test

jobs/fashion_mnist_train/job.py

@@ -6,11 +6,14 @@
 import matplotlib.pyplot as plt
 import numpy as np
 import wandb
+
 # To load the mnist data
 from keras.datasets import fashion_mnist
+
 # importing various types of hidden layers
 from tensorflow.keras.layers import Conv2D, Dense, Flatten, MaxPooling2D
 from tensorflow.keras.models import Sequential
+
 # Adam legacy for m1/m2 macs
 from tensorflow.keras.optimizers.legacy import Adam
 from wandb.keras import WandbMetricsLogger
@@ -59,7 +62,6 @@ def train(project: Optional[str], entity: Optional[str], **kwargs: Any):
         metrics=["sparse_categorical_accuracy"],
     )
     model.summary()
-
     model.fit(
         train_X,
         train_y.astype(np.float32),