frozenleaves/pytorch
1
0
Fork 0
mirror of https://github.com/pytorch/pytorch.git synced 2025-10-20 21:14:14 +08:00
Code Issues Packages Projects Releases Wiki Activity
Files
053065ba239e3421d1b2cbec55e3f177a21d6829
pytorch/lib/TH/generic/THTensorMath.c
Ronan Collobert 053065ba23 initial revamp of torch7 tree
2012-01-25 14:55:20 +01:00

1064 lines
30 KiB
C
Raw Blame History

#ifndef TH_GENERIC_FILE
#define TH_GENERIC_FILE "generic/THTensorMath.c"
#else
void THTensor_(fill)(THTensor *r_, real value)
{
TH_TENSOR_APPLY(real, r_,
THVector_(fill)(r__data, value, r__size); break;);
}
void THTensor_(zero)(THTensor *r_)
{
TH_TENSOR_APPLY(real, r_,
THVector_(fill)(r__data, 0, r__size); break;);
}
accreal THTensor_(dot)(THTensor *tensor, THTensor *src)
{
accreal sum = 0;
/* we use a trick here. careful with that. */
TH_TENSOR_APPLY2(real, tensor, real, src,
long sz = (tensor_size-tensor_i < src_size-src_i ? tensor_size-tensor_i : src_size-src_i);
sum += THBlas_(dot)(sz, src_data, src_stride, tensor_data, tensor_stride);
tensor_i += sz;
src_i += sz;
tensor_data += sz*tensor_stride;
src_data += sz*src_stride;
break;);
return sum;
}
real THTensor_(minall)(THTensor *tensor)
{
real theMin;
THArgCheck(tensor->nDimension > 0, 1, "tensor must have one dimension");
theMin = THTensor_(data)(tensor)[0];
TH_TENSOR_APPLY(real, tensor, if(*tensor_data < theMin) theMin = *tensor_data;);
return theMin;
}
real THTensor_(maxall)(THTensor *tensor)
{
real theMax;
THArgCheck(tensor->nDimension > 0, 1, "tensor must have one dimension");
theMax = THTensor_(data)(tensor)[0];
TH_TENSOR_APPLY(real, tensor, if(*tensor_data > theMax) theMax = *tensor_data;);
return theMax;
}
accreal THTensor_(sumall)(THTensor *tensor)
{
accreal sum = 0;
TH_TENSOR_APPLY(real, tensor, sum += *tensor_data;);
return sum;
}
void THTensor_(add)(THTensor *r_, THTensor *t, real value)
{
THTensor_(resizeAs)(r_, t);
TH_TENSOR_APPLY2(real, r_, real, t, *r__data = *t_data + value;);
}
void THTensor_(mul)(THTensor *r_, THTensor *t, real value)
{
THTensor_(resizeAs)(r_, t);
TH_TENSOR_APPLY2(real, r_, real, t, *r__data = *t_data * value;);
}
void THTensor_(div)(THTensor *r_, THTensor *t, real value)
{
THTensor_(resizeAs)(r_, t);
TH_TENSOR_APPLY2(real, r_, real, t, *r__data = *t_data / value;);
}
void THTensor_(cadd)(THTensor *r_, THTensor *t, real value, THTensor *src)
{
THTensor_(resizeAs)(r_, t);
TH_TENSOR_APPLY3(real, r_, real, t, real, src, *r__data = *t_data + value * *src_data;);
}
void THTensor_(cmul)(THTensor *r_, THTensor *t, THTensor *src)
{
THTensor_(resizeAs)(r_, t);
TH_TENSOR_APPLY3(real, r_, real, t, real, src, *r__data = *t_data * *src_data;);
}
void THTensor_(cdiv)(THTensor *r_, THTensor *t, THTensor *src)
{
THTensor_(resizeAs)(r_, t);
TH_TENSOR_APPLY3(real, r_, real, t, real, src, *r__data = *t_data / *src_data;);
}
void THTensor_(addcmul)(THTensor *r_, THTensor *t, real value, THTensor *src1, THTensor *src2)
{
if(r_ != t)
{
THTensor_(resizeAs)(r_, t);
THTensor_(copy)(r_, t);
}
TH_TENSOR_APPLY3(real, r_, real, src1, real, src2, *r__data += value * *src1_data * *src2_data;);
}
void THTensor_(addcdiv)(THTensor *r_, THTensor *t, real value, THTensor *src1, THTensor *src2)
{
if(r_ != t)
{
THTensor_(resizeAs)(r_, t);
THTensor_(copy)(r_, t);
}
TH_TENSOR_APPLY3(real, r_, real, src1, real, src2, *r__data += value * *src1_data / *src2_data;);
}
void THTensor_(addmv)(THTensor *r_, real beta, THTensor *t, real alpha, THTensor *mat, THTensor *vec)
{
if( (mat->nDimension != 2) || (vec->nDimension != 1) )
THError("matrix and vector expected");
if( mat->size[1] != vec->size[0] )
THError("size mismatch");
if(t->nDimension != 1)
THError("size mismatch");
if(t->size[0] != mat->size[0])
THError("size mismatch");
if(r_ != t)
{
THTensor_(resizeAs)(r_, t);
THTensor_(copy)(r_, t);
}
if(mat->stride[0] == 1)
{
THBlas_(gemv)('n', mat->size[0], mat->size[1],
alpha, THTensor_(data)(mat), mat->stride[1],
THTensor_(data)(vec), vec->stride[0],
beta, THTensor_(data)(r_), r_->stride[0]);
}
else if(mat->stride[1] == 1)
{
THBlas_(gemv)('t', mat->size[1], mat->size[0],
alpha, THTensor_(data)(mat), mat->stride[0],
THTensor_(data)(vec), vec->stride[0],
beta, THTensor_(data)(r_), r_->stride[0]);
}
else
{
THTensor *cmat = THTensor_(newContiguous)(mat);
THBlas_(gemv)('t', mat->size[1], mat->size[0],
alpha, THTensor_(data)(cmat), cmat->stride[0],
THTensor_(data)(vec), vec->stride[0],
beta, THTensor_(data)(r_), r_->stride[0]);
THTensor_(free)(cmat);
}
}
void THTensor_(addmm)(THTensor *r_, real beta, THTensor *t, real alpha, THTensor *m1, THTensor *m2)
{
long r, c;
char transpose, transpose_m1, transpose_m2;
THTensor *r__, *m1_, *m2_;
if( (m1->nDimension != 2) || (m2->nDimension != 2) )
THError("matrix and matrix expected");
if(t->nDimension != 2)
THError("size mismatch");
if( (t->size[0] != m1->size[0]) || (t->size[1] != m2->size[1]) || (m1->size[1] != m2->size[0]) )
THError("size mismatch");
if(t != r_)
{
THTensor_(resizeAs)(r_, t);
THTensor_(copy)(r_, t);
}
/* r_ */
if(r_->stride[0] == 1)
{
transpose = 'n';
r__ = r_;
}
else if(r_->stride[1] == 1)
{
THTensor *swap = m2;
m2 = m1;
m1 = swap;
THTensor_(transpose)(r_, NULL, 0, 1);
THTensor_(transpose)(m1, NULL, 0, 1);
THTensor_(transpose)(m2, NULL, 0, 1);
transpose = 't';
r__ = r_;
}
else
{
transpose = 'n';
THTensor_(transpose)(r_, NULL, 0, 1);
r__ = THTensor_(newClone)(r_);
THTensor_(transpose)(r_, NULL, 0, 1);
THTensor_(transpose)(r__, NULL, 0, 1);
}
/* m1 */
if(m1->stride[0] == 1)
{
transpose_m1 = 'n';
m1_ = m1;
}
else if(m1->stride[1] == 1)
{
transpose_m1 = 't';
m1_ = m1;
}
else
{
transpose_m1 = 't';
m1_ = THTensor_(newContiguous)(m1);
}
/* m2 */
if(m2->stride[0] == 1)
{
transpose_m2 = 'n';
m2_ = m2;
}
else if(m2->stride[1] == 1)
{
transpose_m2 = 't';
m2_ = m2;
}
else
{
transpose_m2 = 't';
m2_ = THTensor_(newContiguous)(m2);
}
/* do the operation */
THBlas_(gemm)(transpose_m1,
transpose_m2,
r__->size[0],
r__->size[1],
m1_->size[1],
alpha,
THTensor_(data)(m1_),
(transpose_m1 == 'n' ? m1_->stride[1] : m1_->stride[0]),
THTensor_(data)(m2_),
(transpose_m2 == 'n' ? m2_->stride[1] : m2_->stride[0]),
beta,
THTensor_(data)(r__),
r__->stride[1]);
/* free intermediate variables */
if(m1_ != m1)
THTensor_(free)(m1_);
if(m2_ != m2)
THTensor_(free)(m2_);
if(r__ != r_)
THTensor_(freeCopyTo)(r__, r_);
if(transpose == 't')
{
THTensor_(transpose)(r_, NULL, 0, 1);
THTensor_(transpose)(m1, NULL, 0, 1);
THTensor_(transpose)(m2, NULL, 0, 1);
}
}
void THTensor_(addr)(THTensor *r_, real beta, THTensor *t, real alpha, THTensor *vec1, THTensor *vec2)
{
if( (vec1->nDimension != 1) || (vec2->nDimension != 1) )
THError("vector and vector expected");
if(t->nDimension != 2)
THError("size mismatch");
if( (t->size[0] != vec1->size[0]) || (t->size[1] != vec2->size[0]) )
THError("size mismatch");
if(r_ != t)
{
THTensor_(resizeAs)(r_, t);
THTensor_(copy)(r_, t);
}
if(beta != 1)
THTensor_(mul)(r_, r_, beta);
if(r_->stride[0] == 1)
{
THBlas_(ger)(vec1->size[0], vec2->size[0],
alpha, THTensor_(data)(vec1), vec1->stride[0],
THTensor_(data)(vec2), vec2->stride[0],
THTensor_(data)(r_), r_->stride[1]);
}
else if(r_->stride[1] == 1)
{
THBlas_(ger)(vec2->size[0], vec1->size[0],
alpha, THTensor_(data)(vec2), vec2->stride[0],
THTensor_(data)(vec1), vec1->stride[0],
THTensor_(data)(r_), r_->stride[0]);
}
else
{
THTensor *cr = THTensor_(newClone)(r_);
THBlas_(ger)(vec2->size[0], vec1->size[0],
alpha, THTensor_(data)(vec2), vec2->stride[0],
THTensor_(data)(vec1), vec1->stride[0],
THTensor_(data)(cr), cr->stride[0]);
THTensor_(freeCopyTo)(cr, r_);
}
}
long THTensor_(numel)(THTensor *t)
{
return THTensor_(nElement)(t);
}
void THTensor_(max)(THTensor *values_, THLongTensor *indices_, THTensor *t, int dimension)
{
THLongStorage *dim;
long i;
THArgCheck(dimension >= 0 && dimension < THTensor_(nDimension)(t), 2, "dimension out of range");
dim = THTensor_(newSizeOf)(t);
THLongStorage_set(dim, dimension, 1);
THTensor_(resize)(values_, dim, NULL);
THLongTensor_resize(indices_, dim, NULL);
THLongStorage_free(dim);
TH_TENSOR_DIM_APPLY3(real, t, real, values_, long, indices_, dimension,
long theIndex = 0;
real theMax = t_data[0];
for(i = 1; i < t_size; i++)
{
if(t_data[i*t_stride] > theMax)
{
theIndex = i;
theMax = t_data[i*t_stride];
}
}
*indices__data = theIndex;
*values__data = theMax;);
}
void THTensor_(min)(THTensor *values_, THLongTensor *indices_, THTensor *t, int dimension)
{
THLongStorage *dim;
long i;
THArgCheck(dimension >= 0 && dimension < THTensor_(nDimension)(t), 2, "dimension out of range");
dim = THTensor_(newSizeOf)(t);
THLongStorage_set(dim, dimension, 1);
THTensor_(resize)(values_, dim, NULL);
THLongTensor_resize(indices_, dim, NULL);
THLongStorage_free(dim);
TH_TENSOR_DIM_APPLY3(real, t, real, values_, long, indices_, dimension,
long theIndex = 0;
real theMin = t_data[0];
for(i = 1; i < t_size; i++)
{
if(t_data[i*t_stride] < theMin)
{
theIndex = i;
theMin = t_data[i*t_stride];
}
}
*indices__data = theIndex;
*values__data = theMin;);
}
void THTensor_(sum)(THTensor *r_, THTensor *t, int dimension)
{
THLongStorage *dim;
THArgCheck(dimension >= 0 && dimension < THTensor_(nDimension)(t), 2, "dimension out of range");
dim = THTensor_(newSizeOf)(t);
THLongStorage_set(dim, dimension, 1);
THTensor_(resize)(r_, dim, NULL);
THLongStorage_free(dim);
TH_TENSOR_DIM_APPLY2(real, t, real, r_, dimension,
accreal sum = 0;
long i;
for(i = 0; i < t_size; i++)
sum += t_data[i*t_stride];
*r__data = (real)sum;);
}
void THTensor_(prod)(THTensor *r_, THTensor *t, int dimension)
{
THLongStorage *dim;
THArgCheck(dimension >= 0 && dimension < THTensor_(nDimension)(t), 2, "dimension out of range");
dim = THTensor_(newSizeOf)(t);
THLongStorage_set(dim, dimension, 1);
THTensor_(resize)(r_, dim, NULL);
THLongStorage_free(dim);
TH_TENSOR_DIM_APPLY2(real, t, real, r_, dimension,
accreal prod = 1;
long i;
for(i = 0; i < t_size; i++)
prod *= t_data[i*t_stride];
*r__data = (real)prod;);
}
void THTensor_(cumsum)(THTensor *r_, THTensor *t, int dimension)
{
THArgCheck(dimension >= 0 && dimension < THTensor_(nDimension)(t), 2, "dimension out of range");
THTensor_(resizeAs)(r_, t);
TH_TENSOR_DIM_APPLY2(real, t, real, r_, dimension,
accreal cumsum = 0;
long i;
for(i = 0; i < t_size; i++)
{
cumsum += t_data[i*t_stride];
r__data[i*r__stride] = (real)cumsum;
});
}
void THTensor_(cumprod)(THTensor *r_, THTensor *t, int dimension)
{
THArgCheck(dimension >= 0 && dimension < THTensor_(nDimension)(t), 2, "dimension out of range");
THTensor_(resizeAs)(r_, t);
TH_TENSOR_DIM_APPLY2(real, t, real, r_, dimension,
accreal cumprod = 1;
long i;
for(i = 0; i < t_size; i++)
{
cumprod *= t_data[i*t_stride];
r__data[i*r__stride] = (real)cumprod;
});
}
void THTensor_(sign)(THTensor *r_, THTensor *t)
{
THTensor_(resizeAs)(r_, t);
#if defined (TH_REAL_IS_BYTE)
TH_TENSOR_APPLY2(real, r_, real, t,
if (*t_data > 0) *r__data = 1;
else *r__data = 0;);
#else
TH_TENSOR_APPLY2(real, r_, real, t,
if (*t_data > 0) *r__data = 1;
else if (*t_data < 0) *r__data = -1;
else *r__data = 0;);
#endif
}
accreal THTensor_(trace)(THTensor *t)
{
real *t_data = THTensor_(data)(t);
accreal sum = 0;
long i = 0;
long t_stride_0, t_stride_1, t_diag_size;
THArgCheck(THTensor_(nDimension)(t) == 2, 1, "not a matrix");
t_stride_0 = THTensor_(stride)(t, 0);
t_stride_1 = THTensor_(stride)(t, 1);
t_diag_size = THMin(THTensor_(size)(t, 0), THTensor_(size)(t, 1));
while(i < t_diag_size)
{
sum += t_data[i*(t_stride_0+t_stride_1)];
i++;
}
return sum;
}
void THTensor_(cross)(THTensor *r_, THTensor *a, THTensor *b, int dimension)
{
int i;
if(THTensor_(nDimension)(a) != THTensor_(nDimension)(b))
THError("inconsitent tensor sizes");
for(i = 0; i < THTensor_(nDimension)(a); i++)
{
if(THTensor_(size)(a, i) != THTensor_(size)(b, i))
THError("inconsistent tensor sizes");
}
if(dimension < 0)
{
for(i = 0; i < THTensor_(nDimension)(a); i++)
{
if(THTensor_(size)(a, i) == 3)
{
dimension = i;
break;
}
}
if(dimension < 0)
THError("no dimension of size 3");
}
THArgCheck(dimension >= 0 && dimension < THTensor_(nDimension)(a), 3, "dimension out of range");
THArgCheck(THTensor_(size)(a, dimension) == 3, 3, "dimension size is not 3");
THTensor_(resizeAs)(r_, a);
TH_TENSOR_DIM_APPLY3(real, a, real, b, real, r_, dimension,
r__data[0*r__stride] = a_data[1*a_stride]*b_data[2*b_stride] - a_data[2*a_stride]*b_data[1*b_stride];
r__data[1*r__stride] = a_data[2*a_stride]*b_data[0*b_stride] - a_data[0*a_stride]*b_data[2*b_stride];
r__data[2*r__stride] = a_data[0*a_stride]*b_data[1*b_stride] - a_data[1*a_stride]*b_data[0*b_stride];);
}
void THTensor_(zeros)(THTensor *r_, THLongStorage *size)
{
THTensor_(resize)(r_, size, NULL);
THTensor_(zero)(r_);
}
void THTensor_(ones)(THTensor *r_, THLongStorage *size)
{
THTensor_(resize)(r_, size, NULL);
THTensor_(fill)(r_, 1);
}
void THTensor_(diag)(THTensor *r_, THTensor *t, int k)
{
THArgCheck(THTensor_(nDimension)(t) == 1 || THTensor_(nDimension)(t) == 2, 1, "matrix or a vector expected");
if(THTensor_(nDimension)(t) == 1)
{
real *t_data = THTensor_(data)(t);
long t_stride_0 = THTensor_(stride)(t, 0);
long t_size = THTensor_(size)(t, 0);
long sz = t_size + (k >= 0 ? k : -k);
real *r__data;
long r__stride_0;
long r__stride_1;
long i;
THTensor_(resize2d)(r_, sz, sz);
THTensor_(zero)(r_);
r__data = THTensor_(data)(r_);
r__stride_0 = THTensor_(stride)(r_, 0);
r__stride_1 = THTensor_(stride)(r_, 1);
r__data += (k >= 0 ? k*r__stride_1 : -k*r__stride_0);
for(i = 0; i < t_size; i++)
r__data[i*(r__stride_0+r__stride_1)] = t_data[i*t_stride_0];
}
else
{
real *t_data = THTensor_(data)(t);
long t_stride_0 = THTensor_(stride)(t, 0);
long t_stride_1 = THTensor_(stride)(t, 1);
long sz;
real *r__data;
long r__stride_0;
long i;
if(k >= 0)
sz = THMin(THTensor_(size)(t, 0), THTensor_(size)(t, 1)-k);
else
sz = THMin(THTensor_(size)(t, 0)+k, THTensor_(size)(t, 1));
THTensor_(resize1d)(r_, sz);
r__data = THTensor_(data)(r_);
r__stride_0 = THTensor_(stride)(r_, 0);
t_data += (k >= 0 ? k*t_stride_1 : -k*t_stride_0);
for(i = 0; i < sz; i++)
r__data[i*r__stride_0] = t_data[i*(t_stride_0+t_stride_1)];
}
}
void THTensor_(eye)(THTensor *r_, long n, long m)
{
real *r__data;
long i, sz;
THArgCheck(n > 0, 1, "invalid argument");
if(m <= 0)
m = n;
THTensor_(resize2d)(r_, n, m);
THTensor_(zero)(r_);
i = 0;
r__data = THTensor_(data)(r_);
sz = THMin(THTensor_(size)(r_, 0), THTensor_(size)(r_, 1));
for(i = 0; i < sz; i++)
r__data[i*(r_->stride[0]+r_->stride[1])] = 1;
}
void THTensor_(range)(THTensor *r_, real xmin, real xmax, real step)
{
long size;
real i = 0;
THArgCheck(step > 0, 3, "step must be a positive number");
THArgCheck(xmax > xmin, 2, "upper bound must be larger than lower bound");
size = (long)((xmax-xmin)/step+1);
THTensor_(resize1d)(r_, size);
TH_TENSOR_APPLY(real, r_, *r__data = xmin + (i++)*step;);
}
void THTensor_(randperm)(THTensor *r_, long n)
{
real *r__data;
long r__stride_0;
long i;
THArgCheck(n > 0, 1, "must be strictly positive");
THTensor_(resize1d)(r_, n);
r__data = THTensor_(data)(r_);
r__stride_0 = THTensor_(stride)(r_,0);
for(i = 0; i < n; i++)
r__data[i*r__stride_0] = (real)(i);
for(i = 0; i < n-1; i++)
{
long z = THRandom_random() % (n-i);
real sav = r__data[i*r__stride_0];
r__data[i*r__stride_0] = r__data[(z+i)*r__stride_0];
r__data[(z+i)*r__stride_0] = sav;
}
}
void THTensor_(reshape)(THTensor *r_, THTensor *t, THLongStorage *size)
{
THTensor_(resize)(r_, size, NULL);
THTensor_(copy)(r_, t);
}
/* I cut and pasted (slightly adapted) the quicksort code from
http://www.alienryderflex.com/quicksort/
This public-domain C implementation by Darel Rex Finley.
Thanks man :)
*/
#define MAX_LEVELS 300
static void THTensor_(quicksortascend)(real *arr, long *idx, long elements, long stride)
{
long beg[MAX_LEVELS], end[MAX_LEVELS], i=0, L, R, swap, pid;
real piv;
beg[0]=0; end[0]=elements;
while (i>=0) {
L=beg[i]; R=end[i]-1;
if (L<R) {
piv=arr[L*stride];
pid=idx[L*stride];
while (L<R) {
while (arr[R*stride]>=piv && L<R) R--; if (L<R) {idx[L*stride]=idx[R*stride]; arr[L*stride]=arr[R*stride]; L++;}
while (arr[L*stride]<=piv && L<R) L++; if (L<R) {idx[R*stride]=idx[L*stride]; arr[R*stride]=arr[L*stride]; R--;} }
idx[L*stride]=pid; arr[L*stride]=piv; beg[i+1]=L+1; end[i+1]=end[i]; end[i++]=L;
if (end[i]-beg[i]>end[i-1]-beg[i-1]) {
swap=beg[i]; beg[i]=beg[i-1]; beg[i-1]=swap;
swap=end[i]; end[i]=end[i-1]; end[i-1]=swap; }}
else {
i--; }}}
static void THTensor_(quicksortdescend)(real *arr, long *idx, long elements, long stride)
{
long beg[MAX_LEVELS], end[MAX_LEVELS], i=0, L, R, swap, pid;
real piv;
beg[0]=0; end[0]=elements;
while (i>=0) {
L=beg[i]; R=end[i]-1;
if (L<R) {
piv=arr[L*stride];
pid=idx[L*stride];
while (L<R) {
while (arr[R*stride]<=piv && L<R) R--; if (L<R) {idx[L*stride]=idx[R*stride]; arr[L*stride]=arr[R*stride]; L++;}
while (arr[L*stride]>=piv && L<R) L++; if (L<R) {idx[R*stride]=idx[L*stride]; arr[R*stride]=arr[L*stride]; R--;} }
idx[L*stride]=pid; arr[L*stride]=piv; beg[i+1]=L+1; end[i+1]=end[i]; end[i++]=L;
if (end[i]-beg[i]>end[i-1]-beg[i-1]) {
swap=beg[i]; beg[i]=beg[i-1]; beg[i-1]=swap;
swap=end[i]; end[i]=end[i-1]; end[i-1]=swap; }}
else {
i--; }}}
void THTensor_(sort)(THTensor *rt_, THLongTensor *ri_, THTensor *t, int dimension, int descendingOrder)
{
THArgCheck(dimension >= 0 && dimension < THTensor_(nDimension)(t), 2, "invalid dimension");
THTensor_(resizeAs)(rt_, t);
THTensor_(copy)(rt_, t);
{
THLongStorage *size = THTensor_(newSizeOf)(t);
THLongTensor_resize(ri_, size, NULL);
THLongStorage_free(size);
}
if(descendingOrder)
{
TH_TENSOR_DIM_APPLY2(real, rt_, long, ri_, dimension,
long i;
for(i = 0; i < ri__size; i++)
ri__data[i*ri__stride] = i;
THTensor_(quicksortdescend)(rt__data, ri__data, rt__size, rt__stride);)
}
else
{
TH_TENSOR_DIM_APPLY2(real, rt_, long, ri_, dimension,
long i;
for(i = 0; i < ri__size; i++)
ri__data[i*ri__stride] = i;
THTensor_(quicksortascend)(rt__data, ri__data, rt__size, rt__stride);)
}
}
void THTensor_(tril)(THTensor *r_, THTensor *t, long k)
{
long t_size_0, t_size_1;
long t_stride_0, t_stride_1;
long r__stride_0, r__stride_1;
real *t_data, *r__data;
long r, c;
THArgCheck(THTensor_(nDimension)(t) == 2, 1, "not a matrix");
THTensor_(resizeAs)(r_, t);
t_size_0 = THTensor_(size)(t, 0);
t_size_1 = THTensor_(size)(t, 1);
t_stride_0 = THTensor_(stride)(t, 0);
t_stride_1 = THTensor_(stride)(t, 1);
r__stride_0 = THTensor_(stride)(r_, 0);
r__stride_1 = THTensor_(stride)(r_, 1);
r__data = THTensor_(data)(r_);
t_data = THTensor_(data)(t);
for(r = 0; r < t_size_0; r++)
{
long sz = THMin(r+k+1, t_size_1);
for(c = THMax(0, r+k); c < t_size_1; c++)
r__data[r*r__stride_0+c*r__stride_1] = 0;
for(c = 0; c < sz; c++)
r__data[r*r__stride_0+c*r__stride_1] = t_data[r*t_stride_0+c*t_stride_1];
}
}
void THTensor_(triu)(THTensor *r_, THTensor *t, long k)
{
long t_size_0, t_size_1;
long t_stride_0, t_stride_1;
long r__stride_0, r__stride_1;
real *t_data, *r__data;
long r, c;
THArgCheck(THTensor_(nDimension)(t) == 2, 1, "not a matrix");
THTensor_(resizeAs)(r_, t);
t_size_0 = THTensor_(size)(t, 0);
t_size_1 = THTensor_(size)(t, 1);
t_stride_0 = THTensor_(stride)(t, 0);
t_stride_1 = THTensor_(stride)(t, 1);
r__stride_0 = THTensor_(stride)(r_, 0);
r__stride_1 = THTensor_(stride)(r_, 1);
r__data = THTensor_(data)(r_);
t_data = THTensor_(data)(t);
for(r = 0; r < t_size_0; r++)
{
long sz = THMin(r+k, t_size_1);
for(c = THMax(0, r+k); c < t_size_1; c++)
r__data[r*r__stride_0+c*r__stride_1] = t_data[r*t_stride_0+c*t_stride_1];
for(c = 0; c < sz; c++)
r__data[r*r__stride_0+c*r__stride_1] = 0;
}
}
void THTensor_(cat)(THTensor *r_, THTensor *ta, THTensor *tb, int dimension)
{
THLongStorage *size;
int i;
int ndim = THMax(ta->nDimension, tb->nDimension);
ndim = THMax(ndim, dimension+1);
THArgCheck(dimension >= 0, 4, "invalid dimension");
size = THLongStorage_newWithSize(ndim);
for(i = 0; i < ndim; i++)
{
int tadi = (i < ta->nDimension ? ta->size[i] : 1);
int tbdi = (i < tb->nDimension ? tb->size[i] : 1);
if(i == dimension)
size->data[i] = tadi+tbdi;
else
{
if(tadi != tbdi)
{
THLongStorage_free(size);
THError("inconsistent tensor sizes");
}
size->data[i] = tadi;
}
}
THTensor_(resize)(r_, size, NULL);
THLongStorage_free(size);
{
THTensor *nta = THTensor_(newWithTensor)(r_);
THTensor_(narrow)(nta, NULL, dimension, 0, (dimension < ta->nDimension ? ta->size[dimension] : 1));
THTensor_(copy)(nta, ta);
THTensor_(free)(nta);
}
{
THTensor *ntb = THTensor_(newWithTensor)(r_);
THTensor_(narrow)(ntb, NULL, dimension, (dimension < ta->nDimension ? ta->size[dimension] : 1), (dimension < tb->nDimension ? tb->size[dimension] : 1));
THTensor_(copy)(ntb, tb);
THTensor_(free)(ntb);
}
}
/* floating point only now */
#if defined(TH_REAL_IS_FLOAT) || defined(TH_REAL_IS_DOUBLE)
#define LAB_IMPLEMENT_BASIC_FUNCTION(NAME, CFUNC) \
void THTensor_(NAME)(THTensor *r_, THTensor *t) \
{ \
THTensor_(resizeAs)(r_, t); \
TH_TENSOR_APPLY2(real, t, real, r_, *r__data = CFUNC(*t_data);); \
} \
#define LAB_IMPLEMENT_BASIC_FUNCTION_VALUE(NAME, CFUNC) \
void THTensor_(NAME)(THTensor *r_, THTensor *t, real value) \
{ \
THTensor_(resizeAs)(r_, t); \
TH_TENSOR_APPLY2(real, t, real, r_, *r__data = CFUNC(*t_data, value);); \
} \
\
LAB_IMPLEMENT_BASIC_FUNCTION(log,log)
LAB_IMPLEMENT_BASIC_FUNCTION(log1p,log1p)
LAB_IMPLEMENT_BASIC_FUNCTION(exp,exp)
LAB_IMPLEMENT_BASIC_FUNCTION(cos,cos)
LAB_IMPLEMENT_BASIC_FUNCTION(acos,acos)
LAB_IMPLEMENT_BASIC_FUNCTION(cosh,cosh)
LAB_IMPLEMENT_BASIC_FUNCTION(sin,sin)
LAB_IMPLEMENT_BASIC_FUNCTION(asin,asin)
LAB_IMPLEMENT_BASIC_FUNCTION(sinh,sinh)
LAB_IMPLEMENT_BASIC_FUNCTION(tan,tan)
LAB_IMPLEMENT_BASIC_FUNCTION(atan,atan)
LAB_IMPLEMENT_BASIC_FUNCTION(tanh,tanh)
LAB_IMPLEMENT_BASIC_FUNCTION_VALUE(pow,pow)
LAB_IMPLEMENT_BASIC_FUNCTION(sqrt,sqrt)
LAB_IMPLEMENT_BASIC_FUNCTION(ceil,ceil)
LAB_IMPLEMENT_BASIC_FUNCTION(floor,floor)
LAB_IMPLEMENT_BASIC_FUNCTION(abs,fabs)
void THTensor_(mean)(THTensor *r_, THTensor *t, int dimension)
{
THLongStorage *dim;
THArgCheck(dimension >= 0 && dimension < THTensor_(nDimension)(t), 2, "invalid dimension");
dim = THTensor_(newSizeOf)(t);
THLongStorage_set(dim, dimension, 1);
THTensor_(resize)(r_, dim, NULL);
THLongStorage_free(dim);
TH_TENSOR_DIM_APPLY2(real, t, real, r_, dimension,
accreal sum = 0;
long i;
for(i = 0; i < t_size; i++)
sum += t_data[i*t_stride];
*r__data = (real)sum/t_size;);
}
void THTensor_(std)(THTensor *r_, THTensor *t, int dimension, int flag)
{
THLongStorage *dim;
THArgCheck(dimension >= 0 && dimension < THTensor_(nDimension)(t), 3, "invalid dimension");
dim = THTensor_(newSizeOf)(t);
THLongStorage_set(dim, dimension, 1);
THTensor_(resize)(r_, dim, NULL);
THLongStorage_free(dim);
TH_TENSOR_DIM_APPLY2(real, t, real, r_, dimension,
accreal sum = 0;
accreal sum2 = 0;
long i;
for(i = 0; i < t_size; i++)
{
real z = t_data[i*t_stride];
sum += z;
sum2 += z*z;
}
if(flag)
{
sum /= t_size;
sum2 /= t_size;
sum2 -= sum*sum;
sum2 = (sum2 < 0 ? 0 : sum2);
*r__data = (real)sqrt(sum2);
}
else
{
sum /= t_size;
sum2 /= t_size-1;
sum2 -= ((real)t_size)/((real)(t_size-1))*sum*sum;
sum2 = (sum2 < 0 ? 0 : sum2);
*r__data = (real)sqrt(sum2);
});
}
void THTensor_(var)(THTensor *r_, THTensor *t, int dimension, int flag)
{
THLongStorage *dim;
THArgCheck(dimension >= 0 && dimension < THTensor_(nDimension)(t), 3, "invalid dimension");
dim = THTensor_(newSizeOf)(t);
THLongStorage_set(dim, dimension, 1);
THTensor_(resize)(r_, dim, NULL);
THLongStorage_free(dim);
TH_TENSOR_DIM_APPLY2(real, t, real, r_, dimension,
accreal sum = 0;
accreal sum2 = 0;
long i;
for(i = 0; i < t_size; i++)
{
real z = t_data[i*t_stride];
sum += z;
sum2 += z*z;
}
if(flag)
{
sum /= t_size;
sum2 /= t_size;
sum2 -= sum*sum;
sum2 = (sum2 < 0 ? 0 : sum2);
*r__data = sum2;
}
else
{
sum /= t_size;
sum2 /= t_size-1;
sum2 -= ((real)t_size)/((real)(t_size-1))*sum*sum;
sum2 = (sum2 < 0 ? 0 : sum2);
*r__data = (real)sum2;
});
}
accreal THTensor_(norm)(THTensor *tensor, real value)
{
accreal sum = 0;
TH_TENSOR_APPLY(real, tensor, sum += pow(fabs(*tensor_data), value););
return pow(sum, 1.0/value);
}
accreal THTensor_(dist)(THTensor *tensor, THTensor *src, real value)
{
real sum = 0;
TH_TENSOR_APPLY2(real, tensor, real, src,
sum += pow(fabs(*tensor_data - *src_data), value);)
return pow(sum, 1.0/value);
}
accreal THTensor_(meanall)(THTensor *tensor)
{
THArgCheck(tensor->nDimension > 0, 1, "empty Tensor");
return THTensor_(sumall)(tensor)/THTensor_(nElement)(tensor);
}
accreal THTensor_(varall)(THTensor *tensor)
{
accreal mean = THTensor_(meanall)(tensor);
accreal sum = 0;
TH_TENSOR_APPLY(real, tensor, sum += (*tensor_data - mean)*(*tensor_data - mean););
sum /= (THTensor_(nElement)(tensor)-1);
return sum;
}
accreal THTensor_(stdall)(THTensor *tensor)
{
return sqrt(THTensor_(varall)(tensor));
}
void THTensor_(linspace)(THTensor *r_, real a, real b, long n)
{
real i = 0;
THArgCheck(n > 0, 3, "invalid number of points");
THArgCheck(a <= b, 2, "end range should be greater than start range");
THTensor_(resize1d)(r_, n);
TH_TENSOR_APPLY(real, r_,
*r__data = a + i*(b-a)/((real)(n-1));
i++;
);
}
void THTensor_(logspace)(THTensor *r_, real a, real b, long n)
{
real i = 0;
THArgCheck(n > 0, 3, "invalid number of points");
THArgCheck(a <= b, 2, "end range should be greater than start range");
THTensor_(resize1d)(r_, n);
TH_TENSOR_APPLY(real, r_,
*r__data = pow(10.0, a + i*(b-a)/((real)(n-1)));
i++;
);
}
void THTensor_(rand)(THTensor *r_, THLongStorage *size)
{
THTensor_(resize)(r_, size, NULL);
THTensor_(uniform)(r_, 0, 1);
}
void THTensor_(randn)(THTensor *r_, THLongStorage *size)
{
THTensor_(resize)(r_, size, NULL);
THTensor_(normal)(r_, 0, 1);
}
#endif /* floating point only part */
#endif
Reference in New Issue View Git Blame Copy Permalink