COMPMID-2980 (Nightly) armv7a build failures
Change-Id: I8c2a20fc345694d1ad6e0fe63e4f22fb73e6c1df
Signed-off-by: Michalis Spyrou <michalis.spyrou@arm.com>
Signed-off-by: Michele Di Giorgio <michele.digiorgio@arm.com>
Reviewed-on: https://review.mlplatform.org/c/2463
Tested-by: Arm Jenkins <bsgcomp@arm.com>
diff --git a/arm_compute/core/CPP/Validate.h b/arm_compute/core/CPP/Validate.h
index 1ec41a9..f195a31 100644
--- a/arm_compute/core/CPP/Validate.h
+++ b/arm_compute/core/CPP/Validate.h
@@ -37,15 +37,15 @@
*
* @return Status
*/
-inline arm_compute::Status error_on_unsupported_cpu_fp16(const char *function, const char *file, const int line,
- const ITensorInfo *tensor_info)
+inline Status error_on_unsupported_cpu_fp16(const char *function, const char *file, const int line,
+ const ITensorInfo *tensor_info)
{
ARM_COMPUTE_RETURN_ERROR_ON_LOC(tensor_info == nullptr, function, file, line);
#ifndef __ARM_FEATURE_FP16_VECTOR_ARITHMETIC
ARM_COMPUTE_RETURN_ERROR_ON_LOC_MSG(tensor_info->data_type() == DataType::F16,
function, file, line, "This CPU architecture does not support F16 data type, you need v8.2 or above");
#endif /* __ARM_FEATURE_FP16_VECTOR_ARITHMETIC */
- return arm_compute::Status {};
+ return Status {};
}
/** Return an error if the data type of the passed tensor is FP16 and FP16 support is not compiled in.
@@ -57,12 +57,12 @@
*
* @return Status
*/
-inline arm_compute::Status error_on_unsupported_cpu_fp16(const char *function, const char *file, const int line,
- const ITensor *tensor)
+inline Status error_on_unsupported_cpu_fp16(const char *function, const char *file, const int line,
+ const ITensor *tensor)
{
ARM_COMPUTE_RETURN_ERROR_ON_LOC(tensor == nullptr, function, file, line);
ARM_COMPUTE_RETURN_ON_ERROR(::arm_compute::error_on_unsupported_cpu_fp16(function, file, line, tensor->info()));
- return arm_compute::Status{};
+ return Status{};
}
#define ARM_COMPUTE_ERROR_ON_CPU_F16_UNSUPPORTED(tensor) \
diff --git a/arm_compute/core/NEON/kernels/convolution/depthwise/depthwise_quantized.hpp b/arm_compute/core/NEON/kernels/convolution/depthwise/depthwise_quantized.hpp
index ef3adc4..37c1f1b 100644
--- a/arm_compute/core/NEON/kernels/convolution/depthwise/depthwise_quantized.hpp
+++ b/arm_compute/core/NEON/kernels/convolution/depthwise/depthwise_quantized.hpp
@@ -31,31 +31,21 @@
using namespace neon_convolution_kernels;
using namespace qasymm8;
-template <typename T, typename U = int32_t>
-inline T saturating_doubling_high_mul(const T&, const U&);
-
-template <>
inline int32x4_t saturating_doubling_high_mul(const int32x4_t& a, const int32x4_t& b)
{
return vqrdmulhq_s32(a, b);
}
-template <>
inline int32x4_t saturating_doubling_high_mul(const int32x4_t& a, const int32_t& b)
{
return vqrdmulhq_n_s32(a, b);
}
-template <>
inline int32_t saturating_doubling_high_mul(const int32_t& a, const int32_t& b)
{
return vget_lane_s32(vqrdmulh_n_s32(vdup_n_s32(a), b), 0);
}
-template <typename T, typename U = int32_t>
-inline T rounding_divide_by_exp2(const T& x, const U exponent);
-
-template <>
inline int32x4_t rounding_divide_by_exp2(const int32x4_t& x, const int32x4_t shift)
{
const int32x4_t fixup = vshrq_n_s32(vandq_s32(x, shift), 31);
@@ -63,7 +53,6 @@
return vrshlq_s32(fixed, shift);
}
-template <>
inline int32x4_t rounding_divide_by_exp2(const int32x4_t& x, const int exponent)
{
const int32x4_t shift = vdupq_n_s32(-exponent);
@@ -72,7 +61,6 @@
return vrshlq_s32(fixed, shift);
}
-template <>
inline int32x2_t rounding_divide_by_exp2(const int32x2_t& x, const int exponent)
{
const int32x2_t shift = vdup_n_s32(-exponent);
@@ -81,7 +69,6 @@
return vrshl_s32(fixed, shift);
}
-template <>
inline int32_t rounding_divide_by_exp2(const int32_t& x, const int exponent)
{
const int32x2_t xs = vdup_n_s32(x);
diff --git a/arm_compute/core/PixelValue.h b/arm_compute/core/PixelValue.h
index 8c2ab92..52b1f65 100644
--- a/arm_compute/core/PixelValue.h
+++ b/arm_compute/core/PixelValue.h
@@ -103,6 +103,15 @@
break;
}
}
+ /** Initialize the union with a S8 pixel value
+ *
+ * @param[in] v S8 value.
+ */
+ PixelValue(int8_t v)
+ : PixelValue()
+ {
+ value.s8 = v;
+ }
/** Initialize the union with a U8 pixel value
*
* @param[in] v U8 value.
diff --git a/arm_compute/core/Types.h b/arm_compute/core/Types.h
index c281312..901d080 100644
--- a/arm_compute/core/Types.h
+++ b/arm_compute/core/Types.h
@@ -1876,11 +1876,11 @@
struct GEMMLowpOutputStageInfo
{
GEMMLowpOutputStageType type{ GEMMLowpOutputStageType::NONE }; /**< GEMMLowp output stage type */
- int gemmlowp_offset{ 0 }; /**< GEMMLowp output stage offset used for quantizing to QASYMM8 */
- int gemmlowp_multiplier{ 0 }; /**< GEMMLowp output stage multiplier used for quantizing to QASYMM8 */
- int gemmlowp_shift{ 0 }; /**< GEMMLowp output stage shift used for quantizing to uint8 */
- int gemmlowp_min_bound{ 0 }; /**< GEMMLowp min value used to saturate down the output result before converting back to QASYMM8 */
- int gemmlowp_max_bound{ 0 }; /**< GEMMLowp max value used to saturate down the output result before converting back to QASYMM8 */
+ int32_t gemmlowp_offset{ 0 }; /**< GEMMLowp output stage offset used for quantizing to QASYMM8 */
+ int32_t gemmlowp_multiplier{ 0 }; /**< GEMMLowp output stage multiplier used for quantizing to QASYMM8 */
+ int32_t gemmlowp_shift{ 0 }; /**< GEMMLowp output stage shift used for quantizing to uint8 */
+ int32_t gemmlowp_min_bound{ 0 }; /**< GEMMLowp min value used to saturate down the output result before converting back to QASYMM8 */
+ int32_t gemmlowp_max_bound{ 0 }; /**< GEMMLowp max value used to saturate down the output result before converting back to QASYMM8 */
std::vector<int32_t> gemmlowp_multipliers{}; /**< GEMMLowp output stage multiplier used for quantizing to QASYMM8 */
std::vector<int32_t> gemmlowp_shifts{}; /**< GEMMLowp output stage multiplier used for quantizing to QASYMM8 */
bool is_quantized_per_channel{ false }; /**< GEMMLowp quantized per-channel flag */
diff --git a/arm_compute/core/Utils.h b/arm_compute/core/Utils.h
index c11fffe..18c5471 100644
--- a/arm_compute/core/Utils.h
+++ b/arm_compute/core/Utils.h
@@ -557,15 +557,15 @@
*/
inline std::tuple<PixelValue, PixelValue> get_min_max(DataType dt)
{
- PixelValue min(0);
- PixelValue max(0);
+ PixelValue min{};
+ PixelValue max{};
switch(dt)
{
case DataType::U8:
case DataType::QASYMM8:
{
- min = PixelValue(std::numeric_limits<uint8_t>::lowest());
- max = PixelValue(std::numeric_limits<uint8_t>::max());
+ min = PixelValue(static_cast<int32_t>(std::numeric_limits<uint8_t>::lowest()));
+ max = PixelValue(static_cast<int32_t>(std::numeric_limits<uint8_t>::max()));
break;
}
case DataType::S8:
@@ -573,22 +573,22 @@
case DataType::QASYMM8_SIGNED:
case DataType::QSYMM8_PER_CHANNEL:
{
- min = PixelValue(std::numeric_limits<int8_t>::lowest());
- max = PixelValue(std::numeric_limits<int8_t>::max());
+ min = PixelValue(static_cast<int32_t>(std::numeric_limits<int8_t>::lowest()));
+ max = PixelValue(static_cast<int32_t>(std::numeric_limits<int8_t>::max()));
break;
}
case DataType::U16:
case DataType::QASYMM16:
{
- min = PixelValue(std::numeric_limits<uint16_t>::lowest());
- max = PixelValue(std::numeric_limits<uint16_t>::max());
+ min = PixelValue(static_cast<int32_t>(std::numeric_limits<uint16_t>::lowest()));
+ max = PixelValue(static_cast<int32_t>(std::numeric_limits<uint16_t>::max()));
break;
}
case DataType::S16:
case DataType::QSYMM16:
{
- min = PixelValue(std::numeric_limits<int16_t>::lowest());
- max = PixelValue(std::numeric_limits<int16_t>::max());
+ min = PixelValue(static_cast<int32_t>(std::numeric_limits<int16_t>::lowest()));
+ max = PixelValue(static_cast<int32_t>(std::numeric_limits<int16_t>::max()));
break;
}
case DataType::U32:
diff --git a/arm_compute/core/utils/quantization/AsymmHelpers.h b/arm_compute/core/utils/quantization/AsymmHelpers.h
index f0b0770..1bdc995 100644
--- a/arm_compute/core/utils/quantization/AsymmHelpers.h
+++ b/arm_compute/core/utils/quantization/AsymmHelpers.h
@@ -40,7 +40,7 @@
*
* @return a status
*/
-Status calculate_quantized_multiplier(float multiplier, int *quant_multiplier, int *shift);
+Status calculate_quantized_multiplier(float multiplier, int32_t *quant_multiplier, int32_t *shift);
/** Calculate quantized representation of multiplier with value less than one.
*
* @param[in] multiplier Real multiplier.
@@ -49,7 +49,7 @@
*
* @return a status
*/
-Status calculate_quantized_multiplier_less_than_one(float multiplier, int *quant_multiplier, int *right_shift);
+Status calculate_quantized_multiplier_less_than_one(float multiplier, int32_t *quant_multiplier, int32_t *right_shift);
/** Calculate quantized representation of multiplier having value greater than one.
*
* @param[in] multiplier Real multiplier.
@@ -58,7 +58,7 @@
*
* @return a status
*/
-Status calculate_quantized_multiplier_greater_than_one(float multiplier, int *quantized_multiplier, int *left_shift);
+Status calculate_quantized_multiplier_greater_than_one(float multiplier, int32_t *quantized_multiplier, int32_t *left_shift);
/** Calculate quantized representation of per-channel multipliers with value less than one.
*
diff --git a/src/core/NEON/kernels/NEDepthwiseConvolutionLayerNativeKernel.cpp b/src/core/NEON/kernels/NEDepthwiseConvolutionLayerNativeKernel.cpp
index a0d45af..a9a3183 100644
--- a/src/core/NEON/kernels/NEDepthwiseConvolutionLayerNativeKernel.cpp
+++ b/src/core/NEON/kernels/NEDepthwiseConvolutionLayerNativeKernel.cpp
@@ -528,8 +528,8 @@
for(size_t i = 0; i < weights_scale.size(); ++i)
{
- int out_mult = 0;
- int out_shift = 0;
+ int32_t out_mult = 0;
+ int32_t out_shift = 0;
const float multiplier = input_scale * weights_scale.at(i) / output_scale;
ARM_COMPUTE_ERROR_ON(multiplier > 1.f);
arm_compute::quantization::calculate_quantized_multiplier_less_than_one(multiplier, &out_mult, &out_shift);
diff --git a/src/core/utils/quantization/AsymmHelpers.cpp b/src/core/utils/quantization/AsymmHelpers.cpp
index 6196662..11241e8 100644
--- a/src/core/utils/quantization/AsymmHelpers.cpp
+++ b/src/core/utils/quantization/AsymmHelpers.cpp
@@ -35,7 +35,7 @@
constexpr int64_t fixed_point_one_Q0 = (1LL << 31);
constexpr float epsilon = 0.00001f;
-Status calculate_quantized_multiplier(float multiplier, int *quant_multiplier, int *shift)
+Status calculate_quantized_multiplier(float multiplier, int32_t *quant_multiplier, int32_t *shift)
{
if(multiplier >= 1.f)
{
@@ -49,9 +49,9 @@
}
}
-Status calculate_quantized_multiplier_less_than_one(float multiplier,
- int *quant_multiplier,
- int *right_shift)
+Status calculate_quantized_multiplier_less_than_one(float multiplier,
+ int32_t *quant_multiplier,
+ int32_t *right_shift)
{
ARM_COMPUTE_RETURN_ERROR_ON(quant_multiplier == nullptr);
ARM_COMPUTE_RETURN_ERROR_ON(right_shift == nullptr);
@@ -64,9 +64,10 @@
return Status{};
}
- const double q = std::frexp(multiplier, right_shift);
- *right_shift *= -1;
- auto q_fixed = static_cast<int64_t>(support::cpp11::round(q * fixed_point_one_Q0));
+ int shift_exp = 0;
+ const double q = std::frexp(multiplier, &shift_exp);
+ *right_shift = -1 * shift_exp;
+ auto q_fixed = static_cast<int64_t>(support::cpp11::round(q * fixed_point_one_Q0));
ARM_COMPUTE_RETURN_ERROR_ON(q_fixed > fixed_point_one_Q0);
if(q_fixed == fixed_point_one_Q0)
{
@@ -80,15 +81,18 @@
return Status{};
}
-Status calculate_quantized_multiplier_greater_than_one(float multiplier,
- int *quantized_multiplier,
- int *left_shift)
+Status calculate_quantized_multiplier_greater_than_one(float multiplier,
+ int32_t *quantized_multiplier,
+ int32_t *left_shift)
{
ARM_COMPUTE_RETURN_ERROR_ON(quantized_multiplier == nullptr);
ARM_COMPUTE_RETURN_ERROR_ON(left_shift == nullptr);
ARM_COMPUTE_RETURN_ERROR_ON(multiplier < 1.f);
- const double q = std::frexp(multiplier, left_shift);
- auto q_fixed = static_cast<int64_t>(support::cpp11::round(q * fixed_point_one_Q0));
+
+ int shift_exp = 0;
+ const double q = std::frexp(multiplier, &shift_exp);
+ *left_shift = shift_exp;
+ auto q_fixed = static_cast<int64_t>(support::cpp11::round(q * fixed_point_one_Q0));
ARM_COMPUTE_RETURN_ERROR_ON(q_fixed > fixed_point_one_Q0);
if(q_fixed == fixed_point_one_Q0)
{
@@ -125,8 +129,8 @@
for(unsigned int i = 0; i < size; ++i)
{
const float multiplier = i_scale * w_scales[i] / o_scale;
- int quant_multiplier = 0;
- int quant_shift = 0;
+ int32_t quant_multiplier = 0;
+ int32_t quant_shift = 0;
ARM_COMPUTE_RETURN_ON_ERROR(calculate_quantized_multiplier_less_than_one(multiplier, &quant_multiplier, &quant_shift));
quant_multipliers[i] = quant_multiplier;
quant_shifts[i] = quant_shift;
@@ -181,8 +185,8 @@
for(unsigned int i = 0; i < num_filters; ++i)
{
- int output_multiplier = 0;
- int output_shift = 0;
+ int32_t output_multiplier = 0;
+ int32_t output_shift = 0;
const float multiplier = iq_info.scale * wq_info.scale()[i] / oq_info.scale;
calculate_quantized_multiplier(multiplier, &output_multiplier, &output_shift);
diff --git a/src/runtime/NEON/functions/NEDepthwiseConvolutionLayer.cpp b/src/runtime/NEON/functions/NEDepthwiseConvolutionLayer.cpp
index 5e47dd5..ca4fe73 100644
--- a/src/runtime/NEON/functions/NEDepthwiseConvolutionLayer.cpp
+++ b/src/runtime/NEON/functions/NEDepthwiseConvolutionLayer.cpp
@@ -202,9 +202,9 @@
const UniformQuantizationInfo wq_info = weights->info()->quantization_info().uniform();
const UniformQuantizationInfo oq_info = (output->info()->total_size() == 0) ? iq_info : output->info()->quantization_info().uniform();
- float multiplier = (iq_info.scale * wq_info.scale) / oq_info.scale;
- int output_multiplier;
- int output_shift;
+ float multiplier = (iq_info.scale * wq_info.scale) / oq_info.scale;
+ int32_t output_multiplier;
+ int32_t output_shift;
quantization::calculate_quantized_multiplier_less_than_one(multiplier, &output_multiplier, &output_shift);
_output_stage_kernel.configure(&_accumulator, biases, _is_nchw ? output : &_permuted_output, output_multiplier, output_shift, oq_info.offset);
_accumulator.allocator()->allocate();
diff --git a/src/runtime/NEON/functions/NEFullyConnectedLayer.cpp b/src/runtime/NEON/functions/NEFullyConnectedLayer.cpp
index ee622f4..b3b90f8 100644
--- a/src/runtime/NEON/functions/NEFullyConnectedLayer.cpp
+++ b/src/runtime/NEON/functions/NEFullyConnectedLayer.cpp
@@ -255,9 +255,9 @@
const UniformQuantizationInfo wq_info = weights->info()->quantization_info().uniform();
const UniformQuantizationInfo oq_info = output->info()->quantization_info().uniform();
- float multiplier = (iq_info.scale * wq_info.scale) / oq_info.scale;
- int output_multiplier;
- int output_shift;
+ float multiplier = (iq_info.scale * wq_info.scale) / oq_info.scale;
+ int32_t output_multiplier;
+ int32_t output_shift;
quantization::calculate_quantized_multiplier_less_than_one(multiplier, &output_multiplier, &output_shift);
_gemmlowp_output_stage.configure(&_gemmlowp_output, biases, output, output_multiplier, output_shift, oq_info.offset);
_gemmlowp_output.allocator()->allocate();
diff --git a/src/runtime/NEON/functions/NEGEMMConvolutionLayer.cpp b/src/runtime/NEON/functions/NEGEMMConvolutionLayer.cpp
index bb9620b..0507c6b 100644
--- a/src/runtime/NEON/functions/NEGEMMConvolutionLayer.cpp
+++ b/src/runtime/NEON/functions/NEGEMMConvolutionLayer.cpp
@@ -33,7 +33,8 @@
#include <set>
#include <tuple>
-using namespace arm_compute;
+namespace arm_compute
+{
using namespace arm_compute::misc::shape_calculator;
NEConvolutionLayerReshapeWeights::NEConvolutionLayerReshapeWeights()
@@ -131,11 +132,11 @@
}
// Merge activation with output stage
- PixelValue type_min = 0;
- PixelValue type_max = 0;
+ PixelValue type_min{};
+ PixelValue type_max{};
std::tie(type_min, type_max) = get_min_max(data_type);
- int min_activation = type_min.get<int>();
- int max_activation = type_max.get<int>();
+ int32_t min_activation = type_min.get<int32_t>();
+ int32_t max_activation = type_max.get<int32_t>();
if(supported_acts.count(act_info.activation()) != 0)
{
@@ -190,11 +191,11 @@
const UniformQuantizationInfo uoqinfo = oqinfo.uniform();
// Merge activation with output stage
- PixelValue type_min = 0;
- PixelValue type_max = 0;
+ PixelValue type_min{};
+ PixelValue type_max{};
std::tie(type_min, type_max) = get_min_max(data_type);
- int min_activation = type_min.get<int>();
- int max_activation = type_max.get<int>();
+ int32_t min_activation = type_min.get<int32_t>();
+ int32_t max_activation = type_max.get<int32_t>();
const std::set<ActivationLayerInfo::ActivationFunction> supported_acts = { ActivationLayerInfo::ActivationFunction::RELU,
ActivationLayerInfo::ActivationFunction::BOUNDED_RELU,
@@ -595,3 +596,4 @@
_is_prepared = true;
}
}
+} // namespace arm_compute
diff --git a/src/runtime/NEON/functions/NELSTMLayerQuantized.cpp b/src/runtime/NEON/functions/NELSTMLayerQuantized.cpp
index cfd996b..cdfc035 100644
--- a/src/runtime/NEON/functions/NELSTMLayerQuantized.cpp
+++ b/src/runtime/NEON/functions/NELSTMLayerQuantized.cpp
@@ -136,8 +136,8 @@
_output_lowp.allocator()->init(TensorInfo(_output_highp.info()->tensor_shape(), 1, DataType::QSYMM16, qsymm_3));
const float multiplier = 4096.f * qasymm.uniform().scale * qweights.uniform().scale;
- int output_multiplier = 0;
- int output_shift = 0;
+ int32_t output_multiplier = 0;
+ int32_t output_shift = 0;
quantization::calculate_quantized_multiplier(multiplier, &output_multiplier, &output_shift);
_memory_group.manage(&_output_lowp);
@@ -342,8 +342,8 @@
const TensorInfo output_lowp(output_highp.tensor_shape(), 1, DataType::QSYMM16, qsymm_3);
const float multiplier = 4096.f * qasymm.uniform().scale * qweights.uniform().scale;
- int output_multiplier = 0;
- int output_shift = 0;
+ int32_t output_multiplier = 0;
+ int32_t output_shift = 0;
ARM_COMPUTE_RETURN_ON_ERROR(quantization::calculate_quantized_multiplier(multiplier, &output_multiplier, &output_shift));
// _output_stage
diff --git a/src/runtime/NEON/functions/assembly/NEDepthwiseConvolutionAssemblyDispatch.cpp b/src/runtime/NEON/functions/assembly/NEDepthwiseConvolutionAssemblyDispatch.cpp
index c564e22..3235eee 100644
--- a/src/runtime/NEON/functions/assembly/NEDepthwiseConvolutionAssemblyDispatch.cpp
+++ b/src/runtime/NEON/functions/assembly/NEDepthwiseConvolutionAssemblyDispatch.cpp
@@ -263,8 +263,8 @@
// Calculate rescale parameters
const float fmultipler = iqinfo.scale * wqinfo.scale / oqinfo.scale;
- int qmultiplier = 0;
- int qshift = 0;
+ int32_t qmultiplier = 0;
+ int32_t qshift = 0;
quantization::calculate_quantized_multiplier_less_than_one(fmultipler, &qmultiplier, &qshift);
qasymm8::QAsymm8RescaleParams rescale_params(qshift, qmultiplier, fmultipler);
@@ -285,15 +285,15 @@
const qasymm8::QAsymm8Params oqinfo{ static_cast<uint8_t>(output_qinfo.offset), output_qinfo.scale };
// Calculate rescale parameters
- std::vector<float> fmultipliers;
- std::vector<int> qmultipliers;
- std::vector<int> qshifts;
+ std::vector<float> fmultipliers;
+ std::vector<int32_t> qmultipliers;
+ std::vector<int32_t> qshifts;
for(auto const s : wqinfo.scales)
{
const float fmultipler = iqinfo.scale * s / oqinfo.scale;
- int qmultiplier = 0;
- int qshift = 0;
+ int32_t qmultiplier = 0;
+ int32_t qshift = 0;
quantization::calculate_quantized_multiplier_less_than_one(fmultipler, &qmultiplier, &qshift);
fmultipliers.push_back(fmultipler);
qmultipliers.push_back(qmultiplier);