提交 8d3ad6c4 authored 作者: Li Yao's avatar Li Yao

c code of grad of maxpool

c code version
上级 352177f3
...@@ -576,8 +576,6 @@ class DownsampleFactorMaxGrad(Op): ...@@ -576,8 +576,6 @@ class DownsampleFactorMaxGrad(Op):
self, 2, gz, 'Hessian not implemented with padding')] self, 2, gz, 'Hessian not implemented with padding')]
def c_code(self, node, name, inp, out, sub): def c_code(self, node, name, inp, out, sub):
if self.ds != self.st or self.padding != (0, 0):
raise theano.gof.utils.MethodNotDefined()
if self.mode != 'max': if self.mode != 'max':
raise theano.gof.utils.MethodNotDefined() raise theano.gof.utils.MethodNotDefined()
x, z, gz = inp x, z, gz = inp
...@@ -585,13 +583,14 @@ class DownsampleFactorMaxGrad(Op): ...@@ -585,13 +583,14 @@ class DownsampleFactorMaxGrad(Op):
fail = sub['fail'] fail = sub['fail']
ignore_border = int(self.ignore_border) ignore_border = int(self.ignore_border)
ds0, ds1 = self.ds ds0, ds1 = self.ds
st0, st1 = self.st
pd0, pd1 = self.padding
return """ return """
// sanity checks
int x_typenum = PyArray_ObjectType((PyObject*)%(x)s, 0); int x_typenum = PyArray_ObjectType((PyObject*)%(x)s, 0);
int z_typenum = PyArray_ObjectType((PyObject*)%(z)s, 0); int z_typenum = PyArray_ObjectType((PyObject*)%(z)s, 0);
int gz_typenum = PyArray_ObjectType((PyObject*)%(gz)s, 0); int gz_typenum = PyArray_ObjectType((PyObject*)%(gz)s, 0);
int x_shp0_usable;
int x_shp1_usable;
int z_shp0, z_shp1;
if ((x_typenum != z_typenum) || (x_typenum != gz_typenum)) if ((x_typenum != z_typenum) || (x_typenum != gz_typenum))
{ {
PyErr_SetString(PyExc_ValueError, "input types must all match"); PyErr_SetString(PyExc_ValueError, "input types must all match");
...@@ -612,18 +611,18 @@ class DownsampleFactorMaxGrad(Op): ...@@ -612,18 +611,18 @@ class DownsampleFactorMaxGrad(Op):
PyErr_SetString(PyExc_ValueError, "gz must be a 4d ndarray"); PyErr_SetString(PyExc_ValueError, "gz must be a 4d ndarray");
%(fail)s; %(fail)s;
} }
z_shp0 = PyArray_DIMS(%(z)s)[2];
z_shp1 = PyArray_DIMS(%(z)s)[3]; int z_r, z_c;
if (%(ignore_border)s) z_r = PyArray_DIMS(%(z)s)[2];
{ z_c = PyArray_DIMS(%(z)s)[3];
x_shp0_usable = z_shp0 * %(ds0)s;
x_shp1_usable = z_shp1 * %(ds1)s; int r, c; // shape of the padded_input
} r = PyArray_DIMS(%(x)s)[2];
else c = PyArray_DIMS(%(x)s)[3];
{ r += %(pd0)s * 2;
x_shp0_usable = PyArray_DIMS(%(x)s)[2]; c += %(pd1)s * 2;
x_shp1_usable = PyArray_DIMS(%(x)s)[3];
} // allocating memory for gx
if ((!%(gx)s) if ((!%(gx)s)
|| *PyArray_DIMS(%(gx)s)!=4 || *PyArray_DIMS(%(gx)s)!=4
||(PyArray_DIMS(%(gx)s)[0] != PyArray_DIMS(%(x)s)[0]) ||(PyArray_DIMS(%(gx)s)[0] != PyArray_DIMS(%(x)s)[0])
...@@ -635,44 +634,70 @@ class DownsampleFactorMaxGrad(Op): ...@@ -635,44 +634,70 @@ class DownsampleFactorMaxGrad(Op):
Py_XDECREF(%(gx)s); Py_XDECREF(%(gx)s);
%(gx)s = (PyArrayObject*) PyArray_ZEROS(4, PyArray_DIMS(%(x)s), x_typenum,0); %(gx)s = (PyArrayObject*) PyArray_ZEROS(4, PyArray_DIMS(%(x)s), x_typenum,0);
} }
int r_st, r_end, c_st, c_end; // used to index into the input img x
dtype_%(z)s maximum; // temp var for maximum value in a region
if (z_r && z_c)
{
for(int b=0; b<PyArray_DIMS(%(x)s)[0]; b++){
for(int k=0; k<PyArray_DIMS(%(x)s)[1]; k++){
for(int i=0; i< z_r; i++){
r_st = i * %(st0)s;
r_end = r_st + %(ds0)s;
// skip the padding
r_st = r_st < %(pd0)s ? %(pd0)s : r_st;
r_end = r_end > (r - %(pd0)s) ? r - %(pd0)s : r_end;
// from padded_img space to img space
r_st -= %(pd0)s;
r_end -= %(pd0)s;
// handle the case where no padding, ignore border is True
if (%(ignore_border)s)
{
r_end = r_end > r ? r : r_end;
}
for(int j=0; j<z_c; j++){
c_st = j * %(st1)s;
c_end = c_st + %(ds1)s;
// skip the padding
c_st = c_st < %(pd1)s ? %(pd1)s : c_st;
c_end = c_end > (c - %(pd1)s) ? c - %(pd1)s : c_end;
for(int b=0;b<PyArray_DIMS(%(x)s)[0];b++){ // change coordinates from padding_img space into img space
for(int k=0;k<PyArray_DIMS(%(x)s)[1];k++){ c_st -= %(pd1)s;
int mini_i = 0; c_end -= %(pd1)s;
int zi = 0; // handle the case where no padding, ignore border is True
for(int i=0;i< x_shp0_usable; i++){ if (%(ignore_border)s)
int mini_j = 0; {
int zj = 0; c_end = c_end > c ? c : c_end;
for(int j=0; j< x_shp1_usable; j++){ }
dtype_%(x)s * __restrict__ xp = ((dtype_%(x)s*)(PyArray_GETPTR4(%(x)s,b,k,i,j))); // the maximum value
dtype_%(gx)s * __restrict__ gxp = ((dtype_%(gx)s*)(PyArray_GETPTR4(%(gx)s,b,k,i,j))); maximum = ((dtype_%(z)s*)(PyArray_GETPTR4(%(z)s,b,k,i,j)))[0];
dtype_%(z)s * __restrict__ zp = ((dtype_%(z)s*)(PyArray_GETPTR4(%(z)s,b,k,zi,zj))); // the gradient corresponding to this maximum value in z
dtype_%(gz)s * __restrict__ gzp = ((dtype_%(gz)s*)(PyArray_GETPTR4(%(gz)s,b,k,zi,zj))); dtype_%(gz)s * gz = (
gxp[0] = (zp[0] == xp[0]) ? gzp[0] : 0; (dtype_%(gz)s*)(PyArray_GETPTR4(%(gz)s, b, k, i, j)));
mini_j = (mini_j + 1 == %(ds1)s) ? 0 : mini_j+1; // go through the pooled region in the unpadded input
zj += (mini_j == 0); for(int m=r_st; m<r_end; m++)
}//for j {
mini_i = (mini_i + 1 == %(ds0)s) ? 0 : mini_i+1; for(int n=c_st; n<c_end; n++)
zi += (mini_i == 0); {
dtype_%(x)s a = ((dtype_%(x)s*)(PyArray_GETPTR4(%(x)s,b,k,m,n)))[0];
for (int j = x_shp1_usable; j < PyArray_DIMS(%(x)s)[3]; ++j) { dtype_%(gx)s * gx = (
dtype_%(gx)s * gxp = ((dtype_%(gx)s*)(PyArray_GETPTR4(%(gx)s,b,k,i,j))); (dtype_%(gx)s*)(PyArray_GETPTR4(%(gx)s, b, k, m, n)));
gxp[0] = 0; if (a == maximum){
} gx[0] = gx[0] + gz[0];
}//for i }
}
for(int i = x_shp0_usable; i < PyArray_DIMS(%(x)s)[2]; i++){ }
for (int j = 0; j < PyArray_DIMS(%(x)s)[3]; ++j) { }
dtype_%(gx)s * gxp = ((dtype_%(gx)s*)(PyArray_GETPTR4(%(gx)s,b,k,i,j))); }
gxp[0] = 0; }
} }
}
}//for k }
}//for b
""" % locals() """ % locals()
def c_code_cache_version(self): def c_code_cache_version(self):
return (0, 2) return (0, 3)
class DownsampleFactorMaxGradGrad(Op): class DownsampleFactorMaxGradGrad(Op):
......
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