jeasinema
/ weight_init.py
Last active
July 30, 2024 16:35
A simple script for parameter initialization for PyTorch
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| #!/usr/bin/env python | |
| # -*- coding:UTF-8 -*- | |
| import torch | |
| import torch.nn as nn | |
| import torch.nn.init as init | |
| def weight_init(m): | |
| ''' |
Tushar-N
/ pad_packed_demo.py
Last active
October 27, 2024 15:17
How to use pad_packed_sequence in pytorch<1.1.0
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| import torch | |
| import torch.nn as nn | |
| from torch.nn.utils.rnn import pack_padded_sequence, pad_packed_sequence | |
| seqs = ['gigantic_string','tiny_str','medium_str'] | |
| # make <pad> idx 0 | |
| vocab = ['<pad>'] + sorted(set(''.join(seqs))) | |
| # make model |
karpathy
/ pg-pong.py
Created
May 30, 2016 22:50
Training a Neural Network ATARI Pong agent with Policy Gradients from raw pixels
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| """ Trains an agent with (stochastic) Policy Gradients on Pong. Uses OpenAI Gym. """ | |
| import numpy as np | |
| import cPickle as pickle | |
| import gym | |
| # hyperparameters | |
| H = 200 # number of hidden layer neurons | |
| batch_size = 10 # every how many episodes to do a param update? | |
| learning_rate = 1e-4 | |
| gamma = 0.99 # discount factor for reward |