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Small fix to tutorial

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Summary: Small fix to `fit_textured_mesh.ipynb` tutorial due to a recent change in numpy

Reviewed By: bottler

Differential Revision: D29219990

fbshipit-source-id: f5feeef9eb952720ea7154d066795fbbe64ce7a1
This commit is contained in:
Nikhila Ravi 2021-06-18 07:39:59 -07:00 committed by Facebook GitHub Bot
parent 029a9da00b
commit a343cf534c
2 changed files with 9 additions and 8 deletions
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8
docs/tutorials/deform_source_mesh_to_target_mesh.ipynb
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@ -406,10 +406,10 @@
" loop.set_description('total_loss = %.6f' % loss)\n", " loop.set_description('total_loss = %.6f' % loss)\n",
" \n", " \n",
" # Save the losses for plotting\n", " # Save the losses for plotting\n",
" chamfer_losses.append(loss_chamfer)\n", " chamfer_losses.append(float(loss_chamfer.detach().cpu()))\n",
" edge_losses.append(loss_edge)\n", " edge_losses.append(float(loss_edge.detach().cpu()))\n",
" normal_losses.append(loss_normal)\n", " normal_losses.append(float(loss_normal.detach().cpu()))\n",
" laplacian_losses.append(loss_laplacian)\n", " laplacian_losses.append(float(loss_laplacian.detach().cpu()))\n",
" \n", " \n",
" # Plot mesh\n", " # Plot mesh\n",
" if i % plot_period == 0:\n", " if i % plot_period == 0:\n",

5
docs/tutorials/fit_textured_mesh.ipynb
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@ -645,7 +645,8 @@
" sum_loss = torch.tensor(0.0, device=device)\n", " sum_loss = torch.tensor(0.0, device=device)\n",
" for k, l in loss.items():\n", " for k, l in loss.items():\n",
" sum_loss += l * losses[k][\"weight\"]\n", " sum_loss += l * losses[k][\"weight\"]\n",
" losses[k][\"values\"].append(l)\n", " losses[k][\"values\"].append(float(l.detach().cpu()))\n",
"\n",
" \n", " \n",
" # Print the losses\n", " # Print the losses\n",
" loop.set_description(\"total_loss = %.6f\" % sum_loss)\n", " loop.set_description(\"total_loss = %.6f\" % sum_loss)\n",
@ -829,7 +830,7 @@
" sum_loss = torch.tensor(0.0, device=device)\n", " sum_loss = torch.tensor(0.0, device=device)\n",
" for k, l in loss.items():\n", " for k, l in loss.items():\n",
" sum_loss += l * losses[k][\"weight\"]\n", " sum_loss += l * losses[k][\"weight\"]\n",
" losses[k][\"values\"].append(l)\n", " losses[k][\"values\"].append(float(l.detach().cpu()))\n",
" \n", " \n",
" # Print the losses\n", " # Print the losses\n",
" loop.set_description(\"total_loss = %.6f\" % sum_loss)\n", " loop.set_description(\"total_loss = %.6f\" % sum_loss)\n",