This tool for Pytorch can analyze your model.
Information include layer memory usage, max memory usage, cumulative memory usage and execution time.
pytorch
matplotlib (python -m pip install -U matplotlib)
No. Layer_memory Max_memory Memory Exec_time Layer
Initial---------------------------------------------------------------------------------------------------
0 61.18 MB 118.39 MB 61.18 MB 3971.82 us Input, label etc.
Forward---------------------------------------------------------------------------------------------------
1 6400.00 kB 87.13 MB 67.43 MB 97.75 us Conv2d(3, 32, kernel_size=(3,
2 6400.00 kB 73.68 MB 73.68 MB 29.56 us LeakyReLU(negative_slope=0.01)
3 6400.00 kB 79.93 MB 79.93 MB 52.21 us BatchNorm2d(32, eps=1e-05, mom
4 4800.00 kB 84.62 MB 84.62 MB 34.57 us MaxPool2d(kernel_size=2, strid
5 3200.00 kB 101.52 MB 87.74 MB 77.01 us Conv2d(32, 64, kernel_size=(3,
6 3200.00 kB 90.87 MB 90.87 MB 25.99 us LeakyReLU(negative_slope=0.01)
7 3200.00 kB 93.99 MB 93.99 MB 44.82 us BatchNorm2d(64, eps=1e-05, mom
8 2400.00 kB 96.34 MB 96.34 MB 30.04 us MaxPool2d(kernel_size=2, strid
9 1600.00 kB 123.90 MB 97.90 MB 87.50 us Conv2d(64, 128, kernel_size=(3
10 1600.00 kB 99.46 MB 99.46 MB 25.27 us LeakyReLU(negative_slope=0.01)
11 1600.00 kB 101.02 MB 101.02 MB 43.15 us BatchNorm2d(128, eps=1e-05, mo
12 800.00 kB 101.81 MB 101.81 MB 67.95 us Conv2d(128, 64, kernel_size=(1
13 800.00 kB 102.59 MB 102.59 MB 25.27 us LeakyReLU(negative_slope=0.01)
14 800.00 kB 103.37 MB 103.37 MB 42.92 us BatchNorm2d(64, eps=1e-05, mom
15 1600.00 kB 130.93 MB 104.93 MB 75.82 us Conv2d(64, 128, kernel_size=(3
16 1600.00 kB 106.49 MB 106.49 MB 25.03 us LeakyReLU(negative_slope=0.01)
17 1600.00 kB 108.06 MB 108.06 MB 42.20 us BatchNorm2d(128, eps=1e-05, mo
18 1200.00 kB 109.23 MB 109.23 MB 29.80 us MaxPool2d(kernel_size=2, strid
19 3125.00 kB 112.28 MB 112.28 MB 72.24 us Conv2d(128, 1000, kernel_size=
20 3125.00 kB 115.33 MB 115.33 MB 24.80 us LeakyReLU(negative_slope=0.01)
21 3125.00 kB 118.38 MB 118.38 MB 43.39 us BatchNorm2d(1000, eps=1e-05, m
22 0.00 kB 118.38 MB 118.38 MB 18.60 us Flatten()
23 2.00 kB 118.39 MB 118.39 MB 66.52 us Linear(in_features=16000, out_
24 2.00 kB 118.39 MB 118.39 MB 25.27 us LeakyReLU(negative_slope=0.01)
- Every layer memory usage
- Total memory usage (cumulative memory usage)
- Every layer execution time
- Import Pytorch_Analyzer in your code
from pytorch_analyzer import Pytorch_Analyzer- Construct Pytorch_Analyzer and input your model.
analyzer = Pytorch_Analyzer(Your_model)- Print the analysis.
analyzer.analysis()- Plot the analysis
analyzer.analysis_plot()https://pytorch.org/docs/stable/cuda.html
https://pytorch.org/tutorials/beginner/former_torchies/nnft_tutorial.html
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