MLflowVisBackend¶

class mmengine.visualization.MLflowVisBackend(save_dir, exp_name=None, run_name=None, tags=None, params=None, tracking_uri=None, artifact_suffix=('.json', '.log', '.py', 'yaml'))[源代码]¶

MLflow visualization backend class.

It can write images, config, scalars, etc. to a mlflow file.

实际案例

>>> from mmengine.visualization import MLflowVisBackend
>>> from mmengine import Config
>>> import numpy as np
>>> vis_backend = MLflowVisBackend(save_dir='temp_dir')
>>> img = np.random.randint(0, 256, size=(10, 10, 3))
>>> vis_backend.add_image('img.png', img)
>>> vis_backend.add_scalar('mAP', 0.6)
>>> vis_backend.add_scalars({'loss': 0.1,'acc':0.8})
>>> cfg = Config(dict(a=1, b=dict(b1=[0, 1])))
>>> vis_backend.add_config(cfg)

参数

save_dir (str) – The root directory to save the files produced by the backend.
exp_name (str, optional) – The experiment name. Default to None.
run_name (str, optional) – The run name. Default to None.
tags (dict, optional) – The tags to be added to the experiment. Default to None.
params (dict, optional) – The params to be added to the experiment. Default to None.
tracking_uri (str, optional) – The tracking uri. Default to None.
artifact_suffix (Tuple[str] or str, optional) – The artifact suffix. Default to (‘.json’, ‘.log’, ‘.py’, ‘yaml’).

add_config(config, **kwargs)[源代码]¶

Record the config to mlflow.

参数: config (Config) – The Config object
返回类型: None

add_image(name, image, step=0, **kwargs)[源代码]¶

Record the image to mlflow.

参数

name (str) – The image identifier.
image (np.ndarray) – The image to be saved. The format should be RGB.
step (int) – Global step value to record. Default to 0.

返回类型

None

add_scalar(name, value, step=0, **kwargs)[源代码]¶

Record the scalar data to mlflow.

参数

name (str) – The scalar identifier.
value (int, float, torch.Tensor, np.ndarray) – Value to save.
step (int) – Global step value to record. Default to 0.

返回类型

None

add_scalars(scalar_dict, step=0, file_path=None, **kwargs)[源代码]¶

Record the scalar’s data to mlflow.

参数

scalar_dict (dict) – Key-value pair storing the tag and corresponding values.
step (int) – Global step value to record. Default to 0.
file_path (str, optional) – Useless parameter. Just for interface unification. Default to None.

返回类型

None

close()[源代码]¶

Close the mlflow.

返回类型: None

property experiment¶: Return MLflow object.