COMPMID-2805: Add QASYMM8_SIGNED support in NEGEMMLowpOutputStage
Add support from requantizing down from S32 to Int8 with fixed point
requantization. This involves the following:
- Compute fixed point multiplication between each entry of input by
result_fixedpoint_multiplier
- Add bias to final result if bias tensor is not a nullptr
- Round to nearest division by a power-of-two using result_shift
- Add offset to each result
- Clamp the value between the specified min and max bounds
- Cast to int8 data type
Change-Id: I641b3fac0833c568d8565ccb859bbc561a24c17d
Signed-off-by: Georgios Pinitas <georgios.pinitas@arm.com>
Reviewed-on: https://review.mlplatform.org/c/2340
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
Reviewed-by: Michele Di Giorgio <michele.digiorgio@arm.com>
Tested-by: Arm Jenkins <bsgcomp@arm.com>
diff --git a/tests/validation/reference/GEMMLowp.cpp b/tests/validation/reference/GEMMLowp.cpp
index 08be4a5..4529b91 100644
--- a/tests/validation/reference/GEMMLowp.cpp
+++ b/tests/validation/reference/GEMMLowp.cpp
@@ -39,6 +39,28 @@
namespace
{
template <typename T>
+struct DataTypeExtractor
+{
+ static DataType data_type()
+ {
+ DataType data_type = DataType::UNKNOWN;
+ if(std::is_same<T, int8_t>::value)
+ {
+ data_type = DataType::QASYMM8_SIGNED;
+ }
+ else if(std::is_same<T, uint8_t>::value)
+ {
+ data_type = DataType::QASYMM8;
+ }
+ else if(std::is_same<T, int16_t>::value)
+ {
+ data_type = DataType::QSYMM16;
+ }
+ return data_type;
+ }
+};
+
+template <typename T>
void quantize_down_int32_to_uint8_scale(const SimpleTensor<T> *in, const SimpleTensor<T> *bias, SimpleTensor<uint8_t> *dst, int32_t result_offset, std::vector<int32_t> result_mult_int,
std::vector<int32_t> result_shift, int32_t min, int32_t max)
{
@@ -68,16 +90,16 @@
}
}
-template <typename T>
-void quantize_down_int32_to_uint8_scale_by_fixedpoint(const SimpleTensor<T> *in, const SimpleTensor<T> *bias, SimpleTensor<uint8_t> *dst, std::vector<int32_t> result_fixedpoint_multiplier,
- std::vector<int32_t> result_shift, int32_t result_offset_after_shift, int32_t min, int32_t max)
+template <typename TIn, typename TOut>
+void quantize_down_scale_by_fixedpoint(const SimpleTensor<TIn> *in, const SimpleTensor<TIn> *bias, SimpleTensor<TOut> *dst, std::vector<int32_t> result_fixedpoint_multiplier,
+ std::vector<int32_t> result_shift, int32_t result_offset_after_shift, int32_t min, int32_t max)
{
const int cols_in = in->shape().x();
const bool is_per_channel = result_fixedpoint_multiplier.size() > 1;
for(int i = 0; i < in->num_elements(); ++i)
{
- int32_t result = (*in)[i];
+ TIn result = (*in)[i];
if(bias != nullptr)
{
@@ -88,7 +110,14 @@
const int32_t multiplier = (is_per_channel) ? result_fixedpoint_multiplier[i % cols_in] : result_fixedpoint_multiplier[0];
const int32_t shift = (is_per_channel) ? result_shift[i % cols_in] : result_shift[0];
- result = asymm_rounding_divide_by_pow2(asymm_int_mult(result, multiplier), shift);
+ if(shift < 0)
+ {
+ result = asymm_int_mult(result * (1 << (-shift)), multiplier);
+ }
+ else
+ {
+ result = asymm_rounding_divide_by_pow2(asymm_int_mult(result, multiplier), shift);
+ }
result += result_offset_after_shift;
// Bounded ReLu
@@ -97,42 +126,8 @@
result = std::max(min, std::min(max, result));
}
- (*dst)[i] = static_cast<uint8_t>(std::max(0, std::min(255, result)));
- }
-}
-
-template <typename T>
-void quantize_down_int32_to_int16_scale_by_fixedpoint(const SimpleTensor<T> *in, const SimpleTensor<T> *bias, SimpleTensor<int16_t> *dst, int32_t result_fixedpoint_multiplier, int32_t result_shift,
- int32_t min, int32_t max)
-{
- const int cols_in = in->shape().x();
-
- for(int i = 0; i < in->num_elements(); ++i)
- {
- int32_t result = (*in)[i];
-
- if(bias != nullptr)
- {
- result += (*bias)[i % cols_in];
- }
-
- // Fixed point multiplication
- if(result_shift < 0)
- {
- result = asymm_int_mult(result * (1 << (-result_shift)), result_fixedpoint_multiplier);
- }
- else
- {
- result = asymm_rounding_divide_by_pow2(asymm_int_mult(result, result_fixedpoint_multiplier), result_shift);
- }
-
- // Bounded ReLu
- if(min != max)
- {
- result = std::max(min, std::min(max, result));
- }
-
- (*dst)[i] = static_cast<int16_t>(std::max(-32768, std::min(32767, result)));
+ (*dst)[i] = static_cast<TOut>(std::max<TIn>(std::numeric_limits<TOut>::lowest(),
+ std::min<TIn>(std::numeric_limits<TOut>::max(), result)));
}
}
} // namespace
@@ -219,59 +214,43 @@
return dst;
}
-template <typename T>
-SimpleTensor<uint8_t> gemmlowp_quantize_down_int32_to_uint8_scale_by_fixedpoint(const SimpleTensor<T> &in, std::vector<int32_t> result_fixedpoint_multiplier, std::vector<int32_t> result_shift,
- int32_t result_offset_after_shift, int32_t min, int32_t max)
+template <typename TIn, typename TOut>
+SimpleTensor<TOut> gemmlowp_quantize_down_scale_by_fixedpoint(const SimpleTensor<TIn> &in, std::vector<int32_t> result_fixedpoint_multiplier, std::vector<int32_t> result_shift,
+ int32_t result_offset_after_shift, int32_t min, int32_t max)
{
- SimpleTensor<uint8_t> dst(in.shape(), DataType::QASYMM8);
+ SimpleTensor<TOut> dst(in.shape(), DataTypeExtractor<TOut>::data_type());
- quantize_down_int32_to_uint8_scale_by_fixedpoint<T>(&in, nullptr, &dst, result_fixedpoint_multiplier, result_shift, result_offset_after_shift, min, max);
+ quantize_down_scale_by_fixedpoint<TIn, TOut>(&in, nullptr, &dst, result_fixedpoint_multiplier, result_shift, result_offset_after_shift, min, max);
return dst;
}
-template <typename T>
-SimpleTensor<uint8_t> gemmlowp_quantize_down_int32_to_uint8_scale_by_fixedpoint(const SimpleTensor<T> &in, const SimpleTensor<T> &bias, std::vector<int32_t> result_fixedpoint_multiplier,
- std::vector<int32_t> result_shift, int32_t result_offset_after_shift, int32_t min, int32_t max)
+template <typename TIn, typename TOut>
+SimpleTensor<TOut> gemmlowp_quantize_down_scale_by_fixedpoint(const SimpleTensor<TIn> &in, const SimpleTensor<TIn> &bias, std::vector<int32_t> result_fixedpoint_multiplier,
+ std::vector<int32_t> result_shift, int32_t result_offset_after_shift, int32_t min, int32_t max)
{
- SimpleTensor<uint8_t> dst(in.shape(), DataType::QASYMM8);
+ SimpleTensor<TOut> dst(in.shape(), DataTypeExtractor<TOut>::data_type());
- quantize_down_int32_to_uint8_scale_by_fixedpoint<T>(&in, &bias, &dst, result_fixedpoint_multiplier, result_shift, result_offset_after_shift, min, max);
+ quantize_down_scale_by_fixedpoint<TIn, TOut>(&in, &bias, &dst, result_fixedpoint_multiplier, result_shift, result_offset_after_shift, min, max);
return dst;
}
-template <typename T>
-SimpleTensor<int16_t> gemmlowp_quantize_down_int32_to_int16_scale_by_fixedpoint(const SimpleTensor<T> &in, int32_t result_fixedpoint_multiplier, int32_t result_shift, int32_t min,
- int32_t max)
-{
- SimpleTensor<int16_t> dst(in.shape(), DataType::QSYMM16);
-
- quantize_down_int32_to_int16_scale_by_fixedpoint<T>(&in, nullptr, &dst, result_fixedpoint_multiplier, result_shift, min, max);
-
- return dst;
-}
-
-template <typename T>
-SimpleTensor<int16_t> gemmlowp_quantize_down_int32_to_int16_scale_by_fixedpoint(const SimpleTensor<T> &in, const SimpleTensor<T> &bias, int32_t result_fixedpoint_multiplier, int32_t result_shift,
- int32_t min, int32_t max)
-{
- SimpleTensor<int16_t> dst(in.shape(), DataType::QSYMM16);
-
- quantize_down_int32_to_int16_scale_by_fixedpoint<T>(&in, &bias, &dst, result_fixedpoint_multiplier, result_shift, min, max);
-
- return dst;
-}
-
-template SimpleTensor<uint8_t> gemmlowp_quantize_down_int32_to_uint8_scale_by_fixedpoint(const SimpleTensor<int32_t> &a, std::vector<int32_t> result_fixedpoint_multiplier,
- std::vector<int32_t> result_shift, int32_t result_offset_after_shift, int32_t min, int32_t max);
-template SimpleTensor<uint8_t> gemmlowp_quantize_down_int32_to_uint8_scale_by_fixedpoint(const SimpleTensor<int32_t> &a, const SimpleTensor<int32_t> &b,
- std::vector<int32_t> result_fixedpoint_multiplier,
- std::vector<int32_t> result_shift, int32_t result_offset_after_shift, int32_t min, int32_t max);
-template SimpleTensor<int16_t> gemmlowp_quantize_down_int32_to_int16_scale_by_fixedpoint(const SimpleTensor<int32_t> &a, int32_t result_fixedpoint_multiplier, int32_t result_shift,
- int32_t min, int32_t max);
-template SimpleTensor<int16_t> gemmlowp_quantize_down_int32_to_int16_scale_by_fixedpoint(const SimpleTensor<int32_t> &a, const SimpleTensor<int32_t> &b, int32_t result_fixedpoint_multiplier,
- int32_t result_shift, int32_t min, int32_t max);
+template SimpleTensor<uint8_t> gemmlowp_quantize_down_scale_by_fixedpoint(const SimpleTensor<int32_t> &a, std::vector<int32_t> result_fixedpoint_multiplier,
+ std::vector<int32_t> result_shift, int32_t result_offset_after_shift, int32_t min, int32_t max);
+template SimpleTensor<uint8_t> gemmlowp_quantize_down_scale_by_fixedpoint(const SimpleTensor<int32_t> &a, const SimpleTensor<int32_t> &b,
+ std::vector<int32_t> result_fixedpoint_multiplier,
+ std::vector<int32_t> result_shift, int32_t result_offset_after_shift, int32_t min, int32_t max);
+template SimpleTensor<int8_t> gemmlowp_quantize_down_scale_by_fixedpoint(const SimpleTensor<int32_t> &a, std::vector<int32_t> result_fixedpoint_multiplier,
+ std::vector<int32_t> result_shift, int32_t result_offset_after_shift, int32_t min, int32_t max);
+template SimpleTensor<int8_t> gemmlowp_quantize_down_scale_by_fixedpoint(const SimpleTensor<int32_t> &a, const SimpleTensor<int32_t> &b,
+ std::vector<int32_t> result_fixedpoint_multiplier,
+ std::vector<int32_t> result_shift, int32_t result_offset_after_shift, int32_t min, int32_t max);
+template SimpleTensor<int16_t> gemmlowp_quantize_down_scale_by_fixedpoint(const SimpleTensor<int32_t> &a, std::vector<int32_t> result_fixedpoint_multiplier,
+ std::vector<int32_t> result_shift, int32_t result_offset_after_shift, int32_t min, int32_t max);
+template SimpleTensor<int16_t> gemmlowp_quantize_down_scale_by_fixedpoint(const SimpleTensor<int32_t> &a, const SimpleTensor<int32_t> &b,
+ std::vector<int32_t> result_fixedpoint_multiplier,
+ std::vector<int32_t> result_shift, int32_t result_offset_after_shift, int32_t min, int32_t max);
template SimpleTensor<uint8_t> gemmlowp_quantize_down_int32_to_uint8_scale(const SimpleTensor<int32_t> &a, int32_t result_offset, std::vector<int32_t> result_mult_int,
std::vector<int32_t> result_shift, int32_t min, int32_t max);
template SimpleTensor<uint8_t> gemmlowp_quantize_down_int32_to_uint8_scale(const SimpleTensor<int32_t> &a, const SimpleTensor<int32_t> &b, int32_t result_offset, std::vector<int32_t> result_mult_int,
diff --git a/tests/validation/reference/GEMMLowp.h b/tests/validation/reference/GEMMLowp.h
index 815527e..7ff01ef 100644
--- a/tests/validation/reference/GEMMLowp.h
+++ b/tests/validation/reference/GEMMLowp.h
@@ -52,20 +52,13 @@
SimpleTensor<uint8_t> gemmlowp_quantize_down_int32_to_uint8_scale(const SimpleTensor<T> &in, const SimpleTensor<T> &bias, int32_t result_offset, std::vector<int32_t> result_mult_int,
std::vector<int32_t> result_shift, int32_t min = 0, int32_t max = 0);
-template <typename T>
-SimpleTensor<uint8_t> gemmlowp_quantize_down_int32_to_uint8_scale_by_fixedpoint(const SimpleTensor<T> &in, std::vector<int32_t> result_fixedpoint_multiplier, std::vector<int32_t> result_shift,
- int32_t result_offset_after_shift, int32_t min = 0, int32_t max = 0);
+template <typename TIn, typename TOut>
+SimpleTensor<TOut> gemmlowp_quantize_down_scale_by_fixedpoint(const SimpleTensor<TIn> &in, std::vector<int32_t> result_fixedpoint_multiplier, std::vector<int32_t> result_shift,
+ int32_t result_offset_after_shift, int32_t min = 0, int32_t max = 0);
-template <typename T>
-SimpleTensor<uint8_t> gemmlowp_quantize_down_int32_to_uint8_scale_by_fixedpoint(const SimpleTensor<T> &in, const SimpleTensor<T> &bias, std::vector<int32_t> result_fixedpoint_multiplier,
- std::vector<int32_t> result_shift, int32_t result_offset_after_shift, int32_t min = 0, int32_t max = 0);
-
-template <typename T>
-SimpleTensor<int16_t> gemmlowp_quantize_down_int32_to_int16_scale_by_fixedpoint(const SimpleTensor<T> &in, int32_t result_fixedpoint_multiplier, int32_t result_shift,
- int32_t min, int32_t max);
-template <typename T>
-SimpleTensor<int16_t> gemmlowp_quantize_down_int32_to_int16_scale_by_fixedpoint(const SimpleTensor<T> &in, const SimpleTensor<T> &bias, int32_t result_fixedpoint_multiplier,
- int32_t result_shift, int32_t min, int32_t max);
+template <typename TIn, typename TOut>
+SimpleTensor<TOut> gemmlowp_quantize_down_scale_by_fixedpoint(const SimpleTensor<TIn> &in, const SimpleTensor<TIn> &bias, std::vector<int32_t> result_fixedpoint_multiplier,
+ std::vector<int32_t> result_shift, int32_t result_offset_after_shift, int32_t min = 0, int32_t max = 0);
} // namespace reference
} // namespace validation
} // namespace test