Add transformer counter to profile #149
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Contributor
HaoKang-Timmy
commented
Oct 7, 2021
•
HaoKang-Timmy
commented
- add transformer counter to rnn_hooks.py
- provide evaluate_transformer.py as an example
count_Transformer for nn.Transformer
The answer is 2.76945964418343e+25 44151808.0.
no embeding ** 2
For one word, about 25G flops and 44M parameters
Lyken17
reviewed
Oct 11, 2021
benchmark/evaluate_transformer.py
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| src = torch.rand((1, 1, 10)) # S,N,x | ||
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| class Model_transformer(nn.Module): |
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Class name should be CamelCased.
Lyken17
reviewed
Oct 11, 2021
thop/profile.py
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| @@ -67,7 +67,7 @@ def prYellow(skk): fprint("\033[93m{}\033[00m".format(skk)) | |||
| nn.RNN: count_rnn, | |||
| nn.GRU: count_gru, | |||
| nn.LSTM: count_lstm, | |||
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| nn.Transformer: count_Transformer, | |||
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function name should be lower case.
Lyken17
reviewed
Oct 11, 2021
thop/rnn_hooks.py
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| @@ -196,3 +196,84 @@ def count_lstm(m: nn.LSTM, x, y): | |||
| total_ops *= batch_size | |||
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| m.total_ops += torch.DoubleTensor([int(total_ops)]) | |||
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| def count_Transformer(m: nn.Transformer, x, y): | |||
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fixed, also changed its subfunction, sorry for forgeting changing it after learning camelcase
added 2 commits
October 13, 2021 20:46
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why not merge this pull? It is very necessary to calculate the flops and prams of transformer. |
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Is there any update now |
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