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author | Gian Marco <gianmarco.iodice@arm.com> | 2017-11-28 09:10:03 +0000 |
---|---|---|
committer | Anthony Barbier <anthony.barbier@arm.com> | 2018-11-02 16:41:58 +0000 |
commit | 58c5794b917dae10ff115dd85ec69e2ca41136c1 (patch) | |
tree | f2cea2d94e6566be720256dc6105056798723699 /src/core/CL/cl_kernels/gemmlowp.cl | |
parent | 754e9526a7caf50876c2db9563dc72f096093b34 (diff) | |
download | ComputeLibrary-58c5794b917dae10ff115dd85ec69e2ca41136c1.tar.gz |
COMPMID-706 - Add GEMMLowp output stage for scaling by a fixed point number
DoD:
- Implement NEON kernel for quantizing down the gemmlowp result. The
result should be scaled by a fixedpoint number
- Implement OpenCL kernel for quantizing down the gemmlowp result. The
result should be scaled by a fixedpoint number
- Add test for validating the result
Required for:
- Integration of GEMMLowp in Android NN
- Convolution quantized
- Fully connected quantized
Change-Id: Ia963d25d695471e963961fb49a5600e78374ac4f
Reviewed-on: https://eu-gerrit-1.euhpc.arm.com/110981
Tested-by: BSG Visual Compute Jenkins server to access repositories on http://mpd-gerrit.cambridge.arm.com <bsgcomp@arm.com>
Reviewed-by: Georgios Pinitas <georgios.pinitas@arm.com>
Reviewed-by: Anthony Barbier <anthony.barbier@arm.com>
Diffstat (limited to 'src/core/CL/cl_kernels/gemmlowp.cl')
-rw-r--r-- | src/core/CL/cl_kernels/gemmlowp.cl | 89 |
1 files changed, 86 insertions, 3 deletions
diff --git a/src/core/CL/cl_kernels/gemmlowp.cl b/src/core/CL/cl_kernels/gemmlowp.cl index 16f8fe9f7f..a8e8e600fe 100644 --- a/src/core/CL/cl_kernels/gemmlowp.cl +++ b/src/core/CL/cl_kernels/gemmlowp.cl @@ -508,6 +508,9 @@ __kernel void gemmlowp_output_stage_quantize_down(TENSOR3D_DECLARATION(src), int16 input_values = vload16(0, (__global int *)src.ptr); + // Add the offset terms to GEMM's result + input_values += (int16)RESULT_OFFSET; + #if defined(ADD_BIAS) // Add bias const int16 biases_values = vload16(0, (__global int *)biases.ptr); @@ -515,10 +518,90 @@ __kernel void gemmlowp_output_stage_quantize_down(TENSOR3D_DECLARATION(src), #endif // defined(ADD_BIAS) // Multiply by result_mult_int and shift - input_values = ASYMM_MULT_BY_QUANT_MULTIPLIER_LESS_THAN_ONE(input_values, RESULT_MULT_INT, RESULT_SHIFT, 16); + input_values *= RESULT_MULT_INT; + + input_values >>= RESULT_SHIFT; + + uchar16 res = convert_uchar16_sat(input_values); + +#if defined(MIN_BOUND) + res = max(res, (uchar16)MIN_BOUND); +#endif // defined(MIN_BOUND) +#if defined(MAX_BOUND) + res = min(res, (uchar16)MAX_BOUND); +#endif // defined(MAX_BOUND) + + // Store the result + vstore16(res, 0, dst.ptr); +} +#endif // defined(RESULT_OFFSET) && defined(RESULT_MULT_INT) && defined(RESULT_SHIFT) + +#if defined(RESULT_OFFSET_AFTER_SHIFT) && defined(RESULT_FIXEDPOINT_MULTIPLIER) && defined(RESULT_SHIFT) +/** This OpenCL kernel is used to quantize down the int32 accumulator values of GEMMLowp to QASYMM8 + * + * This kernel takes a final int32 accumulator value (the output of @ref CLGEMMLowpMatrixMultiplyKernel), and processes it to obtain the final QASYMM8 value. + * The following computations will be performed by the kernel: + * + * -# Compute fixed point multiplication between each entry of input by result_fixedpoint_multiplier + * -# Add bias to final result if bias tensor is not a nullptr + * -# Round to nearest division by a power-of-two using result_shift + * -# Add offset to each result + * -# Clamp the value between the specified min and max bounds + * -# Clamp the resulting int32 values to the [0..255] range and cast to QASYMM8. + * + * @attention The offset, scalar scale factor and number of bits to shift right of output tensor must be passed at compile time using -DRESULT_OFFSET, -RESULT_MULT_INT and -DRESULT_SHIFT + * + * @note In case the addition of int32 biases is required, -DADD_BIAS should be passed at compile time + * @note In case the clamping of the result is required, the min and max bounds can be passed at compile time using -DMIN_BOUND and -DMAX_BOUND. + * These values can be used to implement "rectified linear unit" activation functions + * + * @param[in] src_ptr Pointer to the source tensor. Supported data type: S32 + * @param[in] src_stride_x Stride of the source tensor in X dimension (in bytes) + * @param[in] src_step_x src_stride_x * number of elements along X processed per workitem(in bytes) + * @param[in] src_stride_y Stride of the source tensor in Y dimension (in bytes) + * @param[in] src_step_y src_stride_y * number of elements along Y processed per workitem(in bytes) + * @param[in] src_stride_z Stride of the source tensor in Z dimension (in bytes) + * @param[in] src_step_z src_stride_z * number of elements along Z processed per workitem(in bytes) + * @param[in] src_offset_first_element_in_bytes The offset of the first element in the source tensor + * @param[in] biases_ptr Pointer to the biases tensor. Supported data type: same as @p src_ptr + * @param[in] biases_stride_x Stride of the biases tensor in X dimension (in bytes) + * @param[in] biases_step_x biases_stride_x * number of elements along X processed per workitem(in bytes) + * @param[in] biases_offset_first_element_in_bytes The offset of the first element in the biases tensor + * @param[out] dst_ptr Pointer to the destination tensor Supported data type: QASYMM8 + * @param[in] dst_stride_x Stride of the destination tensor in X dimension (in bytes) + * @param[in] dst_step_x dst_gx_stride_x * number of elements along X processed per workitem(in bytes) + * @param[in] dst_stride_y Stride of the destination tensor in Y dimension (in bytes) + * @param[in] dst_step_y dst_gx_stride_y * number of elements along Y processed per workitem(in bytes) + * @param[in] dst_stride_z Stride of the source tensor in Z dimension (in bytes) + * @param[in] dst_step_z src_stride_z * number of elements along Z processed per workitem(in bytes) + * @param[in] dst_offset_first_element_in_bytes The offset of the first element in the destination tensor + */ +__kernel void gemmlowp_output_stage_quantize_down_fixedpoint(TENSOR3D_DECLARATION(src), +#if defined(ADD_BIAS) + VECTOR_DECLARATION(biases), +#endif // defined(ADD_BIAS) + TENSOR3D_DECLARATION(dst)) +{ + // Compute source and destination addresses + Tensor3D src = CONVERT_TO_TENSOR3D_STRUCT(src); + Tensor3D dst = CONVERT_TO_TENSOR3D_STRUCT(dst); +#if defined(ADD_BIAS) + Vector biases = CONVERT_TO_VECTOR_STRUCT(biases); +#endif // defined(ADD_BIAS) + + int16 input_values = vload16(0, (__global int *)src.ptr); + +#if defined(ADD_BIAS) + // Add bias + const int16 biases_values = vload16(0, (__global int *)biases.ptr); + input_values += (int16)biases_values; +#endif // defined(ADD_BIAS) + + // Multiply by result_mult_int and shift + input_values = ASYMM_MULT_BY_QUANT_MULTIPLIER_LESS_THAN_ONE(input_values, RESULT_FIXEDPOINT_MULTIPLIER, RESULT_SHIFT, 16); // Add the offset terms to GEMM's result - input_values += (int16)RESULT_OFFSET; + input_values += (int16)RESULT_OFFSET_AFTER_SHIFT; uchar16 res = convert_uchar16_sat(input_values); @@ -532,4 +615,4 @@ __kernel void gemmlowp_output_stage_quantize_down(TENSOR3D_DECLARATION(src), // Store the result vstore16(res, 0, dst.ptr); } -#endif // defined(RESULT_OFFSET) && defined(RESULT_MULT_INT) && defined(RESULT_SHIFT)
\ No newline at end of file +#endif // defined(RESULT_OFFSET_AFTER_SHIFT) && defined(RESULT_FIXEDPOINT_MULTIPLIER) && defined(RESULT_SHIFT)
\ No newline at end of file |