small fixes

Author: ayasyrev

README.md

@@ -25,15 +25,15 @@ And by creating constructor object, then modify it and then create model.
 
 First import constructor class, then create model constructor oject.
 
-```python
+```
 from model_constructor.net import *
 ```
 
-```python
+```
 model = Net()
 ```
 
-```python
+```
 model
 ```
 
@@ -46,7 +46,7 @@ model
 
 Now we have model consructor, defoult setting as xresnet18. And we can get model after call it.
 
-```python
+```
 model.c_in
 ```
 
@@ -57,7 +57,7 @@ model.c_in
 
 
 
-```python
+```
 model.c_out
 ```
 
@@ -68,7 +68,7 @@ model.c_out
 
 
 
-```python
+```
 model.stem_sizes
 ```
 
@@ -79,7 +79,7 @@ model.stem_sizes
 
 
 
-```python
+```
 model.layers
 ```
 
@@ -90,7 +90,7 @@ model.layers
 
 
 
-```python
+```
 model.expansion
 ```
 
@@ -101,7 +101,7 @@ model.expansion
 
 
 
-```python
+```
 model()
 ```
 
@@ -277,14 +277,14 @@ model()
 If you want to change model, just change constructor parameters.  
 Lets create xresnet50.
 
-```python
+```
 model.expansion = 4
 model.layers = [3,4,6,3]
 ```
 
 Now we can look at model body and if we call constructor - we have pytorch model!
 
-```python
+```
 model.body
 ```
 
@@ -623,7 +623,7 @@ model.body
 
 
 
-```python
+```
 model.block_szs
 ```
 
@@ -644,20 +644,20 @@ But now lets create model as mxresnet50 from fastai forums tread https://forums.
 
 Lets create mxresnet constructor.
 
-```python
+```
 mxresnet = Net()
 ```
 
 Then lets modify stem.
 
-```python
+```
 mxresnet.stem_sizes = [3,32,64,64]
 ```
 
 Now lets change activation function to Mish.
 Here is link to forum disscussion https://forums.fast.ai/t/meet-mish-new-activation-function-possible-successor-to-relu
 
-```python
+```
 class Mish(nn.Module):
     def __init__(self):
         super().__init__()
@@ -666,7 +666,7 @@ class Mish(nn.Module):
         return x *( torch.tanh(F.softplus(x))) 
 ```
 
-```python
+```
 mxresnet.expansion = 4
 mxresnet.layers = [3,4,6,3]
 mxresnet.act_fn = Mish()
@@ -677,7 +677,7 @@ Now we have mxresnet50 constructor.
 We can inspect some parts of it.  
 And after call it we got model.
 
-```python
+```
 mxresnet
 ```
 
@@ -688,7 +688,7 @@ mxresnet
 
 
 
-```python
+```
 mxresnet.stem.conv_1
 ```
 
@@ -703,7 +703,7 @@ mxresnet.stem.conv_1
 
 
 
-```python
+```
 mxresnet.body.l_0.bl_0
 ```
 
@@ -738,13 +738,13 @@ mxresnet.body.l_0.bl_0
 
 Now lets change Resblock. NewResBlock (stiil not own name yet) is in lib from version 0.1.0
 
-```python
+```
 mxresnet.block = NewResBlock
 ```
 
 That all. Let see what we have.
 
-```python
+```
 mxresnet.body.l_1.bl_0
 ```
 
@@ -782,46 +782,46 @@ mxresnet.body.l_1.bl_0
 
 Usual way to get model - call constructor with parametrs.
 
-```python
+```
 from model_constructor.constructor import *
 ```
 
 Default is resnet18.
 
-```python
+```
 model = Net()
 ```
 
 You cant modify model after call constructor, so define model with parameters.   
 For example, resnet34:
 
-```python
+```
 resnet34 = Net(block=BasicBlock, blocks=[3, 4, 6, 3])
 ```
 
 ## Predefined Resnet models - 18, 34, 50.
 
-```python
+```
 from model_constructor.resnet import *
 ```
 
-```python
+```
 model = resnet34(num_classes=10)
 ```
 
-```python
+```
 model = resnet50(num_classes=10)
 ```
 
 ## 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.
 
-```python
+```
 from model_constructor.xresnet import *
 ```
 
-```python
+```
 model = xresnet50()
 ```
 
@@ -836,11 +836,11 @@ Here is some examples:
 
 Stem with 3 conv layers
 
-```python
+```
 model = Net(stem=partial(Stem, stem_sizes=[32, 32]))
 ```
 
-```python
+```
 model.stem
 ```
 
@@ -869,11 +869,11 @@ model.stem
 
 
 
-```python
+```
 model = Net(stem_sizes=[32, 64])
 ```
 
-```python
+```
 model.stem
 ```
 
@@ -904,11 +904,11 @@ model.stem
 
 ### Activation function before Normalization
 
-```python
+```
 model = Net(bn_1st=False)
 ```
 
-```python
+```
 model.stem
 ```
 
@@ -930,15 +930,15 @@ model.stem
 
 ### Change activation function
 
-```python
+```
 new_act_fn = nn.LeakyReLU(inplace=True)
 ```
 
-```python
+```
 model = Net(act_fn=new_act_fn)
 ```
 
-```python
+```
 model.stem
 ```
 
@@ -957,7 +957,7 @@ model.stem
 
 
 
-```python
+```
 model.body.layer_0.block_0
 ```
 

docs/MXResNet.html

@@ -593,24 +593,6 @@ <h1 id="MXResNet-constructor.">MXResNet constructor.<a class="anchor-link" href=
 <div class="cell border-box-sizing code_cell rendered">
 <div class="input">
 
-<div class="inner_cell">
-    <div class="input_area">
-<div class=" highlight hl-ipython3"><pre><span></span><span class="n">mxresnet34</span>  <span class="o">=</span> <span class="n">partial</span><span class="p">(</span><span class="n">Net</span><span class="p">,</span> <span class="n">name</span><span class="o">=</span><span class="s1">&#39;MXResnet32&#39;</span><span class="p">,</span> <span class="n">expansion</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span> <span class="n">layers</span><span class="o">=</span><span class="p">[</span><span class="mi">3</span><span class="p">,</span> <span class="mi">4</span><span class="p">,</span>  <span class="mi">6</span><span class="p">,</span> <span class="mi">3</span><span class="p">],</span> <span class="o">**</span><span class="n">mxresnet_parameters</span><span class="p">)</span>
-<span class="n">mxresnet50</span>  <span class="o">=</span> <span class="n">partial</span><span class="p">(</span><span class="n">Net</span><span class="p">,</span> <span class="n">name</span><span class="o">=</span><span class="s1">&#39;MXResnet50&#39;</span><span class="p">,</span> <span class="n">expansion</span><span class="o">=</span><span class="mi">4</span><span class="p">,</span> <span class="n">layers</span><span class="o">=</span><span class="p">[</span><span class="mi">3</span><span class="p">,</span> <span class="mi">4</span><span class="p">,</span>  <span class="mi">6</span><span class="p">,</span> <span class="mi">3</span><span class="p">],</span> <span class="o">**</span><span class="n">mxresnet_parameters</span><span class="p">)</span>
-</pre></div>
-
-    </div>
-</div>
-</div>
-
-</div>
-    {% endraw %}
-
-    {% raw %}
-    
-<div class="cell border-box-sizing code_cell rendered">
-<div class="input">
-
 <div class="inner_cell">
     <div class="input_area">
 <div class=" highlight hl-ipython3"><pre><span></span><span class="n">model</span> <span class="o">=</span> <span class="n">mxresnet50</span><span class="p">(</span><span class="n">c_out</span><span class="o">=</span><span class="mi">10</span><span class="p">)</span>

docs/Net.html

@@ -102,7 +102,7 @@ <h1 id="ResBlock">ResBlock<a class="anchor-link" href="#ResBlock"> </a></h1>
 
 
 <div class="output_markdown rendered_html output_subarea ">
-<h2 id="ResBlock" class="doc_header"><code>class</code> <code>ResBlock</code><a href="https://github.com/ayasyrev/model_constructor/tree/master/model_constructor/layers.py#L211" class="source_link" style="float:right">[source]</a></h2><blockquote><p><code>ResBlock</code>(<strong><code>ni</code></strong>, <strong><code>nh</code></strong>, <strong><code>expansion</code></strong>=<em><code>1</code></em>, <strong><code>stride</code></strong>=<em><code>1</code></em>, <strong><code>conv_layer</code></strong>=<em><code>'ConvLayer'</code></em>, <strong><code>conv_block</code></strong>=<em><code>'ConvBlockBasic'</code></em>, <strong><code>downsample</code></strong>=<em><code>'DownsampleLayer'</code></em>, <strong><code>act_fn</code></strong>=<em><code>ReLU(inplace=True)</code></em>, <strong><code>act_id</code></strong>=<em><code>False</code></em>, <strong><code>zero_bn</code></strong>=<em><code>True</code></em>, <strong><code>sa</code></strong>=<em><code>False</code></em>, <strong><code>sym</code></strong>=<em><code>False</code></em>, <strong>**<code>kwargs</code></strong>) :: <code>Module</code></p>
+<h2 id="ResBlock" class="doc_header"><code>class</code> <code>ResBlock</code><a href="https://github.com/ayasyrev/model_constructor/tree/master/model_constructor/layers.py#L209" class="source_link" style="float:right">[source]</a></h2><blockquote><p><code>ResBlock</code>(<strong><code>ni</code></strong>, <strong><code>nh</code></strong>, <strong><code>expansion</code></strong>=<em><code>1</code></em>, <strong><code>stride</code></strong>=<em><code>1</code></em>, <strong><code>conv_layer</code></strong>=<em><code>'ConvLayer'</code></em>, <strong><code>conv_block</code></strong>=<em><code>'ConvBlockBasic'</code></em>, <strong><code>downsample</code></strong>=<em><code>'DownsampleLayer'</code></em>, <strong><code>act_fn</code></strong>=<em><code>ReLU(inplace=True)</code></em>, <strong><code>act_id</code></strong>=<em><code>False</code></em>, <strong><code>zero_bn</code></strong>=<em><code>True</code></em>, <strong><code>sa</code></strong>=<em><code>False</code></em>, <strong><code>sym</code></strong>=<em><code>False</code></em>, <strong>**<code>kwargs</code></strong>) :: <code>Module</code></p>
 </blockquote>
 <p>Base class for all neural network modules.</p>
 <p>Your models should also subclass this class.</p>

docs/YaResNet.html

@@ -699,24 +699,6 @@ <h2 id="YResNet-constructor">YResNet constructor<a class="anchor-link" href="#YR
 <div class="cell border-box-sizing code_cell rendered">
 <div class="input">
 
-<div class="inner_cell">
-    <div class="input_area">
-<div class=" highlight hl-ipython3"><pre><span></span><span class="n">yaresnet34</span>  <span class="o">=</span> <span class="n">partial</span><span class="p">(</span><span class="n">Net</span><span class="p">,</span> <span class="n">name</span><span class="o">=</span><span class="s1">&#39;YaResnet34&#39;</span><span class="p">,</span> <span class="n">expansion</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span> <span class="n">layers</span><span class="o">=</span><span class="p">[</span><span class="mi">3</span><span class="p">,</span> <span class="mi">4</span><span class="p">,</span>  <span class="mi">6</span><span class="p">,</span> <span class="mi">3</span><span class="p">],</span> <span class="o">**</span><span class="n">yaresnet_parameters</span><span class="p">)</span>
-<span class="n">yaresnet50</span>  <span class="o">=</span> <span class="n">partial</span><span class="p">(</span><span class="n">Net</span><span class="p">,</span> <span class="n">name</span><span class="o">=</span><span class="s1">&#39;YaResnet50&#39;</span><span class="p">,</span> <span class="n">expansion</span><span class="o">=</span><span class="mi">4</span><span class="p">,</span> <span class="n">layers</span><span class="o">=</span><span class="p">[</span><span class="mi">3</span><span class="p">,</span> <span class="mi">4</span><span class="p">,</span>  <span class="mi">6</span><span class="p">,</span> <span class="mi">3</span><span class="p">],</span> <span class="o">**</span><span class="n">yaresnet_parameters</span><span class="p">)</span>
-</pre></div>
-
-    </div>
-</div>
-</div>
-
-</div>
-    {% endraw %}
-
-    {% raw %}
-    
-<div class="cell border-box-sizing code_cell rendered">
-<div class="input">
-
 <div class="inner_cell">
     <div class="input_area">
 <div class=" highlight hl-ipython3"><pre><span></span><span class="n">model</span> <span class="o">=</span> <span class="n">yaresnet50</span><span class="p">(</span><span class="n">c_out</span><span class="o">=</span><span class="mi">10</span><span class="p">)</span>

model_constructor/_nbdev.py

@@ -40,7 +40,11 @@
          "ResBlockTwist": "05_Twist.ipynb",
          "YaResBlock": "06_YaResNet.ipynb",
          "yaresnet_parameters": "06_YaResNet.ipynb",
-         "mxresnet_parameters": "07_MXResNet.ipynb"}
+         "yaresnet34": "06_YaResNet.ipynb",
+         "yaresnet50": "06_YaResNet.ipynb",
+         "mxresnet_parameters": "07_MXResNet.ipynb",
+         "mxresnet34": "07_MXResNet.ipynb",
+         "mxresnet50": "07_MXResNet.ipynb"}
 
 modules = ["constructor.py",
            "layers.py",

model_constructor/mxresnet.py

@@ -1,6 +1,6 @@
 # AUTOGENERATED! DO NOT EDIT! File to edit: nbs/07_MXResNet.ipynb (unless otherwise specified).
 
-__all__ = ['mxresnet_parameters']
+__all__ = ['mxresnet_parameters', 'mxresnet34', 'mxresnet50']
 
 # Cell
 import torch.nn as nn
@@ -11,4 +11,6 @@
 from .net import Net
 
 # Cell
-mxresnet_parameters = {'stem_sizes': [3, 32, 64, 64], 'act_fn': Mish()}
+mxresnet_parameters = {'stem_sizes': [3, 32, 64, 64], 'act_fn': Mish()}
+mxresnet34  = partial(Net, name='MXResnet32', expansion=1, layers=[3, 4,  6, 3], **mxresnet_parameters)
+mxresnet50  = partial(Net, name='MXResnet50', expansion=4, layers=[3, 4,  6, 3], **mxresnet_parameters)

model_constructor/net.py

@@ -118,7 +118,7 @@ def __init__(self, name='Net', expansion=1,  c_in=3, c_out=1000,
         self.stem_sizes = stem_sizes if stem_sizes else [c_in,32,32,64]
         self.stem_pool = nn.MaxPool2d(kernel_size=3, stride=2, padding=1)
         self.stem_bn_end = False
-#         self.norm = nn.BatchNorm2d
+        self.norm = nn.BatchNorm2d
         self.bn_1st = True
         self.zero_bn=True
         self.conv_layer = ConvLayer