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Fix triu and tril for zero-strided inputs on gpu #4962

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Merged
soumith merged 1 commit into from
Jan 31, 2018
Merged

Fix triu and tril for zero-strided inputs on gpu #4962

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6 changes: 3 additions & 3 deletions aten/src/THC/THCTensorMathPairwise.cu
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Original file line number Diff line number Diff line change
Expand Up @@ -375,8 +375,8 @@ struct TensorTriOp {
TensorTriOp(T *start_, int64_t stride0_, int64_t stride1_, int64_t k_)
: start(start_), stride0(stride0_), stride1(stride1_), k(k_) {}

__device__ __forceinline__ int mask(T *in) {
ptrdiff_t n = in - start;
__device__ __forceinline__ int mask(T *out) {
ptrdiff_t n = out - start;
int64_t row, col;
if (stride0 > stride1)
{
Expand All @@ -393,7 +393,7 @@ struct TensorTriOp {
}

__device__ __forceinline__ void operator()(T* out, T* in) {
*out = mask(in) ? *in : ScalarConvert<int, T>::to(0);
*out = mask(out) ? *in : ScalarConvert<int, T>::to(0);
}

__device__ __forceinline__ void operator()(T* v) {
Expand Down
39 changes: 15 additions & 24 deletions aten/src/THC/generic/THCTensorMathPairwise.cu
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Original file line number Diff line number Diff line change
Expand Up @@ -193,31 +193,27 @@ void THCTensor_(tril)(THCState *state, THCTensor *self_, THCTensor *src_, int64_
THCAssertSameGPU(THCTensor_(checkGPU)(state, 2, self_, src_));
THArgCheck(src_->nDimension == 2, 1, "expected a matrix");

THCTensor *src = src_;
if (self_ == src_)
src = THCTensor_(newContiguous)(state, src_);
if (self_ != src_)
THCTensor_(resizeAs)(state, self_, src_);

int64_t stride0 = src->stride[0];
int64_t stride1 = src->stride[1];
real *start = THCTensor_(data)(state, src);
int64_t stride0 = self_->stride[0];
int64_t stride1 = self_->stride[1];
real *start = THCTensor_(data)(state, self_);

TensorTriOp<real, 0> op(start, stride0, stride1, k);

if (self_ == src_) {
if (!THC_pointwiseApply1(state, src, op)) {
if (!THC_pointwiseApply1(state, src_, op)) {
THArgCheck(false, 2, CUTORCH_DIM_WARNING);
}
} else {
THCTensor_(resizeAs)(state, self_, src);
THCTensor_(resizeAs)(state, self_, src_);

if (!THC_pointwiseApply2(state, self_, src, op)) {
if (!THC_pointwiseApply2(state, self_, src_, op)) {
THArgCheck(false, 2, CUTORCH_DIM_WARNING);
}
}

if (self_ == src_)
THCTensor_(freeCopyTo)(state, src, src_);

THCudaCheck(cudaGetLastError());
}

Expand All @@ -226,31 +222,26 @@ void THCTensor_(triu)(THCState *state, THCTensor *self_, THCTensor *src_, int64_
THCAssertSameGPU(THCTensor_(checkGPU)(state, 2, self_, src_));
THArgCheck(src_->nDimension == 2, 1, "expected a matrix");

THCTensor *src = src_;
if (self_ == src_)
src = THCTensor_(newContiguous)(state, src_);
if (self_ != src_)
THCTensor_(resizeAs)(state, self_, src_);

int64_t stride0 = src->stride[0];
int64_t stride1 = src->stride[1];
real *start = THCTensor_(data)(state, src);
int64_t stride0 = self_->stride[0];
int64_t stride1 = self_->stride[1];
real *start = THCTensor_(data)(state, self_);

TensorTriOp<real, 1> op(start, stride0, stride1, k);

if (self_ == src_) {
if (!THC_pointwiseApply1(state, src, op)) {
if (!THC_pointwiseApply1(state, src_, op)) {
THArgCheck(false, 2, CUTORCH_DIM_WARNING);
}
} else {
THCTensor_(resizeAs)(state, self_, src);

if (!THC_pointwiseApply2(state, self_, src, op)) {
if (!THC_pointwiseApply2(state, self_, src_, op)) {
THArgCheck(false, 2, CUTORCH_DIM_WARNING);
}
}

if (self_ == src_)
THCTensor_(freeCopyTo)(state, src, src_);

THCudaCheck(cudaGetLastError());
}

Expand Down
28 changes: 25 additions & 3 deletions test/test_cuda.py
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Original file line number Diff line number Diff line change
Expand Up @@ -97,6 +97,10 @@ def medium_2d(t):
return make_tensor(t, M, M)


def medium_2d_expanded(t):
return t(1).expand(M, M)


def medium_2d_scaled(t, scale=10):
return make_tensor(t, M, M).mul(scale)

Expand Down Expand Up @@ -143,6 +147,13 @@ def tmp(t):
return t(*sizes).copy_(torch.randn(*sizes))
return tmp

# Content of each tuple:
# - function name
# - constructor for the tensor, signature: fn(tensor_type) -> tensor
# - constructor for the arguments, signature: fn(tensor_type) -> list
# - postfix name for the test (must be unique for a given function) (default='')
# - tensor types to use (default=types)
# - disable inplace test, if set to True, no inplace test will be done (default=False)
tests = [
('add', small_3d, lambda t: [number(3.14, 3, t)]),
('add', small_3d, lambda t: [small_3d_positive(t)], 'tensor'),
Expand Down Expand Up @@ -296,9 +307,11 @@ def tmp(t):
('topk', small_3d_unique, lambda t: [2, 1, True, True], 'dim_desc_sort'),
('trace', medium_2d, lambda t: [],),
('tril', medium_2d, lambda t: [],),
('tril', medium_2d_expanded, lambda t: [], 'zero_stride', types, True),
('tril', medium_2d, lambda t: [2], 'positive'),
('tril', medium_2d, lambda t: [-2], 'negative'),
('triu', medium_2d, lambda t: [],),
('triu', medium_2d_expanded, lambda t: [], 'zero_stride', types, True),
('triu', medium_2d, lambda t: [2], 'positive'),
('triu', medium_2d, lambda t: [-2], 'negative'),
('unsqueeze', new_t(2, 3, 4), lambda t: [2],),
Expand Down Expand Up @@ -1351,18 +1364,27 @@ def test_nvtx(self):
for t in types:
tensor = t()
gpu_tensor = get_gpu_type(t)()

# Default values
desc = ''
type_subset = types
no_inplace = False
if len(decl) == 3:
name, constr, arg_constr = decl
desc = ''
elif len(decl) == 4:
name, constr, arg_constr, desc = decl
elif len(decl) == 5:
name, constr, arg_constr, desc, type_subset = decl
if t not in type_subset:
continue
elif len(decl) == 6:
name, constr, arg_constr, desc, type_subset, no_inplace = decl

if t not in type_subset:
continue

precision = custom_precision.get(name, TestCuda.precision)
for inplace in (True, False):
if inplace and no_inplace:

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continue
if inplace:
name_inner = name + '_'
else:
Expand Down