Skip to content

P
pytensor
提交 e9ea0187 authored 作者: Frederic's avatar Frederic
浏览文件
操作

Use macro (numpy and cuda backend)

上级 df512c7f
隐藏空白字符变更
内嵌 并排
正在显示 包含 37 行增加 和 37 行删除
theano/sandbox/cuda/GpuConv3D.py
浏览文件 @ e9ea0187
......@@ -50,33 +50,33 @@ class GpuConv3D(GpuOp):
//printf("\t\t\t\tConv3DGPU c code\\n");
//Check dimensionality of inputs
if (%(W)s->nd != 5)
if (CudaNdarray_NDIM(%(W)s) != 5)
{
PyErr_Format(PyExc_ValueError, "GpuConv3D: W must be a 5 dimensional CudaNdarray");
%(fail)s
}
if (%(V)s->nd != 5)
if (CudaNdarray_NDIM(%(V)s) != 5)
{
PyErr_Format(PyExc_ValueError, "GpuConv3D: V must be a 5 dimensional CudaNdarray");
%(fail)s
}
if (%(b)s->nd != 1)
if (CudaNdarray_NDIM(%(b)s) != 1)
{
PyErr_Format(PyExc_ValueError, "GpuConv3D: b must be a vector CudaNdarray");
%(fail)s
}
if (%(d)s->nd != 1)
if (CudaNdarray_NDIM(%(d)s) != 1)
{
PyErr_Format(PyExc_ValueError, "GpuConv3D: d must be a vector CudaNdarray");
%(fail)s
}
if (%(d)s->dimensions[0] != 3)
if (PyArray_DIMS(%(d)s)[0] != 3)
{
PyErr_Format(PyExc_ValueError, "GpuConv3D: 3 stride length arguments expected (row, col, time) but %%li were given", %(d)s->dimensions[0]);
PyErr_Format(PyExc_ValueError, "GpuConv3D: 3 stride length arguments expected (row, col, time) but %%li were given", PyArray_DIMS(%(d)s)[0]);
%(fail)s
}
......
theano/sandbox/cuda/GpuConvGrad3D.py
浏览文件 @ e9ea0187
......@@ -79,33 +79,33 @@ class GpuConvGrad3D(GpuOp):
//printf("\t\t\t\tGpuConvGrad3DW c code\\n");
//Check dimensionality of inputs
if (%(dCdH)s->nd != 5)
if (CudaNdarray_NDIM(%(dCdH)s) != 5)
{
PyErr_Format(PyExc_ValueError, "GpuConvGrad3D: dCdH must be a 5-d CudaNdArray");
%(fail)s
}
if (%(V)s->nd != 5)
if (CudaNdarray_NDIM(%(V)s) != 5)
{
PyErr_Format(PyExc_ValueError, "GpuConvGrad3D: V must be a 5-d CudaNdArray");
%(fail)s
}
if (%(WShape)s->nd != 1)
if (CudaNdarray_NDIM(%(WShape)s) != 1)
{
PyErr_Format(PyExc_ValueError, "GpuConvGrad3D: WShape must be a 1-d CudaNdArray");
%(fail)s
}
if (%(d)s->nd != 1)
if (PyArray_NDIM(%(d)s) != 1)
{
PyErr_Format(PyExc_ValueError, "GpuConvGrad3D: d must be a 1-d CudaNdArray");
%(fail)s
}
if (%(d)s->dimensions[0] != 3)
if (PyArray_DIMS(%(d)s)[0] != 3)
{
PyErr_Format(PyExc_ValueError, "GpuConvGrad3D: 3 stride lengths arguments expected(for row, col, and time) but %%li were given", %(d)s->dimensions[0]);
PyErr_Format(PyExc_ValueError, "GpuConvGrad3D: 3 stride lengths arguments expected(for row, col, and time) but %%li were given", PyArray_DIMS(%(d)s)[0]);
%(fail)s
}
......@@ -113,7 +113,7 @@ class GpuConvGrad3D(GpuOp):
//Read and check sizes of inputs
const int batchSize = CudaNdarray_HOST_DIMS(%(V)s)[0];
if (%(WShape)s->dimensions[0] != 5)
if (PyArray_DIMS(%(WShape)s)[0] != 5)
{
PyErr_Format(PyExc_ValueError, "GpuConvGrad3D: WShape must specify a 5-d shape");
%(fail)s
......
theano/sandbox/cuda/GpuConvTransp3D.py
浏览文件 @ e9ea0187
......@@ -61,34 +61,34 @@ class GpuConvTransp3D(GpuOp):
//printf("\t\t\t\tGpuConvTransp c code\\n");
//Check dimensionality of inputs
if (%(H)s->nd != 5)
if (CudaNdarray_NDIM(%(H)s) != 5)
{
PyErr_Format(PyExc_ValueError, "GpuConvTransp3D: H must be a 5-D tensor but it is %%i-D",%(H)s->nd);
PyErr_Format(PyExc_ValueError, "GpuConvTransp3D: H must be a 5-D tensor but it is %%i-D", CudaNdarray_NDIM(%(H)s));
%(fail)s
}
if (%(W)s->nd != 5)
if (CudaNdarray_NDIM(%(W)s) != 5)
{
PyErr_Format(PyExc_ValueError, "GpuConvTransp3D: W must be a 5-D tensor");
%(fail)s
}
if (%(b)s->nd != 1)
if (CudaNdarray_NDIM(%(b)s) != 1)
{
PyErr_Format(PyExc_ValueError, "GpuConvTransp3D: b must be a vector");
%(fail)s
}
if (%(d)s->nd != 1)
if (PyArray_NDIM(%(d)s) != 1)
{
PyErr_Format(PyExc_ValueError, "GpuConvTransp3D: d must be a vector");
%(fail)s
}
//Read and check stride arguments
if (%(d)s->dimensions[0] != 3)
if (PyArray_DIMS(%(d)s)[0] != 3)
{
PyErr_Format(PyExc_ValueError,"GpuConvTransp3D: 3 stride length arguments expected (for row, col, and time) but %%li were given", %(d)s->dimensions[0]);
PyErr_Format(PyExc_ValueError,"GpuConvTransp3D: 3 stride length arguments expected (for row, col, and time) but %%li were given", PyArray_DIMS(%(d)s)[0]);
%(fail)s
}
{ // for fail
......@@ -138,13 +138,13 @@ class GpuConvTransp3D(GpuOp):
if (%(RShape)s)
{
if (%(RShape)s->nd != 1)
if (PyArray_NDIM(%(RShape)s) != 1)
{
PyErr_Format(PyExc_ValueError, "RShape must be a vector");
%(fail)s
}
if (%(RShape)s->dimensions[0] != 3)
if (PyArray_DIMS(%(RShape)s)[0] != 3)
{
PyErr_Format(PyExc_ValueError, "RShape must specify a 3D shape ( [height,width,duration] )");
%(fail)s
......@@ -189,7 +189,7 @@ class GpuConvTransp3D(GpuOp):
%(fail)s;
}
}
cudaMemset(%(R)s->devdata, 0, 4 * batchSize * inputChannels * videoHeight * videoWidth * videoDur);
cudaMemset(CudaNdarray_DEV_DATA(%(R)s), 0, 4 * batchSize * inputChannels * videoHeight * videoWidth * videoDur);
{ // for fail
......
theano/sandbox/cuda/nnet.py
浏览文件 @ e9ea0187
......@@ -95,17 +95,17 @@ class GpuCrossentropySoftmaxArgmax1HotWithBias(GpuOp):
fail = sub['fail']
sio = StringIO()
print >> sio, """
if (%(y_idx)s->nd != 1)
if (CudaNdarray_NDIM(%(y_idx)s) != 1)
{
PyErr_SetString(PyExc_ValueError, "y_idx not 1d tensor");
%(fail)s;
}
if (%(x)s->nd != 2)
if (CudaNdarray_NDIM(%(x)s) != 2)
{
PyErr_SetString(PyExc_ValueError, "x not 2d tensor");
%(fail)s;
}
if (%(b)s->nd != 1)
if (CudaNdarray_NDIM(%(b)s) != 1)
{
PyErr_SetString(PyExc_ValueError, "b not 1d tensor");
%(fail)s;
......@@ -247,9 +247,9 @@ class GpuCrossentropySoftmax1HotWithBiasDx(GpuOp):
dx, = out
fail = sub['fail']
return """
if ((%(dnll)s->nd != 1)
|| (%(sm)s->nd != 2)
|| (%(y_idx)s->nd != 1))
if ((CudaNdarray_NDIM(%(dnll)s) != 1)
|| (CudaNdarray_NDIM(%(sm)s) != 2)
|| (CudaNdarray_NDIM(%(y_idx)s) != 1))
{
PyErr_SetString(PyExc_ValueError, "rank error");
%(fail)s;
......@@ -391,7 +391,7 @@ class GpuSoftmax(GpuOp):
z, = out
fail = sub['fail']
return """
if (%(x)s->nd != 2)
if (CudaNdarray_NDIM(%(x)s) != 2)
{
PyErr_SetString(PyExc_ValueError, "rank error");
%(fail)s;
......@@ -556,12 +556,12 @@ class GpuSoftmaxWithBias(GpuOp):
z, = out
fail = sub['fail']
return """
if (%(x)s->nd != 2)
if (CudaNdarray_NDIM(%(x)s) != 2)
{
PyErr_SetString(PyExc_ValueError, "rank error input");
%(fail)s;
}
if (%(b)s->nd != 1)
if (CudaNdarray_NDIM(%(b)s) != 1)
{
PyErr_SetString(PyExc_ValueError, "rank error for the bias");
%(fail)s;
......
theano/sandbox/cuda/rng_curand.py
浏览文件 @ e9ea0187
......@@ -148,20 +148,20 @@ class CURAND_Base(GpuOp):
int n_elements = 1;
int must_alloc_sample = ((NULL == %(o_sample)s)
|| !CudaNdarray_Check(py_%(o_sample)s)
|| (%(o_sample)s->nd != %(ndim)s));
|| (CudaNdarray_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
}
if (%(size)s->dimensions[0] != %(ndim)s)
if (PyArray_DIMS(%(size)s)[0] != %(ndim)s)
{
PyErr_Format(PyExc_ValueError, "size must have length %%i (not %%i)",
%(ndim)s, %(size)s->dimensions[0]);
%(ndim)s, PyArray_DIMS(%(size)s)[0]);
%(fail)s
}
if (PyArray_DESCR(%(size)s)->type_num != NPY_INT32)
if (PyArray_TYPE(%(size)s) != NPY_INT32)
{
PyErr_SetString(PyExc_ValueError, "size must be int32");
%(fail)s
......
Markdown 格式
0% 或
您添加了 0 人 到此讨论。请谨慎行事。
请先完成此评论的编辑！
请 注册 或者 后发表评论