A. Unique TensorFlower <******@****.***> 1718231025 -0700

        "@llvm-project//mlir:QuantOps",
        "@llvm-project//mlir:Support",
    ],
)

# Binary to apply quantization on the annotated files.
tf_cc_binary(
    name = "tfl_quantizer",
    srcs = [
        "tfl_quantizer.cc",
    ],
    deps = [
        ":quantize_model",
        "//tensorflow/compiler/mlir/lite/schema:schema_fbs",
        "//tensorflow/lite:framework",

// squashed to a requantize op if the scales are different.
def : Pat<(TFL_QuantizeOp (TFL_DequantizeOp $in), $qt), (replaceWithValue $in)>;

// If the tfl.dequantize op wasn't fused, we shouldn't quantize the floating
// point constant.
def : Pat<(TFL_DequantizeOp
             (TFL_QuantizeOp (Arith_ConstantOp F32ElementsAttr:$cst), $qt)),
          (TFL_ConstOp $cst)>;

include "tensorflow/compiler/mlir/lite/ir/tfl_ops.td"

// Both Quantize and Dequantize ops have side effects, so we have to define
// patterns to remove dead ones after the quantization rewrite.
def : Pat<(TFL_QuantizeOp:$op $in, $qt), (replaceWithValue $in), [(HasNoUseOf:$op)]>;

// TODO(b/185915462): Compare the scale of input and output. This can also be
// squashed to a requantize op if the scales are different.