#1274 Add support MLFlow plugin Pull request opened by kumare3 Signed-off-by: Ketan Umare ketan.umare@gmail.com TL;DR MLFlow plugin for flytekit. Render mlflow metrics and parameters on the flyte decks. Example:

from flytekit import task, workflow
from flytekitplugins.mlflow import mlflow_autolog
import mlflow
import tensorflow as tf


@task(disable_deck=False)
@mlflow_autolog(framework=mlflow.keras)
def train_model(epochs: int):
    # Refer to <https://www.tensorflow.org/tutorials/keras/classification>
    fashion_mnist = tf.keras.datasets.fashion_mnist
    (train_images, train_labels), (_, _) = fashion_mnist.load_data()
    train_images = train_images / 255.0

    model = tf.keras.Sequential([
        tf.keras.layers.Flatten(input_shape=(28, 28)),
        tf.keras.layers.Dense(128, activation='relu'),
        tf.keras.layers.Dense(10)
    ])

    model.compile(optimizer='adam',
                  loss=tf.keras.losses.SparseCategoricalCrossentropy(from_logits=True),
                  metrics=['accuracy'])
    model.fit(train_images, train_labels, epochs=epochs)


@workflow
def ml_pipeline(epochs: int):
    train_model(epochs=epochs)


if __name__ == "__main__":
    ml_pipeline()

Type ☐ Bug Fix ☑︎ Feature ☑︎ Plugin Are all requirements met? ☑︎ Code completed ☑︎ Smoke tested ☑︎ Unit tests added ☐ Code documentation added ☐ Any pending items have an associated Issue Complete description Tracking Issue https://github.com/flyteorg/flyte/issues/ flyteorg/flytekit ✅ All checks have passed 30/30 successful checks