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Apply PEP 8 formatting to transformer_tutorial.py imports #1014

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Merged
merged 3 commits into from
Apr 23, 2021
Merged

Apply PEP 8 formatting to transformer_tutorial.py imports #1014

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a7be5f0
Format imports according to PEP8
jgerityneurala Jun 5, 2020
ab7d5c5
Merge branch 'master' into patch-1
holly1238 Apr 21, 2021
be23f3f
Merge branch 'master' into patch-1
holly1238 Apr 23, 2021
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6 changes: 4 additions & 2 deletions beginner_source/transformer_tutorial.py
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Original file line number Diff line number Diff line change
Expand Up @@ -45,15 +45,16 @@
#

import math

import torch
import torch.nn as nn
import torch.nn.functional as F
from torch.nn import TransformerEncoder, TransformerEncoderLayer

class TransformerModel(nn.Module):

def __init__(self, ntoken, ninp, nhead, nhid, nlayers, dropout=0.5):
super(TransformerModel, self).__init__()
from torch.nn import TransformerEncoder, TransformerEncoderLayer
self.model_type = 'Transformer'
self.pos_encoder = PositionalEncoding(ninp, dropout)
encoder_layers = TransformerEncoderLayer(ninp, nhead, nhid, dropout)
Expand Down Expand Up @@ -251,12 +252,13 @@ def get_batch(source, i):
# function to scale all the gradient together to prevent exploding.
#

import time

criterion = nn.CrossEntropyLoss()
lr = 5.0 # learning rate
optimizer = torch.optim.SGD(model.parameters(), lr=lr)
scheduler = torch.optim.lr_scheduler.StepLR(optimizer, 1.0, gamma=0.95)

import time
def train():
model.train() # Turn on the train mode
total_loss = 0.
Expand Down