我在构建一个多类别CNN模型时，无法编译模型，因为出现了损失形状错误。

• 输出层和标签都应该有正确的形状；标签应为(m, 1, 3)，而最终的全连接层应包含3个神经元，并使用softmax激活函数
• 损失函数为’categorical_crossentropy’

导致以下错误信息：

Traceback (most recent call last):  File "train.py", line 70, in <module>    model.fit(X, y, batch_size=batch_size, epochs=10, verbose=2, use_multiprocessing=True)  File "/home/554282/.local/lib/python3.6/site-packages/tensorflow_core/python/keras/engine/training.py", line 819, in fit    use_multiprocessing=use_multiprocessing)  File "/home/554282/.local/lib/python3.6/site-packages/tensorflow_core/python/keras/engine/training_v2.py", line 235, in fit    use_multiprocessing=use_multiprocessing)  File "/home/554282/.local/lib/python3.6/site-packages/tensorflow_core/python/keras/engine/training_v2.py", line 593, in _process_training_inputs    use_multiprocessing=use_multiprocessing)  File "/home/554282/.local/lib/python3.6/site-packages/tensorflow_core/python/keras/engine/training_v2.py", line 646, in _process_inputs    x, y, sample_weight=sample_weights)  File "/home/554282/.local/lib/python3.6/site-packages/tensorflow_core/python/keras/engine/training.py", line 2383, in _standardize_user_data    batch_size=batch_size)  File "/home/554282/.local/lib/python3.6/site-packages/tensorflow_core/python/keras/engine/training.py", line 2489, in _standardize_tensors    y, self._feed_loss_fns, feed_output_shapes)  File "/home/554282/.local/lib/python3.6/site-packages/tensorflow_core/python/keras/engine/training_utils.py", line 810, in check_loss_and_target_compatibility    ' while using as loss `' + loss_name + '`. 'ValueError: A target array with shape (8, 1, 3) was passed for an output of shape (None, 3) while using as loss `categorical_crossentropy`. This loss expects targets to have the same shape as the output.

回答：

custom_one_hot函数返回一个[M, 1, 3]数组。你应该将其重塑为[M, 3]，因为CNN的输出是[M, 3]。这里的M是批量大小。