Fixing a bug of DynamicConv in the unfolding mode (#593)

Summary:
The unfold1d.py has the same name as the function `unfold1d` function, which will cause an error when using DynamicConv1dTBC with `unfold=True`.
This doesn't affect the NMT models which don't use the unfolding mode though.

I rename `unfold1d.py` as `unfold.py` to fix this bug.

Originally we would get `TypeError` when running this code:
```
import torch
from fairseq.modules import LightweightConv1dTBC, DynamicConv1dTBC

x = torch.rand(4, 10, 8)
m = LightweightConv1dTBC(8, 4, 3)
o = m(x, unfold=True)

m = DynamicConv1dTBC(8, 4, 3)
o = m(x, unfold=True)
```
Pull Request resolved: https://github.com/pytorch/fairseq/pull/593

Differential Revision: D14597117

Pulled By: myleott

fbshipit-source-id: 59752fd7ff62c53a4aba8b56b83155291e5f5792

fairseq/modules/__init__.py

@@ -23,7 +23,7 @@ from .mean_pool_gating_network import MeanPoolGatingNetwork
 from .multihead_attention import MultiheadAttention
 from .scalar_bias import ScalarBias
 from .sinusoidal_positional_embedding import SinusoidalPositionalEmbedding
-from .unfold1d import unfold1d
+from .unfold import unfold1d
 
 __all__ = [
     'AdaptiveInput',

fairseq/modules/dynamic_convolution.py

@@ -10,7 +10,7 @@ import torch.nn as nn
 import torch.nn.functional as F
 
 from fairseq import utils
-from fairseq.modules import unfold1d
+from .unfold import unfold1d
 
 
 def Linear(in_features, out_features, bias=True):

fairseq/modules/lightweight_convolution.py

@@ -12,7 +12,7 @@ import torch.nn as nn
 import torch.nn.functional as F
 
 from fairseq import utils
-from fairseq.modules import unfold1d
+from .unfold import unfold1d
 
 
 class LightweightConv1d(nn.Module):