Keras transfer learning

inputs = keras.Input(shape=(150, 150, 3))
# We make sure that the base_model is running in inference mode here,
# by passing `training=False`. This is important for fine-tuning, as you will
# learn in a few paragraphs.
x = base_model(inputs, training=False)
# Convert features of shape `base_model.output_shape[1:]` to vectors
# Use golbal averaging pool instead of flatten in some cases
x = keras.layers.GlobalAveragePooling2D()(x)
# A Dense classifier with a single unit (binary classification)
outputs = keras.layers.Dense(1)(x)
model = keras.Model(inputs, outputs)

Source: keras.io

Similar codes

7 votes174 views3 answers
Get char of string python
Python
0 vote183 views1 answer
Python program to multiply two numbers and multiply the answer with 2nd variables
Python
16 votes183 views3 answers
Python empty text file
Python
0 vote179 views1 answer
Python setter getter deleter
Python
2 votes180 views2 answers
Poetry add specific version
Python
7 votes184 views3 answers
Pandas empty dataframe with column names
Python
12 votes191 views6 answers
Python flask
Python
0 vote175 views2 answers
Openpyxl _cells_by_row
Python
111 votes171 views6 answers
Python while loop
Python
3 votes166 views2 answers
Python 3.7.9 download
Python