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

3 votes155 views1 answer
Get all indices of a value in list python
Python
1 vote173 views1 answer
Check odd numbers numpy
Python
0 vote148 views1 answer
Zipped hackerrank solution
Python
-3 votes168 views1 answer
How to install chatterbot from github
Python
16 votes148 views6 answers
Map in python 3
Python
1 vote147 views3 answers
Django reverse
Python
0 vote154 views1 answer
Ion Flux Relabeling
Python
0 vote161 views2 answers
Python sort isdigit
Python
6 votes193 views3 answers
Messages django
Python Django
9 votes168 views1 answer
Drop the last row of a dataframe
Python