*
* @param[in] input1 An input tensor. Data types supported: U8/QASYMM8/QASYMM8_SIGNED/S16/QSYMM16/F16/F32.
* @param[in] input2 An input tensor. Data types supported: same as @p input1.
- * @param[out] output The output tensor, Data types supported: same as @p input1. Note: U8 requires both inputs to be U8.
+ * @param[out] output The output tensor, Data types supported:
+ * - U8, only if both input are U8
+ * - QASYMM8, only if both inputs are QASYMM8
+ * - QASYMM8_SIGNED, only if both inputs are QASYMM8_SIGNED
+ * - S16
+ * - QSYMM16, only if both inputs are QSYMM16
+ * - S32, only if both inputs are QSYMM16
+ * - F16
+ * - F32
* @param[in] scale Scale to apply after multiplication.
* Scale must be positive and its value must be either 1/255 or 1/2^n where n is between 0 and 15.
* @param[in] overflow_policy Overflow policy. Supported overflow policies: Wrap, Saturate
*
* @param[in] input1 An input tensor info. Data types supported: U8/QASYMM8/QASYMM8_SIGNED/S16/QSYMM16/F16/F32.
* @param[in] input2 An input tensor info. Data types supported: same as @p input1.
- * @param[in] output The output tensor info, Data types supported: same as @p input1. Note: U8 requires both inputs to be U8.
+ * @param[in] output The output tensor info, Data types supported:
+ * - U8, only if both input are U8
+ * - QASYMM8, only if both inputs are QASYMM8
+ * - QASYMM8_SIGNED, only if both inputs are QASYMM8_SIGNED
+ * - S16
+ * - QSYMM16, only if both inputs are QSYMM16
+ * - S32, only if both inputs are QSYMM16
+ * - F16
+ * - F32
* @param[in] scale Scale to apply after multiplication.
* Scale must be positive and its value must be either 1/255 or 1/2^n where n is between 0 and 15.
* @param[in] overflow_policy Overflow policy. Supported overflow policies: Wrap, Saturate
* The input tensor is [in, out] because its TensorInfo might be modified inside the kernel in case of broadcasting of dimension 0.
* @param[in, out] input2 An input tensor. Data types supported: same as @p input1.
* The input tensor is [in, out] because its TensorInfo might be modified inside the kernel in case of broadcasting of dimension 0.
- * @param[out] output The output tensor, Data types supported: same as @p input1. Note: U8 requires both inputs to be U8.
+ * @param[out] output The output tensor. Data types supported:
+ * - U8, only if both input are U8
+ * - QASYMM8, only if both inputs are QASYMM8
+ * - QASYMM8_SIGNED, only if both inputs are QASYMM8_SIGNED
+ * - S16
+ * - QSYMM16, only if both inputs are QSYMM16
+ * - S32, only if both inputs are QSYMM16
+ * - F16
+ * - F32
* @param[in] scale Scale to apply after multiplication.
* Scale must be positive and its value must be either 1/255 or 1/2^n where n is between 0 and 15.
* @param[in] overflow_policy Overflow policy. Supported overflow policies: Wrap, Saturate
*
* @param[in] input1 An input tensor info. Data types supported: U8/QASYMM8/QASYMM8_SIGNED/S16/QSYMM16/F16/F32.
* @param[in] input2 An input tensor info. Data types supported: same as @p input1.
- * @param[in] output The output tensor info, Data types supported: same as @p input1. Note: U8 requires both inputs to be U8.
+ * @param[in] output The output tensor info. Data types supported:
+ * - U8, only if both input are U8
+ * - QASYMM8, only if both inputs are QASYMM8
+ * - QASYMM8_SIGNED, only if both inputs are QASYMM8_SIGNED
+ * - S16
+ * - QSYMM16, only if both inputs are QSYMM16
+ * - S32, only if both inputs are QSYMM16
+ * - F16
+ * - F32
* @param[in] scale Scale to apply after multiplication.
* Scale must be positive and its value must be either 1/255 or 1/2^n where n is between 0 and 15.
* @param[in] overflow_policy Overflow policy. Supported overflow policies: Wrap, Saturate
#endif /* SATURATE */
#define CONVERT_OP_FLOAT(x, type, round) CONVERT_OP_FLOAT_STR(x, type, round)
-#if defined(DATA_TYPE_IN1) && defined(DATA_TYPE_IN2) && defined(DATA_TYPE_RES) && defined(DATA_TYPE_OUT)
+#if defined(DATA_TYPE_IN1) && defined(DATA_TYPE_IN2) && defined(ACC_DATA_TYPE) && defined(DATA_TYPE_OUT)
#if defined(ACTIVATION_TYPE)
#include "activation_float_helpers.h"
*
* @attention The inputs and output data types need to be passed at compile time using -DDATA_TYPE_IN1, -DDATA_TYPE_IN2 and -DDATA_TYPE_OUT:
* e.g. -DDATA_TYPE_IN1=uchar -DDATA_TYPE_IN2=ushort -DDATA_TYPE_OUT=short
- * @attention The data type of the intermediate result of the multiplication should passed as well using -DDATA_TYPE_RES.
- * e.g. If one of inputs is S16 -DDATA_TYPE_RES=int should be passed else -DDATA_TYPE_RES=short.
+ * @attention The data type of the intermediate result of the multiplication should passed as well using -DACC_DATA_TYPE.
+ * e.g. If one of inputs is S16 -DACC_DATA_TYPE=int should be passed else -DACC_DATA_TYPE=short.
* @attention -DDATA_TYPE_FLOAT must be passed if floating point inputs are provided.
*
* @param[in] in1_ptr Pointer to the source image. Supported data types: U8, S16, F16, F32
Tensor3D out = CONVERT_TO_TENSOR3D_STRUCT(out);
// Load data
- VEC_DATA_TYPE(DATA_TYPE_RES, 16)
- in1_data = CONVERT(vload16(0, (__global DATA_TYPE_IN1 *)in1.ptr), VEC_DATA_TYPE(DATA_TYPE_RES, 16));
- VEC_DATA_TYPE(DATA_TYPE_RES, 16)
- in2_data = CONVERT(vload16(0, (__global DATA_TYPE_IN2 *)in2.ptr), VEC_DATA_TYPE(DATA_TYPE_RES, 16));
+ VEC_DATA_TYPE(ACC_DATA_TYPE, 16)
+ in1_data = CONVERT(vload16(0, (__global DATA_TYPE_IN1 *)in1.ptr), VEC_DATA_TYPE(ACC_DATA_TYPE, 16));
+ VEC_DATA_TYPE(ACC_DATA_TYPE, 16)
+ in2_data = CONVERT(vload16(0, (__global DATA_TYPE_IN2 *)in2.ptr), VEC_DATA_TYPE(ACC_DATA_TYPE, 16));
// Perform multiplication
#ifdef DATA_TYPE_FLOAT
VEC_DATA_TYPE(DATA_TYPE_OUT, 16)
- res = CONVERT(in1_data * in2_data * (DATA_TYPE_RES)scale, VEC_DATA_TYPE(DATA_TYPE_OUT, 16));
+ res = CONVERT(in1_data * in2_data * (ACC_DATA_TYPE)scale, VEC_DATA_TYPE(DATA_TYPE_OUT, 16));
#else /* DATA_TYPE_FLOAT */
VEC_DATA_TYPE(DATA_TYPE_OUT, 16)
- res = CONVERT_OP_FLOAT(CONVERT_OP_FLOAT((convert_float16(in1_data * in2_data) * scale), VEC_DATA_TYPE(DATA_TYPE_RES, 16), ROUND), VEC_DATA_TYPE(DATA_TYPE_OUT, 16), ROUND);
+ res = CONVERT_OP_FLOAT(CONVERT_OP_FLOAT((convert_float16(in1_data * in2_data) * scale), VEC_DATA_TYPE(ACC_DATA_TYPE, 16), ROUND), VEC_DATA_TYPE(DATA_TYPE_OUT, 16), ROUND);
#endif /* DATA_TYPE_FLOAT */
#if defined(ACTIVATION_TYPE)
vstore16(res, 0, (__global DATA_TYPE_OUT *)out.ptr);
#endif // defined(ACTIVATION_TYPE)
}
-#endif /* defined(DATA_TYPE_IN1) && defined(DATA_TYPE_IN2) && defined(DATA_TYPE_RES) && defined(DATA_TYPE_OUT) */
+#endif /* defined(DATA_TYPE_IN1) && defined(DATA_TYPE_IN2) && defined(ACC_DATA_TYPE) && defined(DATA_TYPE_OUT) */
/** Performs a pixelwise multiplication of complex float values
*
#define CONVERT_RTE(x, type) (convert_##type##_rte((x)))
#define CONVERT_DOWN(x, type) CONVERT_RTE(x, type)
-#if defined(DATA_TYPE_IN1) && defined(DATA_TYPE_IN2) && defined(DATA_TYPE_RES) && defined(DATA_TYPE_OUT)
+#if defined(DATA_TYPE_IN1) && defined(DATA_TYPE_IN2) && defined(ACC_DATA_TYPE) && defined(DATA_TYPE_OUT)
/** Performs a pixelwise multiplication with integer scale of integer inputs.
*
* @attention The inputs and output data types need to be passed at compile time using -DDATA_TYPE_IN1, -DDATA_TYPE_IN2 and -DDATA_TYPE_OUT:
* e.g. -DDATA_TYPE_IN1=uchar -DDATA_TYPE_IN2=ushort -DDATA_TYPE_OUT=short
- * @attention The data_type of the intermediate result of the multiplication should passed as well using -DDATA_TYPE_RES.
- * e.g. If one of inputs is S16 -DDATA_TYPE_RES=int should be passed else -DDATA_TYPE_RES=short.
+ * @attention The data_type of the intermediate result of the multiplication should passed as well using -DACC_DATA_TYPE.
+ * e.g. If one of inputs is S16 -DACC_DATA_TYPE=int should be passed else -DACC_DATA_TYPE=short.
*
* @param[in] in1_ptr Pointer to the source image. Supported data types: U8/S16
* @param[in] in1_stride_x Stride of the source image in X dimension (in bytes)
Tensor3D out = CONVERT_TO_TENSOR3D_STRUCT(out);
// Load data
- VEC_DATA_TYPE(DATA_TYPE_RES, 16)
- in1_data = CONVERT(vload16(0, (__global DATA_TYPE_IN1 *)in1.ptr), VEC_DATA_TYPE(DATA_TYPE_RES, 16));
- VEC_DATA_TYPE(DATA_TYPE_RES, 16)
- in2_data = CONVERT(vload16(0, (__global DATA_TYPE_IN2 *)in2.ptr), VEC_DATA_TYPE(DATA_TYPE_RES, 16));
+ VEC_DATA_TYPE(ACC_DATA_TYPE, 16)
+ in1_data = CONVERT(vload16(0, (__global DATA_TYPE_IN1 *)in1.ptr), VEC_DATA_TYPE(ACC_DATA_TYPE, 16));
+ VEC_DATA_TYPE(ACC_DATA_TYPE, 16)
+ in2_data = CONVERT(vload16(0, (__global DATA_TYPE_IN2 *)in2.ptr), VEC_DATA_TYPE(ACC_DATA_TYPE, 16));
// Perform multiplication and store result
vstore16(MUL_OP(in1_data, in2_data, scale, DATA_TYPE_OUT, 16), 0, (__global DATA_TYPE_OUT *)out.ptr);
}
-#endif /* defined(DATA_TYPE_IN1) && defined(DATA_TYPE_IN2) && defined(DATA_TYPE_RES) && defined(DATA_TYPE_OUT) */
+#endif /* defined(DATA_TYPE_IN1) && defined(DATA_TYPE_IN2) && defined(ACC_DATA_TYPE) && defined(DATA_TYPE_OUT) */
#if defined(SCALE_IN1) && defined(SCALE_IN2) && defined(SCALE_OUT) && defined(DATA_TYPE_OUT) && defined(VEC_SIZE)
#include "arm_compute/core/CL/CLValidate.h"
#include "arm_compute/core/CL/ICLTensor.h"
#include "arm_compute/core/CL/OpenCL.h"
-#include "arm_compute/core/Error.h"
-#include "arm_compute/core/Helpers.h"
#include "arm_compute/core/TensorInfo.h"
-#include "arm_compute/core/Window.h"
#include "support/StringSupport.h"
-#include <cmath>
-#include <cstdlib>
-#include <set>
-#include <string>
-
namespace arm_compute
{
namespace
1,
DataType::U8, DataType::QASYMM8, DataType::QASYMM8_SIGNED,
DataType::S16, DataType::QSYMM16, DataType::F16,
- DataType::F32);
+ DataType::S32, DataType::F32);
ARM_COMPUTE_RETURN_ERROR_ON_MSG(output->data_type() == DataType::U8 && (input1->data_type() != DataType::U8 || input2->data_type() != DataType::U8),
"Output can only be U8 if both inputs are U8");
ARM_COMPUTE_RETURN_ERROR_ON_MSG(output->data_type() == DataType::QASYMM8 && (input1->data_type() != DataType::QASYMM8 || input2->data_type() != DataType::QASYMM8),
"Output can only be QASYMM8_SIGNED if both inputs are QASYMM8_SIGNED");
ARM_COMPUTE_RETURN_ERROR_ON_MSG(output->data_type() == DataType::QSYMM16 && (input1->data_type() != DataType::QSYMM16 || input2->data_type() != DataType::QSYMM16),
"Output can only be QSYMM16 if both inputs are QSYMM16");
+ ARM_COMPUTE_RETURN_ERROR_ON_MSG(output->data_type() == DataType::S32 && (input1->data_type() != DataType::QSYMM16 || input2->data_type() != DataType::QSYMM16),
+ "Output can only be S32 if both inputs are QSYMM16");
ARM_COMPUTE_RETURN_ERROR_ON_MSG(detail::have_different_dimensions(out_shape, output->tensor_shape(), 0), "Wrong shape for output");
}
scale_int = std::abs(exponent - 1);
}
- std::string compute_type;
+ std::string acc_type;
// Check if it has float inputs and output
if(is_data_type_float(input1->info()->data_type()) || is_data_type_float(input2->info()->data_type()))
{
- scale_int = -1;
- compute_type = (input1->info()->data_type() == DataType::F32 || input2->info()->data_type() == DataType::F32) ? "float" : "half";
+ scale_int = -1;
+ acc_type = (input1->info()->data_type() == DataType::F32 || input2->info()->data_type() == DataType::F32) ? "float" : "half";
}
else
{
- if(input1->info()->data_type() == DataType::S16 || input2->info()->data_type() == DataType::S16)
+ if(input1->info()->element_size() == 2 || input2->info()->element_size() == 2)
{
- compute_type = "int";
+ // Use 32-bit accumulator for 16-bit input
+ acc_type = "int";
}
else
{
- compute_type = "ushort";
+ // Use 16-bit accumulator for 8-bit input
+ acc_type = "ushort";
}
}
build_opts.add_option("-DDATA_TYPE_IN2=" + get_cl_type_from_data_type(input2->info()->data_type()));
build_opts.add_option("-DDATA_TYPE_OUT=" + get_cl_type_from_data_type(output->info()->data_type()));
build_opts.add_option("-DVEC_SIZE=" + support::cpp11::to_string(num_elems_processed_per_iteration));
- if(is_quantized)
+ if(is_quantized && (output->info()->data_type() != DataType::S32))
{
const UniformQuantizationInfo iq1_info = input1->info()->quantization_info().uniform();
const UniformQuantizationInfo iq2_info = input2->info()->quantization_info().uniform();
kernel_name += (scale_int >= 0) ? "_int" : "_float";
build_opts.add_option_if_else(overflow_policy == ConvertPolicy::WRAP || is_data_type_float(output->info()->data_type()), "-DWRAP", "-DSATURATE");
build_opts.add_option_if_else(rounding_policy == RoundingPolicy::TO_ZERO, "-DROUND=_rtz", "-DROUND=_rte");
- build_opts.add_option("-DDATA_TYPE_RES=" + compute_type);
+ build_opts.add_option("-DACC_DATA_TYPE=" + acc_type);
if(act_info.enabled())
{
build_opts.add_option("-DACTIVATION_TYPE=" + lower_string(string_from_activation_func(act_info.activation())));
VALIDATE(float, 1.f))
template <typename T>
-using CLPixelWiseMultiplicationQuantizedFixture = PixelWiseMultiplicationValidationQuantizedFixture<CLTensor, CLAccessor, CLPixelWiseMultiplication, T, T>;
+using CLPixelWiseMultiplicationQuantizedFixture = PixelWiseMultiplicationValidationQuantizedFixture<CLTensor, CLAccessor, CLPixelWiseMultiplication, T, T>;
+using CLPixelWiseMultiplicationQSYMM16ToS32Fxture = PixelWiseMultiplicationValidationQuantizedFixture<CLTensor, CLAccessor, CLPixelWiseMultiplication, int16_t, int16_t, int32_t>;
TEST_SUITE(Quantized)
TEST_SUITE(QASYMM8)
validate(CLAccessor(_target), _reference, tolerance_qsymm16);
}
TEST_SUITE_END() // QSYMM16
+TEST_SUITE(QSYMM16ToS32)
+FIXTURE_DATA_TEST_CASE(RunSmall, CLPixelWiseMultiplicationQSYMM16ToS32Fxture, framework::DatasetMode::ALL,
+ combine(combine(combine(combine(combine(combine(combine(combine(combine(datasets::SmallShapes(),
+ framework::dataset::make("DataTypeIn1", DataType::QSYMM16)),
+ framework::dataset::make("DataTypeIn2", DataType::QSYMM16)),
+ framework::dataset::make("DataTypeOut", DataType::S32)),
+ framework::dataset::make("Scale", { 1.f })),
+ framework::dataset::make("ConvertPolicy", { ConvertPolicy::SATURATE })),
+ framework::dataset::make("RoundingPolicy", RoundingPolicy::TO_NEAREST_EVEN)),
+ framework::dataset::make("Src0QInfo", { QuantizationInfo(1.f / 32768.f, 0) })),
+ framework::dataset::make("Src1QInfo", { QuantizationInfo(2.f / 32768.f, 0) })),
+ framework::dataset::make("OutQInfo", { QuantizationInfo(1.f, 0) })))
+{
+ // Validate output
+ validate(CLAccessor(_target), _reference, tolerance_qsymm16);
+}
+TEST_SUITE_END() // QSYMM16ToS32
TEST_SUITE_END() // Quantized
TEST_SUITE_END() // PixelWiseMultiplication
projects / platform / upstream / armcl.git / commitdiff