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Multinomial raise error #12490

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ailzhang wants to merge 6 commits into from
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Multinomial raise error #12490

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449b2bc
raise error when replacement=False, but n_samples > n_pos_categories
Oct 9, 2018
16b7a39
add cuda testcase
Oct 9, 2018
b56a5fd
update check condition
Oct 9, 2018
6ad8f89
fix tests
Oct 9, 2018
7d4feec
Merge remote-tracking branch 'upstream/master' into multinomial_raise…
Oct 10, 2018
dec1d34
Merge branch 'master' of https://github.com/pytorch/pytorch into mult…
Oct 10, 2018
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8 changes: 8 additions & 0 deletions aten/src/TH/generic/THTensorRandom.cpp
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Original file line number Diff line number Diff line change
Expand Up @@ -285,6 +285,7 @@ void THTensor_(multinomial)(THLongTensor *self, THGenerator *_generator, THTenso
/* Get normalized cumulative distribution from prob distribution */
double sum = 0;
double val;
int n_zeros = 0;
for (j=0; j<n_categories; j++)
{
val = THStorage_(get)( \
Expand All @@ -300,6 +301,9 @@ void THTensor_(multinomial)(THLongTensor *self, THGenerator *_generator, THTenso
2,
"invalid multinomial distribution (encountering probability entry = infinity or NaN)");
sum += val;
if (val == 0) {
n_zeros += 1;
}
THDoubleStorage_set(
THTensor_getStoragePtr(cum_dist), \
cum_dist->storage_offset()+j*cum_dist->stride(0), \
Expand All @@ -310,6 +314,10 @@ void THTensor_(multinomial)(THLongTensor *self, THGenerator *_generator, THTenso
THCleanup(THDoubleTensor_free(cum_dist); if (start_dim == 1) THTensor_(squeeze1d)(prob_dist, prob_dist, 0);),
2,
"invalid multinomial distribution (sum of probabilities <= 0)");
THArgCheckWithCleanup((with_replacement || (n_categories - n_zeros >= n_sample)),
THCleanup(THDoubleTensor_free(cum_dist); if (start_dim == 1) THTensor_(squeeze1d)(prob_dist, prob_dist, 0);),

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2,
"invalid multinomial distribution (with replacement=False, not enough non-negative category to sample)");
/* normalize cumulative probability distribution so that last val is 1
i.e. doesn't assume original prob_dist row sums to one */
if ( (sum > 0) || ( ( sum < 1.00001) && (sum > 0.99999) ) )
Expand Down
4 changes: 3 additions & 1 deletion aten/src/THC/THCTensorRandom.cuh
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Expand Up @@ -7,7 +7,7 @@

#include <curand_kernel.h>

#define MAX_NUM_BLOCKS 200
#define MAX_NUM_BLOCKS 200
#define BLOCK_SIZE 256
/* Separate kernel because curand_log_normal gets extra parameters. */

Expand Down Expand Up @@ -126,6 +126,8 @@ __device__ int binarySearchForMultinomial(T* dist,
T val) {
int start = 0;
int end = size;
// dist[size - 1] = 0 => all zero prob dist
assert(THCNumerics<T>::gt(dist[size - 1], 0));

while (end - start > 0) {
int mid = start + (end - start) / 2;
Expand Down
22 changes: 6 additions & 16 deletions test/test_cuda.py
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Expand Up @@ -1594,17 +1594,6 @@ def test_multinomial(self):
r = torch.multinomial(p, 1)
self.assertNotEqual(r.min().item(), 0)

# multinomial without repeat but with less nonzero
# elements than draws
# the intention currently is to return 0 for those
# and match CPU behaviour, see issue #9062
p = torch.zeros(1, 5, device="cuda")
p[:, 1] = 1
r = torch.multinomial(p, 2, replacement=False)
expected = torch.zeros(1, 2, device="cuda", dtype=torch.long)
expected[:, 0] = 1
self.assertEqual(r, expected)

@staticmethod
def mute():
os.dup2(os.open(os.devnull, os.O_WRONLY), sys.stderr.fileno())
Expand All @@ -1621,7 +1610,7 @@ def _spawn_method(self, method, arg):
def _test_multinomial_invalid_probs_cuda(probs):
try:
with torch.random.fork_rng(devices=[0]):
torch.multinomial(probs.to('cuda'), 1)
torch.multinomial(probs.to('cuda'), 2)
torch.cuda.synchronize()
return False # Should not be reached
except RuntimeError as e:
Expand All @@ -1635,10 +1624,11 @@ def _test_multinomial_invalid_probs_cuda(probs):
but we need it for creating another process with CUDA")
def test_multinomial_invalid_probs_cuda(self):
test_method = TestCuda._test_multinomial_invalid_probs_cuda
self._spawn_method(test_method, torch.Tensor([0, -1]))
self._spawn_method(test_method, torch.Tensor([0, inf]))
self._spawn_method(test_method, torch.Tensor([0, -inf]))
self._spawn_method(test_method, torch.Tensor([0, nan]))
self._spawn_method(test_method, torch.Tensor([1, -1, 1]))
self._spawn_method(test_method, torch.Tensor([1, inf, 1]))
self._spawn_method(test_method, torch.Tensor([1, -inf, 1]))
self._spawn_method(test_method, torch.Tensor([1, 1, nan]))
self._spawn_method(test_method, torch.Tensor([0, 1, 0]))

@skipIfRocm
def test_broadcast(self):
Expand Down
12 changes: 7 additions & 5 deletions test/test_torch.py
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Original file line number Diff line number Diff line change
Expand Up @@ -2851,7 +2851,8 @@ def _spawn_method(self, method, arg):
@staticmethod
def _test_multinomial_invalid_probs(probs):
try:
torch.multinomial(probs.to('cpu'), 1)
# n_sample = 1 is a special case, test n_sample=2 which is more general
torch.multinomial(probs.to('cpu'), 2)
return False # Should not be reached
except RuntimeError as e:
return 'invalid multinomial distribution' in str(e)
Expand All @@ -2864,10 +2865,11 @@ def _test_multinomial_invalid_probs(probs):
but we need it for for testing failure case for CPU RNG on Windows")
def test_multinomial_invalid_probs(self):
test_method = TestTorch._test_multinomial_invalid_probs
self._spawn_method(test_method, torch.Tensor([0, -1]))
self._spawn_method(test_method, torch.Tensor([0, inf]))
self._spawn_method(test_method, torch.Tensor([0, -inf]))
self._spawn_method(test_method, torch.Tensor([0, nan]))
self._spawn_method(test_method, torch.Tensor([1, -1, 1]))
self._spawn_method(test_method, torch.Tensor([1, inf, 1]))
self._spawn_method(test_method, torch.Tensor([1, -inf, 1]))
self._spawn_method(test_method, torch.Tensor([1, 1, nan]))
self._spawn_method(test_method, torch.Tensor([0, 1, 0]))

@suppress_warnings
def test_range(self):
Expand Down