示例#1
0
            for(x = 0; x<outx; x++)
            {
               for (ch = 0; ch < channels; ch++)
               {
                   odata[batchidx*ostr0 + y*ostr1 + x*ostr2 + ch*ostr3] = idata[batchidx*istr0 + (y+ystart-1)*istr1 + (x+xstart-1)*istr2 + ch*istr3];
               }
            }
        }
     }
  }
  
  
    
  return 1;
}


static const struct luaL_Reg nxn_(Jitter__) [] = {
  {"Jitter_updateOutput", nxn_(Jitter_updateOutput)},
  {NULL, NULL}
};

static void nxn_(Jitter_init)(lua_State *L)
{
  luaT_pushmetatable(L, torch_Tensor);
  luaT_registeratname(L, nxn_(Jitter__), "nxn");
  lua_pop(L,1);
}

#endif
示例#2
0
static void nxn_(Jitter_init)(lua_State *L)
{
  luaT_pushmetatable(L, torch_Tensor);
  luaT_registeratname(L, nxn_(Jitter__), "nxn");
  lua_pop(L,1);
}
static void nxn_(CrossMapNormalization_init)(lua_State *L)
{
  luaT_pushmetatable(L, torch_Tensor);
  luaT_registeratname(L, nxn_(CrossMapNormalization__), "nxn");
  lua_pop(L,1);
}
         {
             curgiptr[ch] -= ai * curzptr[j];
         }         
     }     
  }
  
  
  
  
  
  
  
  
  return 1;
}

static const struct luaL_Reg nxn_(CrossMapNormalization__) [] = {
  {"CrossMapNormalization_updateOutput", nxn_(CrossMapNormalization_updateOutput)},
  {"CrossMapNormalization_updateGradInput", nxn_(CrossMapNormalization_updateGradInput)},
  {NULL, NULL}
};

static void nxn_(CrossMapNormalization_init)(lua_State *L)
{
  luaT_pushmetatable(L, torch_Tensor);
  luaT_registeratname(L, nxn_(CrossMapNormalization__), "nxn");
  lua_pop(L,1);
}

#endif
static void nxn_(SpatialMaxPoolingBHWD_init)(lua_State *L)
{
  luaT_pushmetatable(L, torch_Tensor);
  luaT_registeratname(L, nxn_(SpatialMaxPoolingBHWD__), "nn");
  lua_pop(L,1);
}
                {
                     yi=(int)(maxind[ch-chb*16])/kW;
                     xi=(int)(maxind[ch-chb*16])%kW;
                     ptrgradinput[idx*gistr0+(yo*dH+yi)*gistr1+(xo*dW+xi)*gistr2+ch]+=goval[ch-chb*16];
                }                
            }           
        }
     }
  }

  /* cleanup */
  /*THTensor_(free)(gradOutput);*/

  return 1;
}

static const struct luaL_Reg nxn_(SpatialMaxPoolingBHWD__) [] = {
  {"SpatialMaxPoolingBHWD_updateOutput", nxn_(SpatialMaxPooling_updateOutput)},
  {"SpatialMaxPoolingBHWD_updateGradInput", nxn_(SpatialMaxPooling_updateGradInput)},
  {NULL, NULL}
};

static void nxn_(SpatialMaxPoolingBHWD_init)(lua_State *L)
{
  luaT_pushmetatable(L, torch_Tensor);
  luaT_registeratname(L, nxn_(SpatialMaxPoolingBHWD__), "nn");
  lua_pop(L,1);
}

#endif
示例#7
0
           for(x = 0; x<xmax; x++)
           {
              for (ch = 0; ch < channels; ch++)
              {
                 if(maskdata[batchidx*channels+ch]==0) { gidata[batchidx*gistr0 + y*gistr1 + x*gistr2 + ch*gistr3] = 0; }
                 else                { gidata[batchidx*gistr0 + y*gistr1 + x*gistr2 + ch*gistr3] = godata[batchidx*gostr0 + y*gostr1 + x*gostr2 + ch*gostr3]; }
                  
              }
           }
        }
     }
  }
  
  return 1;
}

static const struct luaL_Reg nxn_(Dropmap__) [] = {
  {"Dropmap_updateOutput", nxn_(Dropmap_updateOutput)},
  {"Dropmap_updateGradInput", nxn_(Dropmap_updateGradInput)},
  {NULL, NULL}
};

static void nxn_(Dropmap_init)(lua_State *L)
{
  luaT_pushmetatable(L, torch_Tensor);
  luaT_registeratname(L, nxn_(Dropmap__), "nxn");
  lua_pop(L,1);
}

#endif