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Generating notes for breakitoff
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0.018300232973530228
Traceback (most recent call last):
  File "C:\dev\StepCOVNet-ef61b36bf2a30bfacb3fdd49a3a613e38d5ca548\stepmania_note_generator.py", line 154, in <module>
    stepmania_note_generator(args.input,
  File "C:\dev\StepCOVNet-ef61b36bf2a30bfacb3fdd49a3a613e38d5ca548\stepmania_note_generator.py", line 126, in stepmania_note_generator
    generate_notes(output_path, tmp_dir, stepcovnet_model, verbose_int)
  File "C:\dev\StepCOVNet-ef61b36bf2a30bfacb3fdd49a3a613e38d5ca548\stepmania_note_generator.py", line 88, in generate_notes
    pred_arrows = inference_executor.execute(input_data=inference_input)
  File "C:\dev\StepCOVNet-ef61b36bf2a30bfacb3fdd49a3a613e38d5ca548\stepcovnet\executor\InferenceExecutor.py", line 43, in execute
    encoded_arrow = np.random.choice(NUM_ARROW_TYPES, 1, p=binary_arrow_prob)[0]
  File "mtrand.pyx", line 939, in numpy.random.mtrand.RandomState.choice
ValueError: probabilities do not sum to 1

PS C:\dev\StepCOVNet-master> python stepmania_note_generator.py -i test_in -o test_out --model dataset\time2_challenge_timing_model -v 1
Loading StepCOVNet retrained model
Failed to retrieve retrained StepCOVNet model. Loading non-retrained model
Traceback (most recent call last):
  File "C:\dev\StepCOVNet-master\stepmania_note_generator.py", line 155, in <module>
    stepmania_note_generator(args.input,
  File "C:\dev\StepCOVNet-master\stepmania_note_generator.py", line 124, in stepmania_note_generator
    stepcovnet_model = StepCOVNetModel.load(input_path=model_path, retrained=False)
  File "C:\dev\StepCOVNet-master\stepcovnet\model\StepCOVNetModel.py", line 40, in load
    model = load_model(model_path, compile=compile_model)
  File "C:\Users\georg\AppData\Roaming\Python\Python39\site-packages\keras\utils\traceback_utils.py", line 70, in error_handler
    raise e.with_traceback(filtered_tb) from None
  File "C:\Users\georg\AppData\Roaming\Python\Python39\site-packages\tensorflow\python\util\nest.py", line 573, in assert_same_structure
    raise type(e)("%s\n"
ValueError: The two structures don't have the same nested structure.

First structure: type=tuple str=(({'input_ids': TensorSpec(shape=(None, 5), dtype=tf.int32, name=None)}, None, None, None, None, None, None, None, None, None, None, None, None, False), {})

Second structure: type=tuple str=((TensorSpec(shape=(None, None), dtype=tf.int32, name='input_ids'), None, TensorSpec(shape=(None, None), dtype=tf.int32, name='attention_mask'), None, None, None, None, None, None, None, None, None, None, False), {})

More specifically: Substructure "type=dict str={'input_ids': TensorSpec(shape=(None, 5), dtype=tf.int32, name=None)}" is a sequence, while substructure "type=TensorSpec str=TensorSpec(shape=(None, None), dtype=tf.int32, name='input_ids')" is not
Entire first structure:
(({'input_ids': .}, ., ., ., ., ., ., ., ., ., ., ., ., .), {})
Entire second structure:
((., ., ., ., ., ., ., ., ., ., ., ., ., .), {})

import librosa
import soundfile as sf

input_audio_data, sample_frequency = librosa.load(filename, sr=16000)
sf.write(file_output_path, input_audio_data, sample_frequency)