提交 1941c278 编写于 作者: W wangxiao

change name & path

上级 2f34f935
*.pyc
__pycache__
pretrain_model
pretrain
output_model
build
dist
......
......@@ -163,7 +163,7 @@ max_seq_len: 512
max_query_len: 64
doc_stride: 128 # 在MRQA数据集中,存在较长的文档,因此我们这里使用滑动窗口处理样本,滑动步长设置为128
do_lower_case: True
vocab_path: "../../pretrain_model/bert/vocab.txt"
vocab_path: "../../pretrain/bert-en-uncased-large/vocab.txt"
```
更详细的任务实例配置方法(为任务实例选择合适的reader、paradigm和backbone)可参考[这里](#readerbackbone与paradigm的选择)
......@@ -178,7 +178,7 @@ task_instance: "mrqa"
save_path: "output_model/firstrun"
backbone: "bert"
backbone_config_path: "../../pretrain_model/bert/bert_config.json"
backbone_config_path: "../../pretrain/bert-en-uncased-large/bert_config.json"
optimizer: "adam"
learning_rate: 3e-5
......@@ -204,7 +204,7 @@ import paddlepalm as palm
if __name__ == '__main__':
controller = palm.Controller('config.yaml')
controller.load_pretrain('../../pretrain_model/bert/params')
controller.load_pretrain('../../pretrain/bert-en-uncased-large/params')
controller.train()
```
......@@ -271,9 +271,9 @@ target_tag: 1,0,0
save_path: "output_model/secondrun"
backbone: "ernie"
backbone_config_path: "../../pretrain_model/ernie/ernie_config.json"
backbone_config_path: "../../pretrain/ernie-en-uncased-large/ernie_config.json"
vocab_path: "../../pretrain_model/ernie/vocab.txt"
vocab_path: "../../pretrain/ernie-en-uncased-large/vocab.txt"
do_lower_case: True
max_seq_len: 512 # 写入全局配置文件的参数会被自动广播到各个任务实例
......@@ -308,7 +308,7 @@ import paddlepalm as palm
if __name__ == '__main__':
controller = palm.Controller('config.yaml', task_dir='tasks')
controller.load_pretrain('../../pretrain_model/ernie/params')
controller.load_pretrain('../../pretrain/ernie-en-uncased-large/params')
controller.train()
```
......@@ -400,9 +400,9 @@ task_reuse_tag: 0, 0, 1, 1, 0, 2
save_path: "output_model/secondrun"
backbone: "ernie"
backbone_config_path: "../../pretrain_model/ernie/ernie_config.json"
backbone_config_path: "../../pretrain/ernie-en-uncased-large/ernie_config.json"
vocab_path: "../../pretrain_model/ernie/vocab.txt"
vocab_path: "../../pretrain/ernie-en-uncased-large/vocab.txt"
do_lower_case: True
max_seq_len: 512 # 写入全局配置文件的参数会被自动广播到各个任务实例
......@@ -422,7 +422,7 @@ import paddlepalm as palm
if __name__ == '__main__':
controller = palm.Controller('config.yaml', task_dir='tasks')
controller.load_pretrain('../../pretrain_model/ernie/params')
controller.load_pretrain('../../pretrain/ernie-en-uncased-large/params')
controller.train()
```
......
......@@ -2,8 +2,8 @@ task_instance: "mrqa"
save_path: "output_model/firstrun"
backbone: "bert"
backbone_config_path: "../../pretrain_model/bert/bert_config.json"
backbone: "bert-en-uncased-large"
backbone_config_path: "../../pretrain/bert-en-uncased-large/bert_config.json"
batch_size: 4
num_epochs: 2
......
......@@ -2,7 +2,7 @@ train_file: data/mrqa/train.json
reader: mrc
paradigm: mrc
vocab_path: "../../pretrain_model/bert/vocab.txt"
vocab_path: "../../pretrain/bert-en-uncased-large/vocab.txt"
do_lower_case: True
max_seq_len: 512
doc_stride: 128
......
......@@ -4,15 +4,15 @@ mix_ratio: 1.0, 0.5, 0.5
save_path: "output_model/secondrun"
backbone: "ernie"
backbone_config_path: "../../pretrain_model/ernie/ernie_config.json"
backbone: "ernie-en-uncased-large"
backbone_config_path: "../../pretrain/ernie-en-uncased-large/ernie_config.json"
vocab_path: "../../pretrain_model/ernie/vocab.txt"
vocab_path: "../../pretrain/ernie-en-uncased-large/vocab.txt"
do_lower_case: True
max_seq_len: 512
batch_size: 4
num_epochs: 2
num_epochs: 0.1
optimizer: "adam"
learning_rate: 3e-5
warmup_proportion: 0.1
......
......@@ -4,10 +4,10 @@ task_reuse_tag: 0,0,1,1,0,2
save_path: "output_model/thirdrun"
backbone: "ernie"
backbone_config_path: "../../pretrain_model/ernie/ernie_config.json"
backbone: "ernie-en-uncased-large"
backbone_config_path: "../../pretrain/ernie-en-uncased-large/ernie_config.json"
vocab_path: "../../pretrain_model/ernie/vocab.txt"
vocab_path: "../../pretrain/ernie-en-uncased-large/vocab.txt"
do_lower_case: True
max_seq_len: 512
......
......@@ -522,15 +522,15 @@ class Controller(object):
inst.reader['pred'] = pred_reader
return pred_prog
def load_pretrain(self, pretrain_model_path=None):
def load_pretrain(self, pretrain_path=None):
# load pretrain model (or ckpt)
if pretrain_model_path is None:
assert 'pretrain_model_path' in self.main_conf, "pretrain_model_path NOT set."
pretrain_model_path = self.main_conf['pretrain_model_path']
if pretrain_path is None:
assert 'pretrain_path' in self.main_conf, "pretrain_path NOT set."
pretrain_path = self.main_conf['pretrain_path']
init_pretraining_params(
self.exe,
pretrain_model_path,
pretrain_path,
main_program=fluid.default_startup_program())
......
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