COMPMID-970 : Remove QS8 / QS16 support
Removed fixed point related code.
Change-Id: I487acf138dace3b0450e0d72ca7071eaec254566
Reviewed-on: https://eu-gerrit-1.euhpc.arm.com/137678
Tested-by: Jenkins <bsgcomp@arm.com>
Reviewed-by: Anthony Barbier <anthony.barbier@arm.com>
diff --git a/src/core/NEON/kernels/NESoftmaxLayerKernel.cpp b/src/core/NEON/kernels/NESoftmaxLayerKernel.cpp
index d91efd2..9946f00 100644
--- a/src/core/NEON/kernels/NESoftmaxLayerKernel.cpp
+++ b/src/core/NEON/kernels/NESoftmaxLayerKernel.cpp
@@ -194,56 +194,7 @@
template <typename T>
T sqsub(T a, T b);
template <typename T>
-T sqmul(T a, T b, int fixed_point_position);
-
-#define DECLARE_NEON_FUNCTIONS_FOR_FIXED_POINT(TYPET, TYPEU, TAGT, TAGU) \
- inline vec_8_byte_t<TYPET> vqsub(vec_8_byte_t<TYPET> a, vec_8_byte_t<TYPET> b) \
- { \
- return vqsub_##TAGT(a, b); \
- } \
- inline vec_8_byte_t<TYPEU> vqadd(vec_8_byte_t<TYPEU> a, vec_8_byte_t<TYPEU> b) \
- { \
- return vqadd_##TAGU(a, b); \
- } \
- inline vec_16_byte_t<TYPEU> vqadd(vec_16_byte_t<TYPEU> a, vec_16_byte_t<TYPEU> b) \
- { \
- return vqaddq_##TAGU(a, b); \
- } \
- inline vec_8_byte_t<TYPET> vqexp(vec_8_byte_t<TYPET> vec, int fixed_point_position) \
- { \
- return vqexp_q##TAGT(vec, fixed_point_position); \
- } \
- inline auto vmovl(vec_8_byte_t<TYPET> vec)->decltype(vmovl_##TAGT(vec)) \
- { \
- return vmovl_##TAGT(vec); \
- } \
- inline vec_16_byte_t<TYPET> vqrecip(vec_16_byte_t<TYPET> vec, int fixed_point_position) \
- { \
- return vqrecipq_q##TAGT(vec, fixed_point_position); \
- } \
- inline vec_16_byte_t<TYPET> vqmul(vec_16_byte_t<TYPET> a, vec_16_byte_t<TYPET> b, int fixed_point_position) \
- { \
- return vqmulq_q##TAGT(a, b, fixed_point_position); \
- } \
- template <> \
- inline TYPEU sqadd<TYPEU>(TYPEU a, TYPEU b) \
- { \
- return sqadd_q##TAGU(a, b); \
- } \
- inline TYPET sqexp(TYPET val, int fixed_point_position) \
- { \
- return sqexp_q##TAGT(val, fixed_point_position); \
- } \
- template <> \
- inline TYPET sqsub<TYPET>(TYPET a, TYPET b) \
- { \
- return sqsub_q##TAGT(a, b); \
- } \
- template <> \
- inline TYPET sqmul<TYPET>(TYPET a, TYPET b, int fixed_point_position) \
- { \
- return sqmul_q##TAGT(a, b, fixed_point_position); \
- }
+T sqmul(T a, T b);
#define DECLARE_NEON_FUNCTIONS_FOR_FLOAT(TYPE, TAG) \
inline vec_8_byte_t<TYPE> vadd(vec_8_byte_t<TYPE> a, vec_8_byte_t<TYPE> b) \
@@ -278,9 +229,6 @@
#endif /* __ARM_FEATURE_FP16_VECTOR_ARITHMETIC */
DECLARE_NEON_FUNCTIONS_FOR_TYPE(float, f32)
-DECLARE_NEON_FUNCTIONS_FOR_FIXED_POINT(int8_t, int16_t, s8, s16)
-DECLARE_NEON_FUNCTIONS_FOR_FIXED_POINT(int16_t, int32_t, s16, s32)
-
#ifdef __ARM_FEATURE_FP16_VECTOR_ARITHMETIC
DECLARE_NEON_FUNCTIONS_FOR_FLOAT(float16_t, f16)
#endif /* __ARM_FEATURE_FP16_VECTOR_ARITHMETIC */
@@ -373,16 +321,15 @@
Status validate_arguments_logits_1d_max(const ITensorInfo &input, const ITensorInfo &output)
{
#ifdef __ARM_FEATURE_FP16_VECTOR_ARITHMETIC
- ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(&input, 1, DataType::QASYMM8, DataType::QS8, DataType::QS16, DataType::F16, DataType::F32);
+ ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(&input, 1, DataType::QASYMM8, DataType::F16, DataType::F32);
#else /* __ARM_FEATURE_FP16_VECTOR_ARITHMETIC */
- ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(&input, 1, DataType::QASYMM8, DataType::QS8, DataType::QS16, DataType::F32);
+ ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(&input, 1, DataType::QASYMM8, DataType::F32);
#endif /* __ARM_FEATURE_FP16_VECTOR_ARITHMETIC */
// Validate in case of configured output
if(output.total_size() != 0)
{
ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(&input, &output);
- ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_FIXED_POINT_POSITION(&input, &output);
ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_QUANTIZATION_INFO(&input, &output);
ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DIMENSIONS(output.tensor_shape(), TensorShape(input.tensor_shape()).set(0, 1));
}
@@ -395,7 +342,7 @@
// Softmax across the x dimension
const TensorShape output_shape = TensorShape(input.tensor_shape()).set(0, 1);
// Output auto initialization if not yet initialized
- auto_init_if_empty(output, output_shape, 1, input.data_type(), input.fixed_point_position(), input.quantization_info());
+ auto_init_if_empty(output, output_shape, 1, input.data_type(), input.quantization_info());
// Configure kernel window
const int input_width = input.valid_region().shape.x();
@@ -488,12 +435,6 @@
case DataType::QASYMM8:
_func = &logits_1d_max<qasymm8_t>;
break;
- case DataType::QS8:
- _func = &logits_1d_max<qint8_t>;
- break;
- case DataType::QS16:
- _func = &logits_1d_max<qint16_t>;
- break;
#ifdef __ARM_FEATURE_FP16_VECTOR_ARITHMETIC
case DataType::F16:
_func = &logits_1d_max<float16_t>;
@@ -543,11 +484,12 @@
Status validate_arguments_logits_softmax(const ITensorInfo &input, const ITensorInfo &max,
const ITensorInfo &output, const float beta, const ITensorInfo &tmp)
{
+ ARM_COMPUTE_UNUSED(beta);
// Check input
#ifdef __ARM_FEATURE_FP16_VECTOR_ARITHMETIC
- ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(&input, 1, DataType::QASYMM8, DataType::QS8, DataType::QS16, DataType::F16, DataType::F32);
+ ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(&input, 1, DataType::QASYMM8, DataType::F16, DataType::F32);
#else /* __ARM_FEATURE_FP16_VECTOR_ARITHMETIC */
- ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(&input, 1, DataType::QASYMM8, DataType::QS8, DataType::QS16, DataType::F32);
+ ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(&input, 1, DataType::QASYMM8, DataType::F32);
#endif /* __ARM_FEATURE_FP16_VECTOR_ARITHMETIC */
const bool is_quantized_asymmetric = is_data_type_quantized_asymmetric(input.data_type());
@@ -555,7 +497,6 @@
// Check max
ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(&input, &max);
ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DIMENSIONS(TensorShape(input.tensor_shape()).set(0, 1), max.tensor_shape());
- ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_FIXED_POINT_POSITION(&input, &max);
ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_QUANTIZATION_INFO(&input, &max);
// Check output if configured
@@ -564,19 +505,14 @@
const QuantizationInfo output_quantization = is_quantized_asymmetric ? QuantizationInfo(1.f / 256.f, 0) : output.quantization_info();
ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(&input, &output);
ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_SHAPES(&input, &output);
- ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_FIXED_POINT_POSITION(&input, &output);
ARM_COMPUTE_RETURN_ERROR_ON(output.quantization_info() != output_quantization);
}
- // Check beta
- ARM_COMPUTE_RETURN_ERROR_ON((beta != 1.0f) && is_data_type_fixed_point(input.data_type()));
-
// Check tmp if configured
if(tmp.total_size() != 0)
{
const DataType tmp_data_type = is_quantized_asymmetric ? DataType::F32 : input.data_type();
ARM_COMPUTE_RETURN_ERROR_ON(tmp.data_type() != tmp_data_type);
- ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_FIXED_POINT_POSITION(&input, &tmp);
// We could potentially reduce tmp memory if we could predict or make an assumption
// on the maximum number of threads that will run in parallel.
ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_SHAPES(&input, &tmp);
@@ -727,88 +663,6 @@
in_it, max_it, out_it);
}
-template <typename T, typename U>
-void logits_1d_softmax_fixed_point(const ITensor &in, const ITensor &max, void *const tmp,
- ITensor &out, const float /*beta*/, const Window &window)
-{
- const int start_x = in.info()->valid_region().anchor.x();
- const int input_width = in.info()->valid_region().shape.x();
-
- const int fixed_point_position = in.info()->fixed_point_position();
-
- Iterator in_it(&in, window);
- Iterator max_it(&max, window);
- Iterator out_it(&out, window);
-
- execute_window_loop(window, [&](const Coordinates &)
- {
- /* Get pointers */
- const auto in_ptr = reinterpret_cast<const T *>(in_it.ptr()) + start_x;
- const auto out_ptr = reinterpret_cast<T *>(out_it.ptr()) + start_x;
- const auto tmp_ptr = reinterpret_cast<T *>(tmp);
-
- vec_16_byte_t<T> vec_sum_inversed;
-
- /* Compute exponentials and sum */
- {
- /* Get max value */
- const auto max_val = *reinterpret_cast<const T *>(max_it.ptr());
- const auto vec_max = vdup_n<vec_8_byte_t<T>>(max_val);
-
- /* Init sum to zero */
- auto vec_sum = vdup_n<vec_16_byte_t<U>>(0);
-
- /* Loop over row and compute exponentials and sum */
- int i = 0;
- constexpr int vec_size = vec_size_of(vec_sum);
- for(; i <= (input_width - vec_size); i += vec_size)
- {
- auto vec_elements = vld<vec_8_byte_t<T>>(in_ptr + i);
- vec_elements = vqsub(vec_elements, vec_max);
- vec_elements = vqexp(vec_elements, fixed_point_position);
- vec_sum = vqadd(vec_sum, vmovl(vec_elements));
- vst(tmp_ptr + i, vec_elements);
- }
- /* Reduce sum */
- const vec_8_byte_t<U> sum_8_byte = vqadd(vget_high(vec_sum), vget_low(vec_sum));
- U sum = reduce_add(sqadd<U>, sum_8_byte);
-
- /* Run remaining elements */
- for(; i < input_width; ++i)
- {
- T element = sqexp(sqsub(in_ptr[i], max_val), fixed_point_position);
- sum = sqadd<U>(sum, element);
- tmp_ptr[i] = element;
- }
-
- const auto qsum = utility::saturate_cast<T>(sum);
- vec_sum_inversed = vqrecip(vdup_n<vec_16_byte_t<T>>(qsum), fixed_point_position);
- }
-
- /* Normalize exponentials */
- {
- /* Loop over row and compute softmax */
- int i = 0;
- constexpr int vec_size = vec_size_of(vec_sum_inversed);
- for(; i <= (input_width - vec_size); i += vec_size)
- {
- const auto vec_in = vld<vec_16_byte_t<T>>(tmp_ptr + i);
- const vec_16_byte_t<T> normalized_value = vqmul(vec_in, vec_sum_inversed, fixed_point_position);
- vst(out_ptr + i, normalized_value);
- }
-
- const T sum_inversed = vget_lane<0>(vec_sum_inversed);
-
- /* Run remaining elements */
- for(; i < input_width; ++i)
- {
- out_ptr[i] = sqmul(tmp_ptr[i], sum_inversed, fixed_point_position);
- }
- }
- },
- in_it, max_it, out_it);
-}
-
template <typename T>
void logits_1d_softmax_float(const ITensor &in, const ITensor &max, void *const tmp,
ITensor &out, const float beta, const Window &window)
@@ -908,12 +762,6 @@
case DataType::QASYMM8:
_func = &logits_1d_softmax_qasymm8;
break;
- case DataType::QS8:
- _func = &logits_1d_softmax_fixed_point<qint8_t, qint16_t>;
- break;
- case DataType::QS16:
- _func = &logits_1d_softmax_fixed_point<qint16_t, qint32_t>;
- break;
#ifdef __ARM_FEATURE_FP16_VECTOR_ARITHMETIC
case DataType::F16:
_func = &logits_1d_softmax_float<float16_t>;