr, "false">:$is_signed
  );

  let results = (outs
    F32Tensor:$outputs
  );
}

    I64Attr:$num_bits,
    // Quantization range starts from 0 or 1; starts from 1 if true.
    DefaultValuedOptionalAttr<BoolAttr, "false">:$narrow_range,
    // The sign of the quantization.
    DefaultValuedOptionalAttr<BoolAttr, "false">:$is_signed
  );

  let results = (outs
    F32Tensor:$outputs
  );
}

                                PatternRewriter& rewriter) const override {
    auto f_attr = mlir::dyn_cast<FlatSymbolRefAttr>(call_op.getFAttr());
    auto module_op = call_op->getParentOfType<ModuleOp>();
    SymbolTable symbol_table(module_op);

    auto f_name = f_attr.getValue();
    func::FuncOp float_func =
        dyn_cast<func::FuncOp>(symbol_table.lookup(f_name));
    if (!float_func) {

    if (callable->hasAttr("tf._XlaMustCompile")) return true;
    auto noinline_attr_name = absl::StrCat("tf.", tensorflow::kNoInlineAttr);
    if (auto noinline_attr =
            callable->getAttrOfType<BoolAttr>(noinline_attr_name))
      return !noinline_attr.getValue();
    return true;
  }

  // Returns if its legal to inline 'src' region into the 'dest' region
  // attached to a TF operation.

    DefaultValuedOptionalAttr<BoolAttr, "false">:$adj_x,
    DefaultValuedOptionalAttr<BoolAttr, "false">:$adj_y,
    DefaultValuedOptionalAttr<BoolAttr, "false">:$grad_x,
    DefaultValuedOptionalAttr<BoolAttr, "false">:$grad_y
  );

  let results = (outs

    auto c_false =
        rewriter.create<arith::ConstantOp>(loc, rewriter.getBoolAttr(false));
    TypeAttr f32_attr = TypeAttr::get(rewriter.getF32Type());
    TFRAttrType output_type = TFRAttrType::get(rewriter.getContext());
    auto constant_f32_op = rewriter.create<ConstOp>(loc, output_type, f32_attr);
    TypeAttr i32_attr = TypeAttr::get(rewriter.getI32Type());