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FIX Validates that weights are 2d in embedding #59314

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FIX Validates that weights are 2d in embedding #59314

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e13e043
FIX Validates that weights are 2d in embedding
thomasjpfan Jun 2, 2021
ae04d08
Merge remote-tracking branch 'upstream/master' into embedding_error_c…
thomasjpfan Jun 2, 2021
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2 changes: 1 addition & 1 deletion aten/src/ATen/native/Embedding.cpp
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Expand Up @@ -15,7 +15,7 @@ namespace at { namespace native {

Tensor embedding(const Tensor & weight, const Tensor & indices,
int64_t padding_idx, bool scale_grad_by_freq, bool sparse) {
TORCH_CHECK(weight.dim() >= 1, "'weight' must be at least 1-D");
TORCH_CHECK(weight.dim() == 2, "'weight' must be 2-D");
auto indices_arg = TensorArg(indices, "indices", 1);
checkScalarTypes("embedding", indices_arg, {kLong, kInt});

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11 changes: 8 additions & 3 deletions test/test_nn.py
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Expand Up @@ -13383,9 +13383,14 @@ def fn(weight):

def test_embedding_scalar_weight_error(self, device):
indices = torch.rand(2, 2, device=device).long()
weight = torch.tensor(1.0, device=device)
with self.assertRaisesRegex(RuntimeError, "'weight' must be at least 1-D"):
torch.nn.functional.embedding(indices, weight)
weights = [
torch.tensor(1.0, device=device),
torch.tensor(1.0, device=device).reshape(1, 1, 1),
]

for weight in weights:
with self.assertRaisesRegex(RuntimeError, "'weight' must be 2-D"):
torch.nn.functional.embedding(indices, weight)

@dtypesIfCUDA(torch.float16, torch.float64)
@dtypes(torch.float64)
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10 changes: 7 additions & 3 deletions test/test_torch.py
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Expand Up @@ -4088,9 +4088,13 @@ def backward_func(slf, device):

def test_embedding_scalar_weight_error(self, device):
indices = torch.rand(2, 2, device=device).long()
weight = torch.tensor(1.0)
with self.assertRaisesRegex(RuntimeError, "'weight' must be at least 1-D"):
torch.embedding(weight, indices)
weights = [
torch.tensor(1.0, device=device),
torch.tensor(1.0, device=device).reshape(1, 1, 1),
]
for weight in weights:
with self.assertRaisesRegex(RuntimeError, "'weight' must be 2-D"):
torch.embedding(weight, indices)

def test_dist(self, device):
def run_test(x, y):
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