❔Question
When trying to save a custom model I get this error: raise TypeError(
TypeError: Cannot serialize object <tfts.models.informer.Informer object at 0x321c6dfd0> of type <class 'tfts.models.informer.Informer'>. To be serializable, a class must implement the get_config() method.
Additional context
def build_and_compile_model(base_model,learning_rate:float)->tf.keras.Model:
model = tf.keras.Sequential([base_model ])
if(classification_or_regression):
model.add(tf.keras.layers.Dense(total_output, activation='softmax'))
model.add(tf.keras.layers.Reshape(out_shape)),
model.compile(
optimizer=tf.keras.optimizers.Adam(learning_rate=learning_rate, clipnorm=1.0),
loss='categorical_crossentropy',
metrics=['binary_accuracy']
)
else:
model.add(tf.keras.layers.Dense(total_output, activation='linear'))
model.add(model.add(tf.keras.layers.Reshape(out_shape)))
model.compile(optimizer=tf.keras.optimizers.Adam(learning_rate=learning_rate, clipnorm=1.0),
loss=[tf.keras.losses.Huber()],
metrics=[tf.keras.metrics.MeanAbsoluteError()])
return model
def informer(input_shape,out_steps):
inputs = Input(input_shape)
config = AutoConfig.for_model("informer")
backbone = AutoModel.from_config(config, predict_sequence_length=out_steps)
outputs = backbone(inputs)
model = tf.keras.Model(inputs=inputs, outputs=outputs)
#model.compile(loss="mse", optimizer="rmsprop")
return model
❔Question
When trying to save a custom model I get this error: raise TypeError(
TypeError: Cannot serialize object <tfts.models.informer.Informer object at 0x321c6dfd0> of type <class 'tfts.models.informer.Informer'>. To be serializable, a class must implement the
get_config()method.Additional context
def build_and_compile_model(base_model,learning_rate:float)->tf.keras.Model:
def informer(input_shape,out_steps):
inputs = Input(input_shape)
config = AutoConfig.for_model("informer")
backbone = AutoModel.from_config(config, predict_sequence_length=out_steps)
outputs = backbone(inputs)
model = tf.keras.Model(inputs=inputs, outputs=outputs)
#model.compile(loss="mse", optimizer="rmsprop")
return model