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
im getting the following error after epoch 15 is finished in this codeblock:
im using this container: ghcr.io/fastmachinelearning/hls4ml-tutorial/hls4ml-0.8.0-vivado-2019.1