How to implement this part of tensorflow code in pytorch i have tried

but I am getting the “Not Implemented error”

this (ConvBNR) is subclass implemented in main class(ConvolutionNet)

```
class ConvBNR(keras.Model):
def __init__(self, ch, kernel_size=3, strides=1, padding='same'):
super(ConvBNR, self).__init__()
self.model = keras.models.Sequential([
layers.Conv2D(ch, kernel_size = kernel_size, strides=strides, padding=padding,
kernel_regularizer=tf.keras.regularizers.l2(0.01)),
layers.BatchNormalization(),
])
def call(self, x, training=None):
x = self.model(x, training=training)
return x ""
class ConvolutionNet(Model): # Vitamon network except inception layer
# Set layers.
def __init__(self, num_classes):
super (ConvolutionNetself).__init__()
# Convolution Layer with 32 filters and a kernel size of 5.
self.conv1 = ConvBNR(64)
# self.concat1 = layers.Concatenate()
# Convolution Layer with 64 filters and a kernel size of 3.
self.conv2 = ConvBNR(64)
# Max Pooling (down-sampling) with kernel size of 2 and strides of 2.
self.maxpool1 = layers.MaxPool2D(2, strides=2)
self.conv3 = ConvBNR(64, kernel_size=3)
# Max Pooling (down-sampling) with kernel size
#some others layers ....
def call(self, x, training=False):
x = self.conv1(x, training=training)
# print(x.shape)
x = self.conv2(x, training=training)
x = self.maxpool1(x)
x = self.conv3(x, training=training)
```