NN | Keras、Pytorch使用 Conv2D替换 Conv1D

Keras、Pytorch实现卷积层替换

替换方法

1. 修改输入数据维度
2. 替换对应网络层（下文所示）

Keras

input = tf.random.normal(10, 512, 1)

conv1d = tf.keras.layers.Conv1D(24, 3, strides=1, use_bias=True, data_format="channels_last")(input)

input_2d = conv1d [..., np.newaxis] # 添加一个维度

conv2d = tf.keras.layers.Conv2D(24, (3,1), strides=1, use_bias=True, data_format="channels_last")(input_2d)

结果对比

Pytorch

import torch

input = torch.randn(20, 16, 50)
conv1d = torch.nn.Conv1d(16, 33, 3, stride=1)  # Conv1d实现
    
output1d = torch.conv1d(input)

input_2d = input [..., np.newaxis] # 添加一个维度

conv2d = torch.nn.Conv2d(16, 33, (3,1), stride=1) # Conv2d实现Conv1d

output2d = conv2d(input_2d)

结果对比：