feat(dnn/fallback): delete nopack onlypacka noneed datatype,and add

im2co and conv1x1 mk4_dot support

GitOrigin-RevId: 096b16a3ab

dnn/src/aarch64/matrix_mul/int8_dot/kernel_mk4_8x12x4.h

@@ -913,10 +913,10 @@ static void gemm_mk4_s8_8x12_pack_B(dt_int8* out, const dt_int8* in, int ldin,
                 *outptr++ = *inptr++;
             }
             for (; i < 4; i++) {
-                *outptr++ = *inptr++;
-                *outptr++ = *inptr++;
-                *outptr++ = *inptr++;
-                *outptr++ = *inptr++;
+                *outptr++ = 0;
+                *outptr++ = 0;
+                *outptr++ = 0;
+                *outptr++ = 0;
             }
         }
 

dnn/src/arm_common/conv_bias/postprocess_helper.h

@@ -39,7 +39,7 @@ namespace {
     megdnn::arm_common::OpCallerUnary<_op<ctype>, megdnn::arm_common::VEC>:: \
             run(static_cast<ctype*>(conv_dst_ptr),                           \
                 reinterpret_cast<ctype*>(dst_ptr), bias_type, dst_type,      \
-                N* OC* OH* OW);
+                N* OC* OH* OW* pack_oc_size);
 
 #define FOR_NONLINEAR_BINARY_BROADCAST(_op)                                    \
     megdnn::arm_common::                                                       \
@@ -63,7 +63,7 @@ namespace {
                     static_cast<ctype*>(conv_dst_ptr),                       \
                     reinterpret_cast<const ctype*>(bias_ptr),                \
                     reinterpret_cast<ctype*>(dst_ptr), bias_type, bias_type, \
-                    dst_type, N* OC* OH* OW);
+                    dst_type, N* OC* OH* OW* pack_oc_size);
 
 #define FOR_BIAS(_mode)                                               \
     switch (_mode) {                                                  \
@@ -113,7 +113,6 @@ struct PostProcess {
                     megdnn::BiasMode bias_mode, megdnn::NonlineMode nonlineMode,
                     megdnn::DType bias_type, megdnn::DType dst_type, size_t N,
                     size_t OC, size_t OH, size_t OW, size_t pack_oc_size = 1) {
-        MEGDNN_MARK_USED_VAR(pack_oc_size);
         FOR_BIAS(bias_mode)
     }
 };
@@ -155,7 +154,8 @@ struct PostProcess<ctype, dtype, megdnn::PostprocessMode::NO_PROCESS> {
             _op<opctype, opdtype>,                                             \
             megdnn::arm_common::VEC>::run(static_cast<opctype*>(conv_dst_ptr), \
                                           reinterpret_cast<opdtype*>(dst_ptr), \
-                                          bias_type, dst_type, N* OC* OH* OW);
+                                          bias_type, dst_type,                 \
+                                          N* OC* OH* OW* pack_oc_size);
 
 #define FOR_NONLINEAR_BINARY_BROADCAST(_op)                                \
     megdnn::arm_common::OpCallerBinary<_op<opctype, opdtype>,              \
@@ -173,8 +173,8 @@ struct PostProcess<ctype, dtype, megdnn::PostprocessMode::NO_PROCESS> {
                 reinterpret_cast<opdtype*>(dst_ptr), bias_type, bias_type,   \
                 dst_type, N, OC, OH* OW, pack_oc_size);
 
-#define HANDLE_IDENTITY(_caller, _op)   \
-    case megdnn::NonlineMode::IDENTITY: \
+#define HANDLE_IDENTITY(_caller, _op)              \
+    case megdnn::NonlineMode::IDENTITY:            \
         _caller(_op) break;
 
 #define FOR_NONLINEAR(_caller)                                      \

dnn/src/armv7/matrix_mul/int8/kernel_mk4_dot_8x6x4.h

@@ -729,10 +729,10 @@ static void gemm_dots8_8x6_pack_B(dt_int8* out, const dt_int8* in, int ldin,
                 *outptr++ = *inptr++;
             }
             for (; i < 4; i++) {
-                *outptr++ = *inptr++;
-                *outptr++ = *inptr++;
-                *outptr++ = *inptr++;
-                *outptr++ = *inptr++;
+                *outptr++ = 0;
+                *outptr++ = 0;
+                *outptr++ = 0;
+                *outptr++ = 0;
             }
         }
         outptr_base += 24;

dnn/src/fallback/conv_bias/conv1x1/algos.cpp

@@ -187,7 +187,8 @@ bool ConvBiasImpl::AlgoConv1x1::usable(ConvBiasImpl* opr,
                                        AlgoSelectionStrategy) const {
     MIDOUT_BEGIN(megdnn_fallback_conv1x1, 0, 2) {
         if (opr->param().format != param::ConvBias::Format::NCHW &&
-            opr->param().format != param::ConvBias::Format::NCHW44)
+            opr->param().format != param::ConvBias::Format::NCHW44 &&
+            opr->param().format != param::ConvBias::Format::NCHW44_DOT)
             return false;
 
         size_t FH = param.filter_meta.spatial[0],
@@ -219,8 +220,8 @@ bool ConvBiasImpl::AlgoConv1x1::usable(ConvBiasImpl* opr,
             param.nonlineMode != megdnn::NonlineMode::IDENTITY)
             return false;
 
-        if (opr->param().format == param::ConvBias::Format::NCHW44) {
-            //! nchw44 hybird mode and channel wise is not support
+        if (opr->param().format == param::ConvBias::Format::NCHW44 ||
+            opr->param().format == param::ConvBias::Format::NCHW44_DOT) {
             if (param.filter_meta.icpg < 4_z || param.filter_meta.icpg == 1 ||
                 param.filter_meta.ocpg == 1) {
                 return false;

dnn/src/fallback/conv_bias/conv1x1/conv1x1_strategy.cpp

@@ -73,32 +73,34 @@ std::unique_ptr<Conv1x1StrategyBase> create_conv1x1_strategy(
         const ConvBiasImpl::NCBKernSizeParam& param,
         MatrixMulImpl::AlgoBase::PackMode pack_mode,
         param::ConvBias::Format format) {
-    size_t pack_size = get_format_pack_size(format);
-#define cb1(_packmode, _dt, _post_ctype, _postprocess_mode, _midout_tag)       \
-    MIDOUT_BEGIN(megdnn_fallback_conv1x1_factory_strategy,                     \
-                 midout_iv(_midout_tag)) {                                     \
-        if (param.filter_type.enumv() == DTypeTrait<_dt>::enumv) {             \
-            return std::make_unique<                                           \
-                    Conv1x1Strategy<_dt, _dt, _dt, _post_ctype, _post_ctype,   \
-                                    _postprocess_mode, _packmode>>(pack_size); \
-        }                                                                      \
-    }                                                                          \
+    size_t pack_c_size = pack_size(format);
+#define cb1(_packmode, _dt, _post_ctype, _postprocess_mode, _midout_tag)     \
+    MIDOUT_BEGIN(megdnn_fallback_conv1x1_factory_strategy,                   \
+                 midout_iv(_midout_tag)) {                                   \
+        if (param.filter_type.enumv() == DTypeTrait<_dt>::enumv) {           \
+            return std::make_unique<                                         \
+                    Conv1x1Strategy<_dt, _dt, _dt, _post_ctype, _post_ctype, \
+                                    _postprocess_mode, _packmode>>(          \
+                    pack_c_size);                                            \
+        }                                                                    \
+    }                                                                        \
     MIDOUT_END()
 
-#define cb2(_packmode, _i_src_type, _i_bias_type, _i_dst_type, _src_ctype,     \
-            _bias_ctype, _dst_ctype, _postprocess_mode, _midout_tag)           \
-    MIDOUT_BEGIN(megdnn_fallback_conv1x1_factory_strategy,                     \
-                 midout_iv(_midout_tag)) {                                     \
-        if (param.filter_type.enumv() == param.src_type.enumv() &&             \
-            param.src_type.enumv() == DTypeTrait<_i_src_type>::enumv &&        \
-            param.dst_type.enumv() == DTypeTrait<_i_dst_type>::enumv) {        \
-            return std::make_unique<                                           \
-                    Conv1x1Strategy<_src_ctype, _bias_ctype, _dst_ctype,       \
-                                    DTypeTrait<_i_bias_type>::ctype,           \
-                                    DTypeTrait<_i_dst_type>::ctype,            \
-                                    _postprocess_mode, _packmode>>(pack_size); \
-        }                                                                      \
-    }                                                                          \
+#define cb2(_packmode, _i_src_type, _i_bias_type, _i_dst_type, _src_ctype, \
+            _bias_ctype, _dst_ctype, _postprocess_mode, _midout_tag)       \
+    MIDOUT_BEGIN(megdnn_fallback_conv1x1_factory_strategy,                 \
+                 midout_iv(_midout_tag)) {                                 \
+        if (param.filter_type.enumv() == param.src_type.enumv() &&         \
+            param.src_type.enumv() == DTypeTrait<_i_src_type>::enumv &&    \
+            param.dst_type.enumv() == DTypeTrait<_i_dst_type>::enumv) {    \
+            return std::make_unique<                                       \
+                    Conv1x1Strategy<_src_ctype, _bias_ctype, _dst_ctype,   \
+                                    DTypeTrait<_i_bias_type>::ctype,       \
+                                    DTypeTrait<_i_dst_type>::ctype,        \
+                                    _postprocess_mode, _packmode>>(        \
+                    pack_c_size);                                          \
+        }                                                                  \
+    }                                                                      \
     MIDOUT_END()
 
     switch (pack_mode) {

dnn/src/fallback/conv_bias/conv1x1/conv1x1_strategy.h

@@ -12,7 +12,6 @@
 
 #pragma once
 
-#include "megdnn/opr_param_defs.h"
 #include "src/fallback/conv_bias/opr_impl.h"
 #if MEGDNN_X86
 #include "src/x86/conv_bias/postprocess_helper.h"
@@ -41,12 +40,15 @@ MatrixMulImpl::KernSizeParam get_matmul_kern_param(
                         param.dst_type.enumv() == DTypeEnum::QuantizedS8) ||
                        (param.src_type.enumv() == DTypeEnum::Quantized8Asymm &&
                         param.dst_type.enumv() == DTypeEnum::Quantized8Asymm);
-    size_t pack_c_size = 1_z;
+    size_t pack_c_size = pack_size(param.filter_meta.format);
     auto format = param::MatrixMul::Format::DEFAULT;
-    if(param.filter_meta.format == param::ConvBias::Format::NCHW44){
-        pack_c_size = 4_z;
+    if (param.filter_meta.format == param::ConvBias::Format::NCHW44) {
         format = param::MatrixMul::Format::MK4;
+    } else if (param.filter_meta.format ==
+               param::ConvBias::Format::NCHW44_DOT) {
+        format = param::MatrixMul::Format::MK4_DOT;
     }
+
     return {param.filter_type,
             param.src_type,
             is_dst_8bit ? param.bias_type : param.dst_type,

dnn/src/fallback/conv_bias/im2col/algos.cpp

@@ -15,7 +15,6 @@
 #include "src/common/opr_delegate.h"
 #include "src/fallback/conv_bias/common.h"
 #include "src/fallback/conv_bias/opr_impl.h"
-#include "src/fallback/conv_bias/winograd/strategy.h"
 #include "src/naive/convolution/helper.h"
 
 #include "midout.h"
@@ -125,7 +124,7 @@ public:
             size_t oc_tile_size) {
         size_t IC = param.filter_meta.icpg, FH = param.filter_meta.spatial[0],
                FW = param.filter_meta.spatial[1];
-        size_t pack_oc_size = get_format_pack_size(param.filter_meta.format);
+        size_t pack_oc_size = pack_size(param.filter_meta.format);
         size_t im2col = 0, packb = 0, bias_temp = 0;
         bool default_pack = matmul_algo->packmode() == Pack_Mode::DEFAULT;
         megdnn_assert(default_pack, "only support default packa");
@@ -319,9 +318,11 @@ ConvBiasImpl::AlgoIm2col ::get_matmul_kern_param(const NCBKernSizeParam& param,
                                                  size_t ohw_tile_size,
                                                  size_t oc_tile_size) const {
     auto format = param::MatrixMul::Format::DEFAULT;
-    size_t pack_oc_size = get_format_pack_size(param.filter_meta.format);
+    size_t pack_oc_size = pack_size(param.filter_meta.format);
     if (param.filter_meta.format == param::ConvBias::Format::NCHW44) {
         format = param::MatrixMul::Format::MK4;
+    } else if(param.filter_meta.format == param::ConvBias::Format::NCHW44_DOT){
+        format = param::MatrixMul::Format::MK4_DOT;
     }
     size_t M = oc_tile_size;
     size_t N = ohw_tile_size;
@@ -351,11 +352,10 @@ ConvBiasImpl::AlgoIm2col ::get_matmul_kern_param(const NCBKernSizeParam& param,
 void ConvBiasImpl::AlgoIm2col::choice_ohw_oc_block(
         const NCBKernSizeParam& param, size_t& oc_tile_size,
         size_t& ohw_tile_size, size_t block_m, size_t block_n,
-        bool need_pack) const {
+        fallback::MatrixMulImpl::AlgoBase::PackMode pack_mode) const {
     size_t nr_threads = param.nr_threads;
     size_t OC = param.filter_meta.ocpg;
     size_t ohw = param.osz[0] * param.osz[1];
-
     oc_tile_size = DEFAULT_OC_TILE_SIZE;
     ohw_tile_size = m_ohw_tile_size;
 
@@ -376,7 +376,8 @@ void ConvBiasImpl::AlgoIm2col::choice_ohw_oc_block(
             }
         }
     } else {
-        if (!need_pack) {  //! no pack ,usually in x86 save memroy
+        //! in no_pack mode don't do block operation when using single thread
+        if (pack_mode == fallback::MatrixMulImpl::AlgoBase::PackMode::NO_PACK) {
             ohw_tile_size = ohw;
             oc_tile_size = OC;
         }
@@ -406,7 +407,7 @@ WorkspaceBundle ConvBiasImpl::AlgoIm2col::get_bundle(
     if (need_pack || only_packA) {
         auto inner_block = m_matmul_algo->get_inner_block_size();
         choice_ohw_oc_block(param, oc_tile_size, ohw_tile_size, inner_block.m,
-                            inner_block.n, need_pack);
+                            inner_block.n, m_matmul_algo->packmode());
         auto im2col_kern_param = get_matmul_kern_param(
                 param, ohw_tile_size, only_packA ? oc_tile_size : OC);
         size_t oc_parallel_times = div_ceil<size_t>(OC, oc_tile_size);
@@ -418,7 +419,7 @@ WorkspaceBundle ConvBiasImpl::AlgoIm2col::get_bundle(
         size_t nopack_default_blockn = 16;
         choice_ohw_oc_block(param, oc_tile_size, ohw_tile_size,
                             nopack_default_blockm, nopack_default_blockn,
-                            need_pack);
+                            m_matmul_algo->packmode());
         packa_group_size = 0;
     }
 
@@ -488,19 +489,20 @@ SmallVector<ConvBiasImpl::NCBKern> ConvBiasImpl::AlgoIm2col::dispatch_kerns(
         if (default_pack || only_packA) {
             auto inner_block = m_matmul_algo->get_inner_block_size();
             choice_ohw_oc_block(param, oc_tile_size, ohw_tile_size,
-                                inner_block.m, inner_block.n, default_pack);
-        } else {  //! not support pack,not need pack
+                                inner_block.m, inner_block.n,
+                                m_matmul_algo->packmode());
+        } else {  //! nopack_mode
             size_t nopack_default_blockm = 8;
             size_t nopack_default_blockn = 16;
             choice_ohw_oc_block(param, oc_tile_size, ohw_tile_size,
                                 nopack_default_blockm, nopack_default_blockn,
-                                no_pack);
+                                m_matmul_algo->packmode());
         }
 
         size_t ohw_parallel_times = div_ceil(ohw, ohw_tile_size);
         size_t oc_parallel_times = div_ceil<size_t>(OC, oc_tile_size);
         size_t packa_parallel_times = 0;
-        size_t pack_oc_size = get_format_pack_size(param.filter_meta.format);
+        size_t pack_oc_size = pack_size(param.filter_meta.format);
 
         if (only_packA) {
             packa_parallel_times = div_ceil<size_t>(OC, oc_tile_size);
@@ -639,9 +641,15 @@ bool ConvBiasImpl::AlgoIm2col::usable(
         ConvBiasImpl* opr, const NCBKernSizeParam& param,
         AlgoSelectionStrategy /*algo_selection_strategy*/) const {
     MIDOUT_BEGIN(megdnn_fallback_im2col, 0, 2) {
+        if (opr->param().format != param::ConvBias::Format::NCHW &&
+            opr->param().format != param::ConvBias::Format::NCHW44_DOT &&
+            opr->param().format != param::ConvBias::Format::NCHW44) {
+            return false;
+        }
+
         //! make sure 8x8x16 and 8x8x32 biasmode is  nobias and nonlineMode is
-        //! identity otherwise return false mean that 8x8x32 and 8x8x16 not support
-        //! PostProcess
+        //! identity otherwise return false mean that 8x8x32 and 8x8x16 not
+        //! support PostProcess
         if (param.src_type.enumv() == param.filter_type.enumv() &&
             ((param.src_type.enumv() == DTypeEnum::Int8 &&
               (param.dst_type.enumv() == DTypeEnum::Int16 ||
@@ -653,9 +661,10 @@ bool ConvBiasImpl::AlgoIm2col::usable(
             param.nonlineMode != megdnn::NonlineMode::IDENTITY) {
             return false;
         }
-        if (opr->param().format == param::ConvBias::Format::NCHW44) {
+        if (opr->param().format == param::ConvBias::Format::NCHW44 ||
+            opr->param().format == param::ConvBias::Format::NCHW44_DOT) {
             //! current NCHW44 im2col only support DEFAULT mode matmul
-            if(m_matmul_algo->packmode() != Pack_Mode::DEFAULT) {
+            if (m_matmul_algo->packmode() != Pack_Mode::DEFAULT) {
                 return false;
                 //! nchw44 hybird mode and channel wise is not support
             } else if (param.filter_meta.icpg < 4_z ||
@@ -668,29 +677,27 @@ bool ConvBiasImpl::AlgoIm2col::usable(
         size_t oc_tile_size = 0, ohw_tile_size = 0;
         Pack_Mode packmode = m_matmul_algo->packmode();
         bool default_pack = packmode == Pack_Mode::DEFAULT;
-        bool no_pack = packmode == Pack_Mode::NO_PACK;
         bool only_packA = packmode == Pack_Mode::ONLY_PACKA;
 
         if (default_pack || only_packA) {
             auto inner_block = m_matmul_algo->get_inner_block_size();
             choice_ohw_oc_block(param, oc_tile_size, ohw_tile_size,
-                                inner_block.m, inner_block.n, default_pack);
+                                inner_block.m, inner_block.n,
+                                m_matmul_algo->packmode());
         } else {  //! not support pack,not need pack
             size_t nopack_default_blockm = 8;
             size_t nopack_default_blockn = 16;
             choice_ohw_oc_block(param, oc_tile_size, ohw_tile_size,
                                 nopack_default_blockm, nopack_default_blockn,
-                                no_pack);
+                                m_matmul_algo->packmode());
         }
         fallback::MatrixMulImpl::KernSizeParam matmul_param =
                 get_matmul_kern_param(param, ohw_tile_size, oc_tile_size);
         bool matmulusable = m_matmul_algo->usable(matmul_param);
         return matmulusable &&
-               (opr->param().format == param::ConvBias::Format::NCHW ||
-                opr->param().format == param::ConvBias::Format::NCHW44) &&
                (!(param.filter_meta.spatial[0] ==
                           param.filter_meta.spatial[1] &&
-                  (param.filter_meta.spatial[0] == 1) &&
+                  param.filter_meta.spatial[0] == 1 &&
                   param.filter_meta.stride[0] == param.filter_meta.stride[1] &&
                   param.filter_meta.stride[0] == 1)) &&
                (param.filter_meta.dilation[0] ==

dnn/src/fallback/conv_bias/im2col/algos.h

@@ -36,10 +36,10 @@ class ConvBiasImpl::AlgoIm2col final : public AlgoBase {
             const NCBKernSizeParam& param, size_t ohw_tile_size,
             size_t oc_tile_size) const;
     WorkspaceBundle get_bundle(const NCBKernSizeParam& param) const;
-    void choice_ohw_oc_block(const NCBKernSizeParam& param,
-                             size_t& oc_tile_size, size_t& ohw_tile_size,
-                             size_t block_m, size_t block_n,
-                             bool pack_default) const;
+    void choice_ohw_oc_block(
+            const NCBKernSizeParam& param, size_t& oc_tile_size,
+            size_t& ohw_tile_size, size_t block_m, size_t block_n,
+            fallback::MatrixMulImpl::AlgoBase::PackMode pack_mode) const;
 
 public:
     AlgoIm2col(MatrixMulImpl::AlgoBase* matmul_algo, size_t ohw_tile_size)

dnn/src/fallback/conv_bias/im2col/factory.h

@@ -230,7 +230,11 @@ public:
                         PostprocessMode::FLOAT,
                         "DefaultStrategyTypeNCHW44::FLOAT"_hash);
                 } else {
-                    megdnn_throw("not support format except nchw44 and nchw\n");
+                    megdnn_throw(
+                            ssprintf("Current only support layout "
+                                     "NCHW44/NCHW for im2col "
+                                     "algo, but got %d\n",
+                                     uint32_t(format)));
                 }
                 break;
 #if __ARM_FEATURE_FP16_VECTOR_ARITHMETIC
@@ -252,12 +256,17 @@ public:
                     cb2(NCHW, DEFAULT, dt_int8, dt_int32, dt_int32, dt_int8,
                         dt_int32, dt_int32, PostprocessMode::NO_PROCESS,
                         "DefaultStrategyType::INT8x8x32"_hash);
-                } else if (format == param::ConvBias::Format::NCHW44) {
+                } else if (format == param::ConvBias::Format::NCHW44 ||
+                           format == param::ConvBias::Format::NCHW44_DOT) {
                     cb2(NCHW44, DEFAULT, dt_int8, dt_int32, dt_int32, dt_int8,
                         dt_int32, dt_int32, PostprocessMode::NO_PROCESS,
                         "DefaultStrategyType::INT8x8x32"_hash);
                 } else {
-                    megdnn_throw("not support format except nchw44 and nchw\n");
+                    megdnn_throw(
+                            ssprintf("Current only support layout "
+                                     "NCHW44/NCHW/NCHW_DOT for im2col "
+                                     "algo, but got %d\n",
+                                     uint32_t(format)));
                 }
 
                 break;
@@ -288,13 +297,18 @@ public:
                         dtype::QuantizedS32, dt_int8, dt_int32, dt_int32,
                         PostprocessMode::NO_PROCESS,
                         "DefaultStrategyTypeNCHW::QINT8x8x32"_hash);
-                } else if (format == param::ConvBias::Format::NCHW44) {
+                } else if (format == param::ConvBias::Format::NCHW44 ||
+                           format == param::ConvBias::Format::NCHW44_DOT) {
                     cb2(NCHW44, DEFAULT, dtype::QuantizedS8,
                         dtype::QuantizedS32, dtype::QuantizedS32, dt_int8,
                         dt_int32, dt_int32, PostprocessMode::NO_PROCESS,
                         "DefaultStrategyTypeHCHW44::QINT8x8x32"_hash);
                 } else {
-                    megdnn_throw("not support format except nchw44 and nchw\n");
+                    megdnn_throw(
+                            ssprintf("Current only support layout "
+                                     "NCHW44/NCHW/NCHW_DOT for im2col "
+                                     "algo, but got %d\n",
+                                     uint32_t(format)));
                 }
                 break;
 
@@ -304,17 +318,22 @@ public:
                         dtype::QuantizedS8, dt_int8, dt_int32, dt_int8,
                         PostprocessMode::QUANTIZED,
                         "DefaultStrategyType::QINT8x8x32x8"_hash);
-                } else if (format == param::ConvBias::Format::NCHW44) {
+                } else if (format == param::ConvBias::Format::NCHW44 ||
+                           format == param::ConvBias::Format::NCHW44_DOT) {
                     cb2(NCHW44, DEFAULT, dtype::QuantizedS8,
                         dtype::QuantizedS32, dtype::QuantizedS8, dt_int8,
                         dt_int32, dt_int8, PostprocessMode::QUANTIZED,
                         "DefaultStrategyTypeNCHW44::QINT8x8x32x8"_hash);
                 } else {
-                    megdnn_throw("not support format except nchw44 and nchw\n");
+                    megdnn_throw(ssprintf("Current only support layout "
+                                          "NCHW44/NCHW/NCHW_DOT for im2col "
+                                          "algo, but got %d\n",
+                                          uint32_t(format)));
                 }
                 break;
         }
-        megdnn_throw("error not support strategy type ");
+        megdnn_throw(ssprintf("Unsupported strategy type %u in default mode",
+                              uint32_t(strategytype)));
     }
 
     static std::unique_ptr<StrategyBase> make_nopack_strategy(
@@ -328,10 +347,6 @@ public:
                     PostprocessMode::FLOAT, "NoPackStrategyType::FLOAT"_hash);
                 break;
 #if __ARM_FEATURE_FP16_VECTOR_ARITHMETIC
-            case StrategyType::FLOAT_FP16:
-                cb1(NCHW, NO_PACK, dt_float16, __fp16, PostprocessMode::FLOAT,
-                    "NoPackStrategyType::FLOAT_FP16"_hash);
-                break;
 #else
 #if !MEGDNN_DISABLE_FLOAT16
             case StrategyType::FLOAT16_FLOAT16:
@@ -341,48 +356,24 @@ public:
                 break;
 #endif
 #endif
-            case StrategyType::INT8x8x32:
-                cb2(NCHW, NO_PACK, dt_int8, dt_int32, dt_int32, dt_int8,
-                    dt_int32, dt_int32, PostprocessMode::NO_PROCESS,
-                    "NoPackStrategyType::INT8x8x32"_hash);
-                break;
-
             case StrategyType::INT8x8x16:
                 cb2(NCHW, NO_PACK, dt_int8, dt_int16, dt_int16, dt_int8,
                     dt_int16, dt_int16, PostprocessMode::NO_PROCESS,
                     "NoPackStrategyType::INT8x8x16"_hash);
                 break;
-
-#if MEGDNN_AARCH64 || MEGDNN_ARMV7
-            case StrategyType::QUINT8x8x32:
-                cb2(NCHW, NO_PACK, dtype::Quantized8Asymm, dtype::QuantizedS32,
-                    dtype::QuantizedS32, dt_uint8, dt_int32, dt_int32,
-                    PostprocessMode::NO_PROCESS,
-                    "NoPackStrategyType::QUINT8x8x32"_hash);
-                break;
-
-            case StrategyType::QUINT8x8x32x8:
-                cb2(NCHW, NO_PACK, dtype::Quantized8Asymm, dtype::QuantizedS32,
-                    dtype::Quantized8Asymm, dt_uint8, dt_int32, dt_uint8,
-                    PostprocessMode::QUANTIZED,
-                    "NoPackStrategyType::QUINT8x8x32x8"_hash);
-                break;
-#endif
-            case StrategyType::QINT8x8x32:
-                cb2(NCHW, NO_PACK, dtype::QuantizedS8, dtype::QuantizedS32,
-                    dtype::QuantizedS32, dt_int8, dt_int32, dt_int32,
-                    PostprocessMode::NO_PROCESS,
-                    "NoPackStrategyType::QINT8x8x32"_hash);
+            case StrategyType::INT8x8x32:
+                cb2(NCHW, NO_PACK, dt_int8, dt_int32, dt_int32, dt_int8,
+                    dt_int32, dt_int32, PostprocessMode::NO_PROCESS,
+                    "NoPackStrategyType::INT8x8x32"_hash);
                 break;
-
-            case StrategyType::QINT8x8x32x8:
-                cb2(NCHW, NO_PACK, dtype::QuantizedS8, dtype::QuantizedS32,
-                    dtype::QuantizedS8, dt_int8, dt_int32, dt_int8,
-                    PostprocessMode::QUANTIZED,
-                    "NoPackStrategyType::QINT8x8x32x8"_hash);
+            default:
+                megdnn_throw(
+                        ssprintf("Unsupported strategy type %u in no_pack mode",
+                                 uint32_t(strategytype)));
                 break;
         }
-        megdnn_throw("error not support strategy type ");
+        megdnn_throw(ssprintf("Unsupported strategy type %u in no_pack mode",
+                              uint32_t(strategytype)));
     }
 
     static std::unique_ptr<StrategyBase> make_onlypacka_strategy(
@@ -396,63 +387,14 @@ public:
                     PostprocessMode::FLOAT,
                     "OnlyPackaStrategyType::FLOAT"_hash);
                 break;
-#if __ARM_FEATURE_FP16_VECTOR_ARITHMETIC
-            case StrategyType::FLOAT_FP16:
-                cb1(NCHW, ONLY_PACKA, dt_float16, __fp16,
-                    PostprocessMode::FLOAT,
-                    "OnlyPackaStrategyType::FLOAT_FP16"_hash);
-                break;
-#else
-#if !MEGDNN_DISABLE_FLOAT16
-            case StrategyType::FLOAT16_FLOAT16:
-                cb1(NCHW, ONLY_PACKA, dt_float16, dt_float16,
-                    PostprocessMode::NO_PROCESS,
-                    "OnlyPackaStrategyType::FLOAT16_FLOAT16"_hash);
-                break;
-#endif
-#endif
-            case StrategyType::INT8x8x32:
-                cb2(NCHW, ONLY_PACKA, dt_int8, dt_int32, dt_int32, dt_int8,
-                    dt_int32, dt_int32, PostprocessMode::NO_PROCESS,
-                    "OnlyPackaStrategyType::INT8x8x32"_hash);
-                break;
-
-            case StrategyType::INT8x8x16:
-                cb2(NCHW, ONLY_PACKA, dt_int8, dt_int16, dt_int16, dt_int8,
-                    dt_int16, dt_int16, PostprocessMode::NO_PROCESS,
-                    "OnlyPackaStrategyType::INT8x8x16"_hash);
-                break;
-
-#if MEGDNN_AARCH64 || MEGDNN_ARMV7
-            case StrategyType::QUINT8x8x32:
-                cb2(NCHW, ONLY_PACKA, dtype::Quantized8Asymm,
-                    dtype::QuantizedS32, dtype::QuantizedS32, dt_uint8,
-                    dt_int32, dt_int32, PostprocessMode::NO_PROCESS,
-                    "OnlyPackaStrategyType::QUINT8x8x32"_hash);
-                break;
-
-            case StrategyType::QUINT8x8x32x8:
-                cb2(NCHW, ONLY_PACKA, dtype::Quantized8Asymm,
-                    dtype::QuantizedS32, dtype::Quantized8Asymm, dt_uint8,
-                    dt_int32, dt_uint8, PostprocessMode::QUANTIZED,
-                    "OnlyPackaStrategyType::QUINT8x8x32x8"_hash);
-                break;
-#endif
-            case StrategyType::QINT8x8x32:
-                cb2(NCHW, ONLY_PACKA, dtype::QuantizedS8, dtype::QuantizedS32,
-                    dtype::QuantizedS32, dt_int8, dt_int32, dt_int32,
-                    PostprocessMode::NO_PROCESS,
-                    "OnlyPackaStrategyType::QINT8x8x32"_hash);
-                break;
-
-            case StrategyType::QINT8x8x32x8:
-                cb2(NCHW, ONLY_PACKA, dtype::QuantizedS8, dtype::QuantizedS32,
-                    dtype::QuantizedS8, dt_int8, dt_int32, dt_int8,
-                    PostprocessMode::QUANTIZED,
-                    "OnlyPackaStrategyType::QINT8x8x32x8"_hash);
+            default:
+                megdnn_throw(ssprintf(
+                        "Unsupported strategy type %u in onlypacka mode",
+                        uint32_t(strategytype)));
                 break;
         }
-        megdnn_throw("error not support strategy type ");
+        megdnn_throw(ssprintf("Unsupported strategy type %u in onlypacka mode",
+                              uint32_t(strategytype)));
     }
 
 #undef cb1

dnn/src/fallback/conv_bias/im2col/strategy_base.h

@@ -11,6 +11,16 @@
 
 #pragma once
 #include "src/fallback/conv_bias/opr_impl.h"
+
+#if MEGDNN_X86
+#include "src/x86/conv_bias/postprocess_helper.h"
+#elif (MEGDNN_ARMV7 || MEGDNN_AARCH64)
+#include "src/arm_common/conv_bias/postprocess_helper.h"
+#endif
+using namespace megdnn;
+#if MEGDNN_X86
+using namespace x86;
+#endif
 namespace megdnn {
 
 using PackMode = fallback::MatrixMulImpl::AlgoBase::PackMode;
@@ -72,6 +82,185 @@ public:
             const StrategyParam& sparam, WorkspaceBundle bundle_thread) = 0;
 };
 
+template <typename src_ctype, typename bias_ctype, typename dst_ctype,
+          typename op_ctype, typename op_dtype,
+          megdnn::PostprocessMode postprocess_mode, PackMode packmode,
+          FormatMode format>
+//! this class is a new base class for StrategyDefault StrategyNoPack and so on,
+//! in order to handle copy pad use the same code
+class StrategyBridge : public StrategyBase {
+public:
+    constexpr static size_t BUNDLE_PADDING_INDEX = 0;
+
+    StrategyBridge() = default;
+
+    virtual void copy_padding_kern(
+            WorkspaceBundle bundle,
+            const fallback::ConvBiasImpl::NCBKernParam& param,
+            const fallback::ConvBiasImpl::NCBKernIndex& ncb_index,
+            size_t pack_oc_size) override {
+        UNPACK_CONV_F32_NCB_KERN_SIZES(param);
+        MEGDNN_MARK_USED_VAR(N);
+        MEGDNN_MARK_USED_VAR(OC);
+        MEGDNN_MARK_USED_VAR(OH);
+        MEGDNN_MARK_USED_VAR(OW);
+        MEGDNN_MARK_USED_VAR(FH);
+        MEGDNN_MARK_USED_VAR(FW);
+        MEGDNN_MARK_USED_VAR(SH);
+        MEGDNN_MARK_USED_VAR(SW);
+        size_t IW2 = IW + 2 * PW;
+        size_t IH2 = IH + 2 * PH;
+        size_t batch_id = ncb_index.ndrange_id[0];
+        size_t group_id = ncb_index.ndrange_id[1];
+        size_t channel_id = ncb_index.ndrange_id[2];
+        size_t PH_SIZE = PH * IW2 * pack_oc_size;
+
+        PW = PW * pack_oc_size;
+        IW = IW * pack_oc_size;
+
+        size_t padding_group_size = IH2 * IW2 * IC;
+        size_t workspace_channel_offset = pack_oc_size * IH2 * IW2 * channel_id;
+        size_t workspace_group_offset = group_id * padding_group_size;
+        size_t workspace_batch_offset =
+                param.filter_meta.group * batch_id * padding_group_size;
+        bundle.set(param.workspace_ptr);
+
+        src_ctype src_zp = static_cast<src_ctype>(0);
+        if (param.src_type.enumv() == DTypeEnum::Quantized8Asymm) {
+            src_zp = param.src_type.param<dtype::Quantized8Asymm>().zero_point;
+        }
+        src_ctype* src = const_cast<src_ctype*>(param.src<src_ctype>(
+                batch_id, group_id, channel_id, 1, pack_oc_size));
+        src_ctype* src2;
+        src2 = static_cast<src_ctype*>(bundle.get(BUNDLE_PADDING_INDEX)) +
+               workspace_group_offset + workspace_batch_offset +
+               workspace_channel_offset;
+        src_ctype* src2_ptr = src2;
+        const src_ctype* src_ptr = src;
+        if (PH != 0) {
+            std::memset(src2_ptr, src_zp, sizeof(src_ctype) * PH_SIZE);
+            src2_ptr += PH_SIZE;
+        }
+        rep(ih, IH) {
+            if (PW != 0)
+                rep(pw, PW) * (src2_ptr++) = src_zp;
+            std::memcpy(src2_ptr, src_ptr, sizeof(src_ctype) * IW);
+            src2_ptr += IW;
+            src_ptr += IW;
+            if (PW != 0)
+                rep(pw, PW) * (src2_ptr++) = src_zp;
+        }
+        if (PH != 0) {
+            std::memset(src2_ptr, src_zp, sizeof(src_ctype) * PH_SIZE);
+            src2_ptr += PH_SIZE;
+        }
+    }
+};
+
+namespace{
+template <typename bias_ctype>
+inline void* get_matmul_dst_ptr(const fallback::ConvBiasImpl::NCBKernParam& param,
+                           const WorkspaceBundle& bundle_thread,
+                           const StrategyParam& sparam,
+                           size_t matmul_bundle_index) {
+    if (sparam.is_dst_8bit || !sparam.is_ohw_size_bigger) {
+        return static_cast<void*>(bundle_thread.get(matmul_bundle_index));
+    } else {
+        bias_ctype* dst =
+                param.dst<bias_ctype>(sparam.batch_id, sparam.group_id) +
+                sparam.oc_cur_index * sparam.ohw;
+        return static_cast<void*>(dst);
+    }
+}
+
+template <typename bias_ctype>
+inline void* get_bias_temp_ptr(
+        const fallback::ConvBiasImpl::NCBKernParam& param,
+        const WorkspaceBundle& bundle_thread, size_t bias_bundle_index) {
+    bias_ctype* bias_tmp_ptr =
+            param.bias_mode == megdnn::BiasMode::BIAS
+                    ? static_cast<bias_ctype*>(
+                              bundle_thread.get(bias_bundle_index))
+                    : nullptr;
+    return bias_tmp_ptr;
+}
+
+template <typename dst_ctype>
+void copy_dst(const fallback::ConvBiasImpl::NCBKernParam& param,
+              const void* matmul_dst, const StrategyParam& sparam) {
+    if (!sparam.skip_copy_dst) {
+        size_t pack_oc_size = sparam.pack_oc_size;
+        dst_ctype* dst_tmp_ptr =
+                reinterpret_cast<dst_ctype*>(const_cast<void*>(matmul_dst));
+        dst_ctype* dst =
+                param.dst<dst_ctype>(sparam.batch_id, sparam.group_id) +
+                sparam.oc_cur_index * sparam.ohw +
+                sparam.ohw_cur_index * pack_oc_size;
+        size_t oc_loop = sparam.output_block_oc_size / pack_oc_size;
+        for (size_t oc = 0; oc < oc_loop; oc++) {
+            std::memcpy(dst, dst_tmp_ptr,
+                        sizeof(dst_ctype) * sparam.output_block_size *
+                                pack_oc_size);
+            dst_tmp_ptr += sparam.output_block_size * pack_oc_size;
+            dst += sparam.ohw * pack_oc_size;
+        }
+    }
+}
+
+template <typename bias_ctype>
+void copy_bias(const fallback::ConvBiasImpl::NCBKernParam& param,
+               WorkspaceBundle bundle_thread, const StrategyParam& sparam,
+               size_t bias_index) {
+    const bias_ctype* bias_ptr = static_cast<const bias_ctype*>(
+            param.bias<bias_ctype>(sparam.batch_id, sparam.group_id));
+    bias_ctype* bias_temp_ptr = static_cast<bias_ctype*>(
+            get_bias_temp_ptr<bias_ctype>(param, bundle_thread, bias_index));
+    if (param.bias_mode == megdnn::BiasMode::BIAS) {
+        bias_ctype* copy_dst = bias_temp_ptr;
+        size_t pack_oc_size = sparam.pack_oc_size;
+        const bias_ctype* copy_src = bias_ptr +
+                                     sparam.oc_cur_index * sparam.ohw +
+                                     sparam.ohw_cur_index * pack_oc_size;
+        for (size_t oc = sparam.oc_cur_index / pack_oc_size;
+             oc < sparam.oc_end_index / pack_oc_size; oc++) {
+            std::memcpy(copy_dst, copy_src,
+                        sizeof(bias_ctype) * sparam.output_block_size *
+                                pack_oc_size);
+            copy_dst += sparam.output_block_size * pack_oc_size;
+            copy_src += sparam.ohw * pack_oc_size;
+        }
+    }
+}
+
+template <typename bias_ctype, typename dst_ctype,
+          typename op_ctype, typename op_dtype,
+          megdnn::PostprocessMode postprocess_mode>
+void do_postprocess(const fallback::ConvBiasImpl::NCBKernParam& param,
+                    const StrategyParam& sparam, WorkspaceBundle bundle_thread,
+                    size_t matmul_bundle_index, size_t bias_bundle_index) {
+    copy_bias<bias_ctype>(param, bundle_thread, sparam, bias_bundle_index);
+    void* matmul_dst = get_matmul_dst_ptr<bias_ctype>(
+            param, bundle_thread, sparam, matmul_bundle_index);
+
+    const bias_ctype* bias_ptr = static_cast<const bias_ctype*>(
+            param.bias<bias_ctype>(sparam.batch_id, sparam.group_id));
+    void* bias_temp_ptr = get_bias_temp_ptr<bias_ctype>(param, bundle_thread,
+                                                        bias_bundle_index);
+    void* bias_preprocess_ptr = const_cast<void*>(
+            param.bias_mode == megdnn::BiasMode::BIAS
+                    ? bias_temp_ptr
+                    : static_cast<void*>(const_cast<bias_ctype*>(
+                              bias_ptr + sparam.oc_cur_index)));
+    size_t pack_oc_size = sparam.pack_oc_size;
+    PostProcess<op_ctype, op_dtype, postprocess_mode>::run(
+            matmul_dst, bias_preprocess_ptr, matmul_dst, param.bias_mode,
+            param.nonlineMode, param.bias_type, param.dst_type, 1_z,
+            sparam.output_block_oc_size / pack_oc_size, 1_z,
+            sparam.output_block_size, pack_oc_size);
+    copy_dst<dst_ctype>(param, matmul_dst, sparam);
+}
+}
+
 template <typename src_ctype, typename bias_ctype, typename dst_ctype,
           typename op_ctype, typename op_dtype,
           megdnn::PostprocessMode postprocess_mode, PackMode packmode,
@@ -82,7 +271,10 @@ template <typename src_ctype, typename bias_ctype, typename dst_ctype,
           typename op_ctype, typename op_dtype,
           megdnn::PostprocessMode postprocess_mode>
 class Strategy<src_ctype, bias_ctype, dst_ctype, op_ctype, op_dtype,
-               postprocess_mode, PackMode::DEFAULT> : public StrategyBase {
+               postprocess_mode, PackMode::DEFAULT>
+        : public StrategyBridge<src_ctype, bias_ctype, dst_ctype, op_ctype,
+                                op_dtype, postprocess_mode, PackMode::DEFAULT,
+                                FormatMode::NCHW> {
 public:
     constexpr static size_t BUNDLE_PADDING_INDEX = 0;
     constexpr static size_t BUNDLE_PACKA_INDEX = 1;
@@ -92,13 +284,7 @@ public:
 
     Strategy() = default;
 
-    void copy_padding_kern(
-            WorkspaceBundle bundle,
-            const fallback::ConvBiasImpl::NCBKernParam& param,
-            const fallback::ConvBiasImpl::NCBKernIndex& ncb_index,
-            size_t pack_size) override;
-
-    void packA_kern(WorkspaceBundle bundle,
+    virtual void packA_kern(WorkspaceBundle bundle,
                     const fallback::ConvBiasImpl::NCBKernParam& param,
                     fallback::MatrixMulImpl::KernSizeParam matmulparam,
                     fallback::MatrixMulImpl::AlgoBase* matmul_algo,
@@ -120,16 +306,13 @@ public:
             const fallback::ConvBiasImpl::NCBKernIndex& ncb_index) override;
     void exec_postprocess(const fallback::ConvBiasImpl::NCBKernParam& param,
                           const StrategyParam& sparam,
-                          WorkspaceBundle bundle_thread) override;
-
-    void copy_dst(const fallback::ConvBiasImpl::NCBKernParam& param,
-                  const void* matmul_dst, const StrategyParam& sparam);
-
-    void copy_bias(const fallback::ConvBiasImpl::NCBKernParam& param,
-                   WorkspaceBundle bundle_thread, const StrategyParam& sparam);
+                          WorkspaceBundle bundle_thread) override {
+        do_postprocess<bias_ctype, dst_ctype, op_ctype, op_dtype,
+                       postprocess_mode>(param, sparam, bundle_thread,
+                                         THREAD_BUNDLE_IM2COL_INDEX,
+                                         THREAD_BUNDLE_BIAS_INDEX);
+    }
 
-    void* get_bias_temp_ptr(const fallback::ConvBiasImpl::NCBKernParam& param,
-                            const WorkspaceBundle& bundle_thread);
     void* get_matmul_dst_ptr(const fallback::ConvBiasImpl::NCBKernParam& param,
                              const WorkspaceBundle& bundle_thread,
                              const StrategyParam& sparam);
@@ -162,7 +345,10 @@ template <typename src_ctype, typename bias_ctype, typename dst_ctype,
           typename op_ctype, typename op_dtype,
           megdnn::PostprocessMode postprocess_mode>
 class Strategy<src_ctype, bias_ctype, dst_ctype, op_ctype, op_dtype,
-               postprocess_mode, PackMode::NO_PACK> : public StrategyBase {
+               postprocess_mode, PackMode::NO_PACK>
+        : public StrategyBridge<src_ctype, bias_ctype, dst_ctype, op_ctype,
+                                op_dtype, postprocess_mode, PackMode::NO_PACK,
+                                FormatMode::NCHW> {
 public:
     constexpr static size_t BUNDLE_PADDING_INDEX = 0;
     constexpr static size_t BUNDLE_PACKA_INDEX = 1;
@@ -173,12 +359,6 @@ public:
 
     Strategy() = default;
 
-    void copy_padding_kern(
-            WorkspaceBundle bundle,
-            const fallback::ConvBiasImpl::NCBKernParam& param,
-            const fallback::ConvBiasImpl::NCBKernIndex& ncb_index,
-            size_t pack_size) override;
-
     void packA_kern(WorkspaceBundle bundle,
                     const fallback::ConvBiasImpl::NCBKernParam& param,
                     fallback::MatrixMulImpl::KernSizeParam matmulparam,
@@ -198,17 +378,6 @@ public:
                              const WorkspaceBundle& bundle_thread,
                              const StrategyParam& sparam);
 
-    inline void* get_bias_temp_ptr(
-            const fallback::ConvBiasImpl::NCBKernParam& param,
-            const WorkspaceBundle& bundle_thread) {
-        bias_ctype* bias_tmp_ptr =
-                param.bias_mode == megdnn::BiasMode::BIAS
-                        ? static_cast<bias_ctype*>(
-                                  bundle_thread.get(THREAD_BUNDLE_BIAS_INDEX))
-                        : nullptr;
-        return bias_tmp_ptr;
-    }
-
     void exec_im2col(WorkspaceBundle bundle, WorkspaceBundle bundle_thread,
                      const StrategyParam& sparam,
                      const fallback::ConvBiasImpl::NCBKernParam& param,
@@ -216,19 +385,22 @@ public:
                      fallback::MatrixMulImpl::AlgoBase* matmul_algo) override;
     void exec_postprocess(const fallback::ConvBiasImpl::NCBKernParam& param,
                           const StrategyParam& sparam,
-                          WorkspaceBundle bundle_thread) override;
-    void copy_dst(const fallback::ConvBiasImpl::NCBKernParam& param,
-                  const void* matmul_dst, const StrategyParam& sparam);
-
-    void copy_bias(const fallback::ConvBiasImpl::NCBKernParam& param,
-                   WorkspaceBundle bundle_thread, const StrategyParam& sparam);
+                          WorkspaceBundle bundle_thread) override {
+        do_postprocess<bias_ctype, dst_ctype, op_ctype, op_dtype,
+                       postprocess_mode>(param, sparam, bundle_thread,
+                                         THREAD_BUNDLE_MATMULDST_INDEX,
+                                         THREAD_BUNDLE_BIAS_INDEX);
+    }
 };
 
 template <typename src_ctype, typename bias_ctype, typename dst_ctype,
           typename op_ctype, typename op_dtype,
           megdnn::PostprocessMode postprocess_mode>
 class Strategy<src_ctype, bias_ctype, dst_ctype, op_ctype, op_dtype,
-               postprocess_mode, PackMode::ONLY_PACKA> : public StrategyBase {
+               postprocess_mode, PackMode::ONLY_PACKA>
+        : public StrategyBridge<src_ctype, bias_ctype, dst_ctype, op_ctype,
+                                op_dtype, postprocess_mode,
+                                PackMode::ONLY_PACKA,FormatMode::NCHW> {
 public:
     constexpr static size_t BUNDLE_PADDING_INDEX = 0;
     constexpr static size_t BUNDLE_PACKA_INDEX = 1;
@@ -239,12 +411,6 @@ public:
 
     Strategy() = default;
 
-    void copy_padding_kern(
-            WorkspaceBundle bundle,
-            const fallback::ConvBiasImpl::NCBKernParam& param,
-            const fallback::ConvBiasImpl::NCBKernIndex& ncb_index,
-            size_t pack_size) override;
-
     void packA_kern(WorkspaceBundle bundle,
                     const fallback::ConvBiasImpl::NCBKernParam& param,
                     fallback::MatrixMulImpl::KernSizeParam matmulparam,
@@ -269,24 +435,15 @@ public:
     void* get_matmul_dst_ptr(const fallback::ConvBiasImpl::NCBKernParam& param,
                              const WorkspaceBundle& bundle_thread,
                              const StrategyParam& sparam);
-    inline void* get_bias_temp_ptr(
-            const fallback::ConvBiasImpl::NCBKernParam& param,
-            const WorkspaceBundle& bundle_thread) {
-        bias_ctype* bias_tmp_ptr =
-                param.bias_mode == megdnn::BiasMode::BIAS
-                        ? static_cast<bias_ctype*>(
-                                  bundle_thread.get(THREAD_BUNDLE_BIAS_INDEX))
-                        : nullptr;
-        return bias_tmp_ptr;
-    }
+
     void exec_postprocess(const fallback::ConvBiasImpl::NCBKernParam& param,
                           const StrategyParam& sparam,
-                          WorkspaceBundle bundle_thread) override;
-    void copy_dst(const fallback::ConvBiasImpl::NCBKernParam& param,
-                  const void* matmul_dst, const StrategyParam& sparam);
-
-    void copy_bias(const fallback::ConvBiasImpl::NCBKernParam& param,
-                   WorkspaceBundle bundle_thread, const StrategyParam& sparam);
+                          WorkspaceBundle bundle_thread) override {
+        do_postprocess<bias_ctype, dst_ctype, op_ctype, op_dtype,
+                       postprocess_mode>(param, sparam, bundle_thread,
+                                         THREAD_BUNDLE_MATMULDST_INDEX,
+                                         THREAD_BUNDLE_BIAS_INDEX);
+    }
 };
 }  // namespace megdnn
 

dnn/src/fallback/conv_bias/im2col/strategy_default.cpp

@@ -10,85 +10,9 @@
  */
 #include "src/fallback/conv_bias/im2col/strategy_base.h"
 #include "src/fallback/convolution/img2col_helper.h"
-#if MEGDNN_X86
-#include "src/x86/conv_bias/postprocess_helper.h"
-#elif (MEGDNN_ARMV7 || MEGDNN_AARCH64)
-#include "src/arm_common/conv_bias/postprocess_helper.h"
-#endif
 
-using namespace megdnn;
-#if MEGDNN_X86
-using namespace x86;
-#endif
 namespace megdnn {
 
-template <typename src_ctype, typename bias_ctype, typename dst_ctype,
-          typename op_ctype, typename op_dtype,
-          megdnn::PostprocessMode postprocess_mode>
-void Strategy<src_ctype, bias_ctype, dst_ctype, op_ctype, op_dtype,
-              postprocess_mode, PackMode::DEFAULT>::
-        copy_padding_kern(WorkspaceBundle bundle,
-                          const fallback::ConvBiasImpl::NCBKernParam& param,
-                          const fallback::ConvBiasImpl::NCBKernIndex& ncb_index,
-                          size_t pack_oc_size) {
-    UNPACK_CONV_F32_NCB_KERN_SIZES(param);
-    MEGDNN_MARK_USED_VAR(N);
-    MEGDNN_MARK_USED_VAR(OC);
-    MEGDNN_MARK_USED_VAR(OH);
-    MEGDNN_MARK_USED_VAR(OW);
-    MEGDNN_MARK_USED_VAR(FH);
-    MEGDNN_MARK_USED_VAR(FW);
-    MEGDNN_MARK_USED_VAR(SH);
-    MEGDNN_MARK_USED_VAR(SW);
-
-    size_t IW2 = IW + 2 * PW;
-    size_t IH2 = IH + 2 * PH;
-    size_t batch_id = ncb_index.ndrange_id[0];
-    size_t group_id = ncb_index.ndrange_id[1];
-    size_t channel_id = ncb_index.ndrange_id[2];
-    size_t PH_SIZE = PH * IW2 * pack_oc_size;
-
-    PW = PW * pack_oc_size;
-    IW = IW * pack_oc_size;
-
-    size_t padding_group_size = IH2 * IW2 * IC;
-    size_t workspace_channel_offset = pack_oc_size * IH2 * IW2 * channel_id;
-    size_t workspace_group_offset = group_id * padding_group_size;
-    size_t workspace_batch_offset =
-            param.filter_meta.group * batch_id * padding_group_size;
-    bundle.set(param.workspace_ptr);
-
-    src_ctype src_zp = static_cast<src_ctype>(0);
-    if (param.src_type.enumv() == DTypeEnum::Quantized8Asymm) {
-        src_zp = param.src_type.param<dtype::Quantized8Asymm>().zero_point;
-    }
-    src_ctype* src = const_cast<src_ctype*>(param.src<src_ctype>(
-            batch_id, group_id, channel_id, 1, pack_oc_size));
-    src_ctype* src2;
-    src2 = static_cast<src_ctype*>(bundle.get(BUNDLE_PADDING_INDEX)) +
-           workspace_group_offset + workspace_batch_offset +
-           workspace_channel_offset;
-    src_ctype* src2_ptr = src2;
-    const src_ctype* src_ptr = src;
-    if (PH != 0) {
-        std::memset(src2_ptr, src_zp, sizeof(src_ctype) * PH_SIZE);
-        src2_ptr += PH_SIZE;
-    }
-    rep(ih, IH) {
-        if (PW != 0)
-            rep(pw, PW) * (src2_ptr++) = src_zp;
-        std::memcpy(src2_ptr, src_ptr, sizeof(src_ctype) * IW);
-        src2_ptr += IW;
-        src_ptr += IW;
-        if (PW != 0)
-            rep(pw, PW) * (src2_ptr++) = src_zp;
-    }
-    if (PH != 0) {
-        std::memset(src2_ptr, src_zp, sizeof(src_ctype) * PH_SIZE);
-        src2_ptr += PH_SIZE;
-    }
-}
-
 template <typename src_ctype, typename bias_ctype, typename dst_ctype,
           typename op_ctype, typename op_dtype,
           megdnn::PostprocessMode postprocess_mode>
@@ -244,100 +168,6 @@ void Strategy<src_ctype, bias_ctype, dst_ctype, op_ctype, op_dtype,
     matmul_kern_naked(matmul_param, a_panel, b_panel);
 }
 
-template <typename src_ctype, typename bias_ctype, typename dst_ctype,
-          typename op_ctype, typename op_dtype,
-          megdnn::PostprocessMode postprocess_mode>
-void Strategy<src_ctype, bias_ctype, dst_ctype, op_ctype, op_dtype,
-              postprocess_mode, PackMode::DEFAULT>::
-        exec_postprocess(const fallback::ConvBiasImpl::NCBKernParam& param,
-                         const StrategyParam& sparam,
-                         WorkspaceBundle bundle_thread) {
-    copy_bias(param, bundle_thread, sparam);
-    void* matmul_dst = get_matmul_dst_ptr(param, bundle_thread, sparam);
-
-    const bias_ctype* bias_ptr = static_cast<const bias_ctype*>(
-            param.bias<bias_ctype>(sparam.batch_id, sparam.group_id));
-    void* bias_temp_ptr = get_bias_temp_ptr(param, bundle_thread);
-    void* bias_preprocess_ptr = const_cast<void*>(
-            param.bias_mode == megdnn::BiasMode::BIAS
-                    ? bias_temp_ptr
-                    : static_cast<void*>(const_cast<bias_ctype*>(
-                              bias_ptr + sparam.oc_cur_index)));
-    size_t pack_oc_size = sparam.pack_oc_size;
-    PostProcess<op_ctype, op_dtype, postprocess_mode>::run(
-            matmul_dst, bias_preprocess_ptr, matmul_dst, param.bias_mode,
-            param.nonlineMode, param.bias_type, param.dst_type, 1_z,
-            sparam.output_block_oc_size / pack_oc_size, 1_z,
-            sparam.output_block_size, pack_oc_size);
-    copy_dst(param, matmul_dst, sparam);
-}
-
-template <typename src_ctype, typename bias_ctype, typename dst_ctype,
-          typename op_ctype, typename op_dtype,
-          megdnn::PostprocessMode postprocess_mode>
-void Strategy<src_ctype, bias_ctype, dst_ctype, op_ctype, op_dtype,
-              postprocess_mode, PackMode::DEFAULT>::
-        copy_dst(const fallback::ConvBiasImpl::NCBKernParam& param,
-                 const void* matmul_dst, const StrategyParam& sparam) {
-    if (!sparam.skip_copy_dst) {
-        size_t pack_oc_size = sparam.pack_oc_size;
-        dst_ctype* dst_tmp_ptr =
-                reinterpret_cast<dst_ctype*>(const_cast<void*>(matmul_dst));
-        dst_ctype* dst =
-                param.dst<dst_ctype>(sparam.batch_id, sparam.group_id) +
-                sparam.oc_cur_index * sparam.ohw +
-                sparam.ohw_cur_index * pack_oc_size;
-        size_t oc_loop = sparam.output_block_oc_size / pack_oc_size;
-        for (size_t oc = 0; oc < oc_loop; oc++) {
-            std::memcpy(dst, dst_tmp_ptr,
-                        sizeof(dst_ctype) * sparam.output_block_size *
-                                pack_oc_size);
-            dst_tmp_ptr += sparam.output_block_size * pack_oc_size;
-            dst += sparam.ohw * pack_oc_size;
-        }
-    }
-}
-
-template <typename src_ctype, typename bias_ctype, typename dst_ctype,
-          typename op_ctype, typename op_dtype,
-          megdnn::PostprocessMode postprocess_mode>
-void* Strategy<src_ctype, bias_ctype, dst_ctype, op_ctype, op_dtype,
-               postprocess_mode, PackMode::DEFAULT>::
-        get_bias_temp_ptr(const fallback::ConvBiasImpl::NCBKernParam& param,
-                          const WorkspaceBundle& bundle_thread) {
-    bias_ctype* bias_tmp_ptr =
-            param.bias_mode == megdnn::BiasMode::BIAS
-                    ? static_cast<bias_ctype*>(
-                              bundle_thread.get(THREAD_BUNDLE_BIAS_INDEX))
-                    : nullptr;
-    return bias_tmp_ptr;
-}
-
-template <typename src_ctype, typename bias_ctype, typename dst_ctype,
-          typename op_ctype, typename op_dtype,
-          megdnn::PostprocessMode postprocess_mode>
-void Strategy<src_ctype, bias_ctype, dst_ctype, op_ctype, op_dtype,
-              postprocess_mode, PackMode::DEFAULT>::
-        copy_bias(const fallback::ConvBiasImpl::NCBKernParam& param,
-                  WorkspaceBundle bundle_thread, const StrategyParam& sparam) {
-    const bias_ctype* bias_ptr = static_cast<const bias_ctype*>(
-            param.bias<bias_ctype>(sparam.batch_id, sparam.group_id));
-    bias_ctype* bias_temp_ptr =
-            static_cast<bias_ctype*>(get_bias_temp_ptr(param, bundle_thread));
-    if (param.bias_mode == megdnn::BiasMode::BIAS) {
-        bias_ctype* copy_dst = bias_temp_ptr;
-        const bias_ctype* copy_src = bias_ptr +
-                                     sparam.oc_cur_index * sparam.ohw +
-                                     sparam.ohw_cur_index;
-        for (size_t oc = sparam.oc_cur_index; oc < sparam.oc_end_index; oc++) {
-            std::memcpy(copy_dst, copy_src,
-                        sizeof(bias_ctype) * sparam.output_block_size);
-            copy_dst += sparam.output_block_size;
-            copy_src += sparam.ohw;
-        }
-    }
-}
-
 #define INSTANTIAL_CLASS(_src_ctype, _bias_ctype, _dst_ctype, _op_ctype,    \
                          _op_dtype, _postprocess_mode)                      \
     template class Strategy<_src_ctype, _bias_ctype, _dst_ctype, _op_ctype, \

dnn/src/fallback/conv_bias/im2col/strategy_nopack.cpp

@@ -11,81 +11,9 @@
 
 #include "src/fallback/conv_bias/im2col/strategy_base.h"
 #include "src/fallback/convolution/img2col_helper.h"
-#if MEGDNN_X86
-#include "src/x86/conv_bias/postprocess_helper.h"
-#elif (MEGDNN_ARMV7 || MEGDNN_AARCH64)
-#include "src/arm_common/conv_bias/postprocess_helper.h"
-#endif
 
-using namespace megdnn;
-#if MEGDNN_X86
-using namespace x86;
-#endif
 namespace megdnn {
 
-template <typename src_ctype, typename bias_ctype, typename dst_ctype,
-          typename op_ctype, typename op_dtype,
-          megdnn::PostprocessMode postprocess_mode>
-void Strategy<src_ctype, bias_ctype, dst_ctype, op_ctype, op_dtype,
-              postprocess_mode, PackMode::NO_PACK>::
-        copy_padding_kern(WorkspaceBundle bundle,
-                          const fallback::ConvBiasImpl::NCBKernParam& param,
-                          const fallback::ConvBiasImpl::NCBKernIndex& ncb_index,
-                          size_t) {
-    UNPACK_CONV_F32_NCB_KERN_SIZES(param);
-    MEGDNN_MARK_USED_VAR(N);
-    MEGDNN_MARK_USED_VAR(OC);
-    MEGDNN_MARK_USED_VAR(OH);
-    MEGDNN_MARK_USED_VAR(OW);
-    MEGDNN_MARK_USED_VAR(FH);
-    MEGDNN_MARK_USED_VAR(FW);
-    MEGDNN_MARK_USED_VAR(SH);
-    MEGDNN_MARK_USED_VAR(SW);
-
-    size_t IW2 = IW + 2 * PW;
-    size_t IH2 = IH + 2 * PH;
-    size_t batch_id = ncb_index.ndrange_id[0];
-    size_t group_id = ncb_index.ndrange_id[1];
-    size_t channel_id = ncb_index.ndrange_id[2];
-
-    size_t padding_group_size = IH2 * IW2 * IC;
-    size_t workspace_channel_offset = IH2 * IW2 * channel_id;
-    size_t workspace_group_offset = group_id * padding_group_size;
-    size_t workspace_batch_offset =
-            param.filter_meta.group * batch_id * padding_group_size;
-    bundle.set(param.workspace_ptr);
-
-    src_ctype src_zp = static_cast<src_ctype>(0);
-    if (param.src_type.enumv() == DTypeEnum::Quantized8Asymm) {
-        src_zp = param.src_type.param<dtype::Quantized8Asymm>().zero_point;
-    }
-    src_ctype* src = const_cast<src_ctype*>(
-            param.src<src_ctype>(batch_id, group_id, channel_id));
-    src_ctype* src2;
-    src2 = static_cast<src_ctype*>(bundle.get(BUNDLE_PADDING_INDEX)) +
-           workspace_group_offset + workspace_batch_offset +
-           workspace_channel_offset;
-    src_ctype* src2_ptr = src2;
-    const src_ctype* src_ptr = src;
-    if (PH != 0) {
-        std::memset(src2_ptr, src_zp, sizeof(src_ctype) * PH * IW2);
-        src2_ptr += PH * IW2;
-    }
-    rep(ih, IH) {
-        if (PW != 0)
-            rep(pw, PW) * (src2_ptr++) = src_zp;
-        std::memcpy(src2_ptr, src_ptr, sizeof(src_ctype) * IW);
-        src2_ptr += IW;
-        src_ptr += IW;
-        if (PW != 0)
-            rep(pw, PW) * (src2_ptr++) = src_zp;
-    }
-    if (PH != 0) {
-        std::memset(src2_ptr, src_zp, sizeof(src_ctype) * PH * IW2);
-        src2_ptr += PH * IW2;
-    }
-}
-
 template <typename src_ctype, typename bias_ctype, typename dst_ctype,
           typename op_ctype, typename op_dtype,
           megdnn::PostprocessMode postprocess_mode>
@@ -220,81 +148,6 @@ void Strategy<src_ctype, bias_ctype, dst_ctype, op_ctype, op_dtype,
     }
 }
 
-template <typename src_ctype, typename bias_ctype, typename dst_ctype,
-          typename op_ctype, typename op_dtype,
-          megdnn::PostprocessMode postprocess_mode>
-void Strategy<src_ctype, bias_ctype, dst_ctype, op_ctype, op_dtype,
-              postprocess_mode, PackMode::NO_PACK>::
-        exec_postprocess(const fallback::ConvBiasImpl::NCBKernParam& param,
-                         const StrategyParam& sparam,
-                         WorkspaceBundle bundle_thread) {
-    copy_bias(param, bundle_thread, sparam);
-    void* matmul_dst = get_matmul_dst_ptr(param, bundle_thread, sparam);
-
-    const bias_ctype* bias_ptr = static_cast<const bias_ctype*>(
-            param.bias<bias_ctype>(sparam.batch_id, sparam.group_id));
-    bias_ctype* bias_temp_ptr =
-            static_cast<bias_ctype*>(get_bias_temp_ptr(param, bundle_thread));
-    PostProcess<op_ctype, op_dtype, postprocess_mode>::run(
-            matmul_dst,
-            const_cast<void*>(
-                    param.bias_mode == megdnn::BiasMode::BIAS
-                            ? bias_temp_ptr
-                            : static_cast<void*>(const_cast<bias_ctype*>(
-                                      bias_ptr + sparam.oc_cur_index))),
-            matmul_dst, param.bias_mode, param.nonlineMode, param.bias_type,
-            param.dst_type, 1_z, sparam.output_block_oc_size, 1_z,
-            sparam.output_block_size);
-    copy_dst(param, matmul_dst, sparam);
-}
-
-template <typename src_ctype, typename bias_ctype, typename dst_ctype,
-          typename op_ctype, typename op_dtype,
-          megdnn::PostprocessMode postprocess_mode>
-void Strategy<src_ctype, bias_ctype, dst_ctype, op_ctype, op_dtype,
-              postprocess_mode, PackMode::NO_PACK>::
-        copy_dst(const fallback::ConvBiasImpl::NCBKernParam& param,
-                 const void* matmul_dst, const StrategyParam& sparam) {
-    if (!sparam.skip_copy_dst) {
-        dst_ctype* dst_tmp_ptr =
-                reinterpret_cast<dst_ctype*>(const_cast<void*>(matmul_dst));
-        dst_ctype* dst =
-                param.dst<dst_ctype>(sparam.batch_id, sparam.group_id) +
-                sparam.oc_cur_index * sparam.ohw + sparam.ohw_cur_index;
-        for (size_t oc = 0; oc < sparam.output_block_oc_size; oc++) {
-            std::memcpy(dst, dst_tmp_ptr,
-                        sizeof(dst_ctype) * sparam.output_block_size);
-            dst_tmp_ptr += sparam.output_block_size;
-            dst += sparam.ohw;
-        }
-    }
-}
-
-template <typename src_ctype, typename bias_ctype, typename dst_ctype,
-          typename op_ctype, typename op_dtype,
-          megdnn::PostprocessMode postprocess_mode>
-void Strategy<src_ctype, bias_ctype, dst_ctype, op_ctype, op_dtype,
-              postprocess_mode, PackMode::NO_PACK>::
-        copy_bias(const fallback::ConvBiasImpl::NCBKernParam& param,
-                  WorkspaceBundle bundle_thread, const StrategyParam& sparam) {
-    const bias_ctype* bias_ptr = static_cast<const bias_ctype*>(
-            param.bias<bias_ctype>(sparam.batch_id, sparam.group_id));
-    bias_ctype* bias_temp_ptr =
-            static_cast<bias_ctype*>(get_bias_temp_ptr(param, bundle_thread));
-    if (param.bias_mode == megdnn::BiasMode::BIAS) {
-        bias_ctype* copy_dst = bias_temp_ptr;
-        const bias_ctype* copy_src = bias_ptr +
-                                     sparam.oc_cur_index * sparam.ohw +
-                                     sparam.ohw_cur_index;
-        for (size_t oc = sparam.oc_cur_index; oc < sparam.oc_end_index; oc++) {
-            std::memcpy(copy_dst, copy_src,
-                        sizeof(bias_ctype) * sparam.output_block_size);
-            copy_dst += sparam.output_block_size;
-            copy_src += sparam.ohw;
-        }
-    }
-}
-
 #define INSTANTIAL_CLASS(_src_ctype, _bias_ctype, _dst_ctype, _op_ctype,    \
                          _op_dtype, _postprocess_mode)                      \
     template class Strategy<_src_ctype, _bias_ctype, _dst_ctype, _op_ctype, \
@@ -302,34 +155,18 @@ void Strategy<src_ctype, bias_ctype, dst_ctype, op_ctype, op_dtype,
 
 INSTANTIAL_CLASS(dt_float32, dt_float32, dt_float32, dt_float32, dt_float32,
                  megdnn::PostprocessMode::FLOAT)
-
+INSTANTIAL_CLASS(dt_int8, dt_int16, dt_int16, dt_int16, dt_int16,
+                 megdnn::PostprocessMode::NO_PROCESS)
+INSTANTIAL_CLASS(dt_int8, dt_int32, dt_int32, dt_int32, dt_int32,
+                 megdnn::PostprocessMode::NO_PROCESS)
 #if __ARM_FEATURE_FP16_VECTOR_ARITHMETIC
-INSTANTIAL_CLASS(dt_float16, dt_float16, dt_float16, __fp16, __fp16,
-                 megdnn::PostprocessMode::FLOAT)
 #else
 #if !MEGDNN_DISABLE_FLOAT16
 INSTANTIAL_CLASS(dt_float16, dt_float16, dt_float16, dt_float16, dt_float16,
                  megdnn::PostprocessMode::NO_PROCESS)
 #endif
 #endif
-
-#if MEGDNN_AARCH64 || MEGDNN_ARMV7
-//! x86 do not have uint8 matmul so only armv7 armv8 support uint8
-INSTANTIAL_CLASS(dt_uint8, dt_int32, dt_uint8, dt_qint32, dt_quint8,
-                 megdnn::PostprocessMode::QUANTIZED)
-INSTANTIAL_CLASS(dt_uint8, dt_int32, dt_int32, dt_qint32, dt_qint32,
-                 megdnn::PostprocessMode::NO_PROCESS)
-#endif
-
-INSTANTIAL_CLASS(dt_int8, dt_int32, dt_int8, dt_qint32, dt_qint8,
-                 megdnn::PostprocessMode::QUANTIZED)
-INSTANTIAL_CLASS(dt_int8, dt_int32, dt_int32, dt_int32, dt_int32,
-                 megdnn::PostprocessMode::NO_PROCESS)
-INSTANTIAL_CLASS(dt_int8, dt_int16, dt_int16, dt_int16, dt_int16,
-                 megdnn::PostprocessMode::NO_PROCESS)
-INSTANTIAL_CLASS(dt_int8, dt_int32, dt_int32, dt_qint32, dt_qint32,
-                 megdnn::PostprocessMode::NO_PROCESS)
-
+#undef INSTANTIAL_CLASS
 }  // namespace megdnn
 
 // vim: syntax=cpp.doxygen

dnn/src/fallback/conv_bias/im2col/strategy_onlypacka.cpp

@@ -11,81 +11,9 @@
 
 #include "src/fallback/conv_bias/im2col/strategy_base.h"
 #include "src/fallback/convolution/img2col_helper.h"
-#if MEGDNN_X86
-#include "src/x86/conv_bias/postprocess_helper.h"
-#elif (MEGDNN_ARMV7 || MEGDNN_AARCH64)
-#include "src/arm_common/conv_bias/postprocess_helper.h"
-#endif
 
-using namespace megdnn;
-#if MEGDNN_X86
-using namespace x86;
-#endif
 namespace megdnn {
 
-template <typename src_ctype, typename bias_ctype, typename dst_ctype,
-          typename op_ctype, typename op_dtype,
-          megdnn::PostprocessMode postprocess_mode>
-void Strategy<src_ctype, bias_ctype, dst_ctype, op_ctype, op_dtype,
-              postprocess_mode, PackMode::ONLY_PACKA>::
-        copy_padding_kern(WorkspaceBundle bundle,
-                          const fallback::ConvBiasImpl::NCBKernParam& param,
-                          const fallback::ConvBiasImpl::NCBKernIndex& ncb_index,
-                          size_t) {
-    UNPACK_CONV_F32_NCB_KERN_SIZES(param);
-    MEGDNN_MARK_USED_VAR(N);
-    MEGDNN_MARK_USED_VAR(OC);
-    MEGDNN_MARK_USED_VAR(OH);
-    MEGDNN_MARK_USED_VAR(OW);
-    MEGDNN_MARK_USED_VAR(FH);
-    MEGDNN_MARK_USED_VAR(FW);
-    MEGDNN_MARK_USED_VAR(SH);
-    MEGDNN_MARK_USED_VAR(SW);
-
-    size_t IW2 = IW + 2 * PW;
-    size_t IH2 = IH + 2 * PH;
-    size_t batch_id = ncb_index.ndrange_id[0];
-    size_t group_id = ncb_index.ndrange_id[1];
-    size_t channel_id = ncb_index.ndrange_id[2];
-
-    size_t padding_group_size = IH2 * IW2 * IC;
-    size_t workspace_channel_offset = IH2 * IW2 * channel_id;
-    size_t workspace_group_offset = group_id * padding_group_size;
-    size_t workspace_batch_offset =
-            param.filter_meta.group * batch_id * padding_group_size;
-    bundle.set(param.workspace_ptr);
-
-    src_ctype src_zp = static_cast<src_ctype>(0);
-    if (param.src_type.enumv() == DTypeEnum::Quantized8Asymm) {
-        src_zp = param.src_type.param<dtype::Quantized8Asymm>().zero_point;
-    }
-    src_ctype* src = const_cast<src_ctype*>(
-            param.src<src_ctype>(batch_id, group_id, channel_id));
-    src_ctype* src2;
-    src2 = static_cast<src_ctype*>(bundle.get(BUNDLE_PADDING_INDEX)) +
-           workspace_group_offset + workspace_batch_offset +
-           workspace_channel_offset;
-    src_ctype* src2_ptr = src2;
-    const src_ctype* src_ptr = src;
-    if (PH != 0) {
-        std::memset(src2_ptr, src_zp, sizeof(src_ctype) * PH * IW2);
-        src2_ptr += PH * IW2;
-    }
-    rep(ih, IH) {
-        if (PW != 0)
-            rep(pw, PW) * (src2_ptr++) = src_zp;
-        std::memcpy(src2_ptr, src_ptr, sizeof(src_ctype) * IW);
-        src2_ptr += IW;
-        src_ptr += IW;
-        if (PW != 0)
-            rep(pw, PW) * (src2_ptr++) = src_zp;
-    }
-    if (PH != 0) {
-        std::memset(src2_ptr, src_zp, sizeof(src_ctype) * PH * IW2);
-        src2_ptr += PH * IW2;
-    }
-}
-
 template <typename src_ctype, typename bias_ctype, typename dst_ctype,
           typename op_ctype, typename op_dtype,
           megdnn::PostprocessMode postprocess_mode>
@@ -120,25 +48,6 @@ void Strategy<src_ctype, bias_ctype, dst_ctype, op_ctype, op_dtype,
     matmul_algo->pack_A(matmul_param, a_panel, 0_z, 0_z);
 }
 
-template <typename src_ctype, typename bias_ctype, typename dst_ctype,
-          typename op_ctype, typename op_dtype,
-          megdnn::PostprocessMode postprocess_mode>
-void* Strategy<src_ctype, bias_ctype, dst_ctype, op_ctype, op_dtype,
-               postprocess_mode, PackMode::ONLY_PACKA>::
-        get_matmul_dst_ptr(const fallback::ConvBiasImpl::NCBKernParam& param,
-                           const WorkspaceBundle& bundle_thread,
-                           const StrategyParam& sparam) {
-    if (sparam.is_dst_8bit || !sparam.is_ohw_size_bigger) {
-        return static_cast<void*>(
-                bundle_thread.get(THREAD_BUNDLE_MATMULDST_INDEX));
-    } else {
-        bias_ctype* dst =
-                param.dst<bias_ctype>(sparam.batch_id, sparam.group_id) +
-                sparam.oc_cur_index * sparam.ohw;
-        return static_cast<void*>(dst);
-    }
-}
-
 template <typename src_ctype, typename bias_ctype, typename dst_ctype,
           typename op_ctype, typename op_dtype,
           megdnn::PostprocessMode postprocess_mode>
@@ -241,63 +150,19 @@ void Strategy<src_ctype, bias_ctype, dst_ctype, op_ctype, op_dtype,
 template <typename src_ctype, typename bias_ctype, typename dst_ctype,
           typename op_ctype, typename op_dtype,
           megdnn::PostprocessMode postprocess_mode>
-void Strategy<src_ctype, bias_ctype, dst_ctype, op_ctype, op_dtype,
-              postprocess_mode, PackMode::ONLY_PACKA>::
-        exec_postprocess(const fallback::ConvBiasImpl::NCBKernParam& param,
-                         const StrategyParam& sparam,
-                         WorkspaceBundle bundle_thread) {
-    void* matmul_dst = get_matmul_dst_ptr(param, bundle_thread, sparam);
-
-    const bias_ctype* bias_ptr = static_cast<const bias_ctype*>(
-            param.bias<bias_ctype>(sparam.batch_id, sparam.group_id));
-    bias_ctype* bias_temp_ptr =
-            static_cast<bias_ctype*>(get_bias_temp_ptr(param, bundle_thread));
-
-    if (param.bias_mode == megdnn::BiasMode::BIAS) {
-        bias_ctype* copy_dst = bias_temp_ptr;
-        const bias_ctype* copy_src = bias_ptr +
-                                     sparam.oc_cur_index * sparam.ohw +
-                                     sparam.ohw_cur_index;
-        for (size_t oc = sparam.oc_cur_index; oc < sparam.oc_end_index; oc++) {
-            std::memcpy(copy_dst, copy_src,
-                        sizeof(bias_ctype) * sparam.output_block_size);
-            copy_dst += sparam.output_block_size;
-            copy_src += sparam.ohw;
-        }
-    }
-
-    PostProcess<op_ctype, op_dtype, postprocess_mode>::run(
-            matmul_dst,
-            const_cast<void*>(
-                    param.bias_mode == megdnn::BiasMode::BIAS
-                            ? bias_temp_ptr
-                            : static_cast<void*>(const_cast<bias_ctype*>(
-                                      bias_ptr + sparam.oc_cur_index))),
-            matmul_dst, param.bias_mode, param.nonlineMode, param.bias_type,
-            param.dst_type, 1_z, sparam.output_block_oc_size, 1_z,
-            sparam.output_block_size);
-    copy_dst(param, matmul_dst, sparam);
-}
-
-template <typename src_ctype, typename bias_ctype, typename dst_ctype,
-          typename op_ctype, typename op_dtype,
-          megdnn::PostprocessMode postprocess_mode>
-void Strategy<src_ctype, bias_ctype, dst_ctype, op_ctype, op_dtype,
-              postprocess_mode, PackMode::ONLY_PACKA>::
-        copy_dst(const fallback::ConvBiasImpl::NCBKernParam& param,
-                 const void* matmul_dst, const StrategyParam& sparam) {
-    if (!sparam.skip_copy_dst) {
-        dst_ctype* dst_tmp_ptr =
-                reinterpret_cast<dst_ctype*>(const_cast<void*>(matmul_dst));
-        dst_ctype* dst =
-                param.dst<dst_ctype>(sparam.batch_id, sparam.group_id) +
-                sparam.oc_cur_index * sparam.ohw + sparam.ohw_cur_index;
-        for (size_t oc = 0; oc < sparam.output_block_oc_size; oc++) {
-            std::memcpy(dst, dst_tmp_ptr,
-                        sizeof(dst_ctype) * sparam.output_block_size);
-            dst_tmp_ptr += sparam.output_block_size;
-            dst += sparam.ohw;
-        }
+void* Strategy<src_ctype, bias_ctype, dst_ctype, op_ctype, op_dtype,
+               postprocess_mode, PackMode::ONLY_PACKA>::
+        get_matmul_dst_ptr(const fallback::ConvBiasImpl::NCBKernParam& param,
+                           const WorkspaceBundle& bundle_thread,
+                           const StrategyParam& sparam) {
+    if (sparam.is_dst_8bit || !sparam.is_ohw_size_bigger) {
+        return static_cast<bias_ctype*>(
+                bundle_thread.get(THREAD_BUNDLE_MATMULDST_INDEX));
+    } else {
+        bias_ctype* dst =
+                param.dst<bias_ctype>(sparam.batch_id, sparam.group_id) +
+                sparam.oc_cur_index * sparam.ohw;
+        return static_cast<void*>(dst);
     }
 }
 
@@ -310,33 +175,6 @@ void Strategy<src_ctype, bias_ctype, dst_ctype, op_ctype, op_dtype,
 INSTANTIAL_CLASS(dt_float32, dt_float32, dt_float32, dt_float32, dt_float32,
                  megdnn::PostprocessMode::FLOAT)
 
-#if __ARM_FEATURE_FP16_VECTOR_ARITHMETIC
-INSTANTIAL_CLASS(dt_float16, dt_float16, dt_float16, __fp16, __fp16,
-                 megdnn::PostprocessMode::FLOAT)
-#else
-#if !MEGDNN_DISABLE_FLOAT16
-INSTANTIAL_CLASS(dt_float16, dt_float16, dt_float16, dt_float16, dt_float16,
-                 megdnn::PostprocessMode::NO_PROCESS)
-#endif
-#endif
-
-#if MEGDNN_AARCH64 || MEGDNN_ARMV7
-//! x86 do not have uint8 matmul so only armv7 armv8 support uint8
-INSTANTIAL_CLASS(dt_uint8, dt_int32, dt_uint8, dt_qint32, dt_quint8,
-                 megdnn::PostprocessMode::QUANTIZED)
-INSTANTIAL_CLASS(dt_uint8, dt_int32, dt_int32, dt_qint32, dt_qint32,
-                 megdnn::PostprocessMode::NO_PROCESS)
-#endif
-
-INSTANTIAL_CLASS(dt_int8, dt_int32, dt_int8, dt_qint32, dt_qint8,
-                 megdnn::PostprocessMode::QUANTIZED)
-INSTANTIAL_CLASS(dt_int8, dt_int32, dt_int32, dt_int32, dt_int32,
-                 megdnn::PostprocessMode::NO_PROCESS)
-INSTANTIAL_CLASS(dt_int8, dt_int16, dt_int16, dt_int16, dt_int16,
-                 megdnn::PostprocessMode::NO_PROCESS)
-INSTANTIAL_CLASS(dt_int8, dt_int32, dt_int32, dt_qint32, dt_qint32,
-                 megdnn::PostprocessMode::NO_PROCESS)
-
 #undef INSTANTIAL_CLASS
 }  // namespace megdnn
 

dnn/src/fallback/conv_bias/opr_impl.cpp

@@ -26,7 +26,7 @@
 using namespace megdnn;
 using namespace fallback;
 
-size_t megdnn::fallback::get_format_pack_size(param::ConvBias::Format format) {
+size_t megdnn::fallback::pack_size(param::ConvBias::Format format) {
     switch (format) {
         case param::ConvBias::Format::NCHW44:
         case param::ConvBias::Format::NCHW44_DOT:

dnn/src/fallback/conv_bias/opr_impl.h

@@ -23,8 +23,10 @@ namespace fallback {
 
 /*!
  * \brief get the pack_size according to the format
+ * Note  TODO: when remove format from param,
+ *       may using like this "opr::param::format specify"
  * */
-size_t get_format_pack_size(param::ConvBias::Format format);
+size_t pack_size(param::ConvBias::Format format);
 
 /*!
  * \brief fallback conv bias forward impl

dnn/src/fallback/matrix_mul/gemm_impl.h

@@ -52,9 +52,21 @@ class GemmInterleaved<Strategy, true> {
     }
 
     size_t get_b_workspace_size() const {
+#if __ARM_FEATURE_DOTPROD
+        size_t new_blockn = m_strategy.block_n;
+        if (m_strategy.KERNEL_W == 6 && m_strategy.UNROLL_K == 4 &&
+            m_strategy.KERNEL_H == 8) {
+                new_blockn = round_up<size_t>((m_strategy.block_n-1) % 6, 4) +
+                             m_strategy.block_n / 6 * 6;
+        }
+        size_t N = round_up(new_blockn, m_strategy.KERNEL_W);
+        size_t K = round_up(m_strategy.block_k, m_strategy.UNROLL_K);
+        return round_up(sizeof(stype) * N * K, CACHELINE_SIZE) + m_align_size;
+#else
         size_t N = round_up(m_strategy.block_n, m_strategy.KERNEL_W);
         size_t K = round_up(m_strategy.block_k, m_strategy.UNROLL_K);
         return round_up(sizeof(stype) * N * K, CACHELINE_SIZE) + m_align_size;
+#endif
     }
 
     //! temporary storage for output, post process such as add bias or relu will

dnn/test/arm_common/conv_bias.cpp

@@ -268,7 +268,7 @@ TEST_F(ARM_COMMON_MULTI_THREADS, BENCHMARK_CONVBIAS_NCHW44) {
     benchmark_convbias(handle(), "IM2COLMATMUL:AARCH64_INT8X8X32_K4X4X16:384",
                        "IM2COLMATMUL:AARCH64_F32K8X12X1:192", false);
 #else
-    benchmark_convbias(handle(), "IM2COLMATMUL:AARCH64_INT8X8X32_K4X4X16:384",
+    benchmark_convbias(handle(), "IM2COLMATMUL:ARMV7_INT8X8X32_K4X8X8:384",
                        "IM2COLMATMUL:ARMV7_F32:192", true);
     benchmark_convbias(handle(), "IM2COLMATMUL:AARCH64_INT8X8X32_K4X4X16:384",
                        "IM2COLMATMUL:ARMV7_F32:192", false);

dnn/test/arm_common/conv_bias_multi_thread.cpp

@@ -72,10 +72,12 @@ std::vector<conv_bias::TestArg> get_int8_quint8_conv_bias_args(
 std::vector<conv_bias::TestArg> get_nchw44_conv_bias_args(
         std::vector<size_t> kernel_vec, size_t stride, bool no_pad = false,
         bool no_bias = false, bool no_nonlinemode = false,
-        bool is_input_nchw = false, bool support_full_bias = false,
-        bool support_sigmoid = false) {
+        bool is_input_nchw = false, bool is_nchw44_dot = false,
+        bool support_full_bias = false, bool support_sigmoid = false,
+        bool only_no_bias = false) {
     using namespace conv_bias;
     using NLMode = param::ConvBias::NonlineMode;
+    
     std::vector<TestArg> args;
 
     auto pack = [&](size_t n, size_t oc, size_t ic, size_t h, size_t w,
@@ -102,7 +104,11 @@ std::vector<conv_bias::TestArg> get_nchw44_conv_bias_args(
         size_t kernel_h = kernel;
         size_t kernel_w = kernel;
         param::ConvBias param;
-        param.format = param::ConvBias::Format::NCHW44;
+        if (!is_nchw44_dot) {
+            param.format = param::ConvBias::Format::NCHW44;
+        } else {
+            param.format = param::ConvBias::Format::NCHW44_DOT;
+        }
         param.stride_h = stride;
         param.stride_w = stride;
         param.pad_h = pad;
@@ -155,18 +161,22 @@ std::vector<conv_bias::TestArg> get_nchw44_conv_bias_args(
     if (support_sigmoid) {
         nonlinemode.emplace_back(NLMode::SIGMOID);
     }
-    
-    std::vector<megdnn::BiasMode> bias_mode = {
-            megdnn::BiasMode::BROADCAST_CHANNEL_BIAS};
-    if (no_bias) {
+
+    std::vector<megdnn::BiasMode> bias_mode;
+    if (!only_no_bias) {
+        bias_mode.emplace_back(megdnn::BiasMode::BROADCAST_CHANNEL_BIAS);
+        if (no_bias) {
+            bias_mode.emplace_back(megdnn::BiasMode::NO_BIAS);
+        }
+    } else {
         bias_mode.emplace_back(megdnn::BiasMode::NO_BIAS);
     }
     if (support_full_bias) {
-        bias_mode.emplace_back(megdnn::BiasMode::BIAS);
+      bias_mode.emplace_back(megdnn::BiasMode::BIAS);
     }
     for (auto bias : bias_mode)
         for (auto nlmode : nonlinemode)
-            for (size_t n : {1, 2})
+            for (size_t n : {1,2})
                 for (size_t kernel : kernel_vec)
                     for (size_t oc : {4, 12})
                         for (size_t ic : {1, 3, 4, 12})
@@ -361,19 +371,19 @@ TEST_F(ARM_COMMON_MULTI_THREADS, CONVBIAS_DIRECT_FP32_NCHW44_S1_K7) {
 
 TEST_F(ARM_COMMON_MULTI_THREADS, CONVBIAS_DIRECT_FP32_NCHW44_S1_K2K3) {
     check_conv_bias(get_nchw44_conv_bias_args({2, 3}, 1, false, false, false,
-                                              false, true, true),
+                                              false, false, true, true),
                     handle(), "F32_CONV_NCHW44_DIRECT");
 }
 
 TEST_F(ARM_COMMON_MULTI_THREADS, CONVBIAS_DIRECT_FP32_NCHW44_S1_K5) {
     check_conv_bias(get_nchw44_conv_bias_args({5}, 1, false, false, false,
-                                              false, true, true),
+                                              false, false, true, true),
                     handle(), "F32_CONV_NCHW44_DIRECT");
 }
 
 TEST_F(ARM_COMMON_MULTI_THREADS, CONVBIAS_DIRECT_FP32_NCHW44_S2) {
     check_conv_bias(get_nchw44_conv_bias_args({2, 3, 5, 7}, 2, false, false,
-                                              false, false, true, true),
+                                              false, false, false, true, true),
                     handle(), "F32_CONV_NCHW44_DIRECT");
 }
 
@@ -1420,6 +1430,111 @@ TEST_F(ARM_COMMON_MULTI_THREADS, CONV_BIAS_IM2COLMATMUL_QUANTIZEDSYM) {
 #endif
 #undef cb
 }
+
+#if __ARM_FEATURE_DOTPROD
+
+TEST_F(ARM_COMMON_MULTI_THREADS, CONV_BIAS_IM2COLMATMUL_QUANTIZEDSYM_MK4_DOT) {
+    UniformIntRNG rng{-50, 50};
+
+#define cb(name)                                                               \
+    checker_conv_bias(get_nchw44_conv_bias_args({2, 3, 4, 5, 6, 7}, 1, false,  \
+                                                false, false, false, true),    \
+                      handle(), &rng, epsilon, dtype::QuantizedS8(2.5f),       \
+                      dtype::QuantizedS8(2.5f), dtype::QuantizedS32(6.25f),    \
+                      dtype::QuantizedS8(60.25f), name);                       \
+    checker_conv_bias(                                                         \
+            get_nchw44_conv_bias_args({1}, 2, false, true, true, false, true), \
+            handle(), &rng, epsilon, dtype::QuantizedS8(2.5f),                 \
+            dtype::QuantizedS8(2.5f), dtype::QuantizedS32(6.25f),              \
+            dtype::QuantizedS8(60.25f), name);
+
+    float epsilon = 0.001;
+#if MEGDNN_AARCH64
+    cb("IM2COLMATMUL:AARCH64_INT8X8X32_MK4_8X12X4_DOTPROD:96");
+#elif MEGDNN_ARMV7
+    cb("IM2COLMATMUL:AARCH32_INT8_MK4_8X6X4_DOTPROD:96");
+#endif
+#undef cb
+}
+
+TEST_F(ARM_COMMON_MULTI_THREADS, CONV_BIAS_IM2COLMATMUL_S8x8x32_MK4_DOT) {
+    UniformIntRNG rng{-50, 50};
+
+#define cb(name)                                                              \
+    checker_conv_bias(                                                        \
+            get_nchw44_conv_bias_args({2, 3, 4, 5, 6, 7}, 1, false, false,    \
+                                      true, false, true, false, false, true), \
+            handle(), &rng, epsilon, dtype::QuantizedS8(2.5f),                \
+            dtype::QuantizedS8(2.5f), dtype::QuantizedS32(6.25f), {}, name);  \
+    checker_conv_bias(                                                        \
+            get_nchw44_conv_bias_args({1}, 2, false, true, true, false, true, \
+                                      false, false, true),                    \
+            handle(), &rng, epsilon, dtype::QuantizedS8(2.5f),                \
+            dtype::QuantizedS8(2.5f), dtype::QuantizedS32(6.25f), {}, name);
+
+    float epsilon = 0.001;
+#if MEGDNN_AARCH64
+    cb("IM2COLMATMUL:AARCH64_INT8X8X32_MK4_8X12X4_DOTPROD:96");
+#elif MEGDNN_ARMV7
+    cb("IM2COLMATMUL:AARCH32_INT8_MK4_8X6X4_DOTPROD:96");
+#endif
+#undef cb
+}
+
+TEST_F(ARM_COMMON_MULTI_THREADS, CONV_BIAS_IM2COLMATMUL_INT8x8x32_MK4_DOT) {
+    UniformIntRNG rng{-50, 50};
+
+#define cb(name)                                                              \
+    checker_conv_bias(                                                        \
+            get_nchw44_conv_bias_args({2, 3, 4, 5, 6, 7}, 1, false, false,    \
+                                      true, false, true, false, false, true), \
+            handle(), &rng, epsilon, dtype::Int8(), dtype::Int8(),            \
+            dtype::Int32(), {}, name);                                        \
+    checker_conv_bias(                                                        \
+            get_nchw44_conv_bias_args({1}, 2, false, true, true, false, true, \
+                                      false, false, true),                    \
+            handle(), &rng, epsilon, dtype::Int8(), dtype::Int8(),            \
+            dtype::Int32(), {}, name);
+
+    float epsilon = 0.001;
+#if MEGDNN_AARCH64
+    cb("IM2COLMATMUL:AARCH64_INT8X8X32_MK4_8X12X4_DOTPROD:96");
+#elif MEGDNN_ARMV7
+    cb("IM2COLMATMUL:AARCH32_INT8_MK4_8X6X4_DOTPROD:96");
+#endif
+#undef cb
+}
+
+TEST_F(ARM_COMMON_MULTI_THREADS, CONV_BIAS_CONV1x1_QUANTIZEDSYM_MK4_DOT) {
+    UniformIntRNG rng{-50, 50};
+
+#define cb(name)                                                               \
+    checker_conv_bias(                                                         \
+            get_nchw44_conv_bias_args({1}, 1, true, true, false, false, true), \
+            handle(), &rng, epsilon, dtype::QuantizedS8(2.5f),                 \
+            dtype::QuantizedS8(2.5f), dtype::QuantizedS32(6.25f),              \
+            dtype::QuantizedS8(60.25f), name);                                 \
+    checker_conv_bias(                                                         \
+            get_nchw44_conv_bias_args({1}, 1, true, true, true, false, true,   \
+                                      false, false, true),                     \
+            handle(), &rng, epsilon, dtype::QuantizedS8(2.5f),                 \
+            dtype::QuantizedS8(2.5f), dtype::QuantizedS32(6.25f), {}, name);   \
+    checker_conv_bias(                                                         \
+            get_nchw44_conv_bias_args({1}, 1, true, true, true, false, true,   \
+                                      false, false, true),                     \
+            handle(), &rng, epsilon, dtype::Int8(), dtype::Int8(),             \
+            dtype::Int32(), {}, name);
+
+    float epsilon = 0.001;
+#if MEGDNN_AARCH64
+    cb("CONV1x1:AARCH64_INT8X8X32_MK4_8X12X4_DOTPROD");
+#elif MEGDNN_ARMV7
+    cb("CONV1x1:AARCH32_INT8_MK4_8X6X4_DOTPROD");
+#endif
+#undef cb
+}
+#endif
+
 // clang-format on
 #if MEGDNN_AARCH64 || MEGDNN_ARMV7
 TEST_F(ARM_COMMON_MULTI_THREADS, CONV_BIAS_IM2COLMATMUL_QUANTIZEDASYM) {
@@ -1685,8 +1800,8 @@ TEST_F(ARM_COMMON_MULTI_THREADS, CONV_BIAS_IM2COLMATMUL_INT8x8x32) {
 
 TEST_F(ARM_COMMON_MULTI_THREADS, CONV_BIAS_IM2COL_S1_MK4_PACK_F32) {
     using namespace conv_bias;
-    std::vector<conv_bias::TestArg> args =
-            get_nchw44_conv_bias_args({2, 4, 7}, 1);
+    std::vector<conv_bias::TestArg> args = get_nchw44_conv_bias_args(
+            {2, 4, 7}, 1, false, false, false, false, false, true,true);
 #if MEGDNN_AARCH64
     check_conv_bias(args, handle(), "IM2COLMATMUL:AARCH64_F32_MK4_K8X12X1");
 #elif MEGDNN_ARMV7
@@ -1696,8 +1811,8 @@ TEST_F(ARM_COMMON_MULTI_THREADS, CONV_BIAS_IM2COL_S1_MK4_PACK_F32) {
 
 TEST_F(ARM_COMMON_MULTI_THREADS, CONV_BIAS_IM2COL_S2_MK4_PACK_F32) {
     using namespace conv_bias;
-    std::vector<conv_bias::TestArg> args =
-            get_nchw44_conv_bias_args({3, 5, 6}, 2);
+    std::vector<conv_bias::TestArg> args = get_nchw44_conv_bias_args(
+            {3, 5, 6}, 2, false, false, false, false, false, true, true);
 #if MEGDNN_AARCH64
     check_conv_bias(args, handle(), "IM2COLMATMUL:AARCH64_F32_MK4_K8X12X1");
 #elif MEGDNN_ARMV7

dnn/test/x86/conv_bias.cpp

@@ -897,6 +897,62 @@ TEST_F(X86_MULTI_THREADS, CONV_BIAS_IM2COLMATMUL_FP32) {
 #undef cb
 }
 
+#if MEGDNN_X86_WITH_MKL || MEGDNN_X86_WITH_OPENBLAS
+TEST_F(X86, CONV_BIAS_IM2COLMATMUL_FP32) {
+    using namespace conv_bias;
+    std::vector<TestArg> args;
+
+    auto run = [&](size_t oc, size_t ic, size_t w, size_t h, size_t kernel,
+                   size_t p, NonlineMode nonline_mode) {
+        if (w + 2 * p < kernel || h + 2 * p < kernel)
+            return;
+        param::ConvBias param;
+        param.stride_h = 1;
+        param.stride_w = 1;
+        param.pad_h = p;
+        param.pad_w = p;
+        param.nonlineMode = nonline_mode;
+
+        //! no bias
+        args.emplace_back(param, TensorShape{1, ic, h, w},
+                          TensorShape{oc, ic, kernel, kernel}, TensorShape{});
+        args.emplace_back(param, TensorShape{1, ic, h, w},
+                          TensorShape{oc, ic, kernel, kernel},
+                          TensorShape{1, oc, 1, 1});
+        args.emplace_back(
+                param, TensorShape{1, ic, h, w},
+                TensorShape{oc, ic, kernel, kernel},
+                TensorShape{1, oc, (h + 2 * p - kernel) / param.stride_h + 1,
+                            (w + 2 * p - kernel) / param.stride_w + 1});
+    };
+
+    for (size_t kernel : {2, 3, 4, 5, 6, 7})
+        for (size_t ic : {1, 4, 8, 16})
+            for (size_t oc : {1, 4, 8, 16, 300})
+                for (size_t p : {0, 2})
+                    for (size_t size : {8, 24})
+                        for (NonlineMode nonline_mode :
+                             {NonlineMode::IDENTITY, NonlineMode::RELU}) {
+                            run(oc, ic, size, size, kernel, p, nonline_mode);
+                        }
+
+    run(2046, 8, 20, 20, 3, 1, NonlineMode::IDENTITY);
+    Checker<ConvBias> checker(handle());
+#define cb(algo_name)                                             \
+    checker.set_before_exec_callback(                             \
+            conv_bias::ConvBiasAlgoChecker<ConvBias>(algo_name)); \
+    for (auto&& arg : args) {                                     \
+        checker.set_param(arg.param).execs(                       \
+                {arg.src, arg.filter, arg.bias, {}, {}});         \
+    }
+
+    cb("IM2COLMATMUL:X86_F32_BLAS");
+
+#undef cb
+}
+#endif
+
+
 #if MEGDNN_X86_WITH_MKL && SUPPORT_MKL_PACKED_GEMM
 TEST_F(X86_MULTI_THREADS, CONV_BIAS_IM2COLMATMUL_FP32_PACKA) {
     using namespace conv_bias;