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Reprocess: Failed notebooks from PR #480 #485

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Reprocess: Failed notebooks from PR #480 #485

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16 changes: 6 additions & 10 deletions tutorials/W2D4_Macrolearning/W2D4_Tutorial3.ipynb
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Original file line number Diff line number Diff line change
Expand Up @@ -58,16 +58,12 @@
"# @title Tutorial slides\n",
"# @markdown These are the slides for the videos in all tutorials today\n",
"\n",
"from IPython.display import IFrame\n",
"from ipywidgets import widgets\n",
"out = widgets.Output()\n",
"from IPython.display import IFrame, display\n",
"\n",
"link_id = \"t36w8\"\n",
"\n",
"with out:\n",
" print(f\"If you want to download the slides: https://osf.io/download/{link_id}/\")\n",
" display(IFrame(src=f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\", width=730, height=410))\n",
"display(out)"
"print(f\"If you want to download the slides: https://osf.io/download/{link_id}/\")\n",
"display(IFrame(src=f\"https://mfr.ca-1.osf.io/render?url=https://osf.io/{link_id}/?direct%26mode=render%26action=download%26mode=render\", width=730, height=410))"
]
},
{
Expand Down Expand Up @@ -160,7 +156,7 @@
"logging.getLogger('matplotlib.font_manager').disabled = True\n",
"\n",
"%matplotlib inline\n",
"%config InlineBackend.figure_format = 'retina' # perfrom high definition rendering for images and plots\n",
"%config InlineBackend.figure_format = 'retina' # perform high definition rendering for images and plots\n",
"plt.style.use(\"https://raw.githubusercontent.com/NeuromatchAcademy/course-content/main/nma.mplstyle\")"
]
},
Expand Down Expand Up @@ -444,7 +440,7 @@
"\n",
" def __len__(self):\n",
" \"\"\"Calculate the length of the dataset. It is obligatory for PyTorch to know in advance how many samples to expect (before training),\n",
" thus we enforced to icnlude number of epochs and tasks per epoch in `FruitSupplyDataset` parameters.\"\"\"\n",
" thus we enforced to include number of epochs and tasks per epoch in `FruitSupplyDataset` parameters.\"\"\"\n",
"\n",
" return self.num_epochs * self.num_tasks\n",
"\n",
Expand Down Expand Up @@ -758,7 +754,7 @@
"\n",
" def __len__(self):\n",
" \"\"\"Calculate the length of the dataset. It is obligatory for PyTorch to know in advance how many samples to expect (before training),\n",
" thus we enforced to icnlude number of epochs and tasks per epoch in `FruitSupplyDataset` parameters.\"\"\"\n",
" thus we enforced to include number of epochs and tasks per epoch in `FruitSupplyDataset` parameters.\"\"\"\n",
"\n",
" return self.num_epochs * self.num_tasks\n",
"\n",
Expand Down