part6 autoqkeras error

[qdlmcfresh]

im getting the following error after epoch 15 is finished in this codeblock:

from qkeras.autoqkeras import AutoQKeras

autoqk = AutoQKeras(baseline_model, output_dir="autoq_cnn", metrics=["acc"], custom_objects={}, **run_config)
autoqk.fit(train_data, validation_data=val_data, epochs=15)

aqmodel = autoqk.get_best_model()
print_qmodel_summary(aqmodel)

# Train for the full epochs
callbacks = [
    tf.keras.callbacks.EarlyStopping(patience=10, verbose=1),
    tf.keras.callbacks.ReduceLROnPlateau(monitor='val_loss', factor=0.5, patience=3, verbose=1),
]

start = time.time()
history = aqmodel.fit(train_data, epochs=n_epochs, validation_data=val_data, callbacks=callbacks, verbose=1)
end = time.time()
print('\n It took {} minutes to train!\n'.format((end - start) / 60.0))

Epoch 1/15

Traceback (most recent call last):
  File "/opt/conda/lib/python3.10/site-packages/keras_tuner/src/engine/base_tuner.py", line 273, in _try_run_and_update_trial
    self._run_and_update_trial(trial, *fit_args, **fit_kwargs)
  File "/opt/conda/lib/python3.10/site-packages/keras_tuner/src/engine/base_tuner.py", line 238, in _run_and_update_trial
    results = self.run_trial(trial, *fit_args, **fit_kwargs)
  File "/opt/conda/lib/python3.10/site-packages/keras_tuner/src/engine/tuner.py", line 314, in run_trial
    obj_value = self._build_and_fit_model(trial, *args, **copied_kwargs)
  File "/opt/conda/lib/python3.10/site-packages/keras_tuner/src/engine/tuner.py", line 233, in _build_and_fit_model
    results = self.hypermodel.fit(hp, model, *args, **kwargs)
  File "/opt/conda/lib/python3.10/site-packages/keras_tuner/src/engine/hypermodel.py", line 149, in fit
    return model.fit(*args, **kwargs)
  File "/opt/conda/lib/python3.10/site-packages/keras/utils/traceback_utils.py", line 70, in error_handler
    raise e.with_traceback(filtered_tb) from None
  File "/tmp/__autograph_generated_file18rk8csp.py", line 15, in tf__train_function
    retval_ = ag__.converted_call(ag__.ld(step_function), (ag__.ld(self), ag__.ld(iterator)), None, fscope)
tensorflow.python.autograph.pyct.error_utils.MultilineMessageKeyError: in user code:

    File "/opt/conda/lib/python3.10/site-packages/keras/engine/training.py", line 1249, in train_function  *
        return step_function(self, iterator)
    File "/opt/conda/lib/python3.10/site-packages/keras/engine/training.py", line 1233, in step_function  **
        outputs = model.distribute_strategy.run(run_step, args=(data,))
    File "/opt/conda/lib/python3.10/site-packages/keras/engine/training.py", line 1222, in run_step  **
        outputs = model.train_step(data)
    File "/opt/conda/lib/python3.10/site-packages/keras/engine/training.py", line 1027, in train_step
        self.optimizer.minimize(loss, self.trainable_variables, tape=tape)
    File "/opt/conda/lib/python3.10/site-packages/keras/optimizers/optimizer_experimental/optimizer.py", line 527, in minimize
        self.apply_gradients(grads_and_vars)
    File "/opt/conda/lib/python3.10/site-packages/keras/optimizers/optimizer_experimental/optimizer.py", line 1140, in apply_gradients
        return super().apply_gradients(grads_and_vars, name=name)
    File "/opt/conda/lib/python3.10/site-packages/keras/optimizers/optimizer_experimental/optimizer.py", line 634, in apply_gradients
        iteration = self._internal_apply_gradients(grads_and_vars)
    File "/opt/conda/lib/python3.10/site-packages/keras/optimizers/optimizer_experimental/optimizer.py", line 1166, in _internal_apply_gradients
        return tf.__internal__.distribute.interim.maybe_merge_call(
    File "/opt/conda/lib/python3.10/site-packages/keras/optimizers/optimizer_experimental/optimizer.py", line 1216, in _distributed_apply_gradients_fn
        distribution.extended.update(
    File "/opt/conda/lib/python3.10/site-packages/keras/optimizers/optimizer_experimental/optimizer.py", line 1213, in apply_grad_to_update_var  **
        return self._update_step(grad, var)
    File "/opt/conda/lib/python3.10/site-packages/keras/optimizers/optimizer_experimental/optimizer.py", line 216, in _update_step
        raise KeyError(

    KeyError: 'The optimizer cannot recognize variable conv_0/kernel:0. This usually means you are trying to call the optimizer to update different parts of the model separately. Please call `optimizer.build(variables)` with the full list of trainable variables before the training loop or use legacy optimizer `tf.keras.optimizers.legacy.{self.__class__.__name__}.'

im using this container: ghcr.io/fastmachinelearning/hls4ml-tutorial/hls4ml-0.8.0-vivado-2019.1

[phucducnguyen]

I have the same problem

[phucducnguyen]

I was able to fix it by using legacy version instead
change
OPTIMIZER = tf.keras.optimizers.Adam()
to
OPTIMIZER = tf.keras.optimizers.legacy.Adam()