Browse Source

!11632 fix gru net usablity bug

From: @qujianwei
Reviewed-by: @linqingke,@liangchenghui
Signed-off-by: @liangchenghui
tags/v1.2.0-rc1
mindspore-ci-bot Gitee 4 years ago
parent
commit
74c2b957f7
6 changed files with 40 additions and 10 deletions
  1. +21
    -1
      model_zoo/official/nlp/gru/README.md
  2. +7
    -2
      model_zoo/official/nlp/gru/eval.py
  3. +2
    -2
      model_zoo/official/nlp/gru/scripts/run_distribute_train_ascend.sh
  4. +2
    -2
      model_zoo/official/nlp/gru/scripts/run_eval.sh
  5. +2
    -2
      model_zoo/official/nlp/gru/scripts/run_standalone_train.sh
  6. +6
    -1
      model_zoo/official/nlp/gru/train.py

+ 21
- 1
model_zoo/official/nlp/gru/README.md View File

@@ -1,4 +1,4 @@
![](https://www.mindspore.cn/static/img/logo.a3e472c9.png)
![](https://www.mindspore.cn/static/img/logo_black.6a5c850d.png)

<!-- TOC -->

@@ -52,6 +52,26 @@ In this model, we use the Multi30K dataset as our train and test dataset.As trai
- [MindSpore Tutorials](https://www.mindspore.cn/tutorial/training/en/master/index.html)
- [MindSpore Python API](https://www.mindspore.cn/doc/api_python/en/master/index.html)

## Requirements

```txt
nltk
numpy
```

To install nltk, you should install nltk as follow:

```bash
pip install nltk
```

Then you should download extra packages as follow:

```python
import nltk
nltk.download()
```

# [Quick Start](#content)

After dataset preparation, you can start training and evaluation as follows:


+ 7
- 2
model_zoo/official/nlp/gru/eval.py View File

@@ -13,7 +13,7 @@
# limitations under the License.
# ============================================================================
"""Transformer evaluation script."""
import os
import argparse
import mindspore.common.dtype as mstype
from mindspore.common.tensor import Tensor
@@ -41,8 +41,13 @@ def run_gru_eval():

context.set_context(mode=context.GRAPH_MODE, device_target=args.device_target, reserve_class_name_in_scope=False, \
device_id=args.device_id, save_graphs=False)
prefix = "multi30k_test_mindrecord_32"
mindrecord_file = os.path.join(args.dataset_path, prefix)
if not os.path.exists(mindrecord_file):
print("dataset file {} not exists, please check!".format(mindrecord_file))
raise ValueError(mindrecord_file)
dataset = create_gru_dataset(epoch_count=config.num_epochs, batch_size=config.eval_batch_size, \
dataset_path=args.dataset_path, rank_size=args.device_num, rank_id=0, do_shuffle=False, is_training=False)
dataset_path=mindrecord_file, rank_size=args.device_num, rank_id=0, do_shuffle=False, is_training=False)
dataset_size = dataset.get_dataset_size()
print("dataset size is {}".format(dataset_size))
network = Seq2Seq(config, is_training=False)


+ 2
- 2
model_zoo/official/nlp/gru/scripts/run_distribute_train_ascend.sh View File

@@ -40,9 +40,9 @@ fi
DATASET_PATH=$(get_real_path $2)
echo $DATASET_PATH

if [ ! -f $DATASET_PATH ]
if [ ! -d $DATASET_PATH ]
then
echo "error: DATASET_PATH=$DATASET_PATH is not a file"
echo "error: DATASET_PATH=$DATASET_PATH is not a directory"
exit 1
fi



+ 2
- 2
model_zoo/official/nlp/gru/scripts/run_eval.sh View File

@@ -41,9 +41,9 @@ fi

DATASET_PATH=$(get_real_path $2)
echo $DATASET_PATH
if [ ! -f $DATASET_PATH ]
if [ ! -d $DATASET_PATH ]
then
echo "error: DATASET_PATH=$DATASET_PATH is not a file"
echo "error: DATASET_PATH=$DATASET_PATH is not a directory"
exit 1
fi
rm -rf ./eval


+ 2
- 2
model_zoo/official/nlp/gru/scripts/run_standalone_train.sh View File

@@ -33,9 +33,9 @@ get_real_path(){

DATASET_PATH=$(get_real_path $1)
echo $DATASET_PATH
if [ ! -f $DATASET_PATH ]
if [ ! -d $DATASET_PATH ]
then
echo "error: DATASET_PATH=$DATASET_PATH is not a file"
echo "error: DATASET_PATH=$DATASET_PATH is not a directory"
exit 1
fi



+ 6
- 1
model_zoo/official/nlp/gru/train.py View File

@@ -99,8 +99,13 @@ if __name__ == '__main__':
else:
rank = 0
device_num = 1
prefix = "multi30k_train_mindrecord_32_"
mindrecord_file = os.path.join(args.dataset_path, prefix+"0")
if not os.path.exists(mindrecord_file):
print("dataset file {} not exists, please check!".format(mindrecord_file))
raise ValueError(mindrecord_file)
dataset = create_gru_dataset(epoch_count=config.num_epochs, batch_size=config.batch_size,
dataset_path=args.dataset_path, rank_size=device_num, rank_id=rank)
dataset_path=mindrecord_file, rank_size=device_num, rank_id=rank)
dataset_size = dataset.get_dataset_size()
print("dataset size is {}".format(dataset_size))
network = Seq2Seq(config)


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