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pytensor
提交 616089ff authored 作者: James Bergstra's avatar James Bergstra
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printf(...) -> fprintf(stderr, ...) in conv.cu

上级 a8ce2352
隐藏空白字符变更
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正在显示 包含 59 行增加 和 57 行删除
theano/sandbox/cuda/conv.cu
浏览文件 @ 616089ff
......@@ -99,11 +99,11 @@ CudaNdarray_conv_valid(const CudaNdarray *img, const CudaNdarray * kern,
if (verbose>1)
{
printf("INFO: Running conv_valid version=%d, MACRO kern_width=%d with inputs:\n",version,THEANO_KERN_WID);
printf("INFO: img dim: %i %i %i %i img stride: %i %i %i %i\n",
fprintf(stderr, "INFO: Running conv_valid version=%d, MACRO kern_width=%d with inputs:\n",version,THEANO_KERN_WID);
fprintf(stderr, "INFO: img dim: %i %i %i %i img stride: %i %i %i %i\n",
CudaNdarray_HOST_DIMS(img)[0], CudaNdarray_HOST_DIMS(img)[1],CudaNdarray_HOST_DIMS(img)[2],CudaNdarray_HOST_DIMS(img)[3],
CudaNdarray_HOST_STRIDES(img)[0], CudaNdarray_HOST_STRIDES(img)[1],CudaNdarray_HOST_STRIDES(img)[2],CudaNdarray_HOST_STRIDES(img)[3]);
printf("INFO: kern dim: %i %i %i %i kern stride: %i %i %i %i\n",
fprintf(stderr, "INFO: kern dim: %i %i %i %i kern stride: %i %i %i %i\n",
CudaNdarray_HOST_DIMS(kern)[0], CudaNdarray_HOST_DIMS(kern)[1],CudaNdarray_HOST_DIMS(kern)[2],CudaNdarray_HOST_DIMS(kern)[3],
CudaNdarray_HOST_STRIDES(kern)[0], CudaNdarray_HOST_STRIDES(kern)[1],CudaNdarray_HOST_STRIDES(kern)[2],CudaNdarray_HOST_STRIDES(kern)[3]);
}
......@@ -151,13 +151,13 @@ CudaNdarray_conv_valid(const CudaNdarray *img, const CudaNdarray * kern,
cudaError_t sts = cudaGetLastError();
if (cudaSuccess == sts)
{
if (verbose) printf("INFO: used 'conv_patch' version %s nb_split=%d\n",threads.y==out_len?"no split": "split",nb_split);
if (verbose) fprintf(stderr, "INFO: used 'conv_patch' version %s nb_split=%d\n",threads.y==out_len?"no split": "split",nb_split);
work_complete = true;
}
else
{
if (verbose) printf("threads.x=%i, threads.y=%i, grid.x=%i, grid.y=%i, shared_size=%i, nb_threads=%i, nb_split=%i\n", threads.x, threads.y, grid.x, grid.y, shared_size, threads.x * threads.y, nb_split);
if (verbose) printf("INFO: impl 'conv_patch' failed (%s), trying next implementation\n",
if (verbose) fprintf(stderr, "threads.x=%i, threads.y=%i, grid.x=%i, grid.y=%i, shared_size=%i, nb_threads=%i, nb_split=%i\n", threads.x, threads.y, grid.x, grid.y, shared_size, threads.x * threads.y, nb_split);
if (verbose) fprintf(stderr, "INFO: impl 'conv_patch' failed (%s), trying next implementation\n",
cudaGetErrorString(sts));
}
}
......@@ -220,27 +220,29 @@ CudaNdarray_conv_valid(const CudaNdarray *img, const CudaNdarray * kern,
cudaError_t sts = cudaGetLastError();
if (cudaSuccess == sts)
{
if (verbose>1)
printf("threads.x=%i, threads.y=%i, grid.x=%i, grid.y=%i, shared_size=%i, nb_threads=%i,"
if (verbose>1)
fprintf(stderr,
"threads.x=%i, threads.y=%i, grid.x=%i, grid.y=%i, shared_size=%i, nb_threads=%i,"
" kern_flipped=true, accumulate=false, kern_width=%i, img_c_contiguous_2d=%i,"
" kern_c_contiguous_2d=%i, nb_split=%i, preload_full_kernel=%i\n",
threads.x, threads.y, grid.x, grid.y, shared_size, threads.x * threads.y,
THEANO_KERN_WID, img_contiguous_2d, kern_contiguous_2d,
nb_split, preload_full_kernel);
if (verbose) printf("INFO: used 'conv_patch_stack' version with nb_split=%i and preload_full_kernel=%i\n",
if (verbose) fprintf(stderr,
"INFO: used 'conv_patch_stack' version with nb_split=%i and preload_full_kernel=%i\n",
nb_split,preload_full_kernel);
work_complete = true;
}
else
{
if (verbose)
printf("threads.x=%i, threads.y=%i, grid.x=%i, grid.y=%i, shared_size=%i, nb_threads=%i,"
if (verbose)
fprintf(stderr, "threads.x=%i, threads.y=%i, grid.x=%i, grid.y=%i, shared_size=%i, nb_threads=%i,"
" kern_flipped=true, accumulate=false, kern_width=%i, img_c_contiguous_2d=%i,"
" kern_c_contiguous_2d=%i, nb_split=%i, preload_full_kernel=%i\n",
threads.x, threads.y, grid.x, grid.y, shared_size, threads.x * threads.y,
THEANO_KERN_WID, img_contiguous_2d, kern_contiguous_2d,
nb_split, preload_full_kernel);
if (verbose) printf("INFO: impl 'conv_patch_stack' failed (%s), trying next implementation\n",
if (verbose) fprintf(stderr, "INFO: impl 'conv_patch_stack' failed (%s), trying next implementation\n",
cudaGetErrorString(sts));
}
}
......@@ -280,12 +282,12 @@ CudaNdarray_conv_valid(const CudaNdarray *img, const CudaNdarray * kern,
if (cudaSuccess == sts)
{
work_complete = true;
if (verbose) printf("INFO: used 'conv_rows' version\n");
if (verbose) fprintf(stderr, "INFO: used 'conv_rows' version\n");
}
else
{
if (verbose) printf("threads.x=%i, threads.y=%i, grid.x=%i, grid.y=%i, shared_size=%i, nb_threads=%i\n", threads.x, threads.y, grid.x, grid.y, shared_size, threads.x * threads.y);
if (verbose) printf("INFO: impl 'conv_rows' failed (%s), trying next implementation\n",
if (verbose) fprintf(stderr, "threads.x=%i, threads.y=%i, grid.x=%i, grid.y=%i, shared_size=%i, nb_threads=%i\n", threads.x, threads.y, grid.x, grid.y, shared_size, threads.x * threads.y);
if (verbose) fprintf(stderr, "INFO: impl 'conv_rows' failed (%s), trying next implementation\n",
cudaGetErrorString(sts));
}
}
......@@ -335,13 +337,13 @@ CudaNdarray_conv_valid(const CudaNdarray *img, const CudaNdarray * kern,
if (cudaSuccess == sts)
{
work_complete = true;
if (verbose>1) printf("threads.x=%i, threads.y=%i, grid.x=%i, grid.y=%i, shared_size=%i, nb_threads=%i\n", threads.x, threads.y, grid.x, grid.y, shared_size, threads.x * threads.y);
if (verbose) printf("INFO: used 'conv_rows_stack' version\n");
if (verbose>1) fprintf(stderr, "threads.x=%i, threads.y=%i, grid.x=%i, grid.y=%i, shared_size=%i, nb_threads=%i\n", threads.x, threads.y, grid.x, grid.y, shared_size, threads.x * threads.y);
if (verbose) fprintf(stderr, "INFO: used 'conv_rows_stack' version\n");
}
else
{
if (verbose) printf("threads.x=%i, threads.y=%i, grid.x=%i, grid.y=%i, shared_size=%i, nb_threads=%i\n", threads.x, threads.y, grid.x, grid.y, shared_size, threads.x * threads.y);
if (verbose) printf("INFO: impl 'conv_rows_stack' failed (%s), trying next implementation\n",
if (verbose) fprintf(stderr, "threads.x=%i, threads.y=%i, grid.x=%i, grid.y=%i, shared_size=%i, nb_threads=%i\n", threads.x, threads.y, grid.x, grid.y, shared_size, threads.x * threads.y);
if (verbose) fprintf(stderr, "INFO: impl 'conv_rows_stack' failed (%s), trying next implementation\n",
cudaGetErrorString(sts));
}
}
......@@ -410,15 +412,15 @@ CudaNdarray_conv_valid(const CudaNdarray *img, const CudaNdarray * kern,
if (cudaSuccess == sts)
{
work_complete = true;
if (verbose>1) printf("threads.x=%i, threads.y=%i, grid.x=%i, grid.y=%i, shared_size=%i, nb_threads=%i\n",
if (verbose>1) fprintf(stderr, "threads.x=%i, threads.y=%i, grid.x=%i, grid.y=%i, shared_size=%i, nb_threads=%i\n",
threads.x, threads.y, grid.x, grid.y, shared_size, threads.x * threads.y);
if (verbose) printf("INFO: used 'conv_rows_stack2' version %s with %d row(s).\n",(version==9?"'load full kernel'":"'load 1 kern row at a time'"),nb_row);
if (verbose) fprintf(stderr, "INFO: used 'conv_rows_stack2' version %s with %d row(s).\n",(version==9?"'load full kernel'":"'load 1 kern row at a time'"),nb_row);
}
else
{
if (verbose) printf("threads.x=%i, threads.y=%i, grid.x=%i, grid.y=%i, shared_size=%i, nb_threads=%i version=%d\n",
if (verbose) fprintf(stderr, "threads.x=%i, threads.y=%i, grid.x=%i, grid.y=%i, shared_size=%i, nb_threads=%i version=%d\n",
threads.x, threads.y, grid.x, grid.y, shared_size, threads.x * threads.y,(version==9?2:3));
if (verbose) printf("INFO: impl 'conv_rows_stack2' failed (%s), trying next implementation\n",
if (verbose) fprintf(stderr, "INFO: impl 'conv_rows_stack2' failed (%s), trying next implementation\n",
cudaGetErrorString(sts));
}
}
......@@ -589,12 +591,12 @@ CudaNdarray_conv_valid(const CudaNdarray *img, const CudaNdarray * kern,
if (cudaSuccess == sts)
{
work_complete = true;
if (verbose) printf("INFO: used 'conv_valid_row_reduce' version\n");
if (verbose) fprintf(stderr, "INFO: used 'conv_valid_row_reduce' version\n");
}
else
{
if (verbose) printf("threads.x=%i, threads.y=%i, grid.x=%i, shared_size=%i, nb_threads=%i\n", n_threads.x, n_threads.y, n_blocks, n_reduce_buf, n_threads.x * n_threads.y);
if (verbose) printf("INFO: impl 'conv_valid_row_reduce' failed (%s), trying next implementation\n",
if (verbose) fprintf(stderr, "threads.x=%i, threads.y=%i, grid.x=%i, shared_size=%i, nb_threads=%i\n", n_threads.x, n_threads.y, n_blocks, n_reduce_buf, n_threads.x * n_threads.y);
if (verbose) fprintf(stderr, "INFO: impl 'conv_valid_row_reduce' failed (%s), trying next implementation\n",
cudaGetErrorString(sts));
}
}
......@@ -604,23 +606,23 @@ CudaNdarray_conv_valid(const CudaNdarray *img, const CudaNdarray * kern,
int outsize = CudaNdarray_SIZE(out);
int n_blocks = std::min(outsize, NUM_VECTOR_OP_BLOCKS);
int n_threads = std::min(ceil_intdiv(outsize, n_blocks), NUM_VECTOR_OP_THREADS_PER_BLOCK);
if (0)
if (1)
{
if (verbose) printf("INFO: launching conv_reference_valid\n");
if (verbose) printf(" img : %i %i %i %i %p %i %i %i %i\n",
if (verbose) fprintf(stderr, "INFO: launching conv_reference_valid\n");
if (verbose) fprintf(stderr, " img : %i %i %i %i %p %i %i %i %i\n",
nbatch, CudaNdarray_HOST_DIMS(img)[1], img_len, img_wid,
img->devdata,
CudaNdarray_HOST_STRIDES(img)[0], CudaNdarray_HOST_STRIDES(img)[1], CudaNdarray_HOST_STRIDES(img)[2], CudaNdarray_HOST_STRIDES(img)[3]);
if (verbose) printf(" kern: %i %i %i %i %p %i %i %i %i\n",
if (verbose) fprintf(stderr, " kern: %i %i %i %i %p %i %i %i %i\n",
nkern, nstack, kern_len, kern_wid,
kern->devdata,
CudaNdarray_HOST_STRIDES(kern)[0], CudaNdarray_HOST_STRIDES(kern)[1], CudaNdarray_HOST_STRIDES(kern)[2], CudaNdarray_HOST_STRIDES(kern)[3]
);
if (verbose) printf(" out : %i %i %i %i %p %i %i %i %i\n",
if (verbose) fprintf(stderr, " out : %i %i %i %i %p %i %i %i %i\n",
CudaNdarray_HOST_DIMS(out)[0], CudaNdarray_HOST_DIMS(out)[1], out_len, out_wid,
out->devdata,
CudaNdarray_HOST_STRIDES(out)[0], CudaNdarray_HOST_STRIDES(out)[1], CudaNdarray_HOST_STRIDES(out)[2], CudaNdarray_HOST_STRIDES(out)[3]);
if (verbose) printf(" launch params: %i %i %i\n", outsize, n_blocks, n_threads);
if (verbose) fprintf(stderr, " launch params: %i %i %i\n", outsize, n_blocks, n_threads);
}
conv_reference_valid<<<n_blocks, n_threads>>>( nbatch, nkern, CudaNdarray_HOST_DIMS(img)[1],
img_len, img_wid,
......@@ -636,7 +638,7 @@ CudaNdarray_conv_valid(const CudaNdarray *img, const CudaNdarray * kern,
if (cudaSuccess == sts)
{
work_complete = true;
if (verbose) printf("INFO: used 'conv_reference_valid' version\n");
if (verbose) fprintf(stderr, "INFO: used 'conv_reference_valid' version\n");
}
else
{
......@@ -770,7 +772,7 @@ CudaNdarray_conv_full(const CudaNdarray *img, const CudaNdarray * kern, CudaNdar
if(kern_len==1 && version==5){
//version 5 don't support kern_len==1 as 1%0 return -1.
version=-1;
if(verbose)printf("WARNING:conv full: Asking version 5 with kern_len==1. Combination not supported!\n");
if(verbose)fprintf(stderr, "WARNING:conv full: Asking version 5 with kern_len==1. Combination not supported!\n");
}
if(img_size_padded_byte+kern_size_byte>shared_avail) version=5;
......@@ -835,14 +837,14 @@ CudaNdarray_conv_full(const CudaNdarray *img, const CudaNdarray * kern, CudaNdar
cudaError_t sts = cudaGetLastError();
if (cudaSuccess == sts)
{
if (verbose>1) printf("threads.x=%i, threads.y=%i, threads.z=%i, grid.x=%i, grid.y=%i,shared_size=%i, nb_threads=%i, out_len=%i, nb_split=%i, version=%i\n", threads.x, threads.y, threads.z, grid.x, grid.y, shared_size, threads.x * threads.y * threads.z, out_len, nb_split, version);
if (verbose) printf("INFO: used 'conv_full_patch_stack_padded' nb_split=%d low_mem=%s\n",nb_split,(version==5?"true":"false"));
if (verbose>1) fprintf(stderr, "threads.x=%i, threads.y=%i, threads.z=%i, grid.x=%i, grid.y=%i,shared_size=%i, nb_threads=%i, out_len=%i, nb_split=%i, version=%i\n", threads.x, threads.y, threads.z, grid.x, grid.y, shared_size, threads.x * threads.y * threads.z, out_len, nb_split, version);
if (verbose) fprintf(stderr, "INFO: used 'conv_full_patch_stack_padded' nb_split=%d low_mem=%s\n",nb_split,(version==5?"true":"false"));
work_complete = true;
}
else
{
if (verbose) printf("threads.x=%i, threads.y=%i, threads.z=%i, grid.x=%i, grid.y=%i,shared_size=%i, nb_threads=%i, out_len=%i, nb_split=%i, version=%i\n", threads.x, threads.y, threads.z, grid.x, grid.y, shared_size, threads.x * threads.y * threads.z, out_len, nb_split, version);
if (verbose) printf("INFO: impl 'conv_full_patch_stack_padded' %s %s failed (%s), trying next implementation\n",
if (verbose) fprintf(stderr, "threads.x=%i, threads.y=%i, threads.z=%i, grid.x=%i, grid.y=%i,shared_size=%i, nb_threads=%i, out_len=%i, nb_split=%i, version=%i\n", threads.x, threads.y, threads.z, grid.x, grid.y, shared_size, threads.x * threads.y * threads.z, out_len, nb_split, version);
if (verbose) fprintf(stderr, "INFO: impl 'conv_full_patch_stack_padded' %s %s failed (%s), trying next implementation\n",
version==3?"no split": "split",(version==5?"low_mem":"not_low_mem"),
cudaGetErrorString(sts));
}
......@@ -872,13 +874,13 @@ CudaNdarray_conv_full(const CudaNdarray *img, const CudaNdarray * kern, CudaNdar
cudaError_t sts = cudaGetLastError();
if (cudaSuccess == sts)
{
if (verbose) printf("INFO: used 'conv_full_patch' version\n");
if (verbose) fprintf(stderr, "INFO: used 'conv_full_patch' version\n");
work_complete = true;
}
else
{
if (verbose) printf("threads.x=%i, threads.y=%i, grid.x=%i, grid.y=%i, shared_size=%i, nb_threads=%i\n", threads.x, threads.y, grid.x, grid.y, shared_size, threads.x * threads.y);
if (verbose) printf("INFO: impl 'conv_full_patch' failed (%s), trying next implementation\n",
if (verbose) fprintf(stderr, "threads.x=%i, threads.y=%i, grid.x=%i, grid.y=%i, shared_size=%i, nb_threads=%i\n", threads.x, threads.y, grid.x, grid.y, shared_size, threads.x * threads.y);
if (verbose) fprintf(stderr, "INFO: impl 'conv_full_patch' failed (%s), trying next implementation\n",
cudaGetErrorString(sts));
}
}
......@@ -922,13 +924,13 @@ CudaNdarray_conv_full(const CudaNdarray *img, const CudaNdarray * kern, CudaNdar
cudaError_t sts = cudaGetLastError();
if (cudaSuccess == sts)
{
if (verbose) printf("INFO: used 'conv_full_load_everything' version\n");
if (verbose) fprintf(stderr, "INFO: used 'conv_full_load_everything' version\n");
work_complete = true;
}
else
{
if (verbose) printf("threads.x=%i, threads.y=%i, grid.x=%i, grid.y=%i, shared_size=%i, nb_threads=%i\n", threads.x, threads.y, grid.x, grid.y, shared_size, threads.x * threads.y);
if (verbose) printf("INFO: impl 'conv_full_load_everything' failed (%s), trying next implementation\n",
if (verbose) fprintf(stderr, "threads.x=%i, threads.y=%i, grid.x=%i, grid.y=%i, shared_size=%i, nb_threads=%i\n", threads.x, threads.y, grid.x, grid.y, shared_size, threads.x * threads.y);
if (verbose) fprintf(stderr, "INFO: impl 'conv_full_load_everything' failed (%s), trying next implementation\n",
cudaGetErrorString(sts));
}
}
......@@ -968,41 +970,41 @@ CudaNdarray_conv_full(const CudaNdarray *img, const CudaNdarray * kern, CudaNdar
cudaError_t sts = cudaGetLastError();
if (cudaSuccess == sts)
{
if (verbose) printf("INFO: used 'conv_full_patch_stack' version\n");
if (verbose) fprintf(stderr, "INFO: used 'conv_full_patch_stack' version\n");
work_complete = true;
}
else
{
if (verbose) printf("threads.x=%i, threads.y=%i, grid.x=%i, grid.y=%i, shared_size=%i, nb_threads=%i\n", threads.x, threads.y, grid.x, grid.y, shared_size, threads.x * threads.y);
if (verbose) printf("INFO: impl 'conv_full_patch_stack' failed (%s), trying next implementation\n",
if (verbose) fprintf(stderr, "threads.x=%i, threads.y=%i, grid.x=%i, grid.y=%i, shared_size=%i, nb_threads=%i\n", threads.x, threads.y, grid.x, grid.y, shared_size, threads.x * threads.y);
if (verbose) fprintf(stderr, "INFO: impl 'conv_full_patch_stack' failed (%s), trying next implementation\n",
cudaGetErrorString(sts));
}
}
if (1 && !work_complete) //conv_reference_full
{
if(verbose>1)printf("INFO: will start conv_reference_full\n");
if(verbose>1) fprintf(stderr, "INFO: will start conv_reference_full\n");
int outsize = CudaNdarray_SIZE(out);
int n_blocks = std::min(outsize, NUM_VECTOR_OP_BLOCKS);
int n_threads = std::min(ceil_intdiv(outsize, n_blocks), NUM_VECTOR_OP_THREADS_PER_BLOCK);
if (0)
{
if (verbose) printf("INFO: launching conv_reference_valid\n");
if (verbose) printf(" img : %i %i %i %i %p %i %i %i %i\n",
if (verbose) fprintf(stderr, "INFO: launching conv_reference_valid\n");
if (verbose) fprintf(stderr, " img : %i %i %i %i %p %i %i %i %i\n",
CudaNdarray_HOST_DIMS(img)[0], CudaNdarray_HOST_DIMS(img)[1], CudaNdarray_HOST_DIMS(img)[2], CudaNdarray_HOST_DIMS(img)[3],
img->devdata,
CudaNdarray_HOST_STRIDES(img)[0], CudaNdarray_HOST_STRIDES(img)[1], CudaNdarray_HOST_STRIDES(img)[2], CudaNdarray_HOST_STRIDES(img)[3]);
if (verbose) printf(" kern: %i %i %i %i %p %i %i %i %i\n",
if (verbose) fprintf(stderr, " kern: %i %i %i %i %p %i %i %i %i\n",
CudaNdarray_HOST_DIMS(kern)[0], CudaNdarray_HOST_DIMS(kern)[1], CudaNdarray_HOST_DIMS(kern)[2], CudaNdarray_HOST_DIMS(kern)[3],
kern->devdata,
CudaNdarray_HOST_STRIDES(kern)[0], CudaNdarray_HOST_STRIDES(kern)[1], CudaNdarray_HOST_STRIDES(kern)[2], CudaNdarray_HOST_STRIDES(kern)[3]
);
if (verbose) printf(" out : %i %i %i %i %p %i %i %i %i\n",
if (verbose) fprintf(stderr, " out : %i %i %i %i %p %i %i %i %i\n",
CudaNdarray_HOST_DIMS(out)[0], CudaNdarray_HOST_DIMS(out)[1], CudaNdarray_HOST_DIMS(out)[2], CudaNdarray_HOST_DIMS(out)[3],
out->devdata,
CudaNdarray_HOST_STRIDES(out)[0], CudaNdarray_HOST_STRIDES(out)[1], CudaNdarray_HOST_STRIDES(out)[2], CudaNdarray_HOST_STRIDES(out)[3]);
if (verbose) printf(" launch params: %i %i %i\n", outsize, n_blocks, n_threads);
if (verbose) printf(" subsample params: %i %i\n", subsample_rows, subsample_cols);
if (verbose) fprintf(stderr, " launch params: %i %i %i\n", outsize, n_blocks, n_threads);
if (verbose) fprintf(stderr, " subsample params: %i %i\n", subsample_rows, subsample_cols);
}
conv_reference_full<<<n_blocks, n_threads>>>(CudaNdarray_HOST_DIMS(img)[0], CudaNdarray_HOST_DIMS(kern)[0], CudaNdarray_HOST_DIMS(img)[1],
CudaNdarray_HOST_DIMS(img)[2], CudaNdarray_HOST_DIMS(img)[3],
......@@ -1017,15 +1019,15 @@ CudaNdarray_conv_full(const CudaNdarray *img, const CudaNdarray * kern, CudaNdar
cudaError_t sts = cudaGetLastError();
if (cudaSuccess == sts)
{
if (verbose) printf("INFO: used 'conv_reference_full' version ishp(%d, %d) kshp(%d, %d) oshp(%d, %d) nbatch=%d nkern=%d nstack=%d subsample=%d\n",
if (verbose) fprintf(stderr, "INFO: used 'conv_reference_full' version ishp(%d, %d) kshp(%d, %d) oshp(%d, %d) nbatch=%d nkern=%d nstack=%d subsample=%d\n",
img_len,img_wid, kern_len, kern_wid,
out_len, out_wid, nbatch, nkern, nstack, subsample);
work_complete = true;
}
else
{
if (verbose) printf("threads.x=%i, threads.y=%i, grid.x=%i, grid.y=%i, shared_size=%i, nb_threads=%i\n", n_threads, 1, n_blocks, 1, 0, n_threads);
if (verbose) printf("INFO: impl 'conv_reference_full' failed (%s), trying next implementation\n",
if (verbose) fprintf(stderr, "threads.x=%i, threads.y=%i, grid.x=%i, grid.y=%i, shared_size=%i, nb_threads=%i\n", n_threads, 1, n_blocks, 1, 0, n_threads);
if (verbose) fprintf(stderr, "INFO: impl 'conv_reference_full' failed (%s), trying next implementation\n",
cudaGetErrorString(sts));
PyErr_Format(PyExc_RuntimeError, "ERROR: all implementations failed for CudaNdarray_conv_full! (%s)",
cudaGetErrorString(sts));
......
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