From 20c246a60869bada4051bd14eb9a3862be5330d7 Mon Sep 17 00:00:00 2001 From: Georgios Pinitas Date: Wed, 12 Sep 2018 16:45:53 +0100 Subject: COMPMID-1532: Add DepthwiseConvolution3x3 FP16 on NEON Change-Id: I780970f317b979b3230e2b471ac01df7fda9ee14 Reviewed-on: https://eu-gerrit-1.euhpc.arm.com/148168 Tested-by: bsgcomp Reviewed-by: Anthony Barbier --- .../kernels/detail/NEDirectConvolutionDetail.h | 22 +++++++++++++++++----- 1 file changed, 17 insertions(+), 5 deletions(-) (limited to 'arm_compute/core/NEON/kernels/detail/NEDirectConvolutionDetail.h') diff --git a/arm_compute/core/NEON/kernels/detail/NEDirectConvolutionDetail.h b/arm_compute/core/NEON/kernels/detail/NEDirectConvolutionDetail.h index b245505ac6..e6dc43a47b 100644 --- a/arm_compute/core/NEON/kernels/detail/NEDirectConvolutionDetail.h +++ b/arm_compute/core/NEON/kernels/detail/NEDirectConvolutionDetail.h @@ -374,8 +374,9 @@ inline void store_results<3>(int32_t *buffer, const int32x4x2_t &values) * * @return The loaded matrix. */ -inline float16x8x3_t load_matrix_row(const float16_t *ptr) +inline float16x8x3_t load_matrix_row(const float16_t *ptr, int weights_offset = 0) { + ARM_COMPUTE_UNUSED(weights_offset); /* ptr is a pointer to a row in a 3x3 matrix, the function returns 3 vectors holding exactly the same value in all lanes: r.val[0] contains the first element, r.val[1] the second element and r.val[2] the third element (in all lanes) */ const float16x8x3_t r = @@ -400,11 +401,16 @@ inline float16x8x3_t load_matrix_row(const float16_t *ptr) * */ template -float16x8x2_t convolve_3x3(const float16_t *in_top, const float16_t *in_mid, const float16_t *in_low, const float16x8x3_t &m0, const float16x8x3_t &m1, const float16x8x3_t &m2); +float16x8x2_t convolve_3x3(const float16_t *in_top, const float16_t *in_mid, const float16_t *in_low, + const float16x8x3_t &m0, const float16x8x3_t &m1, const float16x8x3_t &m2, + int input_offset = 0); template <> -inline float16x8x2_t convolve_3x3<1>(const float16_t *in_top, const float16_t *in_mid, const float16_t *in_low, const float16x8x3_t &m0, const float16x8x3_t &m1, const float16x8x3_t &m2) +inline float16x8x2_t convolve_3x3<1>(const float16_t *in_top, const float16_t *in_mid, const float16_t *in_low, + const float16x8x3_t &m0, const float16x8x3_t &m1, const float16x8x3_t &m2, + int input_offset) { + ARM_COMPUTE_UNUSED(input_offset); const float16x8x3_t vtop = { { @@ -456,8 +462,11 @@ inline float16x8x2_t convolve_3x3<1>(const float16_t *in_top, const float16_t *i } template <> -inline float16x8x2_t convolve_3x3<2>(const float16_t *in_top, const float16_t *in_mid, const float16_t *in_low, const float16x8x3_t &m0, const float16x8x3_t &m1, const float16x8x3_t &m2) +inline float16x8x2_t convolve_3x3<2>(const float16_t *in_top, const float16_t *in_mid, const float16_t *in_low, + const float16x8x3_t &m0, const float16x8x3_t &m1, const float16x8x3_t &m2, + int input_offset) { + ARM_COMPUTE_UNUSED(input_offset); float16x8x2_t out = convolve_3x3<1>(in_top, in_mid, in_low, m0, m1, m2); out.val[0] = vsetq_lane_f16(vgetq_lane_f16(out.val[0], 2), out.val[0], 1); out.val[0] = vsetq_lane_f16(vgetq_lane_f16(out.val[0], 4), out.val[0], 2); @@ -470,8 +479,11 @@ inline float16x8x2_t convolve_3x3<2>(const float16_t *in_top, const float16_t *i } template <> -inline float16x8x2_t convolve_3x3<3>(const float16_t *in_top, const float16_t *in_mid, const float16_t *in_low, const float16x8x3_t &m0, const float16x8x3_t &m1, const float16x8x3_t &m2) +inline float16x8x2_t convolve_3x3<3>(const float16_t *in_top, const float16_t *in_mid, const float16_t *in_low, + const float16x8x3_t &m0, const float16x8x3_t &m1, const float16x8x3_t &m2, + int input_offset) { + ARM_COMPUTE_UNUSED(input_offset); float16x8x2_t out = convolve_3x3<1>(in_top, in_mid, in_low, m0, m1, m2); out.val[0] = vsetq_lane_f16(vgetq_lane_f16(out.val[0], 3), out.val[0], 1); out.val[0] = vsetq_lane_f16(vgetq_lane_f16(out.val[0], 6), out.val[0], 2); -- cgit v1.2.1