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#ifndef TH_GENERIC_FILE
#define TH_GENERIC_FILE "generic/Sqrt.c"
#else
static int nn_(Sqrt_updateOutput)(lua_State *L)
{
THTensor *input = luaT_checkudata(L, 2, torch_Tensor);
real bias = luaT_getfieldchecknumber(L,1,"eps");
THTensor *output = luaT_getfieldcheckudata(L, 1, "output", torch_Tensor);
THTensor_(resizeAs)(output, input);
if (input->nDimension == 1 || !THTensor_(isContiguous)(input) || !THTensor_(isContiguous)(output))
{
TH_TENSOR_APPLY2(real, output, real, input, \
*output_data = sqrt(*input_data + bias););
}
else
{
real* output_data = THTensor_(data)(output);
real* input_data = THTensor_(data)(input);
long i;
#pragma omp parallel for private(i)
for(i = 0; i < THTensor_(nElement)(input); i++)
output_data[i] = sqrt(input_data[i] + bias);
}
return 1;
}
static int nn_(Sqrt_updateGradInput)(lua_State *L)
{
THTensor *input = luaT_checkudata(L, 2, torch_Tensor);
THTensor *gradOutput = luaT_checkudata(L, 3, torch_Tensor);
THTensor *output = luaT_getfieldcheckudata(L, 1, "output", torch_Tensor);
THTensor *gradInput = luaT_getfieldcheckudata(L, 1, "gradInput", torch_Tensor);
THTensor_(resizeAs)(gradInput, input);
if (output->nDimension == 1 ||
!THTensor_(isContiguous)(output) ||
!THTensor_(isContiguous)(gradOutput) ||
!THTensor_(isContiguous)(gradInput))
{
TH_TENSOR_APPLY3(real, gradInput, real, gradOutput, real, output, \
*gradInput_data = 0.5 * (*gradOutput_data / *output_data););
}
else
{
real* gradOutput_data = THTensor_(data)(gradOutput);
real* gradInput_data = THTensor_(data)(gradInput);
real* output_data = THTensor_(data)(output);
long i;
#pragma omp parallel for private(i)
for(i = 0; i < THTensor_(nElement)(output); i++)
gradInput_data[i] = 0.5 * (gradOutput_data[i] / output_data[i]);
}
return 1;
}
static const struct luaL_Reg nn_(Sqrt__) [] = {
{"Sqrt_updateOutput", nn_(Sqrt_updateOutput)},
{"Sqrt_updateGradInput", nn_(Sqrt_updateGradInput)},
{NULL, NULL}
};
static void nn_(Sqrt_init)(lua_State *L)
{
luaT_pushmetatable(L, torch_Tensor);
luaT_registeratname(L, nn_(Sqrt__), "nn");
lua_pop(L,1);
}
#endif
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