I was running the sketch_rnn.ipynb on my jupyter notebook, upon loading the environment to load the trained dataset, it returned an error 'Object arrays cannot be loaded when allow_pickle=False'
This is the code already used by google developers in developing the sketch_rnn algorithm that was even run in the google colab. In the past i have ran it myself on the google colab it worked but seems not to be working on my own jupyter notebook
from magenta.models.sketch_rnn.sketch_rnn_train import *
from magenta.models.sketch_rnn.model import *
from magenta.models.sketch_rnn.utils import *
from magenta.models.sketch_rnn.rnn import *
model_params.batch_size = 1
eval_model_params = sketch_rnn_model.copy_hparams(model_params)
eval_model_params.use_input_dropout = 0
eval_model_params.use_recurrent_dropout = 0
eval_model_params.use_output_dropout = 0
eval_model_params.is_training = 0
sample_model_params = sketch_rnn_model.copy_hparams(eval_model_params)
sample_model_params.max_seq_len = 1
return [model_params, eval_model_params, sample_model_params]
[train_set, valid_set, test_set, hps_model, eval_hps_model,
sample_hps_model] = load_env_compatible(data_dir, model_dir)
i expected the output to be
INFO:tensorflow:Downloading http://github.com/hardmaru/sketch-rnn-
datasets/raw/master/aaron_sheep/aaron_sheep.npz
INFO:tensorflow:Loaded 7400/300/300 from aaron_sheep.npz
INFO:tensorflow:Dataset combined: 8000 (7400/300/300), avg len 125
INFO:tensorflow:model_params.max_seq_len 250.
total images <= max_seq_len is 7400
total images <= max_seq_len is 300
total images <= max_seq_len is 300
INFO:tensorflow:normalizing_scale_factor 18.5198.
But it gave me
ValueError: Object arrays cannot be loaded when allow_pickle=False
Use allow_pickle=True as one of the arguments to np.load().
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