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bug fix“

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yh 2018-11-19 19:16:09 +08:00 committed by yunfan
parent 4149eb9c06
commit 1d5bb0a3b6
2 changed files with 12 additions and 6 deletions
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3
fastNLP/core/dataset.py
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@ -188,7 +188,8 @@ class DataSet(object):
results.append(func(ins))
if new_field_name is not None:
self.add_field(new_field_name, results)
return results
else:
return results
if __name__ == '__main__':
from fastNLP.core.instance import Instance

15
reproduction/CNN-sentence_classification/model.py
View File

@ -4,8 +4,8 @@ import torch.nn.functional as F
class CNN_text(nn.Module):
def __init__(self, kernel_h=[3, 4, 5], kernel_num=100, embed_num=1000, embed_dim=300, dropout=0.5, L2_constrain=3,
batchsize=50, pretrained_embeddings=None):
def __init__(self, kernel_h=[3, 4, 5], kernel_num=100, embed_num=1000, embed_dim=300, num_classes=2, dropout=0.5, L2_constrain=3,
pretrained_embeddings=None):
super(CNN_text, self).__init__()
self.embedding = nn.Embedding(embed_num, embed_dim)
@ -15,11 +15,11 @@ class CNN_text(nn.Module):
# the network structure
# Conv2d: input- N,C,H,W output- (50,100,62,1)
self.conv1 = nn.ModuleList([nn.Conv2d(1, 100, (K, 300)) for K in kernel_h])
self.fc1 = nn.Linear(300, 2)
self.conv1 = nn.ModuleList([nn.Conv2d(1, kernel_num, (K, embed_dim)) for K in kernel_h])
self.fc1 = nn.Linear(len(kernel_h)*kernel_num, num_classes)
def max_pooling(self, x):
x = F.relu(conv(x)).squeeze(3) # N,C,L - (50,100,62)
x = F.relu(self.conv1(x)).squeeze(3) # N,C,L - (50,100,62)
x = F.max_pool1d(x, x.size(2)).squeeze(2)
# x.size(2)=62 squeeze: (50,100,1) -> (50,100)
return x
@ -33,3 +33,8 @@ class CNN_text(nn.Module):
x = self.dropout(x)
x = self.fc1(x)
return x
if __name__ == '__main__':
model = CNN_text(kernel_h=[1, 2, 3, 4],embed_num=3, embed_dim=2)
x = torch.LongTensor([[1, 2, 1, 2, 0]])
print(model(x))