Densenet python keras

Dense layer keras

>>> # Create a `Sequential` model and add a Dense layer as the first layer.  
>>> model = tf.keras.models.Sequential()
>>> model.add(tf.keras.Input(shape=(16,)))
>>> model.add(tf.keras.layers.Dense(32, activation='relu'))
>>> # Now the model will take as input arrays of shape (None, 16)  
>>> # and output arrays of shape (None, 32).  
>>> # Note that after the first layer, you don't need to specify  
>>> # the size of the input anymore:  
>>> model.add(tf.keras.layers.Dense(32))
>>> model.output_shape
(None, 32)

Source: keras.io

Densenet python keras

tf.keras.applications.DenseNet169(
    include_top=True,
    weights="imagenet",
    input_tensor=None,
    input_shape=None,
    pooling=None,
    classes=1000,
)

Source: keras.io

Similar codes

1 vote193 views1 answer
Log loss python
Python
-1 vote188 views1 answer
Smma python
Python
0 vote177 views1 answer
How to add some thing in python list
Python
0 vote184 views1 answer
Jugendwort 2019
Python
0 vote202 views1 answer
Pie chart maptlotlib larger labels
Python
0 vote184 views3 answers
How to catch ctrl c in python
Python
0 vote189 views1 answer
Rectangle function numpy
Python
0 vote251 views1 answer
Data exfiltration icmp
Python
0 vote198 views5 answers
How to count the iteration a list python
Python
1 vote233 views2 answers
How to get the number of rows and columns in a numpy array
Python