Fix embedding bag nan output when input is empty #21400
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```
import torch
Embed = torch.nn.EmbeddingBag(100, 10, sparse=True)
print(Embed(input=torch.LongTensor([]), offsets=torch.LongTensor([0])))
print(Embed(input=torch.LongTensor([]), offsets=torch.LongTensor([0, 0])))
```
Before this fix:
```
tensor([[nan, nan, nan, nan, nan, nan, nan, nan, nan, nan]])
tensor([[0., 0., 0., 0., 0., 0., 0., 0., 0., 0.],
[0., 0., 0., 0., 0., 0., 0., 0., 0., 0.]])
```
After this fix:
```
tensor([[0., 0., 0., 0., 0., 0., 0., 0., 0., 0.]])
tensor([[0., 0., 0., 0., 0., 0., 0., 0., 0., 0.],
[0., 0., 0., 0., 0., 0., 0., 0., 0., 0.]])
```
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zou3519
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Jun 5, 2019
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Jun 6, 2019
Summary:
```
import torch
Embed = torch.nn.EmbeddingBag(100, 10, sparse=True)
print(Embed(input=torch.LongTensor([]), offsets=torch.LongTensor([0])))
print(Embed(input=torch.LongTensor([]), offsets=torch.LongTensor([0, 0])))
```
Before this fix:
```
tensor([[nan, nan, nan, nan, nan, nan, nan, nan, nan, nan]])
tensor([[0., 0., 0., 0., 0., 0., 0., 0., 0., 0.],
[0., 0., 0., 0., 0., 0., 0., 0., 0., 0.]])
```
After this fix:
```
tensor([[0., 0., 0., 0., 0., 0., 0., 0., 0., 0.]])
tensor([[0., 0., 0., 0., 0., 0., 0., 0., 0., 0.],
[0., 0., 0., 0., 0., 0., 0., 0., 0., 0.]])
```
Pull Request resolved: pytorch/pytorch#21400
Differential Revision: D15643357
Pulled By: bddppq
fbshipit-source-id: 119eba38129dc0a3757c331304a18044714fcca5
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Before this fix:
After this fix: