learning/annotated_deep_learning_paper_implementations
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update torch

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Varuna Jayasiri
2021-10-29 09:05:59 +05:30
parent 3a6f8e9135
commit 6cd0ed168e
3 changed files with 9 additions and 5 deletions
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3
labml_nn/experiments/nlp_classification.py
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@ -15,6 +15,7 @@ import torch
import torchtext import torchtext
from torch import nn from torch import nn
from torch.utils.data import DataLoader from torch.utils.data import DataLoader
import torchtext.vocab
from torchtext.vocab import Vocab from torchtext.vocab import Vocab
from labml import lab, tracker, monit from labml import lab, tracker, monit
@ -270,7 +271,7 @@ def ag_news(c: NLPClassificationConfigs):
for (label, line) in valid: for (label, line) in valid:
counter.update(tokenizer(line)) counter.update(tokenizer(line))
# Create vocabulary # Create vocabulary
vocab = Vocab(counter, min_freq=1) vocab = torchtext.vocab.vocab(counter, min_freq=1)
# Create training data loader # Create training data loader
train_loader = DataLoader(train, batch_size=c.batch_size, shuffle=True, train_loader = DataLoader(train, batch_size=c.batch_size, shuffle=True,

7
requirements.txt
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@ -1,8 +1,9 @@
torch>=1.7 torch>=1.10
torchvision>=0.11
torchtext>=0.11
labml>=0.4.133 labml>=0.4.133
labml-helpers>=0.4.84 labml-helpers>=0.4.84
torchvision numpy>=1.19
numpy>=1.16.3
matplotlib>=3.0.3 matplotlib>=3.0.3
einops>=0.3.0 einops>=0.3.0
gym[atari] gym[atari]

4
setup.py
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@ -5,7 +5,7 @@ with open("readme.md", "r") as f:
setuptools.setup( setuptools.setup(
name='labml-nn', name='labml-nn',
version='0.4.116', version='0.4.117',
author="Varuna Jayasiri, Nipun Wijerathne", author="Varuna Jayasiri, Nipun Wijerathne",
author_email="vpjayasiri@gmail.com, hnipun@gmail.com", author_email="vpjayasiri@gmail.com, hnipun@gmail.com",
description="🧑‍🏫 Implementations/tutorials of deep learning papers with side-by-side notes 📝; including transformers (original, xl, switch, feedback, vit), optimizers (adam, radam, adabelief), gans(dcgan, cyclegan, stylegan2), 🎮 reinforcement learning (ppo, dqn), capsnet, distillation, etc. 🧠", description="🧑‍🏫 Implementations/tutorials of deep learning papers with side-by-side notes 📝; including transformers (original, xl, switch, feedback, vit), optimizers (adam, radam, adabelief), gans(dcgan, cyclegan, stylegan2), 🎮 reinforcement learning (ppo, dqn), capsnet, distillation, etc. 🧠",
@ -23,6 +23,8 @@ setuptools.setup(
install_requires=['labml>=0.4.133', install_requires=['labml>=0.4.133',
'labml-helpers>=0.4.84', 'labml-helpers>=0.4.84',
'torch', 'torch',
'torchtext',
'torchvision',
'einops', 'einops',
'numpy'], 'numpy'],
classifiers=[ classifiers=[