Skip to content

ocl.utils.logging

ExtendedMLflowExperiment

MLflow experiment made to mimic tensorboard experiments.

Source code in ocl/utils/logging.py 
 82
 83
 84
 85
 86
 87
 88
 89
 90
 91
 92
 93
 94
 95
 96
 97
 98
 99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
class ExtendedMLflowExperiment:
    """MLflow experiment made to mimic tensorboard experiments."""

    def __init__(self, mlflow_client: MlflowClient, run_id: str):
        self._mlflow_client = mlflow_client
        self._run_id = run_id
        self._tempdir = TemporaryDirectory()

    def _get_tmp_prefix_for_step(self, step: int):
        return os.path.join(self._tempdir.name, f"{step:07d}")

    def add_video(self, vid_tensor, fps: int, tag: str, global_step: int):
        path = tag  # TF paths are typically split using "/"
        filename = write_video_tensor(
            self._get_tmp_prefix_for_step(global_step), prepare_video_tensor(vid_tensor), fps
        )
        self._mlflow_client.log_artifact(self._run_id, filename, path)
        os.remove(filename)

    def add_image(self, img_tensor: torch.Tensor, dataformats: str, tag: str, global_step: int):
        path = tag
        filename = write_image_tensor(
            self._get_tmp_prefix_for_step(global_step),
            prepare_image_tensor(img_tensor, dataformats=dataformats),
        )
        self._mlflow_client.log_artifact(self._run_id, filename, path)
        os.remove(filename)

    def add_images(self, img_tensor, dataformats: str, tag: str, global_step: int):
        # Internally works by having an additional N dimension in `dataformats`.
        self.add_image(img_tensor, dataformats, tag, global_step)

    def add_figure(self, figure, close: bool, tag: str, global_step: int):
        if isinstance(figure, list):
            self.add_image(
                figure_to_image(figure, close),
                dataformats="NCHW",
                tag=tag,
                global_step=global_step,
            )
        else:
            self.add_image(
                figure_to_image(figure, close),
                dataformats="CHW",
                tag=tag,
                global_step=global_step,
            )

    def __getattr__(self, name):
        """Fallback to mlflow client for missing attributes.

        Fallback to make the experiment object still behave like the regular MLflow client.  While
        this is suboptimal, it does allow us to save a lot of handcrafted code by relying on
        inheritance and pytorch lightings implementation of the MLflow logger.
        """
        return getattr(self._mlflow_client, name)

__getattr__

Fallback to mlflow client for missing attributes.

Fallback to make the experiment object still behave like the regular MLflow client. While this is suboptimal, it does allow us to save a lot of handcrafted code by relying on inheritance and pytorch lightings implementation of the MLflow logger.

Source code in ocl/utils/logging.py 
130
131
132
133
134
135
136
137
def __getattr__(self, name):
    """Fallback to mlflow client for missing attributes.

    Fallback to make the experiment object still behave like the regular MLflow client.  While
    this is suboptimal, it does allow us to save a lot of handcrafted code by relying on
    inheritance and pytorch lightings implementation of the MLflow logger.
    """
    return getattr(self._mlflow_client, name)