PyTorch

Model summary in PyTorch similar to model.summary() in Keras

Keras style model.summary() in PyTorch

Keras has a neat API to view the visualization of the model which is very helpful while debugging your network. Here is a barebone code to try and mimic the same in PyTorch. The aim is to provide information complementary to, what is not provided by print(your_model) in PyTorch.

Usage

  • pip install torchsummary or
  • git clone https://github.com/sksq96/pytorch-summary
from torchsummary import summary
summary(your_model, input_size=(channels, H, W))
  • Note that the input_size is required to make a forward pass through the network.

Examples

CNN for MNIST

import torch

import torch.nn as nn

import torch.nn.functional as F

from torchsummary import summary


class Net(nn.Module):

    def __init__(self):

        super(Net, self).__init__()

        self.conv1 = nn.Conv2d(1, 10, kernel_size=5)

        self.conv2 = nn.Conv2d(10, 20, kernel_size=5)

        self.conv2_drop = nn.Dropout2d()

        self.fc1 =


 


 




 


To finish reading, please visit source site