Dense layer
Dense is the only actual network layer in that model.
A Dense layer feeds all outputs from the previous layer to all its neurons, each neuron providing one output to the next layer.
It's the most basic layer in neural networks.
A Dense(10) has ten neurons. A Dense(512) has 512 neurons.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)densenet python keras
tf.keras.applications.DenseNet169(
include_top=True,
weights="imagenet",
input_tensor=None,
input_shape=None,
pooling=None,
classes=1000,
)Copyright © 2021 Codeinu
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