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-rw-r--r--arm_compute/core/Helpers.h20
-rw-r--r--arm_compute/core/Helpers.inl19
-rw-r--r--arm_compute/core/Utils.h39
-rw-r--r--src/core/CL/kernels/CLActivationLayerKernel.cpp85
4 files changed, 122 insertions, 41 deletions
diff --git a/arm_compute/core/Helpers.h b/arm_compute/core/Helpers.h
index 6e4d987180..edb05e99a1 100644
--- a/arm_compute/core/Helpers.h
+++ b/arm_compute/core/Helpers.h
@@ -466,10 +466,15 @@ inline Strides compute_strides(const ITensorInfo &info)
* @param[in] num_channels New number of channels.
* @param[in] data_type New data type
* @param[in] fixed_point_position New fixed point position
+ * @param[in] quantization_info (Optional) New quantization info
*
* @return True if the tensor info has been initialized
*/
-bool auto_init_if_empty(ITensorInfo &info, const TensorShape &shape, int num_channels, DataType data_type, int fixed_point_position);
+bool auto_init_if_empty(ITensorInfo &info,
+ const TensorShape &shape,
+ int num_channels, DataType data_type,
+ int fixed_point_position,
+ QuantizationInfo quantization_info = QuantizationInfo());
/* Set the shape to the specified value if the current assignment is empty.
*
@@ -509,6 +514,17 @@ bool set_data_type_if_unknown(ITensorInfo &info, DataType data_type);
* @return True if the fixed point position has been changed.
*/
bool set_fixed_point_position_if_zero(ITensorInfo &info, int fixed_point_position);
+
+/* Set the quantization info to the specified value if
+ * the current quantization info is empty and the data type of asymmetric quantized type
+ *
+ * @param[in,out] info Tensor info used to check and assign.
+ * @param[in] quantization_info Quantization info
+ *
+ * @return True if the quantization info has been changed.
+ */
+bool set_quantization_info_if_empty(ITensorInfo &info, QuantizationInfo quantization_info);
+
/** Helper function to calculate the Valid Region for Scale.
*
* @param[in] src_info Input tensor info used to check.
@@ -520,6 +536,7 @@ bool set_fixed_point_position_if_zero(ITensorInfo &info, int fixed_point_positio
* @return The corrispondent valid region
*/
ValidRegion calculate_valid_region_scale(const ITensorInfo &src_info, const TensorShape &dst_shape, InterpolationPolicy policy, BorderSize border_size, bool border_undefined);
+
/** Convert a linear index into n-dimensional coordinates.
*
* @param[in] shape Shape of the n-dimensional tensor.
@@ -528,6 +545,7 @@ ValidRegion calculate_valid_region_scale(const ITensorInfo &src_info, const Tens
* @return n-dimensional coordinates.
*/
inline Coordinates index2coords(const TensorShape &shape, int index);
+
/** Convert n-dimensional coordinates into a linear index.
*
* @param[in] shape Shape of the n-dimensional tensor.
diff --git a/arm_compute/core/Helpers.inl b/arm_compute/core/Helpers.inl
index de6c85ec76..1a27684c9c 100644
--- a/arm_compute/core/Helpers.inl
+++ b/arm_compute/core/Helpers.inl
@@ -197,7 +197,12 @@ inline void Iterator::reset(const size_t dimension)
}
}
-inline bool auto_init_if_empty(ITensorInfo &info, const TensorShape &shape, int num_channels, DataType data_type, int fixed_point_position)
+inline bool auto_init_if_empty(ITensorInfo &info,
+ const TensorShape &shape,
+ int num_channels,
+ DataType data_type,
+ int fixed_point_position,
+ QuantizationInfo quantization_info)
{
if(info.tensor_shape().total_size() == 0)
{
@@ -205,6 +210,7 @@ inline bool auto_init_if_empty(ITensorInfo &info, const TensorShape &shape, int
info.set_num_channels(num_channels);
info.set_tensor_shape(shape);
info.set_fixed_point_position(fixed_point_position);
+ info.set_quantization_info(quantization_info);
return true;
}
@@ -255,6 +261,17 @@ inline bool set_fixed_point_position_if_zero(ITensorInfo &info, int fixed_point_
return false;
}
+inline bool set_quantization_info_if_empty(ITensorInfo &info, QuantizationInfo quantization_info)
+{
+ if(info.quantization_info().empty() && (is_data_type_assymetric(info.data_type())))
+ {
+ info.set_quantization_info(quantization_info);
+ return true;
+ }
+
+ return false;
+}
+
inline ValidRegion calculate_valid_region_scale(const ITensorInfo &src_info, const TensorShape &dst_shape, InterpolationPolicy policy, BorderSize border_size, bool border_undefined)
{
const auto wr = static_cast<float>(dst_shape[0]) / static_cast<float>(src_info.tensor_shape()[0]);
diff --git a/arm_compute/core/Utils.h b/arm_compute/core/Utils.h
index 149e404f5b..8e15a0a988 100644
--- a/arm_compute/core/Utils.h
+++ b/arm_compute/core/Utils.h
@@ -708,6 +708,28 @@ inline bool is_data_type_float(DataType dt)
}
}
+/** Check if a given data type is of quantized type
+ *
+ * @note Quantized is considered a super-set of fixed-point and asymmetric data types.
+ *
+ * @param[in] dt Input data type.
+ *
+ * @return True if data type is of quantized type, else false.
+ */
+inline bool is_data_type_quantized(DataType dt)
+{
+ switch(dt)
+ {
+ case DataType::QS8:
+ case DataType::QASYMM8:
+ case DataType::QS16:
+ case DataType::QS32:
+ return true;
+ default:
+ return false;
+ }
+}
+
/** Check if a given data type is of fixed point type
*
* @param[in] dt Input data type.
@@ -727,6 +749,23 @@ inline bool is_data_type_fixed_point(DataType dt)
}
}
+/** Check if a given data type is of asymmetric quantized type
+ *
+ * @param[in] dt Input data type.
+ *
+ * @return True if data type is of symmetric quantized type, else false.
+ */
+inline bool is_data_type_assymetric(DataType dt)
+{
+ switch(dt)
+ {
+ case DataType::QASYMM8:
+ return true;
+ default:
+ return false;
+ }
+}
+
/** Create a string with the float in full precision.
*
* @param val Floating point value
diff --git a/src/core/CL/kernels/CLActivationLayerKernel.cpp b/src/core/CL/kernels/CLActivationLayerKernel.cpp
index bed407a3d1..42f577cb7d 100644
--- a/src/core/CL/kernels/CLActivationLayerKernel.cpp
+++ b/src/core/CL/kernels/CLActivationLayerKernel.cpp
@@ -51,18 +51,18 @@ CLActivationLayerKernel::CLActivationLayerKernel()
void CLActivationLayerKernel::configure(ICLTensor *input, ICLTensor *output, ActivationLayerInfo act_info)
{
ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::U8, DataType::QS8, DataType::QS16, DataType::F16, DataType::F32, DataType::QASYMM8);
-
- // For QA8 only lower/upper bounded relu is supported
- if(input->info()->data_type() == DataType::QASYMM8)
- {
- ARM_COMPUTE_ERROR_ON_MSG(act_info.activation() != ActivationLayerInfo::ActivationFunction::LU_BOUNDED_RELU,
- "For QASYMM8 only lower/upper bounded relu is supported");
- }
+ ARM_COMPUTE_ERROR_ON_MSG((input->info()->data_type() == DataType::QASYMM8) && (act_info.activation() != ActivationLayerInfo::ActivationFunction::LU_BOUNDED_RELU),
+ "For QASYMM8 only lower/upper bounded relu is supported");
if(output != nullptr)
{
// Output auto inizialitation if not yet initialized
- auto_init_if_empty(*output->info(), input->info()->tensor_shape(), 1, input->info()->data_type(), input->info()->fixed_point_position());
+ auto_init_if_empty(*output->info(),
+ input->info()->tensor_shape(),
+ 1,
+ input->info()->data_type(),
+ input->info()->fixed_point_position(),
+ input->info()->quantization_info());
ARM_COMPUTE_ERROR_ON_MISMATCHING_SHAPES(input, output);
ARM_COMPUTE_ERROR_ON_MISMATCHING_DATA_TYPES(input, output);
@@ -70,63 +70,70 @@ void CLActivationLayerKernel::configure(ICLTensor *input, ICLTensor *output, Act
}
const unsigned int num_elems_processed_per_iteration = 16 / input->info()->element_size();
+ DataType dt = input->info()->data_type();
const int fixed_point_position = input->info()->fixed_point_position();
float a_const = act_info.a();
float b_const = act_info.b();
- if(is_data_type_fixed_point(input->info()->data_type()))
+ int a_const_int = 0;
+ int b_const_int = 0;
+
+ // Create quantized version of constants a, b if needed
+ if(is_data_type_quantized(dt))
{
- a_const = static_cast<int>(lround(a_const * (1 << fixed_point_position)));
- b_const = static_cast<int>(lround(b_const * (1 << fixed_point_position)));
+ if(is_data_type_fixed_point(dt))
+ {
+ a_const_int = static_cast<int>(lround(a_const * (1 << fixed_point_position)));
+ b_const_int = static_cast<int>(lround(b_const * (1 << fixed_point_position)));
+ }
+ else
+ {
+ a_const_int = input->info()->quantization_info().quantize(a_const);
+ b_const_int = input->info()->quantization_info().quantize(b_const);
+ }
}
// Set build options
std::set<std::string> build_opts;
build_opts.emplace(("-DACT=" + lower_string(string_from_activation_func(act_info.activation()))));
- build_opts.emplace(("-DDATA_TYPE=" + get_cl_type_from_data_type(input->info()->data_type())));
+ build_opts.emplace(("-DDATA_TYPE=" + get_cl_type_from_data_type(dt)));
build_opts.emplace(("-DVEC_SIZE=" + support::cpp11::to_string(num_elems_processed_per_iteration)));
- if(input->info()->data_type() == DataType::QASYMM8)
+ if(is_data_type_quantized(dt))
{
- // For lower/upper bounded relu make sure that the min/max values are in the quantized input space
- int a_const_u8 = input->info()->quantization_info().quantize(a_const);
- int b_const_u8 = input->info()->quantization_info().quantize(b_const);
+ build_opts.emplace(("-DA_VAL=" + support::cpp11::to_string(a_const_int)));
+ build_opts.emplace(("-DB_VAL=" + support::cpp11::to_string(b_const_int)));
- build_opts.emplace(("-DA_VAL=" + support::cpp11::to_string(a_const_u8)));
- build_opts.emplace(("-DB_VAL=" + support::cpp11::to_string(b_const_u8)));
+ // Set scale and offset of the input and output
+ if(is_data_type_assymetric(dt))
+ {
+ float s1 = input->info()->quantization_info().scale;
+ int o1 = input->info()->quantization_info().offset;
+ // If output is nullptr, assume same quantization scale/offset as input
+ float s2 = output != nullptr ? output->info()->quantization_info().scale : s1;
+ int o2 = output != nullptr ? output->info()->quantization_info().offset : o1;
+ build_opts.emplace(("-DS1_VAL=" + float_to_string_with_full_precision(s1)));
+ build_opts.emplace(("-DS2_VAL=" + float_to_string_with_full_precision(s2)));
+ build_opts.emplace(("-DO1_VAL=" + support::cpp11::to_string(o1)));
+ build_opts.emplace(("-DO2_VAL=" + support::cpp11::to_string(o2)));
+ }
}
else
{
- build_opts.emplace(("-DA_VAL=" + support::cpp11::to_string(a_const)));
- build_opts.emplace(("-DB_VAL=" + support::cpp11::to_string(b_const)));
+ build_opts.emplace(("-DA_VAL=" + float_to_string_with_full_precision(a_const)));
+ build_opts.emplace(("-DB_VAL=" + float_to_string_with_full_precision(b_const)));
}
build_opts.emplace(output == nullptr ? "-DIN_PLACE" : "");
- if(is_data_type_fixed_point(input->info()->data_type()))
+ if(is_data_type_fixed_point(dt))
{
build_opts.emplace(("-DFIXED_POINT_POSITION=" + support::cpp11::to_string(fixed_point_position)));
}
// Create kernel
- if(input->info()->data_type() == DataType::QASYMM8)
- {
- float s1 = input->info()->quantization_info().scale;
- float o1 = input->info()->quantization_info().offset;
- // If output is nullptr, assume same quantization scale/offset as input
- float s2 = output != nullptr ? output->info()->quantization_info().scale : s1;
- float o2 = output != nullptr ? output->info()->quantization_info().offset : o1;
- build_opts.emplace(("-DS1_VAL=" + support::cpp11::to_string(s1)));
- build_opts.emplace(("-DS2_VAL=" + support::cpp11::to_string(s2)));
- build_opts.emplace(("-DO1_VAL=" + support::cpp11::to_string(o1)));
- build_opts.emplace(("-DO2_VAL=" + support::cpp11::to_string(o2)));
- _kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel("activation_layer_qa8", build_opts));
- }
- else
- {
- _kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel("activation_layer", build_opts));
- }
+ std::string kernel_name = is_data_type_assymetric(dt) ? std::string("activation_layer_qa8") : std::string("activation_layer");
+ _kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel(kernel_name, build_opts));
// Make sure _kernel is initialized before calling the parent's configure
-
_input = input;
_output = output;
generated by cgit v1.2.1 (git 2.23.0) at 2024-05-16 13:04:39 +0000