%0 = "tfl.lstm"(%arg0, %arg1, %arg2, %arg3, %arg4, %arg5, %arg6, %arg7, %arg8, %arg9, %arg10, %arg11, %arg12, %arg13, %arg14, %arg15, %arg16, %arg17, %arg18, %arg19, %arg20, %arg21, %arg22, %arg23) ({}) {cell_clip = 1.000000e+00 : f32, fused_activation_function = "NONE", kernel_type = #tfl<lstm_kernel_type_attr BASIC>} : (tensor<?xf32>,...

    // precise than the input types, are used for this op.
    Type kernel_type = mlir::cast<TensorType>(scale.getType()).getElementType();
    grad = rewriter.create<ConvertOp>(loc, grad, kernel_type);
    act = rewriter.create<ConvertOp>(loc, act, kernel_type);

    tensorflow::TensorFormat data_format;
    if (!FormatFromString(op.getDataFormat().str(), &data_format))

    ConfinedAttr<
      DefaultValuedOptionalAttr<TFL_LSTMKernelTypeAttr, "mlir::TFL::LSTMKernelType::BASIC">,
      [TFL_LSTMKernelTypeEqualsTo<"mlir::TFL::LSTMKernelType::BASIC">]>:$kernel_type
  );

  let hasOptions = 1;

  let results = (outs TFL_2DTensorOf<[F32, QUI8]>:$activ_output,
                      TFL_2DTensorOf<[F32, QUI16]>:$state_output,