// Tencent is pleased to support the open source community by making ncnn available. // // Copyright (C) 2019 THL A29 Limited, a Tencent company. All rights reserved. // // Licensed under the BSD 3-Clause License (the "License"); you may not use this file except // in compliance with the License. You may obtain a copy of the License at // // https://opensource.org/licenses/BSD-3-Clause // // Unless required by applicable law or agreed to in writing, software distributed // under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR // CONDITIONS OF ANY KIND, either express or implied. See the License for the // specific language governing permissions and limitations under the License. #include "padding_arm.h" #if __ARM_NEON #include #endif // __ARM_NEON #include "cpu.h" namespace ncnn { #if __ARM_NEON #include "padding_pack4.h" #include "padding_pack4_bf16s_fp16s.h" #include "padding_pack8_int8.h" #if NCNN_ARM82 #include "padding_pack8_fp16s.h" #endif #endif // __ARM_NEON Padding_arm::Padding_arm() { #if __ARM_NEON support_packing = true; #if NCNN_ARM82 support_fp16_storage = cpu_support_arm_asimdhp(); #endif #endif // __ARM_NEON #if NCNN_BF16 support_bf16_storage = true; #endif } int Padding_arm::create_pipeline(const Option& opt) { #if NCNN_ARM82 if (support_fp16_storage && opt.use_fp16_storage) { value_fp16 = float32_to_float16(value); ncnn::cast_float32_to_float16(per_channel_pad_data, per_channel_pad_data_fp16, opt); } #endif #if NCNN_BF16 if (opt.use_bf16_storage) { value_bf16 = float32_to_bfloat16(value); ncnn::cast_float32_to_bfloat16(per_channel_pad_data, per_channel_pad_data_bf16, opt); } #endif return 0; } int Padding_arm::destroy_pipeline(const Option& /*opt*/) { return 0; } int Padding_arm::forward(const Mat& bottom_blob, Mat& top_blob, const Option& opt) const { if (top == 0 && bottom == 0 && left == 0 && right == 0 && front == 0 && behind == 0) { top_blob = bottom_blob; return 0; } int elembits = bottom_blob.elembits(); if (elembits == 8) return forward_int8(bottom_blob, top_blob, opt); #if NCNN_ARM82 if (support_fp16_storage && opt.use_fp16_storage && elembits == 16) return forward_bf16s_fp16s(bottom_blob, top_blob, opt); #endif #if NCNN_BF16 if (opt.use_bf16_storage && elembits == 16) return forward_bf16s_fp16s(bottom_blob, top_blob, opt); #endif int w = bottom_blob.w; int h = bottom_blob.h; int d = bottom_blob.d; int channels = bottom_blob.c; int dims = bottom_blob.dims; size_t elemsize = bottom_blob.elemsize; int elempack = bottom_blob.elempack; #if __ARM_NEON if (elempack == 4) { if (dims == 1) { int outw = w * elempack + left + right; int out_elempack = outw % 4 == 0 ? 4 : 1; size_t out_elemsize = elemsize / elempack * out_elempack; if (left % 4 == 0 && out_elempack == 4 && type == 0) { top_blob.create(outw / out_elempack, out_elemsize, out_elempack, opt.blob_allocator); if (top_blob.empty()) return -100; float32x4_t pad_value = vdupq_n_f32(value); padding_constant_pack4_neon(bottom_blob, top_blob, 0, 0, left / 4, right / 4, pad_value); return 0; } } if (dims == 2) { int outw = w + left + right; int outh = h * elempack + top + bottom; int out_elempack = outh % 4 == 0 ? 4 : 1; size_t out_elemsize = elemsize / elempack * out_elempack; if (top % 4 == 0 && out_elempack == 4 && type == 0) { top_blob.create(outw, outh / out_elempack, out_elemsize, out_elempack, opt.blob_allocator); if (top_blob.empty()) return -100; float32x4_t pad_value = vdupq_n_f32(value); padding_constant_pack4_neon(bottom_blob, top_blob, top / 4, bottom / 4, left, right, pad_value); return 0; } } if (dims == 3) { int outw = w + left + right; int outh = h + top + bottom; int outc = channels * elempack + front + behind; int out_elempack = outc % 4 == 0 ? 4 : 1; size_t out_elemsize = elemsize / elempack * out_elempack; if (front % 4 == 0 && out_elempack == 4 && !(outc != channels * elempack && type != 0)) { top_blob.create(outw, outh, outc / out_elempack, out_elemsize, out_elempack, opt.blob_allocator); if (top_blob.empty()) return -100; int front_ = front / elempack; #pragma omp parallel for num_threads(opt.num_threads) for (int q = 0; q < outc / out_elempack; q++) { Mat borderm = top_blob.channel(q); float32x4_t pad_value = per_channel_pad_data_size ? vld1q_f32((const float*)per_channel_pad_data + q * 4) : vdupq_n_f32(value); //Channel padding if ((q - front_) < 0 || (q - front_) >= channels) { borderm.fill(pad_value); } else { const Mat m = bottom_blob.channel(q - front_); if (type == 0) padding_constant_pack4_neon(m, borderm, top, bottom, left, right, pad_value); if (type == 1) padding_replicate_pack4_neon(m, borderm, top, bottom, left, right); if (type == 2) padding_reflect_pack4_neon(m, borderm, top, bottom, left, right); } } return 0; } } if (dims == 4) { int outw = w + left + right; int outh = h + top + bottom; int outd = d + front + behind; if (type == 0) { top_blob.create(outw, outh, outd, channels, elemsize, elempack, opt.blob_allocator); if (top_blob.empty()) return -100; #pragma omp parallel for num_threads(opt.num_threads) for (int q = 0; q < channels; q++) { float32x4_t pad_value = per_channel_pad_data_size ? vld1q_f32((const float*)per_channel_pad_data + q * 4) : vdupq_n_f32(value); for (int z = 0; z < outd; z++) { Mat borderm = top_blob.channel(q).depth(z); // depth padding if ((z - front) < 0 || (z - front) >= d) { borderm.fill(pad_value); } else { const Mat m = bottom_blob.channel(q).depth(z - front); padding_constant_pack4_neon(m, borderm, top, bottom, left, right, pad_value); } } } return 0; } } } #endif // __ARM_NEON Mat bottom_blob_unpacked = bottom_blob; if (elempack != 1) { Option opt_pack1 = opt; opt_pack1.blob_allocator = opt.workspace_allocator; convert_packing(bottom_blob, bottom_blob_unpacked, 1, opt_pack1); } return Padding::forward(bottom_blob_unpacked, top_blob, opt); } int Padding_arm::forward_bf16s_fp16s(const Mat& bottom_blob, Mat& top_blob, const Option& opt) const { int w = bottom_blob.w; int h = bottom_blob.h; int d = bottom_blob.d; int channels = bottom_blob.c; int dims = bottom_blob.dims; size_t elemsize = bottom_blob.elemsize; int elempack = bottom_blob.elempack; #if __ARM_NEON #if NCNN_ARM82 if (elempack == 8) { if (dims == 1) { int outw = w * elempack + left + right; int out_elempack = outw % 8 == 0 ? 8 : outw % 4 == 0 ? 4 : 1; size_t out_elemsize = elemsize / elempack * out_elempack; if (left % 8 == 0 && out_elempack == 8 && type == 0) { top_blob.create(outw / out_elempack, out_elemsize, out_elempack, opt.blob_allocator); if (top_blob.empty()) return -100; uint16x8_t pad_value = vdupq_n_u16(value_fp16); padding_constant_pack8_fp16s_neon(bottom_blob, top_blob, 0, 0, left / 8, right / 8, pad_value); return 0; } } if (dims == 2) { int outw = w + left + right; int outh = h * elempack + top + bottom; int out_elempack = outh % 8 == 0 ? 8 : outh % 4 == 0 ? 4 : 1; size_t out_elemsize = elemsize / elempack * out_elempack; if (top % 8 == 0 && out_elempack == 8 && type == 0) { top_blob.create(outw, outh / out_elempack, out_elemsize, out_elempack, opt.blob_allocator); if (top_blob.empty()) return -100; uint16x8_t pad_value = vdupq_n_u16(value_fp16); padding_constant_pack8_fp16s_neon(bottom_blob, top_blob, top / 8, bottom / 8, left, right, pad_value); return 0; } } if (dims == 3) { int outw = w + left + right; int outh = h + top + bottom; int outc = channels * elempack + front + behind; int out_elempack = outc % 8 == 0 ? 8 : outc % 4 == 0 ? 4 : 1; size_t out_elemsize = elemsize / elempack * out_elempack; if (front % 8 == 0 && out_elempack == 8 && !(outc != channels * elempack && type != 0)) { top_blob.create(outw, outh, outc / out_elempack, out_elemsize, out_elempack, opt.blob_allocator); if (top_blob.empty()) return -100; int front_ = front / elempack; #pragma omp parallel for num_threads(opt.num_threads) for (int q = 0; q < outc / out_elempack; q++) { Mat borderm = top_blob.channel(q); uint16x8_t pad_value = per_channel_pad_data_size ? vld1q_u16((const unsigned short*)per_channel_pad_data_fp16 + q * 8) : vdupq_n_u16(value_fp16); //Channel padding if ((q - front_) < 0 || (q - front_) >= channels) { borderm.fill(pad_value); } else { const Mat m = bottom_blob.channel(q - front_); if (type == 0) padding_constant_pack8_fp16s_neon(m, borderm, top, bottom, left, right, pad_value); if (type == 1) padding_replicate_pack8_fp16s_neon(m, borderm, top, bottom, left, right); if (type == 2) padding_reflect_pack8_fp16s_neon(m, borderm, top, bottom, left, right); } } return 0; } } if (dims == 4) { int outw = w + left + right; int outh = h + top + bottom; int outd = d + front + behind; if (type == 0) { top_blob.create(outw, outh, outd, channels, elemsize, elempack, opt.blob_allocator); if (top_blob.empty()) return -100; #pragma omp parallel for num_threads(opt.num_threads) for (int q = 0; q < channels; q++) { uint16x8_t pad_value = per_channel_pad_data_size ? vld1q_u16((const unsigned short*)per_channel_pad_data_fp16 + q * 8) : vdupq_n_u16(value_fp16); for (int z = 0; z < outd; z++) { Mat borderm = top_blob.channel(q).depth(z); // depth padding if ((z - front) < 0 || (z - front) >= d) { borderm.fill(pad_value); } else { const Mat m = bottom_blob.channel(q).depth(z - front); padding_constant_pack8_fp16s_neon(m, borderm, top, bottom, left, right, pad_value); } } } return 0; } } } #endif if (elempack == 4) { if (dims == 1) { int outw = w * elempack + left + right; #if NCNN_ARM82 int out_elempack = support_fp16_storage && opt.use_fp16_arithmetic && outw % 8 == 0 ? 8 : outw % 4 == 0 ? 4 : 1; #else int out_elempack = outw % 4 == 0 ? 4 : 1; #endif size_t out_elemsize = elemsize / elempack * out_elempack; if (left % 4 == 0 && out_elempack == 4 && type == 0) { top_blob.create(outw / out_elempack, out_elemsize, out_elempack, opt.blob_allocator); if (top_blob.empty()) return -100; // clang-format off // *INDENT-OFF* uint16x4_t pad_value; #if NCNN_ARM82 if (support_fp16_storage && opt.use_fp16_storage) { pad_value = vdup_n_u16(value_fp16); } else #endif #if NCNN_BF16 if (opt.use_bf16_storage) { pad_value = vdup_n_u16(value_bf16); } else #endif { // shall never reach here pad_value = vdup_n_u16(0); } // *INDENT-ON* // clang-format on padding_constant_pack4_bf16_fp16s_neon(bottom_blob, top_blob, 0, 0, left / 4, right / 4, vcombine_u16(pad_value, pad_value)); return 0; } } if (dims == 2) { int outw = w + left + right; int outh = h * elempack + top + bottom; #if NCNN_ARM82 int out_elempack = support_fp16_storage && opt.use_fp16_arithmetic && outh % 8 == 0 ? 8 : outh % 4 == 0 ? 4 : 1; #else int out_elempack = outh % 4 == 0 ? 4 : 1; #endif size_t out_elemsize = elemsize / elempack * out_elempack; if (top % 4 == 0 && out_elempack == 4 && type == 0) { top_blob.create(outw, outh / out_elempack, out_elemsize, out_elempack, opt.blob_allocator); if (top_blob.empty()) return -100; // clang-format off // *INDENT-OFF* uint16x4_t pad_value; #if NCNN_ARM82 if (support_fp16_storage && opt.use_fp16_storage) { pad_value = vdup_n_u16(value_fp16); } else #endif #if NCNN_BF16 if (opt.use_bf16_storage) { pad_value = vdup_n_u16(value_bf16); } else #endif { // shall never reach here pad_value = vdup_n_u16(0); } // *INDENT-ON* // clang-format on padding_constant_pack4_bf16_fp16s_neon(bottom_blob, top_blob, top / 4, bottom / 4, left, right, vcombine_u16(pad_value, pad_value)); return 0; } } if (dims == 3) { int outw = w + left + right; int outh = h + top + bottom; int outc = channels * elempack + front + behind; #if NCNN_ARM82 int out_elempack = support_fp16_storage && opt.use_fp16_arithmetic && outc % 8 == 0 ? 8 : outc % 4 == 0 ? 4 : 1; #else int out_elempack = outc % 4 == 0 ? 4 : 1; #endif size_t out_elemsize = elemsize / elempack * out_elempack; if (front % 4 == 0 && out_elempack == 4 && !(outc != channels * elempack && type != 0)) { top_blob.create(outw, outh, outc / out_elempack, out_elemsize, out_elempack, opt.blob_allocator); if (top_blob.empty()) return -100; int front_ = front / elempack; #pragma omp parallel for num_threads(opt.num_threads) for (int q = 0; q < outc / out_elempack; q++) { Mat borderm = top_blob.channel(q); // clang-format off // *INDENT-OFF* uint16x4_t pad_value; #if NCNN_ARM82 if (support_fp16_storage && opt.use_fp16_storage) { pad_value = per_channel_pad_data_size ? vld1_u16((const unsigned short*)per_channel_pad_data_fp16 + q * 4) : vdup_n_u16(value_fp16); } else #endif #if NCNN_BF16 if (opt.use_bf16_storage) { pad_value = per_channel_pad_data_size ? vld1_u16((const unsigned short*)per_channel_pad_data_bf16 + q * 4) : vdup_n_u16(value_bf16); } else #endif { // shall never reach here pad_value = vdup_n_u16(0); } // *INDENT-ON* // clang-format on //Channel padding if ((q - front_) < 0 || (q - front_) >= channels) { borderm.fill(pad_value); } else { const Mat m = bottom_blob.channel(q - front_); if (type == 0) padding_constant_pack4_bf16_fp16s_neon(m, borderm, top, bottom, left, right, vcombine_u16(pad_value, pad_value)); if (type == 1) padding_replicate_pack4_bf16_fp16s_neon(m, borderm, top, bottom, left, right); if (type == 2) padding_reflect_pack4_bf16_fp16s_neon(m, borderm, top, bottom, left, right); } } return 0; } } if (dims == 4) { int outw = w + left + right; int outh = h + top + bottom; int outd = d + front + behind; if (type == 0) { top_blob.create(outw, outh, outd, channels, elemsize, elempack, opt.blob_allocator); if (top_blob.empty()) return -100; #pragma omp parallel for num_threads(opt.num_threads) for (int q = 0; q < channels; q++) { // clang-format off // *INDENT-OFF* uint16x4_t pad_value; #if NCNN_ARM82 if (support_fp16_storage && opt.use_fp16_storage) { pad_value = per_channel_pad_data_size ? vld1_u16((const unsigned short*)per_channel_pad_data_fp16 + q * 4) : vdup_n_u16(value_fp16); } else #endif #if NCNN_BF16 if (opt.use_bf16_storage) { pad_value = per_channel_pad_data_size ? vld1_u16((const unsigned short*)per_channel_pad_data_bf16 + q * 4) : vdup_n_u16(value_bf16); } else #endif { // shall never reach here pad_value = vdup_n_u16(0); } // *INDENT-ON* // clang-format on for (int z = 0; z < outd; z++) { Mat borderm = top_blob.channel(q).depth(z); // depth padding if ((z - front) < 0 || (z - front) >= d) { borderm.fill(pad_value); } else { const Mat m = bottom_blob.channel(q).depth(z - front); padding_constant_pack4_bf16_fp16s_neon(m, borderm, top, bottom, left, right, vcombine_u16(pad_value, pad_value)); } } } return 0; } } } #endif // __ARM_NEON Mat bottom_blob_unpacked = bottom_blob; if (elempack != 1) { Option opt_pack1 = opt; opt_pack1.blob_allocator = opt.workspace_allocator; convert_packing(bottom_blob, bottom_blob_unpacked, 1, opt_pack1); } return Padding::forward(bottom_blob_unpacked, top_blob, opt); } int Padding_arm::forward_int8(const Mat& bottom_blob, Mat& top_blob, const Option& opt) const { int w = bottom_blob.w; int h = bottom_blob.h; int d = bottom_blob.d; int channels = bottom_blob.c; int dims = bottom_blob.dims; size_t elemsize = bottom_blob.elemsize; int elempack = bottom_blob.elempack; #if __ARM_NEON if (elempack == 8) { if (dims == 1) { int outw = w * elempack + left + right; int out_elempack = outw % 8 == 0 ? 8 : 1; size_t out_elemsize = elemsize / elempack * out_elempack; if (left % 8 == 0 && out_elempack == 8 && type == 0) { top_blob.create(outw / out_elempack, out_elemsize, out_elempack, opt.blob_allocator); if (top_blob.empty()) return -100; int8x8_t pad_value = vdup_n_s8((signed char)value); padding_constant_pack8_int8_neon(bottom_blob, top_blob, 0, 0, left / 8, right / 8, pad_value); return 0; } } if (dims == 2) { int outw = w + left + right; int outh = h * elempack + top + bottom; int out_elempack = outh % 8 == 0 ? 8 : 1; size_t out_elemsize = elemsize / elempack * out_elempack; if (top % 8 == 0 && out_elempack == 8 && type == 0) { top_blob.create(outw, outh / out_elempack, out_elemsize, out_elempack, opt.blob_allocator); if (top_blob.empty()) return -100; int8x8_t pad_value = vdup_n_s8((signed char)value); padding_constant_pack8_int8_neon(bottom_blob, top_blob, top / 8, bottom / 8, left, right, pad_value); return 0; } } if (dims == 3) { int outw = w + left + right; int outh = h + top + bottom; int outc = channels * elempack + front + behind; int out_elempack = outc % 8 == 0 ? 8 : 1; size_t out_elemsize = elemsize / elempack * out_elempack; top_blob.create(outw, outh, outc / out_elempack, out_elemsize, out_elempack, opt.blob_allocator); if (top_blob.empty()) return -100; if (front % 8 == 0 && out_elempack == 8 && !(outc != channels * elempack && type != 0)) { int front_ = front / elempack; #pragma omp parallel for num_threads(opt.num_threads) for (int q = 0; q < outc / out_elempack; q++) { Mat borderm = top_blob.channel(q); // TODO perchannel // int8x8_t pad_value = per_channel_pad_data_size ? vld1_s8(per_channel_pad_data + q * 8) : vdup_n_s8((signed char)value); int8x8_t pad_value = vdup_n_s8((signed char)value); //Channel padding if ((q - front_) < 0 || (q - front_) >= channels) { borderm.fill(pad_value); } else { const Mat m = bottom_blob.channel(q - front_); if (type == 0) padding_constant_pack8_int8_neon(m, borderm, top, bottom, left, right, pad_value); if (type == 1) padding_replicate_pack8_int8_neon(m, borderm, top, bottom, left, right); if (type == 2) padding_reflect_pack8_int8_neon(m, borderm, top, bottom, left, right); } } return 0; } } if (dims == 4) { int outw = w + left + right; int outh = h + top + bottom; int outd = d + front + behind; top_blob.create(outw, outh, outd, channels, elemsize, elempack, opt.blob_allocator); if (top_blob.empty()) return -100; if (type == 0) { #pragma omp parallel for num_threads(opt.num_threads) for (int q = 0; q < channels; q++) { // TODO perchannel // int8x8_t pad_value = per_channel_pad_data_size ? vld1_s8(per_channel_pad_data + q * 8) : vdup_n_s8((signed char)value); int8x8_t pad_value = vdup_n_s8((signed char)value); for (int z = 0; z < outd; z++) { Mat borderm = top_blob.channel(q).depth(z); // depth padding if ((z - front) < 0 || (z - front) >= d) { borderm.fill(pad_value); } else { const Mat m = bottom_blob.channel(q).depth(z - front); padding_constant_pack8_int8_neon(m, borderm, top, bottom, left, right, pad_value); } } } return 0; } } } #endif // __ARM_NEON Mat bottom_blob_unpacked = bottom_blob; if (elempack != 1) { Option opt_pack1 = opt; opt_pack1.blob_allocator = opt.workspace_allocator; convert_packing(bottom_blob, bottom_blob_unpacked, 1, opt_pack1); } return Padding::forward(bottom_blob_unpacked, top_blob, opt); } } // namespace ncnn