问题描述
Traceback (most recent call last):
File "E:\PythonProjects\cotton5\main.py", line 19, in <module>
train.start()
File "E:\PythonProjects\cotton5\train.py", line 38, in start
self.start_train()
File "E:\PythonProjects\cotton5\train.py", line 80, in start_train
history = self.model_3.fit(
File "D:\Anaconda3\envs\tensorflow\lib\site-packages\tensorflow\python\keras\engine\training.py", line 1189, in fit
tmp_logs = self.train_function(iterator)
File "D:\Anaconda3\envs\tensorflow\lib\site-packages\tensorflow\python\util\traceback_utils.py", line 153, in error_handler
raise e.with_traceback(filtered_tb) from None
File "D:\Anaconda3\envs\tensorflow\lib\site-packages\tensorflow\python\framework\func_graph.py", line 1147, in autograph_handler
raise e.ag_error_metadata.to_exception(e)
ValueError: in user code:
ValueError: slice index 0 of dimension 0 out of bounds. for '{{node strided_slice}} = StridedSlice[Index=DT_INT32, T=DT_INT32, begin_mask=0, ellipsis_mask=0, end_mask=0, new_axis_mask=0, shrink_axis_mask=1](Shape, strided_slice/stack, strided_slice/stack_1, strided_slice/stack_2)' with input shapes: [0], [1], [1], [1] and with computed input tensors: input[1] = <0>, input[2] = <1>, input[3] = <1>.
（初学tensorflow，选择学习tensorflow2，折腾来去，遇到问题一大把，突然想到可以记录一下。）
寻找相关
在github上找到相关问题，链接：Error: slice index 0 of dimension 0 out of bounds #34850
经过仔细查看，受到如下图的一个回复启发：
得知该错误可能与batch_size有关，才想起来在写初始化数据集时删掉了类似方法调用.batch(batch_size)，所以当前代码如下：
self.ds_train = ds_train.map(preprocess).shuffle(1000).prefetch(AUTOTUNE).repeat()
修改过后：
self.ds_train = ds_train.map(preprocess).batch(self.batch_size).shuffle(1000).prefetch(AUTOTUNE).repeat()
这样就解决了。
到目前为止，我只大概知道batch_size与数据集图片有关，反正不能超过各个类别中的最少图片数的最小。
总结
DataSet数据集添加一个.batch(self.batch_size)的调用。
