rename models, change Net init, clear comments

Author: ayasyrev

model_constructor/__init__.py

@@ -1 +1 @@
-__version__ = "0.1.0"
+__version__ = "0.1.1"

model_constructor/_nbdev.py

@@ -27,12 +27,14 @@
          "resnet34": "02_resnet.ipynb",
          "resnet50": "02_resnet.ipynb",
          "xresnet18": "03_xresnet.ipynb",
-         "xresnet34": "04_Net.ipynb",
+         "xresnet34": "03_xresnet.ipynb",
          "xresnet50": "81_Net.ipynb",
          "init_cnn": "81_Net.ipynb",
          "NewResBlock": "81_Net.ipynb",
-         "me": "81_Net.ipynb",
-         "NewConvLayer": "81_Net.ipynb"}
+         "net34": "04_Net.ipynb",
+         "net50": "04_Net.ipynb",
+         "NewConvLayer": "81_Net.ipynb",
+         "me": "81_Net.ipynb"}
 
 modules = ["constructor.py",
            "layers.py",

model_constructor/net.py

@@ -1,6 +1,6 @@
 # AUTOGENERATED! DO NOT EDIT! File to edit: nbs/04_Net.ipynb (unless otherwise specified).
 
-__all__ = ['init_cnn', 'act_fn', 'ResBlock', 'NewResBlock', 'Net', 'me', 'xresnet34', 'xresnet50']
+__all__ = ['init_cnn', 'act_fn', 'ResBlock', 'NewResBlock', 'Net', 'net34', 'net50']
 
 # Cell
 import torch.nn as nn
@@ -104,18 +104,19 @@ def _make_head(self):
 # Cell
 # v8
 class Net():
-    def __init__(self, expansion=1, layers=[2,2,2,2], c_in=3, c_out=1000, name='Net'):
+    def __init__(self, expansion=1, layers=[2,2,2,2], c_in=3, c_out=1000, name='Net',
+                act_fn=nn.ReLU(inplace=True), pool = nn.AvgPool2d(2, ceil_mode=True), sa=0):
         super().__init__()
         self.name = name
         self.c_in, self.c_out,self.expansion,self.layers = c_in,c_out,expansion,layers # todo setter for expansion
+        self.act_fn, self.pool, self.sa = act_fn, pool, sa
+
+
         self.stem_sizes = [c_in,32,32,64]
         self.stem_pool = nn.MaxPool2d(kernel_size=3, stride=2, padding=1)
         self.stem_bn_end = False
         self.block = ResBlock
         self.norm = nn.BatchNorm2d
-        self.act_fn=nn.ReLU(inplace=True)
-        self.pool = nn.AvgPool2d(2, ceil_mode=True)
-        self.sa=False
         self.bn_1st = True
         self.zero_bn=True
         self.conv_layer = ConvLayer
@@ -143,37 +144,6 @@ def head(self):
     def body(self):
         return self._make_body(self)
 
-#     def _make_stem(self):
-#         stem = [(f"conv_{i}", self.conv_layer(self.stem_sizes[i], self.stem_sizes[i+1],
-#                     stride=2 if i==0 else 1,
-#                     bn_layer=(not self.stem_bn_end) if i==(len(self.stem_sizes)-2) else True,
-#                     act_fn=self.act_fn, bn_1st=self.bn_1st))
-#                 for i in range(len(self.stem_sizes)-1)]
-#         stem.append(('stem_pool', self.stem_pool))
-#         if self.stem_bn_end: stem.append(('norm', self.norm(self.stem_sizes[-1])))
-#         return nn.Sequential(OrderedDict(stem))
-
-#     def _make_head(self):
-#         head = [('pool', nn.AdaptiveAvgPool2d(1)),
-#                 ('flat', Flatten()),
-#                 ('fc',   nn.Linear(self.block_szs[-1]*self.expansion, self.c_out))]
-#         return nn.Sequential(OrderedDict(head))
-
-#     def _make_body(self):
-#         blocks = [(f"l_{i}", self._make_layer(self.expansion,
-#                         self.block_szs[i], self.block_szs[i+1], l,
-#                         1 if i==0 else 2, self.sa if i==0 else False))
-#                   for i,l in enumerate(self.layers)]
-#         return nn.Sequential(OrderedDict(blocks))
-
-#     def _make_layer(self,expansion,ni,nf,blocks,stride,sa):
-#         return nn.Sequential(OrderedDict(
-#             [(f"bl_{i}", self.block(expansion, ni if i==0 else nf, nf,
-#                     stride if i==0 else 1, sa=sa if i==blocks-1 else False,
-#                     conv_layer=self.conv_layer, act_fn=self.act_fn, pool=self.pool,
-#                                     zero_bn=self.zero_bn, bn_1st=self.bn_1st))
-#               for i in range(blocks)]))
-
     def __call__(self):
         model = nn.Sequential(OrderedDict([
             ('stem', self.stem),
@@ -187,13 +157,13 @@ def __repr__(self):
         return f" constr {self.name}"
 
 # Cell
-me = sys.modules[__name__]
-for n,e,l in [[ 18 , 1, [2,2,2 ,2] ],
-    [ 34 , 1, [3,4,6 ,3] ],
-    [ 50 , 4, [3,4,6 ,3] ],
-    [ 101, 4, [3,4,23,3] ],
-    [ 152, 4, [3,8,36,3] ],]:
-    name = f'net{n}'
-    setattr(me, name, partial(Net, expansion=e, layers=l, name=name))
-xresnet34  = partial(Net, expansion=1, layers=[3, 4,  6, 3], name='xresnet34')
-xresnet50  = partial(Net, expansion=4, layers=[3, 4,  6, 3], name='xresnet50')
+# me = sys.modules[__name__]
+# for n,e,l in [[ 18 , 1, [2,2,2 ,2] ],
+#     [ 34 , 1, [3,4,6 ,3] ],
+#     [ 50 , 4, [3,4,6 ,3] ],
+#     [ 101, 4, [3,4,23,3] ],
+#     [ 152, 4, [3,8,36,3] ],]:
+#     name = f'net{n}'
+#     setattr(me, name, partial(Net, expansion=e, layers=l, name=name))
+net34  = partial(Net, expansion=1, layers=[3, 4,  6, 3], name='xresnet34')
+net50  = partial(Net, expansion=4, layers=[3, 4,  6, 3], name='xresnet50')

nbs/04_Net.ipynb

@@ -428,18 +428,19 @@
     "# export\n",
     "# v8\n",
     "class Net():\n",
-    "    def __init__(self, expansion=1, layers=[2,2,2,2], c_in=3, c_out=1000, name='Net'):\n",
+    "    def __init__(self, expansion=1, layers=[2,2,2,2], c_in=3, c_out=1000, name='Net',\n",
+    "                act_fn=nn.ReLU(inplace=True), pool = nn.AvgPool2d(2, ceil_mode=True), sa=0):\n",
     "        super().__init__()\n",
     "        self.name = name\n",
     "        self.c_in, self.c_out,self.expansion,self.layers = c_in,c_out,expansion,layers # todo setter for expansion\n",
+    "        self.act_fn, self.pool, self.sa = act_fn, pool, sa\n",
+    "        \n",
+    "        \n",
     "        self.stem_sizes = [c_in,32,32,64]\n",
     "        self.stem_pool = nn.MaxPool2d(kernel_size=3, stride=2, padding=1)\n",
     "        self.stem_bn_end = False\n",
     "        self.block = ResBlock\n",
     "        self.norm = nn.BatchNorm2d\n",
-    "        self.act_fn=nn.ReLU(inplace=True)\n",
-    "        self.pool = nn.AvgPool2d(2, ceil_mode=True)\n",
-    "        self.sa=False\n",
     "        self.bn_1st = True\n",
     "        self.zero_bn=True\n",
     "        self.conv_layer = ConvLayer\n",
@@ -467,37 +468,6 @@
     "    def body(self):\n",
     "        return self._make_body(self)\n",
     "    \n",
-    "#     def _make_stem(self):\n",
-    "#         stem = [(f\"conv_{i}\", self.conv_layer(self.stem_sizes[i], self.stem_sizes[i+1], \n",
-    "#                     stride=2 if i==0 else 1, \n",
-    "#                     bn_layer=(not self.stem_bn_end) if i==(len(self.stem_sizes)-2) else True,\n",
-    "#                     act_fn=self.act_fn, bn_1st=self.bn_1st))\n",
-    "#                 for i in range(len(self.stem_sizes)-1)]\n",
-    "#         stem.append(('stem_pool', self.stem_pool))\n",
-    "#         if self.stem_bn_end: stem.append(('norm', self.norm(self.stem_sizes[-1])))\n",
-    "#         return nn.Sequential(OrderedDict(stem))\n",
-    "    \n",
-    "#     def _make_head(self):\n",
-    "#         head = [('pool', nn.AdaptiveAvgPool2d(1)),\n",
-    "#                 ('flat', Flatten()),\n",
-    "#                 ('fc',   nn.Linear(self.block_szs[-1]*self.expansion, self.c_out))]\n",
-    "#         return nn.Sequential(OrderedDict(head))\n",
-    "    \n",
-    "#     def _make_body(self):\n",
-    "#         blocks = [(f\"l_{i}\", self._make_layer(self.expansion, \n",
-    "#                         self.block_szs[i], self.block_szs[i+1], l, \n",
-    "#                         1 if i==0 else 2, self.sa if i==0 else False))\n",
-    "#                   for i,l in enumerate(self.layers)]\n",
-    "#         return nn.Sequential(OrderedDict(blocks))\n",
-    "    \n",
-    "#     def _make_layer(self,expansion,ni,nf,blocks,stride,sa):\n",
-    "#         return nn.Sequential(OrderedDict(\n",
-    "#             [(f\"bl_{i}\", self.block(expansion, ni if i==0 else nf, nf, \n",
-    "#                     stride if i==0 else 1, sa=sa if i==blocks-1 else False,\n",
-    "#                     conv_layer=self.conv_layer, act_fn=self.act_fn, pool=self.pool,\n",
-    "#                                     zero_bn=self.zero_bn, bn_1st=self.bn_1st))\n",
-    "#               for i in range(blocks)]))\n",
-    "    \n",
     "    def __call__(self):\n",
     "        model = nn.Sequential(OrderedDict([\n",
     "            ('stem', self.stem),\n",
@@ -1266,16 +1236,16 @@
    "outputs": [],
    "source": [
     "# export\n",
-    "me = sys.modules[__name__]\n",
-    "for n,e,l in [[ 18 , 1, [2,2,2 ,2] ],\n",
-    "    [ 34 , 1, [3,4,6 ,3] ],\n",
-    "    [ 50 , 4, [3,4,6 ,3] ],\n",
-    "    [ 101, 4, [3,4,23,3] ],\n",
-    "    [ 152, 4, [3,8,36,3] ],]:\n",
-    "    name = f'net{n}'\n",
-    "    setattr(me, name, partial(Net, expansion=e, layers=l, name=name))\n",
-    "xresnet34  = partial(Net, expansion=1, layers=[3, 4,  6, 3], name='xresnet34')\n",
-    "xresnet50  = partial(Net, expansion=4, layers=[3, 4,  6, 3], name='xresnet50')"
+    "# me = sys.modules[__name__]\n",
+    "# for n,e,l in [[ 18 , 1, [2,2,2 ,2] ],\n",
+    "#     [ 34 , 1, [3,4,6 ,3] ],\n",
+    "#     [ 50 , 4, [3,4,6 ,3] ],\n",
+    "#     [ 101, 4, [3,4,23,3] ],\n",
+    "#     [ 152, 4, [3,8,36,3] ],]:\n",
+    "#     name = f'net{n}'\n",
+    "#     setattr(me, name, partial(Net, expansion=e, layers=l, name=name))\n",
+    "net34  = partial(Net, expansion=1, layers=[3, 4,  6, 3], name='xresnet34')\n",
+    "net50  = partial(Net, expansion=4, layers=[3, 4,  6, 3], name='xresnet50')"
    ]
   },
   {
@@ -1284,7 +1254,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "m = xresnet50(c_out=10)"
+    "m = net50(c_out=10)"
    ]
   },
   {