diff options
Diffstat (limited to 'arm_compute/runtime/CL/functions/CLGEMMLowpOutputStage.h')
| -rw-r--r-- | arm_compute/runtime/CL/functions/CLGEMMLowpOutputStage.h | 93 |
1 files changed, 93 insertions, 0 deletions
diff --git a/arm_compute/runtime/CL/functions/CLGEMMLowpOutputStage.h b/arm_compute/runtime/CL/functions/CLGEMMLowpOutputStage.h index 4c11e51950..06cb759b16 100644 --- a/arm_compute/runtime/CL/functions/CLGEMMLowpOutputStage.h +++ b/arm_compute/runtime/CL/functions/CLGEMMLowpOutputStage.h @@ -75,6 +75,23 @@ public: ARM_COMPUTE_DEPRECATED_REL(20.05) void configure(const ICLTensor *input, const ICLTensor *bias, ICLTensor *output, int result_offset, int result_mult_int, int result_shift, int min = std::numeric_limits<int32_t>::lowest(), int max = std::numeric_limits<int32_t>::max()); + /** Initialise the kernel's inputs, output + * + * @param[in] compile_context The compile context to be used. + * @param[in] input Input tensor. It is the output of @ref CLGEMMLowpMatrixMultiplyCore function. Data type supported: S32 + * @param[in] bias Biases tensor. Only shared biases supported and it can be a nullptr if the addition of biases is not required. + * Biases are 1D tensor with dimensions [OFM]. Data type supported: Same as @p input. + * @param[out] output Output tensor. Data type supported: QASYMM8 + * @param[in] result_offset Offset to be added to each element of the input matrix + * @param[in] result_mult_int Value to be multiplied to each element of the input matrix when once the result_offset has been add + * @param[in] result_shift Number of bits to shift right the result before converting back to QASYMM8 + * @param[in] min (Optional) Min value used to saturate down the output result before converting back to QASYMM8. Defaults to the minimum possible 32-bit signed integer. + * @param[in] max (Optional) Max value used to saturate up the output result before converting back to QASYMM8, + * Along with @p min, this value can be used to implement "rectified linear unit" activation functions. Defaults to the maximum possible 32-bit signed integer. + */ + ARM_COMPUTE_DEPRECATED_REL(20.05) + void configure(const CLCompileContext &compile_context, const ICLTensor *input, const ICLTensor *bias, ICLTensor *output, int result_offset, int result_mult_int, int result_shift, + int min = std::numeric_limits<int32_t>::lowest(), int max = std::numeric_limits<int32_t>::max()); /** Static function to check if given info will lead to a valid configuration of @ref CLGEMMLowpQuantizeDownInt32ToUint8Scale * * @param[in] input Input tensor. It is the output of @ref CLGEMMLowpMatrixMultiplyCore function. Data type supported: S32 @@ -137,6 +154,23 @@ public: */ void configure(const ICLTensor *input, const ICLTensor *bias, ICLTensor *output, int result_fixedpoint_multiplier, int result_shift, int result_offset_after_shift, int min = std::numeric_limits<int32_t>::lowest(), int max = std::numeric_limits<int32_t>::max()); + /** Initialise the kernel's inputs, output + * + * @param[in] compile_context The compile context to be used. + * @param[in] input Input tensor. Data type supported: S32 + * @param[in] bias Biases tensor. Only shared biases supported and it can be a nullptr if the biases addition is not required. + * Biases are 1D tensor with dimensions [OFM]. Data type supported: Same as @p input. + * @param[out] output Output tensor. Data type supported: QASYMM8 + * @param[in] result_fixedpoint_multiplier Fixed point value to be multiplied to each element of the input matrix when once the result_offset has been add + * @param[in] result_shift Number of bits to shift right the result after the fixed point multiplication + * @param[in] result_offset_after_shift Offset to be applied to result before converting it back to QASYMM8 + * @param[in] min (Optional) Min value used to saturate down the output result before converting back to QASYMM8. Defaults to the minimum possible 32-bit signed integer. + * @param[in] max (Optional) Max value used to saturate up the output result before converting back to QASYMM8, + * Along with @p min, this value can be used to implement "rectified linear unit" activation functions. Defaults to the maximum possible 32-bit signed integer. + */ + void configure(const CLCompileContext &compile_context, const ICLTensor *input, const ICLTensor *bias, ICLTensor *output, int result_fixedpoint_multiplier, int result_shift, + int result_offset_after_shift, + int min = std::numeric_limits<int32_t>::lowest(), int max = std::numeric_limits<int32_t>::max()); /** Static function to check if given info will lead to a valid configuration of @ref CLGEMMLowpQuantizeDownInt32ToUint8ScaleByFixedPoint * * @param[in] input Input tensor. It is the output of @ref CLGEMMLowpMatrixMultiplyCore function. Data type supported: S32 @@ -198,6 +232,23 @@ public: */ void configure(const ICLTensor *input, const ICLTensor *bias, ICLTensor *output, int result_fixedpoint_multiplier, int result_shift, int result_offset_after_shift, int min = std::numeric_limits<int32_t>::lowest(), int max = std::numeric_limits<int32_t>::max()); + /** Initialise the kernel's inputs, output + * + * @param[in] compile_context The compile context to be used. + * @param[in] input Input tensor. Data type supported: S32 + * @param[in] bias Biases tensor. Only shared biases supported and it can be a nullptr if the biases addition is not required. + * Biases are 1D tensor with dimensions [OFM]. Data type supported: Same as @p input. + * @param[out] output Output tensor. Data type supported: QASYMM8_SIGNED + * @param[in] result_fixedpoint_multiplier Fixed point value to be multiplied to each element of the input matrix when once the result_offset has been add + * @param[in] result_shift Number of bits to shift right the result after the fixed point multiplication + * @param[in] result_offset_after_shift Offset to be applied to result before converting it back to QASYMM8_SIGNED + * @param[in] min (Optional) Min value used to saturate down the output result before converting back to QASYMM8_SIGNED. Defaults to the minimum possible 32-bit signed integer. + * @param[in] max (Optional) Max value used to saturate up the output result before converting back to QASYMM8_SIGNED. Defaults to 0 + * Along with @p min, this value can be used to implement "rectified linear unit" activation functions. Defaults to the maximum possible 32-bit signed integer. + */ + void configure(const CLCompileContext &compile_context, const ICLTensor *input, const ICLTensor *bias, ICLTensor *output, int result_fixedpoint_multiplier, int result_shift, + int result_offset_after_shift, + int min = std::numeric_limits<int32_t>::lowest(), int max = std::numeric_limits<int32_t>::max()); /** Static function to check if given info will lead to a valid configuration of @ref CLGEMMLowpQuantizeDownInt32ToInt8ScaleByFixedPoint * * @param[in] input Input tensor. It is the output of @ref CLGEMMLowpMatrixMultiplyCore function. Data type supported: S32 @@ -240,6 +291,23 @@ public: ARM_COMPUTE_DEPRECATED_REL(20.05) void configure(const ICLTensor *input, const ICLTensor *bias, ICLTensor *output, float multiplier, int offset, int min = std::numeric_limits<int32_t>::lowest(), int max = std::numeric_limits<int32_t>::max()); + /** Initialise the kernel's inputs, output + * + * @param[in] compile_context The compile context to be used. + * @param[in] input Input tensor. Data type supported: S32 + * @param[in] bias Biases tensor. Only shared biases supported and it can be a nullptr if the biases addition is not required. + * Biases are 1D tensor with dimensions [OFM]. Data type supported: Same as @p input. + * @param[out] output Output tensor. Data type supported: QASYMM8 + * @param[in] multiplier Float multiplier to be multiplied to each element of the input matrix + * @param[in] offset Offset to be applied to result before converting it back to QASYMM8 + * @param[in] min (Optional) Min value used to saturate down the output result before converting back to QASYMM8. Defaults to the minimum possible 32-bit signed integer. + * @param[in] max (Optional) Max value used to saturate up the output result before converting back to QASYMM8, + * Along with @p min, this value can be used to implement "rectified linear unit" activation functions. Defaults to the maximum possible 32-bit signed integer. + */ + ARM_COMPUTE_DEPRECATED_REL(20.05) + void configure(const CLCompileContext &compile_context, const ICLTensor *input, const ICLTensor *bias, ICLTensor *output, float multiplier, int offset, + int min = std::numeric_limits<int32_t>::lowest(), + int max = std::numeric_limits<int32_t>::max()); /** Static function to check if given info will lead to a valid configuration of @ref CLGEMMLowpQuantizeDownInt32ToUint8ScaleByFixedPoint * * @param[in] input Input tensor. It is the output of @ref CLGEMMLowpMatrixMultiplyCore function. Data type supported: S32 @@ -300,6 +368,21 @@ public: */ void configure(const ICLTensor *input, const ICLTensor *bias, ICLTensor *output, int result_fixedpoint_multiplier, int result_shift, int min = std::numeric_limits<int32_t>::lowest(), int max = std::numeric_limits<int32_t>::max()); + /** Initialise the kernel's inputs, output + * + * @param[in] compile_context The compile context to be used. + * @param[in] input Input tensor. Data type supported: S32 + * @param[in] bias Biases tensor. Only shared biases supported and it can be a nullptr if the biases addition is not required. + * Biases are 1D tensor with dimensions [OFM]. Data type supported: Same as @p input. + * @param[out] output Output tensor. Data type supported: QSYMM16 + * @param[in] result_fixedpoint_multiplier Fixed point value to be multiplied to each element of the input matrix when once the result_offset has been add + * @param[in] result_shift Number of bits to shift right the result after the fixed point multiplication + * @param[in] min (Optional) Min value used to saturate down the output result before converting back to QSYMM16. Defaults to the minimum possible 32-bit signed integer. + * @param[in] max (Optional) Max value used to saturate up the output result before converting back to QSYMM16. + * Along with @p min, this value can be used to implement "rectified linear unit" activation functions. Defaults to the maximum possible 32-bit signed integer. + */ + void configure(const CLCompileContext &compile_context, const ICLTensor *input, const ICLTensor *bias, ICLTensor *output, int result_fixedpoint_multiplier, int result_shift, + int min = std::numeric_limits<int32_t>::lowest(), int max = std::numeric_limits<int32_t>::max()); /** Static function to check if given info will lead to a valid configuration of @ref CLGEMMLowpQuantizeDownInt32ToInt16ScaleByFixedPoint * * @param[in] input Input tensor info. It is the output of @ref CLGEMMLowpMatrixMultiplyCore function. Data type supported: S32 @@ -336,6 +419,16 @@ public: * @param[in] info GEMMLowp output stage metadata. */ void configure(const ICLTensor *input, const ICLTensor *bias, ICLTensor *output, const GEMMLowpOutputStageInfo &info); + /** Initialise the kernel's inputs, output + * + * @param[in] compile_context The compile context to be used. + * @param[in] input Input tensor. Data type supported: S32 + * @param[in] bias Biases tensor. Only shared biases supported and it can be a nullptr if the biases addition is not required. + * Biases are 1D tensor with dimensions [OFM]. Data type supported: Same as @p input. + * @param[out] output Output tensor. Data type supported: QASYMM8/QASYMM8_SIGNED + * @param[in] info GEMMLowp output stage metadata. + */ + void configure(const CLCompileContext &compile_context, const ICLTensor *input, const ICLTensor *bias, ICLTensor *output, const GEMMLowpOutputStageInfo &info); /** Static function to check if given info will lead to a valid configuration of @ref CLGEMMLowpQuantizeDownInt32ToUint8ScaleByFixedPointKernel * * @param[in] input Input tensor. It is the output of @ref CLGEMMLowpMatrixMultiplyCore function. Data type supported: S32 |