Nishtha Varshney
07/14/2021, 4:39 PMKevin Kho
Kevin Kho
flow.visualize
?Nishtha Varshney
07/14/2021, 4:49 PMKevin Kho
Nishtha Varshney
07/14/2021, 4:53 PMKevin Kho
Nishtha Varshney
07/14/2021, 5:06 PMMARKDOWN2="""
Summary : {Summary}
"""
@task
def model(x_train,y_train,x_test,y_test):
num_classes = 10
input_shape = (28, 28, 1)
model = tensorflow.keras.Sequential(
[
tensorflow.keras.Input(shape=input_shape),
tensorflow.keras.layers.Conv2D(32, kernel_size=(3, 3), activation="relu"),
tensorflow.keras.layers.MaxPooling2D(pool_size=(2, 2)),
tensorflow.keras.layers.Conv2D(64, kernel_size=(3, 3), activation="relu"),
tensorflow.keras.layers.MaxPooling2D(pool_size=(2, 2)),
tensorflow.keras.layers.Flatten(),
tensorflow.keras.layers.Dropout(0.5),
tensorflow.keras.layers.Dense(num_classes, activation="softmax"),
]
)
logger = prefect.context.get("logger")
<http://logger.info|logger.info>(model.summary())
prefect.artifacts.create_markdown(MARKDOWN2.format(Summary=model.summary()))
Nishtha Varshney
07/14/2021, 5:06 PMNishtha Varshney
07/14/2021, 5:07 PMKevin Kho
model.summary()
? Is it None because training didn’t happen yet? Or is summary supposed to print the layers?Nishtha Varshney
07/14/2021, 6:08 PMKevin Kho
Nishtha Varshney
07/15/2021, 5:24 PMKevin Kho
model.summary()
returns a dataframe?Nishtha Varshney
07/15/2021, 5:30 PMNishtha Varshney
07/15/2021, 5:37 PMstringlist = []
model.summary(print_fn=lambda x: stringlist.append(x))
short_model_summary = "\n".join(stringlist)
I used this code to convert it into a stringKevin Kho