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comet.py 2.13 KiB
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import tensorflow as tf
from tools.keras import PlottingCallback


class MulticlassificationConfusionMatrix(tf.keras.callbacks.Callback):
    def __init__(
        self,
        comet_experiment,
        x=None,
        y=None,
        sample_weights=None,
        batch_size=None,
        labels=None,
        freq=100,
        verbose=0,
    ):
        self.comet_experiment = comet_experiment
        self.data_x = x
        self.data_label = y
        self.data_weights = sample_weights
        self.batch_size = batch_size
        self.freq = freq
        self.labels = labels
        self.verbose = verbose

    def on_train_begin(self, logs=None):
        if self.verbose:
            print("Logging confusion matrix to comet experiment")
        pred = self.model.predict(x=self.data_x, batch_size=self.batch_size)
        self.comet_experiment.log_confusion_matrix(
            y_true=self.data_label,
            y_predicted=pred,
            labels=self.labels,
            title="Confusion Start",
            epoch=0,
            file_name="confusion-matrix-0.json",
        )

    def on_epoch_end(self, epoch, logs=None):
        if epoch % self.freq == 0 and epoch != 0:
            if self.verbose:
                print("Logging confusion matrix to comet experiment")
            pred = self.model.predict(x=self.data_x, batch_size=self.batch_size)
            self.comet_experiment.log_confusion_matrix(
                y_true=self.data_label,
                y_predicted=pred,
                labels=self.labels,
                title="Confusion Epoch {}".format(epoch),
                epoch=epoch,
                file_name="confusion-matrix-{}.json".format(epoch),
            )

    def on_train_end(self, logs=None):
        if self.verbose:
            print("Logging confusion matrix to comet experiment")
        pred = self.model.predict(x=self.data_x, batch_size=self.batch_size)
        self.comet_experiment.log_confusion_matrix(
            y_true=self.data_label,
            y_predicted=pred,
            labels=self.labels,
            title="Confusion End",
            epoch=-1,
            file_name="confusion-matrix-end.json",
        )