tfa.callbacks.TQDMProgressBar

TQDM Progress Bar for Tensorflow Keras.

tfa.callbacks.TQDMProgressBar(
    metrics_separator: str = ' - ',
    overall_bar_format: str = '{l_bar}{bar} {n_fmt}/{total_fmt} ETA: {remaining}s,  {rate_fmt}{postfix}',
    epoch_bar_format: str = '{n_fmt}/{total_fmt}{bar} ETA: {remaining}s - {desc}',
    metrics_format: str = '{name}: {value:0.4f}',
    update_per_second: int = 10,
    leave_epoch_progress: bool = True,
    leave_overall_progress: bool = True,
    show_epoch_progress: bool = True,
    show_overall_progress: bool = True
)

Used in the notebooks

Used in the tutorials

metrics_separator Custom separator between metrics. Defaults to ' - '.
overall_bar_format Custom bar format for overall (outer) progress bar, see https://github.com/tqdm/tqdm#parameters for more detail.
epoch_bar_format Custom bar format for epoch (inner) progress bar, see https://github.com/tqdm/tqdm#parameters for more detail.
update_per_second Maximum number of updates in the epochs bar per second, this is to prevent small batches from slowing down training. Defaults to 10.
metrics_format Custom format for how metrics are formatted. See https://github.com/tqdm/tqdm#parameters for more detail.
leave_epoch_progress True to leave epoch progress bars.
leave_overall_progress True to leave overall progress bar.
show_epoch_progress False to hide epoch progress bars.
show_overall_progress False to hide overall progress bar.

Methods

format_metrics

View source

format_metrics(
    logs={}, factor=1
)

Format metrics in logs into a string.

Args
logs dictionary of metrics and their values. Defaults to empty dictionary.
factor int

The factor we want to divide the metrics in logs by, useful when we are computing the logs after each batch. Defaults to 1.

Returns
metrics_string a string displaying metrics using the given formators passed in through the constructor.

get_config

View source

get_config()

set_model

set_model(
    model
)

set_params

set_params(
    params
)