Update and add clean

DataScienceandAIVE · Mar 6, 2020 · b2f1c12 · b2f1c12
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diff --git a/01_intro.ipynb b/01_intro.ipynb
diff --git a/02_production.ipynb b/02_production.ipynb
@@ -1629,7 +1629,8 @@
    ],
    "source": [
     "#hide_output\n",
-    "VBox([widgets.Label('Select your bear!'), btn_upload, btn_run, out_pl, lbl_pred])"
+    "VBox([widgets.Label('Select your bear!'), \n",
+    "      btn_upload, btn_run, out_pl, lbl_pred])"
    ]
   },
   {
@@ -1946,20 +1947,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.7.5"
-  },
-  "toc": {
-   "base_numbering": 1,
-   "nav_menu": {},
-   "number_sections": false,
-   "sideBar": true,
-   "skip_h1_title": true,
-   "title_cell": "Table of Contents",
-   "title_sidebar": "Contents",
-   "toc_cell": false,
-   "toc_position": {},
-   "toc_section_display": true,
-   "toc_window_display": false
+   "version": "3.7.4"
   }
  },
  "nbformat": 4,

diff --git a/03_ethics.ipynb b/03_ethics.ipynb
@@ -1041,34 +1041,6 @@
    "display_name": "Python 3",
    "language": "python",
    "name": "python3"
-  },
-  "language_info": {
-   "codemirror_mode": {
-    "name": "ipython",
-    "version": 3
-   },
-   "file_extension": ".py",
-   "mimetype": "text/x-python",
-   "name": "python",
-   "nbconvert_exporter": "python",
-   "pygments_lexer": "ipython3",
-   "version": "3.7.5"
-  },
-  "toc": {
-   "base_numbering": 1,
-   "nav_menu": {
-    "height": "600px",
-    "width": "365px"
-   },
-   "number_sections": false,
-   "sideBar": true,
-   "skip_h1_title": true,
-   "title_cell": "Table of Contents",
-   "title_sidebar": "Contents",
-   "toc_cell": false,
-   "toc_position": {},
-   "toc_section_display": true,
-   "toc_window_display": false
   }
  },
  "nbformat": 4,

diff --git a/05_pet_breeds.ipynb b/05_pet_breeds.ipynb
@@ -2543,20 +2543,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.7.5"
-  },
-  "toc": {
-   "base_numbering": 1,
-   "nav_menu": {},
-   "number_sections": false,
-   "sideBar": true,
-   "skip_h1_title": true,
-   "title_cell": "Table of Contents",
-   "title_sidebar": "Contents",
-   "toc_cell": false,
-   "toc_position": {},
-   "toc_section_display": true,
-   "toc_window_display": false
+   "version": "3.7.4"
   }
  },
  "nbformat": 4,

diff --git a/06_multicat.ipynb b/06_multicat.ipynb
@@ -1445,11 +1445,14 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "biwi = DataBlock(blocks=(ImageBlock, PointBlock),\n",
-    "                 get_items=get_image_files,\n",
-    "                 get_y=get_ctr,\n",
-    "                 splitter=FuncSplitter(lambda o: o.parent.name=='13'),\n",
-    "                 batch_tfms=[*aug_transforms(size=(240,320)), Normalize.from_stats(*imagenet_stats)])"
+    "biwi = DataBlock(\n",
+    "    blocks=(ImageBlock, PointBlock),\n",
+    "    get_items=get_image_files,\n",
+    "    get_y=get_ctr,\n",
+    "    splitter=FuncSplitter(lambda o: o.parent.name=='13'),\n",
+    "    batch_tfms=[*aug_transforms(size=(240,320)), \n",
+    "                Normalize.from_stats(*imagenet_stats)]\n",
+    ")"
    ]
   },
   {
@@ -1925,6 +1928,18 @@
    "display_name": "Python 3",
    "language": "python",
    "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.7.4"
   }
  },
  "nbformat": 4,

diff --git a/07_sizing_and_tta.ipynb b/07_sizing_and_tta.ipynb
@@ -460,7 +460,8 @@
    ],
    "source": [
     "dls = get_dls(128, 128)\n",
-    "learn = Learner(dls, xresnet50(), loss_func=CrossEntropyLossFlat(), metrics=accuracy)\n",
+    "learn = Learner(dls, xresnet50(), loss_func=CrossEntropyLossFlat(), \n",
+    "                metrics=accuracy)\n",
     "learn.fit_one_cycle(4, 3e-3)"
    ]
   },
@@ -1011,6 +1012,18 @@
    "display_name": "Python 3",
    "language": "python",
    "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.7.4"
   }
  },
  "nbformat": 4,

diff --git a/08_collab.ipynb b/08_collab.ipynb
@@ -2296,6 +2296,18 @@
    "display_name": "Python 3",
    "language": "python",
    "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.7.4"
   }
  },
  "nbformat": 4,

diff --git a/09_tabular.ipynb b/09_tabular.ipynb
@@ -9740,31 +9740,6 @@
    "display_name": "Python 3",
    "language": "python",
    "name": "python3"
-  },
-  "language_info": {
-   "codemirror_mode": {
-    "name": "ipython",
-    "version": 3
-   },
-   "file_extension": ".py",
-   "mimetype": "text/x-python",
-   "name": "python",
-   "nbconvert_exporter": "python",
-   "pygments_lexer": "ipython3",
-   "version": "3.7.5"
-  },
-  "toc": {
-   "base_numbering": 1,
-   "nav_menu": {},
-   "number_sections": false,
-   "sideBar": true,
-   "skip_h1_title": true,
-   "title_cell": "Table of Contents",
-   "title_sidebar": "Contents",
-   "toc_cell": false,
-   "toc_position": {},
-   "toc_section_display": true,
-   "toc_window_display": false
   }
  },
  "nbformat": 4,

diff --git a/10_nlp.ipynb b/10_nlp.ipynb
@@ -1708,7 +1708,8 @@
     "TEXT = \"I liked this movie because\"\n",
     "N_WORDS = 40\n",
     "N_SENTENCES = 2\n",
-    "preds = [learn.predict(TEXT, N_WORDS, temperature=0.75) for _ in range(N_SENTENCES)]"
+    "preds = [learn.predict(TEXT, N_WORDS, temperature=0.75) \n",
+    "         for _ in range(N_SENTENCES)]"
    ]
   },
   {
@@ -1891,7 +1892,8 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "learn = text_classifier_learner(dls_clas, AWD_LSTM, drop_mult=0.5, metrics=accuracy).to_fp16()"
+    "learn = text_classifier_learner(dls_clas, AWD_LSTM, drop_mult=0.5, \n",
+    "                                metrics=accuracy).to_fp16()"
    ]
   },
   {
@@ -2260,20 +2262,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.7.5"
-  },
-  "toc": {
-   "base_numbering": 1,
-   "nav_menu": {},
-   "number_sections": false,
-   "sideBar": true,
-   "skip_h1_title": true,
-   "title_cell": "Table of Contents",
-   "title_sidebar": "Contents",
-   "toc_cell": false,
-   "toc_position": {},
-   "toc_section_display": true,
-   "toc_window_display": false
+   "version": "3.7.4"
   }
  },
  "nbformat": 4,

diff --git a/11_midlevel_data.ipynb b/11_midlevel_data.ipynb
@@ -602,7 +602,8 @@
    "source": [
     "cut = int(len(files)*0.8)\n",
     "splits = [list(range(cut)), list(range(cut,len(files)))]\n",
-    "tls = TfmdLists(files, [Tokenizer.from_folder(path), Numericalize], splits=splits)"
+    "tls = TfmdLists(files, [Tokenizer.from_folder(path), Numericalize], \n",
+    "                splits=splits)"
    ]
   },
   {
@@ -1083,7 +1084,8 @@
     "class SiameseTransform(Transform):\n",
     "    def __init__(self, files, label_func, splits):\n",
     "        self.labels = files.map(label_func).unique()\n",
-    "        self.lbl2files = {l: L(f for f in files if label_func(f) == l) for l in self.labels}\n",
+    "        self.lbl2files = {l: L(f for f in files if label_func(f) == l) \n",
+    "                          for l in self.labels}\n",
     "        self.label_func = label_func\n",
     "        self.valid = {f: self._draw(f) for f in files[splits[1]]}\n",
     "        \n",
@@ -1095,7 +1097,8 @@
     "    def _draw(self, f):\n",
     "        same = random.random() < 0.5\n",
     "        cls = self.label_func(f)\n",
-    "        if not same: cls = random.choice(L(l for l in self.labels if l != cls)) \n",
+    "        if not same: \n",
+    "            cls = random.choice(L(l for l in self.labels if l != cls)) \n",
     "        return random.choice(self.lbl2files[cls]),same"
    ]
   },
@@ -1246,20 +1249,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.7.5"
-  },
-  "toc": {
-   "base_numbering": 1,
-   "nav_menu": {},
-   "number_sections": false,
-   "sideBar": true,
-   "skip_h1_title": true,
-   "title_cell": "Table of Contents",
-   "title_sidebar": "Contents",
-   "toc_cell": false,
-   "toc_position": {},
-   "toc_section_display": true,
-   "toc_window_display": false
+   "version": "3.7.4"
   }
  },
  "nbformat": 4,

diff --git a/12_nlp_dive.ipynb b/12_nlp_dive.ipynb
@@ -497,7 +497,8 @@
     }
    ],
    "source": [
-    "learn = Learner(dls, LMModel1(len(vocab), 64), loss_func=F.cross_entropy, metrics=accuracy)\n",
+    "learn = Learner(dls, LMModel1(len(vocab), 64), loss_func=F.cross_entropy, \n",
+    "                metrics=accuracy)\n",
     "learn.fit_one_cycle(4, 1e-3)"
    ]
   },
@@ -654,7 +655,8 @@
     }
    ],
    "source": [
-    "learn = Learner(dls, LMModel2(len(vocab), 64), loss_func=F.cross_entropy, metrics=accuracy)\n",
+    "learn = Learner(dls, LMModel2(len(vocab), 64), loss_func=F.cross_entropy, \n",
+    "                metrics=accuracy)\n",
     "learn.fit_one_cycle(4, 1e-3)"
    ]
   },
@@ -1474,7 +1476,8 @@
     }
    ],
    "source": [
-    "learn = Learner(dls, LMModel5(len(vocab), 64, 2), loss_func=CrossEntropyLossFlat(), \n",
+    "learn = Learner(dls, LMModel5(len(vocab), 64, 2), \n",
+    "                loss_func=CrossEntropyLossFlat(), \n",
     "                metrics=accuracy, cbs=ModelReseter)\n",
     "learn.fit_one_cycle(15, 3e-3)"
    ]
@@ -1867,7 +1870,8 @@
     }
    ],
    "source": [
-    "learn = Learner(dls, LMModel6(len(vocab), 64, 2), loss_func=CrossEntropyLossFlat(), \n",
+    "learn = Learner(dls, LMModel6(len(vocab), 64, 2), \n",
+    "                loss_func=CrossEntropyLossFlat(), \n",
     "                metrics=accuracy, cbs=ModelReseter)\n",
     "learn.fit_one_cycle(15, 1e-2)"
    ]
@@ -2354,20 +2358,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.7.5"
-  },
-  "toc": {
-   "base_numbering": 1,
-   "nav_menu": {},
-   "number_sections": false,
-   "sideBar": true,
-   "skip_h1_title": true,
-   "title_cell": "Table of Contents",
-   "title_sidebar": "Contents",
-   "toc_cell": false,
-   "toc_position": {},
-   "toc_section_display": true,
-   "toc_window_display": false
+   "version": "3.7.4"
   }
  },
  "nbformat": 4,

diff --git a/13_convolutions.ipynb b/13_convolutions.ipynb
@@ -3757,6 +3757,18 @@
    "display_name": "Python 3",
    "language": "python",
    "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.7.4"
   }
  },
  "nbformat": 4,