old resblock -> xresblock, new resblock, some refactoring

Author: ayasyrev

README.md

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 # model_constructor
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 > Constructor to create pytorch model.
 
 
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 ## How to use
 
 model = Net()
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 ```python
 model = Net()
 ```
 
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 # Resnet as example
 
 Lets create resnet18 and resnet34 (default Net() is resnet18()).
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 ```python
 resnet18 = Net(block=BasicBlock, blocks=[2, 2, 2, 2])
 ```
 
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 ```python
 resnet34 = Net(block=BasicBlock, blocks=[3, 4, 6, 3])
 ```
 
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 # Predefined Resnet models - 18, 34, 50.
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 ```python
 from model_constructor.resnet import *
 ```
 
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 ```python
 model = resnet34(num_classes=10)
 ```
 
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 ```python
 model = resnet50(num_classes=10)
 ```
 
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 # Predefined Xresnet from fastai 1.
 
 This ie simplified version from fastai v1. I did refactoring for better understand and experiment with models. For example, it's very simple to change activation funtions, different stems, batchnorm and activation order etc. In v2 much powerfull realisation.
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 ```python
 from model_constructor.xresnet import *
 ```
 
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 ```python
 model = xresnet50()
 ```
 
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 # Some examples.
 
 We can experiment with models by changing some parts of model. Here only base functionality, but it can be easily extanded.
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 ## Custom stem
 
 Stem with 3 conv layers
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 ```python
 model = Net(stem=partial(Stem, stem_sizes=[32, 32]))
 ```
 
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 ```python
 model.stem
 ```
 
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 ```python
 model = Net(stem_sizes=[32, 64])
 ```
 
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 ```python
 model.stem
 ```
 
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 ## Activation function before Normalization
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 ```python
 model = Net(bn_1st=False)
 ```
 
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 ```python
 model.stem
 ```
 
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 ## Change activation function
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 ```python
 new_act_fn = nn.LeakyReLU(inplace=True)
 ```
 
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 ```python
 model = Net(act_fn=new_act_fn)
 ```
 
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 ```python
 model.stem
 ```
 
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 ```python
 model.body.layer_0.block_0
 ```
 
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     )
 
 
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docs/_data/sidebars/home_sidebar.yml

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       title: xresnet
       url: /xresnet
     - output: web,pdf
-      title: Layers_tests
-      url: /test_layers
+      title: Title
+      url: /test_xresnet
     output: web
     title: model_constructor
   output: web