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#ifndef TH_GENERIC_FILE
#define TH_GENERIC_FILE "generic/Min.c"
#else
static int nn_(Min_updateOutput)(lua_State *L)
{
THTensor *input = luaT_checkudata(L, 2, torch_(Tensor_id));
int dimension = luaT_getfieldcheckint(L, 1, "dimension")-1;
THTensor *indices = luaT_getfieldcheckudata(L, 1, "indices", torch_(Tensor_id));
THTensor *output = luaT_getfieldcheckudata(L, 1, "output", torch_(Tensor_id));
THLongStorage *dim;
long i;
luaL_argcheck(L, dimension >= 0 && dimension < input->nDimension, 2, "dimension out of range");
dim = THLongStorage_newWithSize(input->nDimension);
for(i = 0; i < input->nDimension; i++)
dim->data[i] = input->size[i];
dim->data[dimension] = 1;
THTensor_(resize)(output, dim, NULL);
THTensor_(resize)(indices, dim, NULL);
THLongStorage_free(dim);
TH_TENSOR_DIM_APPLY3(real, output, real, input, real, indices, dimension,
long theIndex = 0;
real theMin = input_data[0];
for(i = 1; i < input_size; i++)
{
if(input_data[i*input_stride] < theMin)
{
theIndex = i;
theMin = input_data[i*input_stride];
}
}
*indices_data = theIndex+1;
*output_data = theMin;)
THTensor_(select)(output, NULL, dimension, 0);
return 1;
}
static int nn_(Min_updateGradInput)(lua_State *L)
{
THTensor *input = luaT_checkudata(L, 2, torch_(Tensor_id));
THTensor *gradOutput = luaT_checkudata(L, 3, torch_(Tensor_id));
THTensor *indices = luaT_getfieldcheckudata(L, 1, "indices", torch_(Tensor_id));
int dimension = luaT_getfieldcheckint(L, 1, "dimension")-1;
THTensor *gradInput = luaT_getfieldcheckudata(L, 1, "gradInput", torch_(Tensor_id));
THTensor *gradOutputPlusOneDim;
THLongStorage *dim, *str;
int i, j;
THTensor_(resizeAs)(gradInput, input);
THTensor_(zero)(gradInput);
dim = THLongStorage_newWithSize(gradOutput->nDimension+1);
str = THLongStorage_newWithSize(gradOutput->nDimension+1);
for(i = 0, j = 0; j < gradOutput->nDimension+1; j++)
{
if(j == dimension)
{
dim->data[j] = input->size[dimension];
str->data[j] = 0;
continue;
}
dim->data[j] = gradOutput->size[i];
str->data[j] = gradOutput->stride[i];
i++;
}
gradOutputPlusOneDim = THTensor_(newWithStorage)(gradOutput->storage, gradOutput->storageOffset, dim, str);
THLongStorage_free(dim);
THLongStorage_free(str);
TH_TENSOR_DIM_APPLY3(real, gradInput, real, gradOutputPlusOneDim, real, indices, dimension,
gradInput_data[ ((long)(*indices_data)-1)*gradInput_stride ] = *gradOutputPlusOneDim_data;)
THTensor_(free)(gradOutputPlusOneDim);
return 1;
}
static const struct luaL_Reg nn_(Min__) [] = {
{"Min_updateOutput", nn_(Min_updateOutput)},
{"Min_updateGradInput", nn_(Min_updateGradInput)},
{NULL, NULL}
};
static void nn_(Min_init)(lua_State *L)
{
luaT_pushmetaclass(L, torch_(Tensor_id));
luaT_registeratname(L, nn_(Min__), "nn");
lua_pop(L,1);
}
#endif
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