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

0 vote298 views1 answer
Crontab python
Python
3 votes286 views2 answers
Copy a 2d array in python
Python
13 votes302 views3 answers
Permutation python
Python
0 vote321 views1 answer
Python sum over specific indexes
Python
-1 vote313 views1 answer
Can only use .dt accessor with datetimelike values
Python
0 vote344 views1 answer
Python datetime add one week
Python
0 vote310 views2 answers
How to make SAPI.SpVoice say a variable in python
Python
0 vote353 views2 answers
Cronometer python
Python
0 vote308 views1 answer
Get cuda memory pytorch
Python
10 votes324 views3 answers
__name__ == '__main__'
Python