在使用 CNN的时候，报错： TypeError: ('Keyword argument not understood:', 'padding')
将“padding”改为“border_mode”，即可：
原因：padding 是Keras 2.X的语法，而我的PC安装的是 Keras 1.X版本。
二者的API 有一些地方是有变化的。
如下：（从 1.X 到 2.X ）
========【Models】
1、Constructor arguments for Model have been renamed：
- input -> inputs
- output -> outputs
2、The Sequential model not longer supports the set_input method.
3、For any model saved with Keras 2.0 or higher, weights trained with backend X will be converted to work with backend Y without any manual conversion step.
========【Layers】
1、Dense layer
- Changed interface：
- output_dim -> units
- init -> kernel_initializer
- added bias_initializer argument
- W_regularizer -> kernel_regularizer
- b_regularizer -> bias_regularizer
- b_constraint -> bias_constraint
- bias -> use_bias
2、Embedding
Convolutional layers ：
Interface changes common to all convolutional layers：
- nb_filter -> filters
- float kernel dimension arguments become a single tuple argument, kernel size. E.g. a legacy call Conv2D(10, 3, 3) becomes Conv2D(10, (3, 3))
- kernel_size can be set to an integer instead of a tuple, e.g. Conv2D(10, 3) is equivalent toConv2D(10, (3, 3)).
- subsample -> strides. Can also be set to an integer.
- border_mode -> padding
- init -> kernel_initializer
- added bias_initializer argument
- W_regularizer -> kernel_regularizer
- b_regularizer -> bias_regularizer
- b_constraint -> bias_constraint
- bias -> use_bias
- dim_ordering -> data_format
- In the SeparableConv2D layers, init is split into depthwise_initializer andpointwise_initializer.
- Added dilation_rate argument in Conv2D and Conv1D.
- 1D convolution kernels are now saved as a 3D tensor (instead of 4D as before).
- 2D and 3D convolution kernels are now saved in format spatial_dims + (input_depth, depth)), even with data_format="channels_first".
3、Pooling1D
pool_length->pool_sizestride->stridesborder_mode->padding
4、Pooling2D，3D
border_mode->paddingdim_ordering->data_format
【Reference】
1、Keras 2.x和1.x的区别 ：https://blog.csdn.net/ch1209498273/article/details/78287145
2、Keras 官方发布的 ：Keras 2.0 release notes ：https://github.com/keras-team/keras/wiki/Keras-2.0-release-notes