未验证 提交 330cf3ee 编写于 作者: T Tao Luo 提交者: GitHub

Merge pull request #538 from weixing02/08

fix 08.machine_translation/README.cn.md
...@@ -173,6 +173,7 @@ $$e_{ij} = {align(z_i, h_j)}$$ ...@@ -173,6 +173,7 @@ $$e_{ij} = {align(z_i, h_j)}$$
# 加载 paddle的python包 # 加载 paddle的python包
import sys import sys
import paddle.v2 as paddle import paddle.v2 as paddle
import numpy as np
# 配置只使用cpu,并且使用一个cpu进行训练 # 配置只使用cpu,并且使用一个cpu进行训练
paddle.init(use_gpu=False, trainer_count=1) paddle.init(use_gpu=False, trainer_count=1)
...@@ -273,11 +274,11 @@ is_generating = False ...@@ -273,11 +274,11 @@ is_generating = False
output_mem=decoder_mem, output_mem=decoder_mem,
size=decoder_size) size=decoder_size)
out = paddle.layer.mixed( out = paddle.layer.fc(
size=target_dict_dim, size=target_dict_dim,
bias_attr=True, bias_attr=True,
act=paddle.activation.Softmax(), act=paddle.activation.Softmax(),
input=paddle.layer.full_matrix_projection(input=gru_step)) input=gru_step)
return out return out
``` ```
...@@ -325,7 +326,7 @@ is_generating = False ...@@ -325,7 +326,7 @@ is_generating = False
6. 生成模式下的解码器调用: 6. 生成模式下的解码器调用:
- 首先,在序列生成任务中,由于解码阶段的RNN总是引用上一时刻生成出的词的词向量,作为当前时刻的输入,因此,使用`GeneratedInput`来自动完成这一过程。具体说明可见[GeneratedInput文档](https://github.com/PaddlePaddle/Paddle/blob/develop/doc/howto/deep_model/rnn/recurrent_group_cn.md#输入) - 首先,在序列生成任务中,由于解码阶段的RNN总是引用上一时刻生成出的词的词向量,作为当前时刻的输入,因此,使用`GeneratedInput`来自动完成这一过程。具体说明可见[GeneratedInput文档](https://github.com/PaddlePaddle/Paddle/blob/develop/doc/v2/howto/rnn/recurrent_group_cn.md#输入)
- 其次,使用`beam_search`函数循环调用`gru_decoder_with_attention`函数,生成出序列id。 - 其次,使用`beam_search`函数循环调用`gru_decoder_with_attention`函数,生成出序列id。
```python ```python
......
...@@ -215,6 +215,7 @@ This subset has 193319 instances of training data and 6003 instances of test dat ...@@ -215,6 +215,7 @@ This subset has 193319 instances of training data and 6003 instances of test dat
```python ```python
import sys import sys
import paddle.v2 as paddle import paddle.v2 as paddle
import numpy as np
# train with a single CPU # train with a single CPU
paddle.init(use_gpu=False, trainer_count=1) paddle.init(use_gpu=False, trainer_count=1)
...@@ -326,7 +327,7 @@ is_generating = False ...@@ -326,7 +327,7 @@ is_generating = False
return out return out
``` ```
4. Define the name for the decoder and the first two input for `gru_decoder_with_attention`. Note that `StaticInput` is used for the two inputs. Please refer to [StaticInput Document](https://github.com/PaddlePaddle/Paddle/blob/develop/doc/v2/howto/rnn/recurrent_group_en.md#input) for more details. 1. Define the name for the decoder and the first two input for `gru_decoder_with_attention`. Note that `StaticInput` is used for the two inputs. Please refer to [StaticInput Document](https://github.com/PaddlePaddle/Paddle/blob/develop/doc/v2/howto/rnn/recurrent_group_cn.md#input) for more details.
```python ```python
decoder_group_name = "decoder_group" decoder_group_name = "decoder_group"
......
Markdown is supported
0% .
You are about to add 0 people to the discussion. Proceed with caution.
先完成此消息的编辑!
想要评论请 注册