gan/utils/inference_utils.py [23:61]:
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def load_melody_samples(n_sample=10):    
    """Load the samples used for evaluation."""
    
    sample_source_path = './dataset/eval.npy'
    
    data = np.load(sample_source_path)
    data = np.asarray(data, dtype=np.float32) # {-1, 1}

    random_idx = np.random.choice(len(data), n_sample, replace=False)
    
    sample_x = data[random_idx]

    sample_z = tf.random.truncated_normal((n_sample, 2, 8, 512))
    
    print("Loaded {} melody samples".format(len(sample_x)))

    return sample_x, sample_z

# --- Training ------------------------------------------------------------------

def generate_pianoroll(generator, conditioned_track, noise_vector=None):
    if noise_vector == None:
        noise_vector = tf.random.truncated_normal((1, 2, 8, 512))
    return generator((conditioned_track, noise_vector), training=False)


def generate_midi(generator, saveto_dir, input_midi_file='./Experiments/data/happy_birthday_easy.mid'):
    conditioned_track = midi_utils.get_conditioned_track(midi=input_midi_file)
    generated_pianoroll = generate_pianoroll(generator, conditioned_track)
    
    destination_path = path_utils.new_temp_midi_path(saveto_dir=saveto_dir)
    midi_utils.save_pianoroll_as_midi(generated_pianoroll.numpy(), destination_path=destination_path)
    return destination_path
    
def show_generated_pianorolls(generator, eval_dir, input_midi_file='./Experiments/data/happy_birthday_easy.mid', n_pr = 4):    
    conditioned_track = midi_utils.get_conditioned_track(midi=input_midi_file)
    for i in range(n_pr):
        generated_pianoroll = generate_pianoroll(generator, conditioned_track)
        display_utils.show_pianoroll(generated_pianoroll)
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reinvent-labs/lab-2/utils/inference_utils.py [23:61]:
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def load_melody_samples(n_sample=10):    
    """Load the samples used for evaluation."""
    
    sample_source_path = './dataset/eval.npy'
    
    data = np.load(sample_source_path)
    data = np.asarray(data, dtype=np.float32) # {-1, 1}

    random_idx = np.random.choice(len(data), n_sample, replace=False)
    
    sample_x = data[random_idx]

    sample_z = tf.random.truncated_normal((n_sample, 2, 8, 512))
    
    print("Loaded {} melody samples".format(len(sample_x)))

    return sample_x, sample_z

# --- Training ------------------------------------------------------------------

def generate_pianoroll(generator, conditioned_track, noise_vector=None):
    if noise_vector == None:
        noise_vector = tf.random.truncated_normal((1, 2, 8, 512))
    return generator((conditioned_track, noise_vector), training=False)


def generate_midi(generator, saveto_dir, input_midi_file='./Experiments/data/happy_birthday_easy.mid'):
    conditioned_track = midi_utils.get_conditioned_track(midi=input_midi_file)
    generated_pianoroll = generate_pianoroll(generator, conditioned_track)
    
    destination_path = path_utils.new_temp_midi_path(saveto_dir=saveto_dir)
    midi_utils.save_pianoroll_as_midi(generated_pianoroll.numpy(), destination_path=destination_path)
    return destination_path
    
def show_generated_pianorolls(generator, eval_dir, input_midi_file='./Experiments/data/happy_birthday_easy.mid', n_pr = 4):    
    conditioned_track = midi_utils.get_conditioned_track(midi=input_midi_file)
    for i in range(n_pr):
        generated_pianoroll = generate_pianoroll(generator, conditioned_track)
        display_utils.show_pianoroll(generated_pianoroll)
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