add winograd c4 implement (#2494) (#2508)

* add winograd c4 implement (#2494)

fix: fix conv_block prepack_input_nxwc4 bug
* fix: optimize sgemm_c4 in armv7
     change condition of choose winograd kernel
* fix: change conv choose kernel condition

* fix winograd reinitwhenneed (#2511)

lite/backends/arm/math/CMakeLists.txt

@@ -79,6 +79,7 @@ if (NOT HAS_ARM_MATH_LIB_DIR)
       conv5x5s1_depthwise_int8.cc
       conv5x5s1_depthwise_fp32.cc
       conv5x5s2_depthwise_fp32.cc
+      conv3x3_winograd_fp32_c4.cc
       conv_winograd_3x3.cc
       conv_impl.cc
       softmax.cc

lite/backends/arm/math/conv_block_utils.h

@@ -254,6 +254,7 @@ inline void prepack_input_nxwc4_dw(const float* din,
     LOG(FATAL) << "prepack_dw_input, valid height must > zero";
   }
   float32x4_t vzero = vdupq_n_f32(0.f);
+  auto out_data = dout;
 
   int size_w = we - ws;
   int w0 = ws < 0 ? 0 : ws;
@@ -269,6 +270,7 @@ inline void prepack_input_nxwc4_dw(const float* din,
 
   bool flag_ext_l = left_remain > 0;
   int left_sl = 4 - left_remain;
+  int left_valid_sl = left_sl > width ? width : left_sl;
   uint32x4_t vmask_padl;
   bool flag_mask_l = false;
   if (flag_ext_l) {
@@ -290,6 +292,7 @@ inline void prepack_input_nxwc4_dw(const float* din,
   }
   int size_c = width * height;
   for (int h = hs; h < he; ++h) {
+    dout = out_data + (h - hs) * 4 * size_w;
     auto ptr_c0 = din + cs * size_c + h * width;
     auto ptr_c1 = ptr_c0 + size_c;
     auto ptr_c2 = ptr_c1 + size_c;
@@ -351,10 +354,10 @@ inline void prepack_input_nxwc4_dw(const float* din,
       }
       transpose_4x4(vc0, vc1, vc2, vc3, dout);
       dout += 16;
-      ptr_c0 += left_sl;
-      ptr_c1 += left_sl;
-      ptr_c2 += left_sl;
-      ptr_c3 += left_sl;
+      ptr_c0 += left_valid_sl;
+      ptr_c1 += left_valid_sl;
+      ptr_c2 += left_valid_sl;
+      ptr_c3 += left_valid_sl;
     }
     /// valid
     for (int i = 0; i < cnt_valid; ++i) {
@@ -986,7 +989,9 @@ inline bool write_to_output_c4_fp32(const float* din,
 
   int size_h = (he > height ? height : he) - hs;  // size_h == hei_n
 
-  int cnt = (width - ws) / w4;
+  int valid_we = we > width ? width : we;
+  int cnt = (valid_we - ws) / w4;
+  int remain = valid_we - ws - cnt * w4;
 
   for (int i = 0; i < size_h; i++) {
     int size_w = i * width;
@@ -1087,12 +1092,12 @@ inline bool write_to_output_c4_fp32(const float* din,
 #endif
       }
     }
-    if (we > width) {
+    if (remain > 0) {
       int offset = i * w_round * c4 + c4 * w4 * cnt;
       din_hei_ptr = ptr_din + offset;
-      int j = we - w4;
+      int j = 0;
       if (flag_relu) {
-        for (; j < width; ++j) {
+        for (; j < remain; ++j) {
           *(doutc0_ptr++) = LITEMAX(din_hei_ptr[0], 0.f);
           *(doutc1_ptr++) = LITEMAX(din_hei_ptr[1], 0.f);
           *(doutc2_ptr++) = LITEMAX(din_hei_ptr[2], 0.f);
@@ -1100,7 +1105,7 @@ inline bool write_to_output_c4_fp32(const float* din,
           din_hei_ptr += w4;
         }
       } else {
-        for (; j < width; ++j) {
+        for (; j < remain; ++j) {
           *(doutc0_ptr++) = din_hei_ptr[0];
           *(doutc1_ptr++) = din_hei_ptr[1];
           *(doutc2_ptr++) = din_hei_ptr[2];

lite/backends/arm/math/conv_impl.h

@@ -314,7 +314,23 @@ void fill_bias_int8(int* tensor,
                     const int* bias,
                     int channel,
                     int channel_size);
+// new winograd
 
+void weight_trans_c4(
+    float* dest, const float* src, int ic, int oc, void* workspace);
+void conv_compute_6x6_3x3(const float* input,
+                          float* output,
+                          int num,
+                          int chout,
+                          int hout,
+                          int wout,
+                          int chin,
+                          int hin,
+                          int win,
+                          const float* weight,
+                          const float* bias,
+                          const operators::ConvParam& param,
+                          ARMContext* ctx);
 }  // namespace math
 }  // namespace arm
 }  // namespace lite

lite/backends/arm/math/packed_sgemm_c4.h

@@ -37,6 +37,16 @@ void sgemm_prepack_c4(int M,
                       bool has_bias,
                       bool has_relu,
                       ARMContext* ctx);
+void sgemm_prepack_c4_small(int M,
+                            int N,
+                            int K,
+                            const float* A_packed,
+                            const float* B,
+                            float* C,
+                            const float* bias,
+                            bool has_bias,
+                            bool has_relu,
+                            ARMContext* ctx);
 }  // namespace math
 }  // namespace arm
 }  // namespace lite

lite/kernels/arm/conv_compute.cc

@@ -40,6 +40,7 @@ void ConvCompute<PRECISION(kFloat), PRECISION(kFloat)>::PrepareForRun() {
   int kw = w_dims[3];
   int pad = paddings[0];
   int stride = param.strides[0];
+  int threads = ctx.threads();
 
   bool pads_equal =
       ((paddings[0] == paddings[1]) && (paddings[2] == paddings[3]));
@@ -67,7 +68,11 @@ void ConvCompute<PRECISION(kFloat), PRECISION(kFloat)>::PrepareForRun() {
     VLOG(3) << "invoking dw conv";
   } else if (param.groups == 1 && kw == 3 && stride == 1 && kps_equal &&
              no_dilation) {
-    if (ic >= 32 && oc >= 32 && hout > 16 && wout > 16) {
+    bool use_winograd =
+        (threads == 1 && oc >= 4 && ic >= 4 && hout >= 6 && wout >= 6 &&
+         pads_equal) ||
+        (oc >= 32 && ic >= 32 && hout >= 16 && wout >= 16 && pads_equal);
+    if (use_winograd) {
       /// winograd conv impl
       impl_ = new WinogradConv<PRECISION(kFloat), PRECISION(kFloat)>;
       VLOG(3) << "invoking winograd conv";

lite/kernels/arm/conv_winograd.cc

@@ -26,6 +26,7 @@ template <>
 void WinogradConv<PRECISION(kFloat), PRECISION(kFloat)>::ReInitWhenNeeded() {
   auto& param = this->Param<param_t>();
   auto& ctx = this->ctx_->template As<ARMContext>();
+  int threads = ctx.threads();
 
   auto x_dims = param.x->dims();
   auto w_dims = param.filter->dims();
@@ -36,46 +37,62 @@ void WinogradConv<PRECISION(kFloat), PRECISION(kFloat)>::ReInitWhenNeeded() {
   }
 
   int ic = x_dims[1];
-  int ow = o_dims[3];
-  int oh = o_dims[2];
+  int ih = x_dims[2];
+  int iw = x_dims[3];
   int oc = o_dims[1];
+  int oh = o_dims[2];
+  int ow = o_dims[3];
+  int tile_block = 8;
+#ifdef __aarch64__
+  tile_block = 16;
+#endif
+  int parallel_threads =
+      (((ow + 5) / 6) * ((oh + 5) / 6) + tile_block - 1) / tile_block;
+  if (threads <= 2 && parallel_threads >= threads) {
+    if (last_kernel_is_c4_ == 1) {
+      return;
+    }
+    last_kernel_is_c4_ = 1;
+    auto pad = *(param.paddings);
+    int pad_h = pad[0];
+    int pad_w = pad[2];
+    int oc_pad = (oc + 3) / 4 * 4;
+    int ic_pad = (ic + 3) / 4 * 4;
+    const int new_input_size =
+        (ic + 3) / 4 * 4 * (ih + pad_h * 2) * (iw + pad_w * 2);
+    const int temp_size =
+        (tile_block * ((ic + 3) / 4 + (oc + 3) / 4) * 256 + 512) * threads;
+    ctx.ExtendWorkspace((temp_size + new_input_size) * sizeof(float));
+
+    weights_.Resize({1, 1, 1, 64 * oc_pad * ic_pad});
+    ctx.ExtendWorkspace((temp_size + new_input_size) * sizeof(float));
+    void* trans_tmp_ptr = malloc(sizeof(float) * 8 * 8 * oc * ic);
+    auto weights_data_ = weights_.mutable_data<float>();
+    lite::arm::math::weight_trans_c4(
+        weights_data_, param.filter->data<float>(), ic, oc, trans_tmp_ptr);
+    free(trans_tmp_ptr);
+  } else {
+    if (last_kernel_is_c4_ == 0) {
+      return;
+    }
+    last_kernel_is_c4_ = 0;
     int tile_w = (ow + 5) / 6;
     int tile_h = (oh + 5) / 6;
+
     int size_tile = tile_h * tile_w;
     int size_trans_channel = 8 * 8 * size_tile;
     int max_ch = ic > oc ? ic : oc;
 
     const int n_wino = size_tile;
-  workspace_size_ = (size_trans_channel * max_ch * 2 + n_wino) * sizeof(float);
-  last_shape_ = x_dims;
-}
-
-template <>
-void WinogradConv<PRECISION(kFloat), PRECISION(kFloat)>::PrepareForRun() {
-  auto& param = this->Param<param_t>();
-  auto& ctx = this->ctx_->template As<ARMContext>();
-
-  auto x_dims = param.x->dims();
-  auto w_dims = param.filter->dims();
-  auto o_dims = param.output->dims();
-  last_shape_ = x_dims;
-
-  int ic = x_dims[1];
-  int ow = o_dims[3];
-  int oh = o_dims[2];
-  int oc = o_dims[1];
-  int tile_w = (ow + 5) / 6;
-  int tile_h = (oh + 5) / 6;
-  int size_tile = tile_h * tile_w;
-  int size_trans_channel = 8 * 8 * size_tile;
-  int max_ch = ic > oc ? ic : oc;
+    ctx.ExtendWorkspace((size_trans_channel * max_ch * 2 + n_wino) *
+                        sizeof(float));
 
     const int m_wino = oc;
-  const int n_wino = size_tile;
     int hblock = lite::arm::math::get_hblock(&ctx);
     int m_round = hblock * ((m_wino + hblock - 1) / hblock);
     weights_.Resize({1, 1, 1, 8 * 8 * m_round * ic});
-  workspace_size_ = (size_trans_channel * max_ch * 2 + n_wino) * sizeof(float);
+    ctx.ExtendWorkspace((size_trans_channel * max_ch * 2 + n_wino) *
+                        sizeof(float));
     auto weights_wino =
         static_cast<float*>(malloc(sizeof(float) * 8 * 8 * oc * ic));
     void* trans_tmp_ptr = malloc(sizeof(float) * 8 * 8 * oc * ic);
@@ -98,15 +115,19 @@ void WinogradConv<PRECISION(kFloat), PRECISION(kFloat)>::PrepareForRun() {
     }
     free(trans_tmp_ptr);
     free(weights_wino);
+  }
+  last_shape_ = x_dims;
+}
+
+template <>
+void WinogradConv<PRECISION(kFloat), PRECISION(kFloat)>::PrepareForRun() {
+  ReInitWhenNeeded();
 }
 
 template <>
 void WinogradConv<PRECISION(kFloat), PRECISION(kFloat)>::Run() {
   auto& param = this->Param<param_t>();
   auto& ctx = this->ctx_->template As<ARMContext>();
-  // extend workspace
-  ctx.ExtendWorkspace(workspace_size_);
-
   const auto* i_data = param.x->data<float>();
   const auto* w_data = weights_.data<float>();
   const auto* b_data = param.bias ? param.bias->data<float>() : nullptr;
@@ -124,8 +145,42 @@ void WinogradConv<PRECISION(kFloat), PRECISION(kFloat)>::Run() {
   int ow = o_dims[3];
   int oc = o_dims[1];
 
-  lite::arm::math::conv_winograd3x3(
-      i_data, o_data, bs, oc, oh, ow, ic, ih, iw, w_data, b_data, param, &ctx);
+  int tile_block = 8;
+#ifdef __aarch64__
+  tile_block = 16;
+#endif
+  int threads = ctx.threads();
+  int parallel_threads =
+      (((ow + 5) / 6) * ((oh + 5) / 6) + tile_block - 1) / tile_block;
+  if (threads <= 2 && parallel_threads >= threads) {
+    lite::arm::math::conv_compute_6x6_3x3(i_data,
+                                          o_data,
+                                          bs,
+                                          oc,
+                                          oh,
+                                          ow,
+                                          ic,
+                                          ih,
+                                          iw,
+                                          w_data,
+                                          b_data,
+                                          param,
+                                          &ctx);
+  } else {
+    lite::arm::math::conv_winograd3x3(i_data,
+                                      o_data,
+                                      bs,
+                                      oc,
+                                      oh,
+                                      ow,
+                                      ic,
+                                      ih,
+                                      iw,
+                                      w_data,
+                                      b_data,
+                                      param,
+                                      &ctx);
+  }
 }
 
 }  // namespace arm

lite/kernels/arm/conv_winograd.h

@@ -40,6 +40,7 @@ class WinogradConv : public KernelLite<TARGET(kARM), Ptype> {
   Tensor weights_;
   DDim last_shape_;
   int workspace_size_{0};
+  int last_kernel_is_c4_{-1};
 };
 
 }  // namespace arm