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added 'cpu' to the summary function in torchsummary as it assumes 'cu…
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…da' by default,

cosmetic changes,
added requirements.txt
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@johschmidt42
johschmidt42 committed Apr 14, 2021
1 parent 82383d8 commit fe8967a
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23 changes: 17 additions & 6 deletions Part1.ipynb
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{
"data": {
"text/plain": [
"<napari.viewer.Viewer at 0x21663894a00>"
"Viewer(axes=Axes(visible=False, labels=True, colored=True, dashed=False, arrows=True), camera=Camera(center=(0.0, 639.5, 958.5), zoom=0.2859415753781951, angles=(0.0, 0.0, 90.0), interactive=True), cursor=Cursor(position=(0.0, 0.0), scaled=True, size=10, style='standard'), dims=Dims(ndim=2, ndisplay=2, last_used=1, range=((0.0, 1279.0, 1.0), (0.0, 1917.0, 1.0)), current_step=(0, 0), order=(0, 1), axis_labels=('0', '1')), grid=GridCanvas(enabled=False, stride=1, shape=(-1, -1)), layers=[<Image layer 'input_training' at 0x20a86a790a0>, <Labels layer 'target_training' at 0x20a86a79b50>], scale_bar=ScaleBar(visible=False, colored=False, ticks=True, position='bottom_right'), active_layer=<Labels layer 'target_training' at 0x20a86a79b50>, help='enter paint or fill mode to edit labels', status='Ready', theme='dark', title='napari', mouse_move_callbacks=[], mouse_drag_callbacks=[], mouse_wheel_callbacks=[<function dims_scroll at 0x0000020A80C60790>], _persisted_mouse_event={}, _mouse_drag_gen={}, _mouse_wheel_gen={}, keymap={'T': <function show_input_target_pair_napari.<locals>.next_batch_training at 0x0000020A8FDD9670>})"
]
},
"execution_count": 3,
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},
{
"cell_type": "code",
"execution_count": null,
"execution_count": 6,
"metadata": {},
"outputs": [],
"outputs": [
{
"data": {
"text/plain": [
"Viewer(axes=Axes(visible=False, labels=True, colored=True, dashed=False, arrows=True), camera=Camera(center=(0.0, 639.5, 958.5), zoom=0.2859415753781951, angles=(0.0, 0.0, 90.0), interactive=True), cursor=Cursor(position=(0.0, 0.0), scaled=True, size=10, style='standard'), dims=Dims(ndim=2, ndisplay=2, last_used=1, range=((0.0, 1279.0, 1.0), (0.0, 1917.0, 1.0)), current_step=(0, 0), order=(0, 1), axis_labels=('0', '1')), grid=GridCanvas(enabled=False, stride=1, shape=(-1, -1)), layers=[<Image layer 'input_training' at 0x20a97119760>, <Labels layer 'target_training' at 0x20a97060be0>], scale_bar=ScaleBar(visible=False, colored=False, ticks=True, position='bottom_right'), active_layer=<Labels layer 'target_training' at 0x20a97060be0>, help='enter paint or fill mode to edit labels', status='Ready', theme='dark', title='napari', mouse_move_callbacks=[], mouse_drag_callbacks=[], mouse_wheel_callbacks=[<function dims_scroll at 0x0000020A80C60790>], _persisted_mouse_event={}, _mouse_drag_gen={}, _mouse_wheel_gen={}, keymap={'T': <function show_input_target_pair_napari.<locals>.next_batch_training at 0x0000020A9D207AF0>, 'V': <function show_input_target_pair_napari.<locals>.next_batch_validation at 0x0000020A9D207B80>})"
]
},
"execution_count": 6,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"%gui qt\n",
"from visual import Input_Target_Pair_Generator\n",
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"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.8.5"
"version": "3.8.8"
}
},
"nbformat": 4,
"nbformat_minor": 1
}
"nbformat_minor": 4
}
203 changes: 104 additions & 99 deletions Part2.ipynb
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"name": "stdout",
"output_type": "stream",
"text": [
"==========================================================================================\n",
"Layer (type:depth-idx) Output Shape Param #\n",
"==========================================================================================\n",
"├─ModuleList: 1 [] --\n",
"| └─DownBlock: 2-1 [-1, 32, 256, 256] --\n",
"| | └─Conv2d: 3-1 [-1, 32, 512, 512] 320\n",
"| | └─ReLU: 3-2 [-1, 32, 512, 512] --\n",
"| | └─BatchNorm2d: 3-3 [-1, 32, 512, 512] 64\n",
"| | └─Conv2d: 3-4 [-1, 32, 512, 512] 9,248\n",
"| | └─ReLU: 3-5 [-1, 32, 512, 512] --\n",
"| | └─BatchNorm2d: 3-6 [-1, 32, 512, 512] 64\n",
"| | └─MaxPool2d: 3-7 [-1, 32, 256, 256] --\n",
"| └─DownBlock: 2-2 [-1, 64, 128, 128] --\n",
"| | └─Conv2d: 3-8 [-1, 64, 256, 256] 18,496\n",
"| | └─ReLU: 3-9 [-1, 64, 256, 256] --\n",
"| | └─BatchNorm2d: 3-10 [-1, 64, 256, 256] 128\n",
"| | └─Conv2d: 3-11 [-1, 64, 256, 256] 36,928\n",
"| | └─ReLU: 3-12 [-1, 64, 256, 256] --\n",
"| | └─BatchNorm2d: 3-13 [-1, 64, 256, 256] 128\n",
"| | └─MaxPool2d: 3-14 [-1, 64, 128, 128] --\n",
"| └─DownBlock: 2-3 [-1, 128, 64, 64] --\n",
"| | └─Conv2d: 3-15 [-1, 128, 128, 128] 73,856\n",
"| | └─ReLU: 3-16 [-1, 128, 128, 128] --\n",
"| | └─BatchNorm2d: 3-17 [-1, 128, 128, 128] 256\n",
"| | └─Conv2d: 3-18 [-1, 128, 128, 128] 147,584\n",
"| | └─ReLU: 3-19 [-1, 128, 128, 128] --\n",
"| | └─BatchNorm2d: 3-20 [-1, 128, 128, 128] 256\n",
"| | └─MaxPool2d: 3-21 [-1, 128, 64, 64] --\n",
"| └─DownBlock: 2-4 [-1, 256, 64, 64] --\n",
"| | └─Conv2d: 3-22 [-1, 256, 64, 64] 295,168\n",
"| | └─ReLU: 3-23 [-1, 256, 64, 64] --\n",
"| | └─BatchNorm2d: 3-24 [-1, 256, 64, 64] 512\n",
"| | └─Conv2d: 3-25 [-1, 256, 64, 64] 590,080\n",
"| | └─ReLU: 3-26 [-1, 256, 64, 64] --\n",
"| | └─BatchNorm2d: 3-27 [-1, 256, 64, 64] 512\n",
"├─ModuleList: 1 [] --\n",
"| └─UpBlock: 2-5 [-1, 128, 128, 128] --\n",
"| | └─ConvTranspose2d: 3-28 [-1, 128, 128, 128] 131,200\n",
"| | └─ReLU: 3-29 [-1, 128, 128, 128] --\n",
"| | └─BatchNorm2d: 3-30 [-1, 128, 128, 128] 256\n",
"| | └─Concatenate: 3-31 [-1, 256, 128, 128] --\n",
"| | └─Conv2d: 3-32 [-1, 128, 128, 128] 295,040\n",
"| | └─ReLU: 3-33 [-1, 128, 128, 128] --\n",
"| | └─BatchNorm2d: 3-34 [-1, 128, 128, 128] 256\n",
"| | └─Conv2d: 3-35 [-1, 128, 128, 128] 147,584\n",
"| | └─ReLU: 3-36 [-1, 128, 128, 128] --\n",
"| | └─BatchNorm2d: 3-37 [-1, 128, 128, 128] 256\n",
"| └─UpBlock: 2-6 [-1, 64, 256, 256] --\n",
"| | └─ConvTranspose2d: 3-38 [-1, 64, 256, 256] 32,832\n",
"| | └─ReLU: 3-39 [-1, 64, 256, 256] --\n",
"| | └─BatchNorm2d: 3-40 [-1, 64, 256, 256] 128\n",
"| | └─Concatenate: 3-41 [-1, 128, 256, 256] --\n",
"| | └─Conv2d: 3-42 [-1, 64, 256, 256] 73,792\n",
"| | └─ReLU: 3-43 [-1, 64, 256, 256] --\n",
"| | └─BatchNorm2d: 3-44 [-1, 64, 256, 256] 128\n",
"| | └─Conv2d: 3-45 [-1, 64, 256, 256] 36,928\n",
"| | └─ReLU: 3-46 [-1, 64, 256, 256] --\n",
"| | └─BatchNorm2d: 3-47 [-1, 64, 256, 256] 128\n",
"| └─UpBlock: 2-7 [-1, 32, 512, 512] --\n",
"| | └─ConvTranspose2d: 3-48 [-1, 32, 512, 512] 8,224\n",
"| | └─ReLU: 3-49 [-1, 32, 512, 512] --\n",
"| | └─BatchNorm2d: 3-50 [-1, 32, 512, 512] 64\n",
"| | └─Concatenate: 3-51 [-1, 64, 512, 512] --\n",
"| | └─Conv2d: 3-52 [-1, 32, 512, 512] 18,464\n",
"| | └─ReLU: 3-53 [-1, 32, 512, 512] --\n",
"| | └─BatchNorm2d: 3-54 [-1, 32, 512, 512] 64\n",
"| | └─Conv2d: 3-55 [-1, 32, 512, 512] 9,248\n",
"| | └─ReLU: 3-56 [-1, 32, 512, 512] --\n",
"| | └─BatchNorm2d: 3-57 [-1, 32, 512, 512] 64\n",
"├─Conv2d: 1-1 [-1, 2, 512, 512] 66\n",
"==========================================================================================\n",
"----------------------------------------------------------------\n",
" Layer (type) Output Shape Param #\n",
"================================================================\n",
" Conv2d-1 [-1, 32, 512, 512] 320\n",
" ReLU-2 [-1, 32, 512, 512] 0\n",
" BatchNorm2d-3 [-1, 32, 512, 512] 64\n",
" Conv2d-4 [-1, 32, 512, 512] 9,248\n",
" ReLU-5 [-1, 32, 512, 512] 0\n",
" BatchNorm2d-6 [-1, 32, 512, 512] 64\n",
" MaxPool2d-7 [-1, 32, 256, 256] 0\n",
" DownBlock-8 [[-1, 32, 256, 256], [-1, 32, 512, 512]] 0\n",
" Conv2d-9 [-1, 64, 256, 256] 18,496\n",
" ReLU-10 [-1, 64, 256, 256] 0\n",
" BatchNorm2d-11 [-1, 64, 256, 256] 128\n",
" Conv2d-12 [-1, 64, 256, 256] 36,928\n",
" ReLU-13 [-1, 64, 256, 256] 0\n",
" BatchNorm2d-14 [-1, 64, 256, 256] 128\n",
" MaxPool2d-15 [-1, 64, 128, 128] 0\n",
" DownBlock-16 [[-1, 64, 128, 128], [-1, 64, 256, 256]] 0\n",
" Conv2d-17 [-1, 128, 128, 128] 73,856\n",
" ReLU-18 [-1, 128, 128, 128] 0\n",
" BatchNorm2d-19 [-1, 128, 128, 128] 256\n",
" Conv2d-20 [-1, 128, 128, 128] 147,584\n",
" ReLU-21 [-1, 128, 128, 128] 0\n",
" BatchNorm2d-22 [-1, 128, 128, 128] 256\n",
" MaxPool2d-23 [-1, 128, 64, 64] 0\n",
" DownBlock-24 [[-1, 128, 64, 64], [-1, 128, 128, 128]] 0\n",
" Conv2d-25 [-1, 256, 64, 64] 295,168\n",
" ReLU-26 [-1, 256, 64, 64] 0\n",
" BatchNorm2d-27 [-1, 256, 64, 64] 512\n",
" Conv2d-28 [-1, 256, 64, 64] 590,080\n",
" ReLU-29 [-1, 256, 64, 64] 0\n",
" BatchNorm2d-30 [-1, 256, 64, 64] 512\n",
" DownBlock-31 [[-1, 256, 64, 64], [-1, 256, 64, 64]] 0\n",
" ConvTranspose2d-32 [-1, 128, 128, 128] 131,200\n",
" ReLU-33 [-1, 128, 128, 128] 0\n",
" BatchNorm2d-34 [-1, 128, 128, 128] 256\n",
" Concatenate-35 [-1, 256, 128, 128] 0\n",
" Conv2d-36 [-1, 128, 128, 128] 295,040\n",
" ReLU-37 [-1, 128, 128, 128] 0\n",
" BatchNorm2d-38 [-1, 128, 128, 128] 256\n",
" Conv2d-39 [-1, 128, 128, 128] 147,584\n",
" ReLU-40 [-1, 128, 128, 128] 0\n",
" BatchNorm2d-41 [-1, 128, 128, 128] 256\n",
" UpBlock-42 [-1, 128, 128, 128] 0\n",
" ConvTranspose2d-43 [-1, 64, 256, 256] 32,832\n",
" ReLU-44 [-1, 64, 256, 256] 0\n",
" BatchNorm2d-45 [-1, 64, 256, 256] 128\n",
" Concatenate-46 [-1, 128, 256, 256] 0\n",
" Conv2d-47 [-1, 64, 256, 256] 73,792\n",
" ReLU-48 [-1, 64, 256, 256] 0\n",
" BatchNorm2d-49 [-1, 64, 256, 256] 128\n",
" Conv2d-50 [-1, 64, 256, 256] 36,928\n",
" ReLU-51 [-1, 64, 256, 256] 0\n",
" BatchNorm2d-52 [-1, 64, 256, 256] 128\n",
" UpBlock-53 [-1, 64, 256, 256] 0\n",
" ConvTranspose2d-54 [-1, 32, 512, 512] 8,224\n",
" ReLU-55 [-1, 32, 512, 512] 0\n",
" BatchNorm2d-56 [-1, 32, 512, 512] 64\n",
" Concatenate-57 [-1, 64, 512, 512] 0\n",
" Conv2d-58 [-1, 32, 512, 512] 18,464\n",
" ReLU-59 [-1, 32, 512, 512] 0\n",
" BatchNorm2d-60 [-1, 32, 512, 512] 64\n",
" Conv2d-61 [-1, 32, 512, 512] 9,248\n",
" ReLU-62 [-1, 32, 512, 512] 0\n",
" BatchNorm2d-63 [-1, 32, 512, 512] 64\n",
" UpBlock-64 [-1, 32, 512, 512] 0\n",
" Conv2d-65 [-1, 2, 512, 512] 66\n",
"================================================================\n",
"Total params: 1,928,322\n",
"Trainable params: 1,928,322\n",
"Non-trainable params: 0\n",
"Total mult-adds (M): -14267.05\n",
"==========================================================================================\n",
"----------------------------------------------------------------\n",
"Input size (MB): 1.00\n",
"Forward/backward pass size (MB): 1156.00\n",
"Forward/backward pass size (MB): 2096.00\n",
"Params size (MB): 7.36\n",
"Estimated Total Size (MB): 1164.36\n",
"==========================================================================================\n"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"C:\\ProgramData\\Miniconda3\\envs\\test_env\\lib\\site-packages\\torchsummary\\layer_info.py:122: RuntimeWarning: overflow encountered in long_scalars\n",
" self.macs += int(param.nelement() * np.prod(self.output_size[2:]))\n"
"Estimated Total Size (MB): 2104.36\n",
"----------------------------------------------------------------\n"
]
}
],
"source": [
"from torchsummary import summary\n",
"summary = summary(model, (1, 512, 512))"
"summary = summary(model, (1, 512, 512), device='cpu')"
]
},
{
Expand Down Expand Up @@ -183,8 +172,30 @@
},
{
"cell_type": "code",
"execution_count": null,
"outputs": [],
"execution_count": 4,
"metadata": {
"collapsed": false,
"jupyter": {
"outputs_hidden": false
},
"pycharm": {
"name": "#%%\n"
}
},
"outputs": [
{
"data": {
"text/plain": [
"{256: [256, 128.0, 64.0, 32.0, 16.0, 8.0, 4.0, 2.0],\n",
" 384: [384, 192.0, 96.0, 48.0, 24.0, 12.0, 6.0, 3.0],\n",
" 512: [512, 256.0, 128.0, 64.0, 32.0, 16.0, 8.0, 4.0]}"
]
},
"execution_count": 4,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"low = 10\n",
"high = 512\n",
Expand All @@ -203,17 +214,11 @@
" return possible_shapes\n",
"possible_shapes = compute_possible_shapes(low, high, depth)\n",
"possible_shapes"
],
"metadata": {
"collapsed": false,
"pycharm": {
"name": "#%%\n"
}
}
]
},
{
"cell_type": "code",
"execution_count": 4,
"execution_count": 5,
"metadata": {},
"outputs": [
{
Expand All @@ -224,7 +229,7 @@
" 512: [512, 256.0, 128.0, 64.0, 32.0, 16.0, 8.0, 4.0]}"
]
},
"execution_count": 4,
"execution_count": 5,
"metadata": {},
"output_type": "execute_result"
}
Expand Down Expand Up @@ -266,9 +271,9 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.8.5"
"version": "3.8.8"
}
},
"nbformat": 4,
"nbformat_minor": 1
}
"nbformat_minor": 4
}
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