北大跨平台开源的深度学习框架TensorLayerX来了！且团队在招募中，后附联系方式

pip3 install tensorlayerx#==0.5.2

import osos.environ['TL_BACKEND'] = 'tensorflow'# os.environ['TL_BACKEND'] = 'mindspore'# os.environ['TL_BACKEND'] = 'paddle'

#Linuxexport TL_BACKEND= 'tensorflow'#Windowsset TL_BACKEND= 'tensorflow'

    
from tensorlayerx.nn import Moduleimport tensorlayerx as tlxfrom tensorlayerx.nn import (Conv2d, Linear, Flatten, MaxPool2d, BatchNorm2d)
class CNN(Module):
def __init__(self):super(CNN, self).__init__()self.conv1 = Conv2d(64, (5, 5), (1, 1), padding='SAME', W_init=W_init, b_init=None, name='conv1', in_channels=3)self.bn = BatchNorm2d(num_features=64, act=tlx.ReLU)self.maxpool1 = MaxPool2d((3, 3), (2, 2), padding='SAME', name='pool1')
self.conv2 = Conv2d(64, (5, 5), (1, 1), padding='SAME', act=tlx.ReLU, W_init=W_init, b_init=None, name='conv2', in_channels=64        )self.maxpool2 = MaxPool2d((3, 3), (2, 2), padding='SAME', name='pool2')
self.flatten = Flatten(name='flatten')self.linear1 = Linear(384, act=tlx.ReLU, W_init=W_init2, b_init=b_init2, name='linear1relu', in_features=2304)self.linear2 = Linear(192, act=tlx.ReLU, W_init=W_init2, b_init=b_init2, name='linear2relu', in_features=384)self.linear3 = Linear(10, act=None, W_init=W_init2, name='output', in_features=192)
def forward(self, x):        z = self.conv1(x)        z = self.bn(z)        z = self.maxpool1(z)        z = self.conv2(z)        z = self.maxpool2(z)        z = self.flatten(z)        z = self.linear1(z)        z = self.linear2(z)        z = self.linear3(z)        return z