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pytensor
提交 5a48dea2 authored 作者: Frederic's avatar Frederic
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replace PyArrayObejct->nd to PyArray_NDIM(PyArrayObject) for numpy 1.7 compatibility.

上级 64bd8434
全部展开 隐藏空白字符变更
内嵌 并排
正在显示 包含 119 行增加 和 107 行删除
theano/compile/tests/test_debugmode.py
浏览文件 @ 5a48dea2
......@@ -56,8 +56,8 @@ class BROKEN_ON_PURPOSE_Add(gof.Op):
a, b = inp
z, = out
return """
if (%(a)s->nd != 1) {PyErr_SetString(PyExc_NotImplementedError, "rank(a) != 1"); %(fail)s;}
if (%(b)s->nd != 1) {PyErr_SetString(PyExc_NotImplementedError, "rank(b) != 1"); %(fail)s;}
if (PyArray_NDIM(%(a)s) != 1) {PyErr_SetString(PyExc_NotImplementedError, "rank(a) != 1"); %(fail)s;}
if (PyArray_NDIM(%(b)s) != 1) {PyErr_SetString(PyExc_NotImplementedError, "rank(b) != 1"); %(fail)s;}
if (%(a)s->descr->type_num != NPY_DOUBLE)
{PyErr_SetString(PyExc_NotImplementedError, "a dtype not NPY_DOUBLE"); %(fail)s;}
......@@ -603,8 +603,8 @@ class BrokenCImplementationAdd(gof.Op):
debug = 0
return """
//printf("executing c_code\\n");
if (%(a)s->nd != 2) {PyErr_SetString(PyExc_NotImplementedError, "rank(a) != 2"); %(fail)s;}
if (%(b)s->nd != 2) {PyErr_SetString(PyExc_NotImplementedError, "rank(b) != 2"); %(fail)s;}
if (PyArray_NDIM(%(a)s) != 2) {PyErr_SetString(PyExc_NotImplementedError, "rank(a) != 2"); %(fail)s;}
if (PyArray_NDIM(%(b)s) != 2) {PyErr_SetString(PyExc_NotImplementedError, "rank(b) != 2"); %(fail)s;}
if (%(a)s->descr->type_num != NPY_FLOAT)
{PyErr_SetString(PyExc_NotImplementedError, "a dtype not NPY_FLOAT"); %(fail)s;}
......
theano/sandbox/cuda/cuda_ndarray.cu
浏览文件 @ 5a48dea2
......@@ -783,7 +783,7 @@ CudaNdarray_TakeFrom(CudaNdarray * self, PyObject *args){
PyErr_SetString(PyExc_TypeError, "CudaNdarray_TakeFrom: need a ndarray for indices with dtype int32");
return NULL;
}
if (((PyArrayObject*)indices_obj)->nd != 1) {
if (PyArray_NDIM(((PyArrayObject*)indices_obj)) != 1) {
PyErr_SetString(PyExc_TypeError, "CudaNdarray_TakeFrom: need a CudaNdarray of indices with only 1 dimensions");
return NULL;
}
......@@ -2900,7 +2900,7 @@ filter(PyObject* __unsed_self, PyObject *args) // args = (data, broadcastable, s
Py_DECREF(broadcastable);
return NULL;
}
for (int i = 0; i < data->nd; ++i)
for (int i = 0; i < PyArray_NDIM(data); ++i)
{
if ((data->dimensions[i] > 1) && PyInt_AsLong(PyTuple_GetItem(broadcastable, Py_ssize_t(i))))
{
......@@ -3080,7 +3080,7 @@ cublas_shutdown()
int
CudaNdarray_CopyFromArray(CudaNdarray * self, PyArrayObject*obj)
{
int err = CudaNdarray_alloc_contiguous(self, obj->nd, obj->dimensions);
int err = CudaNdarray_alloc_contiguous(self, PyArray_NDIM(obj), obj->dimensions);
if (err) {
return err;
}
......
theano/sandbox/multinomial.py
浏览文件 @ 5a48dea2
......@@ -55,12 +55,12 @@ class MultinomialFromUniform(Op):
fail = sub['fail']
return """
if (%(pvals)s->nd != 2)
if (PyArray_NDIM(%(pvals)s) != 2)
{
PyErr_Format(PyExc_TypeError, "pvals wrong rank");
%(fail)s;
}
if (%(unis)s->nd != 1)
if (PyArray_NDIM(%(unis)s) != 1)
{
PyErr_Format(PyExc_TypeError, "unis wrong rank");
%(fail)s;
......@@ -233,12 +233,12 @@ class GpuMultinomialFromUniform(MultinomialFromUniform, GpuOp):
fail = sub['fail']
return """
if (%(pvals)s->nd != 2)
if (PyArray_NDIM(%(pvals)s) != 2)
{
PyErr_Format(PyExc_TypeError, "pvals wrong rank");
%(fail)s;
}
if (%(unis)s->nd != 1)
if (PyArray_NDIM(%(unis)s) != 1)
{
PyErr_Format(PyExc_TypeError, "unis wrong rank");
%(fail)s;
......
theano/sandbox/neighbours.py
浏览文件 @ 5a48dea2
......@@ -114,12 +114,12 @@ class Images2Neibs(Op):
int grid_c = -1; //number of patch in height
int grid_d = -1; //number of patch in width
{
if (%(ten4)s->nd != 4)
if (PyArray_NDIM(%(ten4)s) != 4)
{
PyErr_Format(PyExc_TypeError, "ten4 wrong rank");
%(fail)s;
}
if (%(neib_shape)s->nd != 1)
if (PyArray_NDIM(%(neib_shape)s) != 1)
{
PyErr_Format(PyExc_TypeError, "neib_shape wrong rank");
%(fail)s;
......@@ -130,7 +130,7 @@ class Images2Neibs(Op):
" contain 2 elements");
%(fail)s;
}
if (%(neib_step)s->nd != 1)
if (PyArray_NDIM(%(neib_step)s) != 1)
{
PyErr_Format(PyExc_TypeError, "neib_step wrong rank");
%(fail)s;
......
theano/sandbox/rng_mrg.py
浏览文件 @ 5a48dea2
......@@ -241,7 +241,7 @@ class mrg_uniform(mrg_uniform_base):
int n_elements = 1;
int n_streams = 0;
int must_alloc_sample = ((NULL == %(o_sample)s)
|| (%(o_sample)s->nd != %(ndim)s)
|| (PyArray_NDIM(%(o_sample)s) != %(ndim)s)
|| !(PyArray_ISCONTIGUOUS(%(o_sample)s)));
%(otype)s * sample_data;
npy_int32 * state_data;
......@@ -261,7 +261,7 @@ class mrg_uniform(mrg_uniform_base):
const npy_int32 MASK2 = 65535; //2^16 - 1
const npy_int32 MULT2 = 21069;
if (%(size)s->nd != 1)
if (PyArray_NDIM(%(size)s) != 1)
{
PyErr_SetString(PyExc_ValueError, "size must be vector");
%(fail)s
......@@ -296,7 +296,7 @@ class mrg_uniform(mrg_uniform_base):
Py_XDECREF(%(o_rstate)s);
%(o_rstate)s = (PyArrayObject*)PyArray_FromAny(py_%(rstate)s, NULL, 0, 0, %(o_rstate_requirement)s,NULL);
if (%(o_rstate)s->nd != 2)
if (PyArray_NDIM(%(o_rstate)s) != 2)
{
PyErr_SetString(PyExc_ValueError, "rstate must be matrix");
%(fail)s
......@@ -501,9 +501,9 @@ class GPU_mrg_uniform(mrg_uniform_base, GpuOp):
int must_alloc_sample = ((NULL == %(o_sample)s)
|| !CudaNdarray_Check(py_%(o_sample)s)
|| !CudaNdarray_is_c_contiguous(%(o_sample)s)
|| (%(o_sample)s->nd != %(ndim)s));
|| (PyArray_NDIM(%(o_sample)s) != %(ndim)s));
if (%(size)s->nd != 1)
if (PyArray_NDIM(%(size)s) != 1)
{
PyErr_SetString(PyExc_ValueError, "size must be vector");
%(fail)s
......@@ -552,7 +552,7 @@ class GPU_mrg_uniform(mrg_uniform_base, GpuOp):
%(o_rstate)s = (CudaNdarray*)CudaNdarray_Copy(%(rstate)s);
}
if (%(o_rstate)s->nd != 1)
if (PyArray_NDIM(%(o_rstate)s) != 1)
{
PyErr_SetString(PyExc_ValueError, "rstate must be vector");
%(fail)s;
......
theano/sparse/basic.py
浏览文件 @ 5a48dea2
......@@ -3006,10 +3006,10 @@ class StructuredDotGradCSC(gof.Op):
'g_ab')
return """
if (%(_d)s->nd != 2) {PyErr_SetString(PyExc_NotImplementedError, "rank(d) != 2"); %(fail)s;}
if (%(_g)s->nd != 2) {PyErr_SetString(PyExc_NotImplementedError, "rank(g) != 2"); %(fail)s;}
if (%(_indices)s->nd != 1) {PyErr_SetString(PyExc_NotImplementedError, "rank(indices) != 1"); %(fail)s;}
if (%(_indptr)s->nd != 1) {PyErr_SetString(PyExc_NotImplementedError, "rank(indptr) != 1"); %(fail)s;}
if (PyArray_NDIM(%(_d)s) != 2) {PyErr_SetString(PyExc_NotImplementedError, "rank(d) != 2"); %(fail)s;}
if (PyArray_NDIM(%(_g)s) != 2) {PyErr_SetString(PyExc_NotImplementedError, "rank(g) != 2"); %(fail)s;}
if (PyArray_NDIM(%(_indices)s) != 1) {PyErr_SetString(PyExc_NotImplementedError, "rank(indices) != 1"); %(fail)s;}
if (PyArray_NDIM(%(_indptr)s) != 1) {PyErr_SetString(PyExc_NotImplementedError, "rank(indptr) != 1"); %(fail)s;}
if( %(_indices)s->descr->type_num != NPY_INT32) {
PyErr_SetString(PyExc_NotImplementedError, "C"); %(fail)s;}
......@@ -3142,10 +3142,10 @@ class StructuredDotGradCSR(gof.Op):
'g_ab')
return """
if (%(_d)s->nd != 2) {PyErr_SetString(PyExc_NotImplementedError, "rank(d) != 2"); %(fail)s;}
if (%(_g)s->nd != 2) {PyErr_SetString(PyExc_NotImplementedError, "rank(g) != 2"); %(fail)s;}
if (%(_indices)s->nd != 1) {PyErr_SetString(PyExc_NotImplementedError, "rank(indices) != 1"); %(fail)s;}
if (%(_indptr)s->nd != 1) {PyErr_SetString(PyExc_NotImplementedError, "rank(indptr) != 1"); %(fail)s;}
if (PyArray_NDIM(%(_d)s) != 2) {PyErr_SetString(PyExc_NotImplementedError, "rank(d) != 2"); %(fail)s;}
if (PyArray_NDIM(%(_g)s) != 2) {PyErr_SetString(PyExc_NotImplementedError, "rank(g) != 2"); %(fail)s;}
if (PyArray_NDIM(%(_indices)s) != 1) {PyErr_SetString(PyExc_NotImplementedError, "rank(indices) != 1"); %(fail)s;}
if (PyArray_NDIM(%(_indptr)s) != 1) {PyErr_SetString(PyExc_NotImplementedError, "rank(indptr) != 1"); %(fail)s;}
if( %(_indices)s->descr->type_num != NPY_INT32) {
PyErr_SetString(PyExc_NotImplementedError, "C"); %(fail)s;}
......
theano/sparse/opt.py
浏览文件 @ 5a48dea2
差异被折叠。
theano/tensor/basic.py
浏览文件 @ 5a48dea2
......@@ -4063,7 +4063,7 @@ class Subtensor(Op):
PyErr_Format(PyExc_ValueError, "x and xview"
"(with %%d dims) have the same dimensions"
" pointers: %%p and %%p",
%(x)s->nd, xview->dimensions, %(x)s->dimensions);
PyArray_NDIM(%(x)s), xview->dimensions, %(x)s->dimensions);
%(fail)s;
}
if (xview->strides == %(x)s->strides
......@@ -4072,7 +4072,7 @@ class Subtensor(Op):
PyErr_Format(PyExc_ValueError, "x and xview"
"(with %%d dims) have the same strides"
" pointers: %%p and %%p",
%(x)s->nd, xview->strides, %(x)s->strides);
PyArray_NDIM(%(x)s), xview->strides, %(x)s->strides);
%(fail)s;
}
......@@ -4176,10 +4176,10 @@ class Subtensor(Op):
spec_pos += 1;
}
}
assert (inner_ii <= xview->nd);
while (inner_ii < xview->nd)
assert (inner_ii <= PyArray_NDIM(xview));
while (inner_ii < PyArray_NDIM(xview))
{
assert (outer_ii < %(x)s->nd);
assert (outer_ii < PyArray_NDIM(%(x)s));
xview->dimensions[inner_ii] = %(x)s->dimensions[outer_ii];
xview->strides[inner_ii] = %(x)s->strides[outer_ii];
inner_ii += 1;
......@@ -5373,7 +5373,7 @@ class Reshape(Op):
new_ndim = self.ndim
fail = sub['fail']
return """
assert (%(shp)s->nd == 1);
assert (PyArray_NDIM(%(shp)s) == 1);
npy_intp new_dims[%(new_ndim)s];
PyArray_Dims newshape;
newshape.ptr = new_dims;
......
theano/tensor/blas.py
浏览文件 @ 5a48dea2
......@@ -511,12 +511,22 @@ class GemmRelated(Op):
#setup_z_Nz_Sz = None
check_xyz_rank2 = """
if (%(_x)s->nd != 2) {
PyErr_Format(PyExc_NotImplementedError, "rank(x) != 2. rank(x) is %%d.", %(_x)s->nd); %(fail)s;}
if (%(_y)s->nd != 2) {
PyErr_Format(PyExc_NotImplementedError, "rank(y) != 2. rank(y) is %%d.", %(_y)s->nd); %(fail)s;}
if (%(_zout)s && %(_zout)s->nd != 2) {
PyErr_Format(PyExc_NotImplementedError, "rank(z) != 2. rank(z) is %%d.", %(_zout)s->nd); %(fail)s;}
if (PyArray_NDIM(%(_x)s) != 2) {
PyErr_Format(PyExc_NotImplementedError,
"rank(x) != 2. rank(x) is %%d.",
PyArray_NDIM(%(_x)s));
%(fail)s;
}
if (PyArray_NDIM(%(_y)s) != 2) {
PyErr_Format(PyExc_NotImplementedError,
"rank(y) != 2. rank(y) is %%d.", PyArray_NDIM(%(_y)s));
%(fail)s;
}
if (%(_zout)s && PyArray_NDIM(%(_zout)s) != 2) {
PyErr_Format(PyExc_NotImplementedError,
"rank(z) != 2. rank(z) is %%d.", PyArray_NDIM(%(_zout)s));
%(fail)s;
}
"""
check_xyz_double_or_float = """
if ((%(_x)s->descr->type_num != NPY_DOUBLE)
......
theano/tensor/blas_c.py
浏览文件 @ 5a48dea2
......@@ -33,13 +33,13 @@ def ger_c_code(A, a, x, y, Z, destructive, fail):
int elemsize ;
if (%(A)s->nd != 2)
if (PyArray_NDIM(%(A)s) != 2)
{PyErr_SetString(PyExc_NotImplementedError, "rank(A) != 2"); %(fail)s;}
if (%(x)s->nd != 1)
if (PyArray_NDIM(%(x)s) != 1)
{PyErr_SetString(PyExc_NotImplementedError, "rank(x) != 1"); %(fail)s;}
if (%(y)s->nd != 1)
if (PyArray_NDIM(%(y)s) != 1)
{PyErr_SetString(PyExc_NotImplementedError, "rank(y) != 1"); %(fail)s;}
if (%(a)s->nd != 0)
if (PyArray_NDIM(%(a)s) != 0)
{PyErr_SetString(PyExc_NotImplementedError, "rank(a) != 0"); %(fail)s;}
if (%(A)s->descr->type_num != %(x)s->descr->type_num)
......@@ -290,27 +290,27 @@ def gemv_c_code(aa, xx, yy, zz, alpha, beta, destructive, fail):
float fbeta;
double dbeta;
if (%(aa)s->nd != 1)
if (PyArray_NDIM(%(aa)s) != 1)
{
PyErr_SetString(PyExc_NotImplementedError, "Gemv: rank(aa) != 1");
%(fail)s;
}
if (%(xx)s->nd != 2)
if (PyArray_NDIM(%(xx)s) != 2)
{
PyErr_SetString(PyExc_NotImplementedError, "Gemv: rank(xx) != 2");
%(fail)s;
}
if (%(yy)s->nd != 1)
if (PyArray_NDIM(%(yy)s) != 1)
{
PyErr_SetString(PyExc_NotImplementedError, "Gemv: rank(yy) != 1");
%(fail)s;
}
if (%(alpha)s->nd != 0)
if (PyArray_NDIM(%(alpha)s) != 0)
{
PyErr_SetString(PyExc_NotImplementedError, "Gemv: rank(alpha) != 0");
%(fail)s;
}
if (%(beta)s->nd != 0)
if (PyArray_NDIM(%(beta)s) != 0)
{
PyErr_SetString(PyExc_NotImplementedError, "Gemv: rank(beta) != 0");
%(fail)s;
......
theano/tensor/blas_headers.py
浏览文件 @ 5a48dea2
......@@ -809,9 +809,9 @@ def ____gemm_code(check_ab, a_init, b_init):
int unit = 0;
if (_x->nd != 2) goto _dot_execute_fallback;
if (_y->nd != 2) goto _dot_execute_fallback;
if (_z->nd != 2) goto _dot_execute_fallback;
if (PyArray_NDIM(_x) != 2) goto _dot_execute_fallback;
if (PyArray_NDIM(_y) != 2) goto _dot_execute_fallback;
if (PyArray_NDIM(_z) != 2) goto _dot_execute_fallback;
%(check_ab)s
......
theano/tensor/elemwise.py
浏览文件 @ 5a48dea2
......@@ -270,7 +270,7 @@ class DimShuffle(Op):
nd_in = len(self.input_broadcastable)
nd_out = len(self.new_order)
check_input_nd = [('if (%(input)s->nd != ' + str(nd_in) + ')'
check_input_nd = [('if (PyArray_NDIM(%(input)s) != ' + str(nd_in) + ')'
'{PyErr_SetString(PyExc_NotImplementedError, "input nd"); %(fail)s;}')]
clear_output = ['if (%(res)s) {Py_XDECREF(%(res)s);}']
......@@ -1341,7 +1341,7 @@ class CAReduce(Op):
pattern_ = str(pattern)[1:-1]
decl += """int tosum[]={%(pattern_)s};""" % locals()
alloc += """
for(int i=0;i<%(iname)s->nd;i++){
for(int i=0;i<PyArray_NDIM(%(iname)s);i++){
if(PyArray_DIMS(%(iname)s)[i]==0 && tosum[i]){
PyErr_Format(PyExc_ValueError,
"Input of CAReduce{%(scal_name)s} has zero-size on axis %%d",i);
......
theano/tensor/elemwise_cgen.py
浏览文件 @ 5a48dea2
......@@ -47,7 +47,7 @@ def make_checks(loop_orders, dtypes, sub):
# tensor is as expected.
min_nd = max(nonx) + 1
init += """
if (%(var)s->nd < %(min_nd)s) {
if (PyArray_NDIM(%(var)s) < %(min_nd)s) {
PyErr_SetString(PyExc_ValueError, "Not enough dimensions on input.");
%%(fail)s
}
......
theano/tensor/nnet/Conv3D.py
浏览文件 @ 5a48dea2
......@@ -182,26 +182,26 @@ class Conv3D(theano.Op):
//printf("\t\t\t\tConv3D c code\\n");
//Check dimensionality of inputs
if (%(W)s->nd != 5)
if (PyArray_NDIM(%(W)s) != 5)
{
PyErr_Format(PyExc_ValueError, "Conv3D: W must be a 5 dimensional tensor");
%(fail)s
}
if (%(V)s->nd != 5)
if (PyArray_NDIM(%(V)s) != 5)
{
PyErr_Format(PyExc_ValueError, "Conv3D: V must be a 5 dimensional tensor");
%(fail)s
}
if (%(b)s->nd != 1)
if (PyArray_NDIM(%(b)s) != 1)
{
PyErr_Format(PyExc_ValueError,"Conv3D: b must be a vector.");
%(fail)s
}
if (%(d)s->nd != 1)
if (PyArray_NDIM(%(d)s) != 1)
{
PyErr_Format(PyExc_ValueError,"Conv3D: d must be a vector.");
%(fail)s
......
theano/tensor/nnet/ConvGrad3D.py
浏览文件 @ 5a48dea2
......@@ -97,25 +97,25 @@ class ConvGrad3D(theano.Op):
//printf("\t\t\t\tConvGradW3D c code\\n");
//Check dimensionality of inputs
if (%(dCdH)s->nd != 5)
if (PyArray_NDIM(%(dCdH)s) != 5)
{
PyErr_Format(PyExc_ValueError, "ConvGrad3D: dCdH must be a 5 dimensional tensor");
%(fail)s
}
if (%(V)s->nd != 5)
if (PyArray_NDIM(%(V)s) != 5)
{
PyErr_Format(PyExc_ValueError, "ConvGrad3D: V must be a 5 dimensional tensor");
%(fail)s
}
if (%(WShape)s->nd != 1)
if (PyArray_NDIM(%(WShape)s) != 1)
{
PyErr_Format(PyExc_ValueError,"ConvGrad3D: WShape must be a vector.");
%(fail)s
}
if (%(d)s->nd != 1)
if (PyArray_NDIM(%(d)s) != 1)
{
PyErr_Format(PyExc_ValueError,"ConvGrad3D: d must be a vector.");
%(fail)s
......
theano/tensor/nnet/ConvTransp3D.py
浏览文件 @ 5a48dea2
......@@ -99,25 +99,27 @@ class ConvTransp3D(theano.Op):
//printf("\t\t\t\tConvTransp3D c code\\n");
//Check dimensionality of inputs
if (%(H)s->nd != 5)
if (PyArray_NDIM(%(H)s) != 5)
{
PyErr_Format(PyExc_ValueError, "H must be a 5-D tensor but it is %%i-D",%(H)s->nd);
PyErr_Format(PyExc_ValueError,
"H must be a 5-D tensor but it is %%i-D",
PyArray_NDIM(%(H)s));
%(fail)s
}
if (%(W)s->nd != 5)
if (PyArray_NDIM(%(W)s) != 5)
{
PyErr_Format(PyExc_ValueError, "ConvTransp3D: W must be a 5-D tensor");
%(fail)s
}
if (%(b)s->nd != 1)
if (PyArray_NDIM(%(b)s) != 1)
{
PyErr_Format(PyExc_ValueError, "ConvTransp3D: b must be a vector");
%(fail)s
}
if (%(d)s->nd != 1)
if (PyArray_NDIM(%(d)s) != 1)
{
PyErr_Format(PyExc_ValueError, "ConvTransp3D: d must be a vector");
%(fail)s
......@@ -179,7 +181,7 @@ class ConvTransp3D(theano.Op):
if (%(RShape)s)
{
if (%(RShape)s->nd != 1)
if (PyArray_NDIM(%(RShape)s) != 1)
{
PyErr_Format(PyExc_ValueError, "ConvTransp3D: RShape must be a vector");
%(fail)s
......
theano/tensor/nnet/conv.py
浏览文件 @ 5a48dea2
......@@ -1266,14 +1266,14 @@ kerns_shape.len=4;
PyObject *img2d=NULL, *contig, *filtersflipped=NULL;
if(%(img2d)s->nd==2){
if(PyArray_NDIM(%(img2d)s)==2){
img2d_dim[3]=%(img2d)s->dimensions[1];
img2d_dim[2]=%(img2d)s->dimensions[0];
}else if(%(img2d)s->nd==3){
}else if(PyArray_NDIM(%(img2d)s)==3){
img2d_dim[3]=%(img2d)s->dimensions[2];
img2d_dim[2]=%(img2d)s->dimensions[1];
img2d_dim[0]=%(img2d)s->dimensions[0];
}else if(%(img2d)s->nd==4){
}else if(PyArray_NDIM(%(img2d)s)==4){
img2d_dim[3]=%(img2d)s->dimensions[3];
img2d_dim[2]=%(img2d)s->dimensions[2];
img2d_dim[1]=%(img2d)s->dimensions[1];
......@@ -1283,18 +1283,18 @@ if(%(img2d)s->nd==2){
%(fail)s;
}
if(%(filtersflipped)s->nd==3){
if(PyArray_NDIM(%(filtersflipped)s)==3){
kerns_dim[3]=%(filtersflipped)s->dimensions[2];
kerns_dim[2]=%(filtersflipped)s->dimensions[1];
kerns_dim[0]=%(filtersflipped)s->dimensions[0];
}else if(%(filtersflipped)s->nd==4){
}else if(PyArray_NDIM(%(filtersflipped)s)==4){
kerns_dim[3]=%(filtersflipped)s->dimensions[3];
kerns_dim[2]=%(filtersflipped)s->dimensions[2];
kerns_dim[1]=%(filtersflipped)s->dimensions[1];
kerns_dim[0]=%(filtersflipped)s->dimensions[0];
}else{
std::stringstream temp;
temp << "nddim="<<%(filtersflipped)s->nd;
temp << "nddim="<<PyArray_NDIM(%(filtersflipped)s);
std::string param = temp.str();
PyErr_SetString(PyExc_ValueError,
("kernel don't have a good shape. " + param).c_str());
......@@ -1536,14 +1536,14 @@ kerns_shape.ptr=kerns_dim;
kerns_shape.len=4;
PyObject *img2d=NULL, *contig;
if(%(img2d)s->nd==2){
if(PyArray_NDIM(%(img2d)s)==2){
img2d_dim[3]=%(img2d)s->dimensions[1];
img2d_dim[2]=%(img2d)s->dimensions[0];
}else if(%(img2d)s->nd==3){
}else if(PyArray_NDIM(%(img2d)s)==3){
img2d_dim[3]=%(img2d)s->dimensions[2];
img2d_dim[2]=%(img2d)s->dimensions[1];
img2d_dim[0]=%(img2d)s->dimensions[0];
}else if(%(img2d)s->nd==4){
}else if(PyArray_NDIM(%(img2d)s)==4){
img2d_dim[3]=%(img2d)s->dimensions[3];
img2d_dim[2]=%(img2d)s->dimensions[2];
img2d_dim[1]=%(img2d)s->dimensions[1];
......@@ -1553,18 +1553,18 @@ if(%(img2d)s->nd==2){
%(fail)s;
}
if(%(filtersflipped)s->nd==3){
if(PyArray_NDIM(%(filtersflipped)s)==3){
kerns_dim[3]=%(filtersflipped)s->dimensions[2];
kerns_dim[2]=%(filtersflipped)s->dimensions[1];
kerns_dim[0]=%(filtersflipped)s->dimensions[0];
}else if(%(filtersflipped)s->nd==4){
}else if(PyArray_NDIM(%(filtersflipped)s)==4){
kerns_dim[3]=%(filtersflipped)s->dimensions[3];
kerns_dim[2]=%(filtersflipped)s->dimensions[2];
kerns_dim[1]=%(filtersflipped)s->dimensions[1];
kerns_dim[0]=%(filtersflipped)s->dimensions[0];
}else{
std::stringstream temp;
temp << "nddim="<<%(filtersflipped)s->nd;
temp << "nddim="<<PyArray_NDIM(%(filtersflipped)s);
std::string param = temp.str();
PyErr_SetString(PyExc_ValueError,
("kernel don't have a good shape. " + param).c_str());
......@@ -1637,7 +1637,7 @@ for(int i=0;i < kerns_dim[0];++i){
for(int j=0;j < kerns_dim[1];++j){
for(int k=0;k < kerns_dim[2];++k){
for(int l=0;l < kerns_dim[3];++l){
%(type)s * ff = ((%(filtersflipped)s)->nd == 3)
%(type)s * ff = ((PyArray_NDIM(%(filtersflipped)s)) == 3)
? (%(type)s *)PyArray_GETPTR3(%(filtersflipped)s, i, kerns_dim[2]-1-k, kerns_dim[3]-1-l)
: (%(type)s *)PyArray_GETPTR4(%(filtersflipped)s, i, j, kerns_dim[2]-1-k, kerns_dim[3]-1-l);
myfilters[i * (kerns_dim[1]*kerns_dim[2]*kerns_dim[3])
......@@ -1788,32 +1788,32 @@ kerns_shape.ptr=kerns_dim;
kerns_shape.len=4;
PyObject *img2d=NULL, *contig, *filtersflipped=NULL;
if(%(img2d)s->nd==2){
if(PyArray_NDIM(%(img2d)s)==2){
img2d_dim[3]=%(img2d)s->dimensions[1];
img2d_dim[2]=%(img2d)s->dimensions[0];
}else if(%(img2d)s->nd==3){
}else if(PyArray_NDIM(%(img2d)s)==3){
img2d_dim[3]=%(img2d)s->dimensions[2];
img2d_dim[2]=%(img2d)s->dimensions[1];
img2d_dim[0]=%(img2d)s->dimensions[0];
}else if(%(img2d)s->nd==4){
}else if(PyArray_NDIM(%(img2d)s)==4){
img2d_dim[3]=%(img2d)s->dimensions[3];
img2d_dim[2]=%(img2d)s->dimensions[2];
img2d_dim[1]=%(img2d)s->dimensions[1];
img2d_dim[0]=%(img2d)s->dimensions[0];
}else {
std::stringstream temp;
temp << "nddim="<<%(img2d)s->nd;
temp << "nddim="<<PyArray_NDIM(%(img2d)s);
std::string param = temp.str();
PyErr_SetString(PyExc_ValueError,
("img don't have a good shape. " + param).c_str());
%(fail)s;
}
if(%(filtersflipped)s->nd==3){
if(PyArray_NDIM(%(filtersflipped)s)==3){
kerns_dim[3]=%(filtersflipped)s->dimensions[2];
kerns_dim[2]=%(filtersflipped)s->dimensions[1];
kerns_dim[0]=%(filtersflipped)s->dimensions[0];
}else if(%(filtersflipped)s->nd==4){
}else if(PyArray_NDIM(%(filtersflipped)s)==4){
kerns_dim[3]=%(filtersflipped)s->dimensions[3];
kerns_dim[2]=%(filtersflipped)s->dimensions[2];
kerns_dim[1]=%(filtersflipped)s->dimensions[1];
......@@ -2025,36 +2025,36 @@ kerns_shape.ptr=kerns_dim;
kerns_shape.len=4;
PyObject *img2d=NULL, *contig, *filtersflipped=NULL;
if(%(img2d)s->nd==2){
if(PyArray_NDIM(%(img2d)s)==2){
img2d_dim[3]=%(img2d)s->dimensions[1];
img2d_dim[2]=%(img2d)s->dimensions[0];
}else if(%(img2d)s->nd==3){
}else if(PyArray_NDIM(%(img2d)s)==3){
img2d_dim[3]=%(img2d)s->dimensions[2];
img2d_dim[2]=%(img2d)s->dimensions[1];
img2d_dim[0]=%(img2d)s->dimensions[0];
}else if(%(img2d)s->nd==4){
}else if(PyArray_NDIM(%(img2d)s)==4){
img2d_dim[3]=%(img2d)s->dimensions[3];
img2d_dim[2]=%(img2d)s->dimensions[2];
img2d_dim[1]=%(img2d)s->dimensions[1];
img2d_dim[0]=%(img2d)s->dimensions[0];
}else {
PyErr_Format(PyExc_ValueError,
"image don't have a good number of dimensions %%d. ", %(filtersflipped)s->nd);
"image don't have a good number of dimensions %%d. ", PyArray_NDIM(%(filtersflipped)s));
%(fail)s;
}
if(%(filtersflipped)s->nd==3){
if(PyArray_NDIM(%(filtersflipped)s)==3){
kerns_dim[3]=%(filtersflipped)s->dimensions[2];
kerns_dim[2]=%(filtersflipped)s->dimensions[1];
kerns_dim[0]=%(filtersflipped)s->dimensions[0];
}else if(%(filtersflipped)s->nd==4){
}else if(PyArray_NDIM(%(filtersflipped)s)==4){
kerns_dim[3]=%(filtersflipped)s->dimensions[3];
kerns_dim[2]=%(filtersflipped)s->dimensions[2];
kerns_dim[1]=%(filtersflipped)s->dimensions[1];
kerns_dim[0]=%(filtersflipped)s->dimensions[0];
}else{
PyErr_Format(PyExc_ValueError,
"kernel don't have a good number of dimensions %%d. ", %(filtersflipped)s->nd);
"kernel don't have a good number of dimensions %%d. ", PyArray_NDIM(%(filtersflipped)s));
%(fail)s;
}
......
theano/tensor/nnet/nnet.py
浏览文件 @ 5a48dea2
......@@ -107,12 +107,12 @@ class SoftmaxWithBias(gof.Op):
init_decl = """
npy_intp* Nx = %(x)s->dimensions;
if (%(x)s->nd != 2)
if (PyArray_NDIM(%(x)s) != 2)
{
PyErr_SetString(PyExc_ValueError, "a not 2d tensor");
%(fail)s;
}
if (%(b)s->nd != 1)
if (PyArray_NDIM(%(b)s) != 1)
{
PyErr_SetString(PyExc_ValueError, "b not 1d tensor");
%(fail)s;
......@@ -277,8 +277,8 @@ class SoftmaxGrad(gof.Op):
"types should be float or float64");
%(fail)s;
}
if ((%(dy)s->nd != 2)
|| (%(sm)s->nd != 2))
if ((PyArray_NDIM(%(dy)s) != 2)
|| (PyArray_NDIM(%(sm)s) != 2))
{
PyErr_SetString(PyExc_ValueError, "rank error");
%(fail)s;
......@@ -773,7 +773,7 @@ class CrossentropySoftmaxArgmax1HotWithBias(gof.Op):
SoftmaxWithBias.c_code_template()
return (init_decl,
"""
if (%(y_idx)s->nd != 1)
if (PyArray_NDIM(%(y_idx)s) != 1)
{
PyErr_SetString(PyExc_ValueError, "y_idx not 1d tensor");
%(fail)s;
......@@ -937,9 +937,9 @@ class CrossentropySoftmax1HotWithBiasDx (gof.Op):
"y_idx not int8, int16, int32, or int64");
%(fail)s;
}
if ((%(dnll)s->nd != 1)
|| (%(sm)s->nd != 2)
|| (%(y_idx)s->nd != 1))
if ((PyArray_NDIM(%(dnll)s) != 1)
|| (PyArray_NDIM(%(sm)s) != 2)
|| (PyArray_NDIM(%(y_idx)s) != 1))
{
PyErr_SetString(PyExc_ValueError, "rank error");
%(fail)s;
......
theano/tensor/signal/downsample.py
浏览文件 @ 5a48dea2
......@@ -176,7 +176,7 @@ class DownsampleFactorMax(Op):
int x_shp0_usable;
int x_shp1_usable;
int z_shp0, z_shp1;
if(%(x)s->nd!=4)
if(PyArray_NDIM(%(x)s)!=4)
{
PyErr_SetString(PyExc_ValueError, "x must be a 4d ndarray");
%(fail)s;
......@@ -306,17 +306,17 @@ class DownsampleFactorMaxGrad(Op):
PyErr_SetString(PyExc_ValueError, "input types must all match");
%(fail)s;
}
if(%(x)s->nd!=4)
if(PyArray_NDIM(%(x)s)!=4)
{
PyErr_SetString(PyExc_ValueError, "x must be a 4d ndarray");
%(fail)s;
}
if(%(z)s->nd!=4)
if(PyArray_NDIM(%(z)s)!=4)
{
PyErr_SetString(PyExc_ValueError, "z must be a 4d ndarray");
%(fail)s;
}
if(%(gz)s->nd!=4)
if(PyArray_NDIM(%(gz)s)!=4)
{
PyErr_SetString(PyExc_ValueError, "gz must be a 4d ndarray");
%(fail)s;
......
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