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emilwallner / Screenshot-to-code

A neural network that transforms a design mock-up into a static website.

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Bootstrap generator not working on Google Colab (Keras 2.4, Tensorflow 2.3.0)

ScruffySilky opened this issue · comments

commented

This error only happens on the data generator in the bootstrap_generator file. Bootstrap version trains but it cant take a dataset larger than 25 files due to memory error making it practically useless. Gist here: https://colab.research.google.com/gist/amahendrakar/39db0b14bce096a12d6f4c9961f687de/42038.ipynb
Error I get

ValueError                                
Traceback (most recent call last)
<ipython-input-4-6927891f43ca> in <module>()
  1 # test the data generator
  2 generator = data_generator(texts, train_features, 1, max_sequence)
----> 3 loaded_model.fit_generator(generator, steps_per_epoch=steps, epochs=5, callbacks=callbacks_list, verbose=1)
  4 loaded_model.save(mydrive + '/output/weights.hdf5')

12 frames
/usr/local/lib/python3.6/dist-packages/tensorflow/python/framework/func_graph.py in wrapper(*args, **kwargs)
971           except Exception as e:  # pylint:disable=broad-except
972             if hasattr(e, "ag_error_metadata"):
--> 973               raise e.ag_error_metadata.to_exception(e)
974             else:
975               raise

ValueError: in user code:

/usr/local/lib/python3.6/dist-packages/tensorflow/python/keras/engine/training.py:806 train_function  *
    return step_function(self, iterator)
/usr/local/lib/python3.6/dist-packages/tensorflow/python/keras/engine/training.py:796 step_function  **
    outputs = model.distribute_strategy.run(run_step, args=(data,))
/usr/local/lib/python3.6/dist-packages/tensorflow/python/distribute/distribute_lib.py:1211 run
    return self._extended.call_for_each_replica(fn, args=args, kwargs=kwargs)
/usr/local/lib/python3.6/dist-packages/tensorflow/python/distribute/distribute_lib.py:2585 call_for_each_replica
    return self._call_for_each_replica(fn, args, kwargs)
/usr/local/lib/python3.6/dist-packages/tensorflow/python/distribute/distribute_lib.py:2945 _call_for_each_replica
    return fn(*args, **kwargs)
/usr/local/lib/python3.6/dist-packages/tensorflow/python/keras/engine/training.py:789 run_step  **
    outputs = model.train_step(data)
/usr/local/lib/python3.6/dist-packages/tensorflow/python/keras/engine/training.py:757 train_step
    self.trainable_variables)
/usr/local/lib/python3.6/dist-packages/tensorflow/python/keras/engine/training.py:2737 _minimize
    trainable_variables))
/usr/local/lib/python3.6/dist-packages/tensorflow/python/keras/optimizer_v2/optimizer_v2.py:562 _aggregate_gradients
    filtered_grads_and_vars = _filter_grads(grads_and_vars)
/usr/local/lib/python3.6/dist-packages/tensorflow/python/keras/optimizer_v2/optimizer_v2.py:1271 _filter_grads
    ([v.name for _, v in grads_and_vars],))

ValueError: No gradients provided for any variable: ['embedding_1/embeddings:0', 'lstm_1/lstm_cell/kernel:0', 'lstm_1/lstm_cell/recurrent_kernel:0', 'lstm_1/lstm_cell/bias:0', 'conv2d_1/kernel:0', 'conv2d_1/bias:0', 'conv2d_2/kernel:0', 'conv2d_2/bias:0', 'conv2d_3/kernel:0', 'conv2d_3/bias:0', 'conv2d_4/kernel:0', 'conv2d_4/bias:0', 'conv2d_5/kernel:0', 'conv2d_5/bias:0', 'conv2d_6/kernel:0', 'conv2d_6/bias:0', 'conv2d_7/kernel:0', 'conv2d_7/bias:0', 'dense_1/kernel:0', 'dense_1/bias:0', 'dense_2/kernel:0', 'dense_2/bias:0', 'lstm_2/lstm_cell_1/kernel:0', 'lstm_2/lstm_cell_1/recurrent_kernel:0', 'lstm_2/lstm_cell_1/bias:0', 'lstm_3/lstm_cell_2/kernel:0', 'lstm_3/lstm_cell_2/recurrent_kernel:0', 'lstm_3/lstm_cell_2/bias:0', 'lstm_4/lstm_cell_3/kernel:0', 'lstm_4/lstm_cell_3/recurrent_kernel:0', 'lstm_4/lstm_cell_3/bias:0', 'dense_3/kernel:0', 'dense_3/bias:0'].