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Support PyTorch-0.4.1 #17

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3 changes: 2 additions & 1 deletion models/ops/depthavgpooling/build.py
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Original file line number Diff line number Diff line change
Expand Up @@ -28,7 +28,8 @@
define_macros=defines,
relative_to=__file__,
with_cuda=with_cuda,
extra_objects=extra_objects
extra_objects=extra_objects,
extra_compile_args=["-std=c++11"]
)

if __name__ == '__main__':
Expand Down
74 changes: 37 additions & 37 deletions models/ops/depthavgpooling/src/depthavgpooling_cuda.c
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Original file line number Diff line number Diff line change
Expand Up @@ -14,7 +14,7 @@ void shape_check(THCState *state,
THArgCheck(dW > 0 && dH > 0, 8,
"stride should be greater than zero, but got dH: %d dW: %d", dH, dW);

int ndim = input->nDimension;
int ndim = THCudaTensor_nDimension(state, input);
int dimf = 0;
int dimh = 1;
int dimw = 2;
Expand All @@ -36,16 +36,16 @@ void shape_check(THCState *state,
// "padW = %d, padH = %d, kW = %d, kH = %d",
// padW, padH, kW, kH);

long nInputPlane = input->size[dimh-1];
long nInputRows = input->size[dimh];
long nInputCols = input->size[dimw];
long nInputPlane = THCudaTensor_size(state, input, dimh-1);
long nInputRows = THCudaTensor_size(state, input, dimh);
long nInputCols = THCudaTensor_size(state, input, dimw);
long nOutputRows, nOutputCols;
long nOutputPlane = nInputPlane;


/////////check depth map shape /////////

int ndim_depth = input_depth->nDimension;
int ndim_depth = THCudaTensor_nDimension(state, input_depth);
int dimf_depth = 0;
int dimh_depth = 1;
int dimw_depth = 2;
Expand All @@ -59,25 +59,25 @@ void shape_check(THCState *state,
THArgCheck(ndim_depth == 3 || ndim_depth == 4, 3,
"3D input depth tensor expected but got: %s", ndim);

long inputHeight_depth = input_depth->size[dimh_depth];
long inputWidth_depth = input_depth->size[dimw_depth];
long inputHeight_depth = THCudaTensor_size(state, input_depth, dimh_depth);
long inputWidth_depth = THCudaTensor_size(state, input_depth, dimw_depth);

THArgCheck(input_depth->size[1] == 1, 3,
THArgCheck(THCudaTensor_size(state, input_depth, 1) == 1, 3,
"input depth should have only 1 channel",
nInputPlane, input->size[1]);
nInputPlane, THCudaTensor_size(state, input, 1));

THArgCheck((nInputRows == inputHeight_depth && nInputCols == inputWidth_depth), 3,
"input image and input depth should be the same size, but got: weightcount(%d,%d), depth(%d,%d)",
nInputRows, inputHeight_depth, nInputCols, inputWidth_depth);

if (depthweightcount!=NULL){
THArgCheck(depthweightcount->size[1] == 1, 3,
THArgCheck(THCudaTensor_size(state, depthweightcount, 1) == 1, 3,
"input depth should have only 1 channel",
nInputPlane, input->size[1]);
nInputPlane, THCudaTensor_size(state, input, 1));

THArgCheck((inputHeight_depth == depthweightcount->size[2] && inputWidth_depth == depthweightcount->size[3]), 3,
THArgCheck((inputHeight_depth == THCudaTensor_size(state, depthweightcount, 2) && inputWidth_depth == THCudaTensor_size(state, depthweightcount, 3)), 3,
"input depth and input depthweightcount should be the same size, but got: weightcount(%d,%d), depth(%d,%d)",
depthweightcount->size[dimh_depth], depthweightcount->size[dimw_depth], inputHeight_depth, inputWidth_depth);
THCudaTensor_size(state, depthweightcount, dimh_depth), THCudaTensor_size(state, depthweightcount, dimw_depth), inputHeight_depth, inputWidth_depth);
}
//////////////////////////////////////////

Expand All @@ -103,14 +103,14 @@ void shape_check(THCState *state,
// THCUNN_check_dim_size(state, gradOutput, ndim, dimh, nOutputRows);
// THCUNN_check_dim_size(state, gradOutput, ndim, dimw, nOutputCols);

THArgCheck(gradOutput->size[dimf] == nOutputPlane, 4,
THArgCheck(THCudaTensor_size(state, gradOutput, dimf) == nOutputPlane, 4,
"invalid number of gradOutput planes, expected: %d, but got: %d",
nOutputPlane, gradOutput->size[dimf]);
nOutputPlane, THCudaTensor_size(state, gradOutput, dimf));

THArgCheck((gradOutput->size[dimh] == nOutputRows &&
gradOutput->size[dimw] == nOutputCols),
THArgCheck((THCudaTensor_size(state, gradOutput, dimh) == nOutputRows &&
THCudaTensor_size(state, gradOutput, dimw) == nOutputCols),
4, "invalid size of gradOutput, expected height: %d width: %d , but got height: %d width: %d", nOutputRows, nOutputCols,
gradOutput->size[dimh], gradOutput->size[dimw]);
THCudaTensor_size(state, gradOutput, dimh), THCudaTensor_size(state, gradOutput, dimw));
}
}

Expand All @@ -133,21 +133,21 @@ int depthavgpooling_forward_cuda(THCudaTensor *input,
long nInputCols, nInputRows, nInputPlane, batchSize;
long nOutputCols, nOutputRows;

if (input->nDimension == 3) {
nInputCols = input->size[2];
nInputRows = input->size[1];
nInputPlane = input->size[0];
if (THCudaTensor_nDimension(state, input) == 3) {
nInputCols = THCudaTensor_size(state, input, 2);
nInputRows = THCudaTensor_size(state, input, 1);
nInputPlane = THCudaTensor_size(state, input, 0);
batchSize = 1;
batch = 0;
THCudaTensor_resize4d(state, input, 1, input->size[0], input->size[1], input->size[2]);
THCudaTensor_resize4d(state, input_depth, 1, input_depth->size[0], input_depth->size[1], input_depth->size[2]);
THCudaTensor_resize4d(state, input, 1, THCudaTensor_size(state, input, 0), THCudaTensor_size(state, input, 1), THCudaTensor_size(state, input, 2));
THCudaTensor_resize4d(state, input_depth, 1, THCudaTensor_size(state, input_depth, 0), THCudaTensor_size(state, input_depth, 1), THCudaTensor_size(state, input_depth, 2));
}
else
{
nInputCols = input->size[3];
nInputRows = input->size[2];
nInputPlane = input->size[1];
batchSize = input->size[0];
nInputCols = THCudaTensor_size(state, input, 3);
nInputRows = THCudaTensor_size(state, input, 2);
nInputPlane = THCudaTensor_size(state, input, 1);
batchSize = THCudaTensor_size(state, input, 0);
}

nOutputCols = floor(float(nInputCols - kW + 2*padW) / float(dW)) + 1;
Expand Down Expand Up @@ -237,22 +237,22 @@ int depthavgpooling_backward_input_cuda(
int dimRow = 1;

int batch = 1;
if (input->nDimension == 3) {
nInputPlane = input->size[0];
if (THCudaTensor_nDimension(state, input) == 3) {
nInputPlane = THCudaTensor_size(state, input, 0);
batchSize = 1;
batch = 0;
THCudaTensor_resize4d(state, input, 1, input->size[0], input->size[1],input->size[2]);
THCudaTensor_resize4d(state, gradOutput, 1, gradOutput->size[0], gradOutput->size[1], gradOutput->size[2]);
THCudaTensor_resize4d(state, input, 1, THCudaTensor_size(state, input, 0), THCudaTensor_size(state, input, 1),THCudaTensor_size(state, input, 2));
THCudaTensor_resize4d(state, gradOutput, 1, THCudaTensor_size(state, gradOutput, 0), THCudaTensor_size(state, gradOutput, 1), THCudaTensor_size(state, gradOutput, 2));
}
else
{
dimCol = 3;
dimRow = 2;
nInputPlane = input->size[1];
batchSize = input->size[0];
nInputPlane = THCudaTensor_size(state, input, 1);
batchSize = THCudaTensor_size(state, input, 0);
}
nInputCols = input->size[dimCol];
nInputRows = input->size[dimRow];
nInputCols = THCudaTensor_size(state, input, dimCol);
nInputRows = THCudaTensor_size(state, input, dimRow);

nOutputCols = floor(float(nInputCols - kW + 2*padW) / float(dW)) + 1;
nOutputRows = floor(float(nInputRows - kH + 2*padH) / float(dH)) + 1;
Expand All @@ -269,7 +269,7 @@ int depthavgpooling_backward_input_cuda(
// THCUNN_check_dim_size(state, gradOutput, input->nDimension, dimRow, nOutputRows);
// THCUNN_check_dim_size(state, gradOutput, input->nDimension, dimCol, nOutputCols);

THArgCheck((input_depth->size[0] == batchSize), 3, "invalid batch size of input depth");
THArgCheck((THCudaTensor_size(state, input_depth, 0) == batchSize), 3, "invalid batch size of input depth");
THCudaTensor_resizeAs(state, gradInput, input);

// float* input_depth_data = THCudaTensor_data(state, input_depth);
Expand Down
3 changes: 2 additions & 1 deletion models/ops/depthconv/build.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -28,7 +28,8 @@
define_macros=defines,
relative_to=__file__,
with_cuda=with_cuda,
extra_objects=extra_objects
extra_objects=extra_objects,
extra_compile_args=["-std=c++11"]
)

if __name__ == '__main__':
Expand Down
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