Rebuild

Author: 9bow

docs/.buildinfo

@@ -1,4 +1,4 @@
 # Sphinx build info version 1
 # This file hashes the configuration used when building these files. When it is not found, a full rebuild will be done.
-config: d3c78aee0796eaca17b472b08560486c
+config: 85edaa44f46a784d15b287d6d8ea99db
 tags: 645f666f9bcd5a90fca523b33c5a78b7

docs/_downloads/1ceade89aedc4c99a944f752a51c6d35/mario_rl_tutorial.ipynb

@@ -80,7 +80,7 @@
       },
       "outputs": [],
       "source": [
-        "# \ubaa8\ub378\uc5d0 \ub300\ud55c \uc785\ub825\uac12\nx = torch.randn(batch_size, 1, 224, 224, requires_grad=True)\ntorch_out = torch_model(x)\n\n# \ubaa8\ub378 \ubcc0\ud658\ntorch.onnx.export(torch_model,               # \uc2e4\ud589\ub420 \ubaa8\ub378\n                  x,                         # \ubaa8\ub378 \uc785\ub825\uac12 (\ud29c\ud50c \ub610\ub294 \uc5ec\ub7ec \uc785\ub825\uac12\ub4e4\ub3c4 \uac00\ub2a5)\n                  \"super_resolution.onnx\",   # \ubaa8\ub378 \uc800\uc7a5 \uacbd\ub85c (\ud30c\uc77c \ub610\ub294 \ud30c\uc77c\uacfc \uc720\uc0ac\ud55c \uac1d\uccb4 \ubaa8\ub450 \uac00\ub2a5)\n                  export_params=True,        # \ubaa8\ub378 \ud30c\uc77c \uc548\uc5d0 \ud559\uc2b5\ub41c \ubaa8\ub378 \uac00\uc911\uce58\ub97c \uc800\uc7a5\ud560\uc9c0\uc758 \uc5ec\ubd80\n                  opset_version=10,          # \ubaa8\ub378\uc744 \ubcc0\ud658\ud560 \ub54c \uc0ac\uc6a9\ud560 ONNX \ubc84\uc804\n                  do_constant_folding=True,  # \ucd5c\uc801\ud558\uc2dc \uc0c1\uc218\ud3f4\ub529\uc744 \uc0ac\uc6a9\ud560\uc9c0\uc758 \uc5ec\ubd80\n                  input_names = ['input'],   # \ubaa8\ub378\uc758 \uc785\ub825\uac12\uc744 \uac00\ub9ac\ud0a4\ub294 \uc774\ub984\n                  output_names = ['output'], # \ubaa8\ub378\uc758 \ucd9c\ub825\uac12\uc744 \uac00\ub9ac\ud0a4\ub294 \uc774\ub984\n                  dynamic_axes={'input' : {0 : 'batch_size'},    # \uac00\ubcc0\uc801\uc778 \uae38\uc774\ub97c \uac00\uc9c4 \ucc28\uc6d0\n                                'output' : {0 : 'batch_size'}})"
+        "# \ubaa8\ub378\uc5d0 \ub300\ud55c \uc785\ub825\uac12\nx = torch.randn(batch_size, 1, 224, 224, requires_grad=True)\ntorch_out = torch_model(x)\n\n# \ubaa8\ub378 \ubcc0\ud658\ntorch.onnx.export(torch_model,               # \uc2e4\ud589\ub420 \ubaa8\ub378\n                  x,                         # \ubaa8\ub378 \uc785\ub825\uac12 (\ud29c\ud50c \ub610\ub294 \uc5ec\ub7ec \uc785\ub825\uac12\ub4e4\ub3c4 \uac00\ub2a5)\n                  \"super_resolution.onnx\",   # \ubaa8\ub378 \uc800\uc7a5 \uacbd\ub85c (\ud30c\uc77c \ub610\ub294 \ud30c\uc77c\uacfc \uc720\uc0ac\ud55c \uac1d\uccb4 \ubaa8\ub450 \uac00\ub2a5)\n                  export_params=True,        # \ubaa8\ub378 \ud30c\uc77c \uc548\uc5d0 \ud559\uc2b5\ub41c \ubaa8\ub378 \uac00\uc911\uce58\ub97c \uc800\uc7a5\ud560\uc9c0\uc758 \uc5ec\ubd80\n                  opset_version=10,          # \ubaa8\ub378\uc744 \ubcc0\ud658\ud560 \ub54c \uc0ac\uc6a9\ud560 ONNX \ubc84\uc804\n                  do_constant_folding=True,  # \ucd5c\uc801\ud654\uc2dc \uc0c1\uc218\ud3f4\ub529\uc744 \uc0ac\uc6a9\ud560\uc9c0\uc758 \uc5ec\ubd80\n                  input_names = ['input'],   # \ubaa8\ub378\uc758 \uc785\ub825\uac12\uc744 \uac00\ub9ac\ud0a4\ub294 \uc774\ub984\n                  output_names = ['output'], # \ubaa8\ub378\uc758 \ucd9c\ub825\uac12\uc744 \uac00\ub9ac\ud0a4\ub294 \uc774\ub984\n                  dynamic_axes={'input' : {0 : 'batch_size'},    # \uac00\ubcc0\uc801\uc778 \uae38\uc774\ub97c \uac00\uc9c4 \ucc28\uc6d0\n                                'output' : {0 : 'batch_size'}})"
       ]
     },
     {

docs/_downloads/934f425a64afc04a1466c778c945fb84/mario_rl_tutorial.py

@@ -126,7 +126,7 @@ def _initialize_weights(self):
                   "super_resolution.onnx",   # 모델 저장 경로 (파일 또는 파일과 유사한 객체 모두 가능)
                   export_params=True,        # 모델 파일 안에 학습된 모델 가중치를 저장할지의 여부
                   opset_version=10,          # 모델을 변환할 때 사용할 ONNX 버전
-                  do_constant_folding=True,  # 최적하시 상수폴딩을 사용할지의 여부
+                  do_constant_folding=True,  # 최적화시 상수폴딩을 사용할지의 여부
                   input_names = ['input'],   # 모델의 입력값을 가리키는 이름
                   output_names = ['output'], # 모델의 출력값을 가리키는 이름
                   dynamic_axes={'input' : {0 : 'batch_size'},    # 가변적인 길이를 가진 차원

docs/_downloads/dba562a36c81e67ddf3b2f9503b7009b/super_resolution_with_onnxruntime.ipynb

@@ -613,7 +613,7 @@
 .. customcalloutitem::
    :header: (비공식) 한국어 튜토리얼 저장소(GitHub)
    :description: GitHub에서 (비공식) 한국어 튜토리얼을 만나보세요.
-   :button_link: https://github.com/9bow/PyTorch-tutorials-kr
+   :button_link: https://github.com/PyTorchKorea/tutorials-kr
    :button_text: Go To GitHub
 
 .. customcalloutitem::