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dive-into-dl-pytorch
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体验新版 GitCode,发现更多精彩内容 >>
提交
39328348
编写于
1月 02, 2020
作者:
S
shusentang
浏览文件
操作
浏览文件
下载
电子邮件补丁
差异文件
fix bug #84
上级
b3401dd6
变更
2
隐藏空白更改
内联
并排
Showing
2 changed file
with
33 addition
and
26 deletion
+33
-26
code/chapter10_natural-language-processing/10.7_sentiment-analysis-rnn.ipynb
...ral-language-processing/10.7_sentiment-analysis-rnn.ipynb
+31
-24
code/d2lzh_pytorch/utils.py
code/d2lzh_pytorch/utils.py
+2
-2
未找到文件。
code/chapter10_natural-language-processing/10.7_sentiment-analysis-rnn.ipynb
浏览文件 @
39328348
...
...
@@ -21,7 +21,7 @@
"name": "stdout",
"output_type": "stream",
"text": [
"1.
0
.0 cuda\n"
"1.
1
.0 cuda\n"
]
}
],
...
...
@@ -39,10 +39,10 @@
"sys.path.append(\"..\") \n",
"import d2lzh_pytorch as d2l\n",
"\n",
"os.environ[\"CUDA_VISIBLE_DEVICES\"] = \"
7
\"\n",
"os.environ[\"CUDA_VISIBLE_DEVICES\"] = \"
2
\"\n",
"device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')\n",
"\n",
"DATA_ROOT = \"/
S1/CSCL
/tangss/Datasets\"\n",
"DATA_ROOT = \"/
data1
/tangss/Datasets\"\n",
"\n",
"print(torch.__version__, device)"
]
...
...
@@ -88,10 +88,10 @@
"name": "stderr",
"output_type": "stream",
"text": [
"100%|██████████| 12500/12500 [00:0
4<00:00, 2930.03
it/s]\n",
"100%|██████████| 12500/12500 [00:0
4<00:00, 3008
.48it/s]\n",
"100%|██████████| 12500/12500 [00:0
3<00:00, 3365.08
it/s]\n",
"100%|██████████| 12500/12500 [00:0
3<00:00, 3305.63
it/s]\n"
"100%|██████████| 12500/12500 [00:0
0<00:00, 34211.42
it/s]\n",
"100%|██████████| 12500/12500 [00:0
0<00:00, 38506
.48it/s]\n",
"100%|██████████| 12500/12500 [00:0
0<00:00, 31316.61
it/s]\n",
"100%|██████████| 12500/12500 [00:0
0<00:00, 29664.72
it/s]\n"
]
}
],
...
...
@@ -108,7 +108,8 @@
" random.shuffle(data)\n",
" return data\n",
"\n",
"train_data, test_data = read_imdb('train'), read_imdb('test')"
"data_root = os.path.join(DATA_ROOT, \"aclImdb\")\n",
"train_data, test_data = read_imdb('train', data_root), read_imdb('test', data_root)"
]
},
{
...
...
@@ -152,7 +153,7 @@
{
"data": {
"text/plain": [
"('# words in vocab:', 4615
1
)"
"('# words in vocab:', 4615
2
)"
]
},
"execution_count": 5,
...
...
@@ -330,8 +331,7 @@
"ExecuteTime": {
"end_time": "2019-07-03T04:26:47.895604Z",
"start_time": "2019-07-03T04:26:47.685801Z"
},
"collapsed": true
}
},
"outputs": [],
"source": [
...
...
@@ -345,10 +345,17 @@
"ExecuteTime": {
"end_time": "2019-07-03T04:26:48.102388Z",
"start_time": "2019-07-03T04:26:47.897582Z"
},
"collapsed": true
}
},
"outputs": [],
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"There are 21202 oov words.\n"
]
}
],
"source": [
"def load_pretrained_embedding(words, pretrained_vocab):\n",
" \"\"\"从预训练好的vocab中提取出words对应的词向量\"\"\"\n",
...
...
@@ -359,9 +366,9 @@
" idx = pretrained_vocab.stoi[word]\n",
" embed[i, :] = pretrained_vocab.vectors[idx]\n",
" except KeyError:\n",
" oov_count +=
0
\n",
" oov_count +=
1
\n",
" if oov_count > 0:\n",
" print(\"There are %d oov words.\")\n",
" print(\"There are %d oov words.\"
% oov_count
)\n",
" return embed\n",
"\n",
"net.embedding.weight.data.copy_(load_pretrained_embedding(vocab.itos, glove_vocab))\n",
...
...
@@ -390,11 +397,11 @@
"output_type": "stream",
"text": [
"training on cuda\n",
"epoch 1, loss 0.5
759, train acc 0.666, test acc 0.832, time 250.8
sec\n",
"epoch 2, loss 0.1
785, train acc 0.842, test acc 0.852, time 253.3
sec\n",
"epoch 3, loss 0.1
042, train acc 0.866, test acc 0.856, time 253.7
sec\n",
"epoch 4, loss 0.0
682, train acc 0.888, test acc 0.868, time 254.2
sec\n",
"epoch 5, loss 0.0
483, train acc 0.901, test acc 0.862, time 251.4
sec\n"
"epoch 1, loss 0.5
415, train acc 0.719, test acc 0.819, time 48.7
sec\n",
"epoch 2, loss 0.1
897, train acc 0.837, test acc 0.852, time 53.0
sec\n",
"epoch 3, loss 0.1
105, train acc 0.857, test acc 0.844, time 51.6
sec\n",
"epoch 4, loss 0.0
719, train acc 0.881, test acc 0.865, time 52.1
sec\n",
"epoch 5, loss 0.0
519, train acc 0.894, test acc 0.852, time 51.2
sec\n"
]
}
],
...
...
@@ -488,9 +495,9 @@
],
"metadata": {
"kernelspec": {
"display_name": "Python [conda env:py36]",
"display_name": "Python [conda env:py36
_pytorch
]",
"language": "python",
"name": "conda-env-py36-py"
"name": "conda-env-py36
_pytorch
-py"
},
"language_info": {
"codemirror_mode": {
...
...
@@ -502,7 +509,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.6.
3
"
"version": "3.6.
2
"
},
"varInspector": {
"cols": {
...
...
code/d2lzh_pytorch/utils.py
浏览文件 @
39328348
...
...
@@ -1203,9 +1203,9 @@ def load_pretrained_embedding(words, pretrained_vocab):
idx
=
pretrained_vocab
.
stoi
[
word
]
embed
[
i
,
:]
=
pretrained_vocab
.
vectors
[
idx
]
except
KeyError
:
oov_count
+=
0
oov_count
+=
1
if
oov_count
>
0
:
print
(
"There are %d oov words."
)
print
(
"There are %d oov words."
%
oov_count
)
return
embed
def
predict_sentiment
(
net
,
vocab
,
sentence
):
...
...
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