Loads a model saved via model.save()
.
tf.keras.models.load_model(
filepath, custom_objects=None, compile=True, safe_mode=True
)
Used in the notebooks
Used in the guide | Used in the tutorials |
---|---|
Returns | |
---|---|
A Keras model instance. If the original model was compiled,
and the argument compile=True is set, then the returned model
will be compiled. Otherwise, the model will be left uncompiled.
|
Example:
model = keras.Sequential([
keras.layers.Dense(5, input_shape=(3,)),
keras.layers.Softmax()])
model.save("model.keras")
loaded_model = keras.saving.load_model("model.keras")
x = np.random.random((10, 3))
assert np.allclose(model.predict(x), loaded_model.predict(x))
Note that the model variables may have different name values
(var.name
property, e.g. "dense_1/kernel:0"
) after being reloaded.
It is recommended that you use layer attributes to
access specific variables, e.g. model.get_layer("dense_1").kernel
.