[Docs] Translate fileio doc (#753)
* translate the fileio doc * Update docs/en/advanced_tutorials/fileio.md Co-authored-by: Zaida Zhou <58739961+zhouzaida@users.noreply.github.com> * Update docs/en/advanced_tutorials/fileio.md Co-authored-by: Zaida Zhou <58739961+zhouzaida@users.noreply.github.com>pull/792/head
yancong
Zaida Zhou
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# File IO
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Coming soon. Please refer to [chinese documentation](https://mmengine.readthedocs.io/zh_CN/latest/advanced_tutorials/fileio.html).
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`MMEngine` implements a unified set of file reading and writing interfaces in `fileio` module. With the `fileio` module, we can use the same function to handle different file formats, such as `json`, `yaml` and `pickle`. Other file formats can also be easily extended.
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The `fileio` module also supports reading and writing files from a variety of file storage backends, including disk, Petrel (for internal use), Memcached, LMDB, and HTTP.
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## Load and dump data
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`MMEngine` provides a universal API for loading and dumping data, currently supported formats are `json`, `yaml`, and `pickle`.
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### Load from disk or dump to disk
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```python
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from mmengine import load, dump
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# load data from a file
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data = load('test.json')
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data = load('test.yaml')
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data = load('test.pkl')
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# load data from a file-like object
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with open('test.json', 'r') as f:
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data = load(f, file_format='json')
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# dump data to a string
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json_str = dump(data, file_format='json')
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# dump data to a file with a filename (infer format from file extension)
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dump(data, 'out.pkl')
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# dump data to a file with a file-like object
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with open('test.yaml', 'w') as f:
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data = dump(data, f, file_format='yaml')
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```
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### Load from other backends or dump to other backends
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```python
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from mmengine import load, dump
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# load data from a file
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data = load('s3://bucket-name/test.json')
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data = load('s3://bucket-name/test.yaml')
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data = load('s3://bucket-name/test.pkl')
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# dump data to a file with a filename (infer format from file extension)
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dump(data, 's3://bucket-name/out.pkl')
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```
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It is also very convenient to extend the API to support more file formats. All you need to do is to write a file handler inherited from `BaseFileHandler` and register it with one or several file formats.
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```python
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from mmengine import register_handler, BaseFileHandler
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# To register multiple file formats, a list can be used as the argument.
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# @register_handler(['txt', 'log'])
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@register_handler('txt')
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class TxtHandler1(BaseFileHandler):
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def load_from_fileobj(self, file):
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return file.read()
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def dump_to_fileobj(self, obj, file):
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file.write(str(obj))
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def dump_to_str(self, obj, **kwargs):
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return str(obj)
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```
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Here is an example of `PickleHandler`.
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```python
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from mmengine import BaseFileHandler
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import pickle
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class PickleHandler(BaseFileHandler):
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def load_from_fileobj(self, file, **kwargs):
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return pickle.load(file, **kwargs)
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def load_from_path(self, filepath, **kwargs):
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return super(PickleHandler, self).load_from_path(
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filepath, mode='rb', **kwargs)
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def dump_to_str(self, obj, **kwargs):
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kwargs.setdefault('protocol', 2)
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return pickle.dumps(obj, **kwargs)
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def dump_to_fileobj(self, obj, file, **kwargs):
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kwargs.setdefault('protocol', 2)
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pickle.dump(obj, file, **kwargs)
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def dump_to_path(self, obj, filepath, **kwargs):
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super(PickleHandler, self).dump_to_path(
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obj, filepath, mode='wb', **kwargs)
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```
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## Load a text file as a list or dict
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For example `a.txt` is a text file with 5 lines.
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```
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a
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b
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c
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d
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e
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```
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### Load from disk
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Use `list_from_file` to load the list from `a.txt`.
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```python
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from mmengine import list_from_file
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print(list_from_file('a.txt'))
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# ['a', 'b', 'c', 'd', 'e']
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print(list_from_file('a.txt', offset=2))
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# ['c', 'd', 'e']
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print(list_from_file('a.txt', max_num=2))
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# ['a', 'b']
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print(list_from_file('a.txt', prefix='/mnt/'))
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# ['/mnt/a', '/mnt/b', '/mnt/c', '/mnt/d', '/mnt/e']
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```
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For example `b.txt` is a text file with 3 lines.
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```
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1 cat
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2 dog cow
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3 panda
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```
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Then use `dict_from_file` to load the dict from `b.txt`.
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```python
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from mmengine import dict_from_file
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print(dict_from_file('b.txt'))
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# {'1': 'cat', '2': ['dog', 'cow'], '3': 'panda'}
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print(dict_from_file('b.txt', key_type=int))
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# {1: 'cat', 2: ['dog', 'cow'], 3: 'panda'}
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```
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### Load from other backends
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Use `list_from_file` to load the list from `s3://bucket-name/a.txt`.
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```python
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from mmengine import list_from_file
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print(list_from_file('s3://bucket-name/a.txt'))
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# ['a', 'b', 'c', 'd', 'e']
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print(list_from_file('s3://bucket-name/a.txt', offset=2))
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# ['c', 'd', 'e']
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print(list_from_file('s3://bucket-name/a.txt', max_num=2))
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# ['a', 'b']
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print(list_from_file('s3://bucket-name/a.txt', prefix='/mnt/'))
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# ['/mnt/a', '/mnt/b', '/mnt/c', '/mnt/d', '/mnt/e']
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```
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Use `dict_from_file` to load the dict from `s3://bucket-name/b.txt`.
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```python
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from mmengine import dict_from_file
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print(dict_from_file('s3://bucket-name/b.txt'))
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# {'1': 'cat', '2': ['dog', 'cow'], '3': 'panda'}
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print(dict_from_file('s3://bucket-name/b.txt', key_type=int))
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# {1: 'cat', 2: ['dog', 'cow'], 3: 'panda'}
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```
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## Load and dump checkpoints
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We can read the checkpoints from disk or internet in the following way.
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```python
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import torch
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filepath1 = '/path/of/your/checkpoint1.pth'
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filepath2 = 'http://path/of/your/checkpoint3.pth'
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# read filepath1 from disk
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checkpoint = torch.load(filepath1)
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# save checkpoints to disk
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torch.save(checkpoint, filepath1)
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# read filepath2 from internet
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checkpoint = torch.utils.model_zoo.load_url(filepath2)
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```
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In `MMEngine`, reading and writing checkpoints in different storage forms can be uniformly implemented with `load_checkpoint` and `save_checkpoint`.
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```python
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from mmengine import load_checkpoint, save_checkpoint
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filepath1 = '/path/of/your/checkpoint1.pth'
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filepath2 = 's3://bucket-name/path/of/your/checkpoint1.pth'
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filepath3 = 'http://path/of/your/checkpoint3.pth'
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# read checkpoints from disk
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checkpoint = load_checkpoint(filepath1)
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# save checkpoints from disk
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save_checkpoint(checkpoint, filepath1)
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# read checkpoints from s3
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checkpoint = load_checkpoint(filepath2)
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# save checkpoints from s3
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save_checkpoint(checkpoint, filepath2)
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# read checkpoints from internet
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checkpoint = load_checkpoint(filepath3)
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```
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checkpoint = torch.utils.model_zoo.load_url(filepath2)
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```
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在 `mmengine` 中，得益于多文件存储后端的支持，不同存储形式的权重文件读写可以通过
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在 `MMEngine` 中，得益于多文件存储后端的支持，不同存储形式的权重文件读写可以通过
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`load_checkpoint` 和 `save_checkpoint` 来统一实现。
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```python
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