TypeError: int() argument must be a string, a bytes-like object or a number, not 'NoneType'

[xueyuanyuan0410]

错误如下： Traceback (most recent call last): File "example.py", line 8, in model.train(ckpt_dir='ckpt') File "/home/zy/ORGAN/ORGAN-master/organ/init.py", line 738, in train self.pretrain() File "/home/zy/ORGAN/ORGAN-master/organ/init.py", line 663, in pretrain _, g_loss, g_pred = self.generator.pretrain_step(self.sess,batch) File "/home/zy/ORGAN/ORGAN-master/organ/generator.py", line 205, in pretrain_step feed_dict={self.x: x}) File "/home/zy/.local/lib/python3.7/site-packages/tensorflow/python/client/session.py", line 968, in run run_metadata_ptr) File "/home/zy/.local/lib/python3.7/site-packages/tensorflow/python/client/session.py", line 1160, in _run np_val = np.asarray(subfeed_val, dtype=subfeed_dtype) File "/home/zy/.local/lib/python3.7/site-packages/numpy/core/_asarray.py", line 83, in asarray return array(a, dtype, copy=False, order=order) TypeError: int() argument must be a string, a bytes-like object or a number, not 'NoneType' 我找了很多教程，但没有一个教程适用于我这一种情况。我曾尝试看自己的x和batch的类型，发现他们并不是None类型的数据。我怀疑是由于tf.session.run()中的fetches是一个tf.Operation,它会返回None造成的，但我不知道怎么改。请问有遇到这种情况的吗？可以和我说一下您当时是怎么解决的吗？ 报错代码片段如下： 片段1： for epoch in t_bar: supervised_g_losses = [] self.gen_loader.reset_pointer() for it in range(self.gen_loader.num_batch): batch = self.gen_loader.next_batch() _, g_loss, g_pred = self.generator.pretrain_step(self.sess, batch) supervised_g_losses.append(g_loss) # print results mean_g_loss = np.mean(supervised_g_losses) t_bar.set_postfix(G_loss=mean_g_loss) samples = self.generate_samples(self.SAMPLE_NUM) self.mle_loader.create_batches(samples)

片段2： def pretrain_step(self, session, x): """Performs a pretraining step on the generator.""" outputs = session.run([self.pretrain_updates, self.pretrain_loss, self.g_predictions], feed_dict={self.x: x}) return outputs