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nupic_fastai.ipynb
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| { | |
| "nbformat": 4, | |
| "nbformat_minor": 0, | |
| "metadata": { | |
| "kernelspec": { | |
| "name": "python3", | |
| "display_name": "Python 3" | |
| }, | |
| "language_info": { | |
| "codemirror_mode": { | |
| "name": "ipython", | |
| "version": 3 | |
| }, | |
| "file_extension": ".py", | |
| "mimetype": "text/x-python", | |
| "name": "python", | |
| "nbconvert_exporter": "python", | |
| "pygments_lexer": "ipython3", | |
| "version": "3.7.2" | |
| }, | |
| "colab": { | |
| "name": "nupic_fastai.ipynb", | |
| "provenance": [], | |
| "collapsed_sections": [], | |
| "include_colab_link": true | |
| }, | |
| "accelerator": "GPU" | |
| }, | |
| "cells": [ | |
| { | |
| "cell_type": "markdown", | |
| "metadata": { | |
| "id": "view-in-github", | |
| "colab_type": "text" | |
| }, | |
| "source": [ | |
| "<a href=\"https://colab.research.google.com/gist/zlapp/147ecf737c53342d46e77634d97fb8db/nupic_fastai.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>" | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "metadata": { | |
| "id": "Kjx22v1B8-SZ", | |
| "colab_type": "text" | |
| }, | |
| "source": [ | |
| "# Nupic FastAI\n", | |
| "\n", | |
| "## References\n", | |
| "Paper:\n", | |
| "\n", | |
| "https://arxiv.org/abs/1903.11257\n", | |
| "\n", | |
| "\n", | |
| "Code:\n", | |
| "\n", | |
| "https://github.com/fastai/fastai/blob/master/examples/dogs_cats.ipynb\n", | |
| "\n", | |
| "https://github.com/fastai/fastai/blob/master/examples/train_imagenette.py\n", | |
| "\n", | |
| "https://github.com/numenta/nupic.torch/blob/master/nupic/torch/models/sparse_cnn.py" | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "metadata": { | |
| "id": "NwqK8f5xAi4o", | |
| "colab_type": "text" | |
| }, | |
| "source": [ | |
| "# Setup" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "metadata": { | |
| "id": "xYhkOE4u9N3N", | |
| "colab_type": "code", | |
| "colab": { | |
| "base_uri": "https://localhost:8080/", | |
| "height": 51 | |
| }, | |
| "outputId": "0b5594ef-d465-4d35-d457-a2a4f4862555" | |
| }, | |
| "source": [ | |
| "!curl -s https://course.fast.ai/setup/colab | bash" | |
| ], | |
| "execution_count": 1, | |
| "outputs": [ | |
| { | |
| "output_type": "stream", | |
| "text": [ | |
| "Updating fastai...\n", | |
| "Done.\n" | |
| ], | |
| "name": "stdout" | |
| } | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "metadata": { | |
| "id": "-gUH_VUB8-Sc", | |
| "colab_type": "code", | |
| "colab": { | |
| "base_uri": "https://localhost:8080/", | |
| "height": 105 | |
| }, | |
| "outputId": "3a3a1efb-2f0f-4db6-a775-69389f024448" | |
| }, | |
| "source": [ | |
| "!pip install git+https://github.com/numenta/nupic.torch.git#egg=nupic.torch" | |
| ], | |
| "execution_count": 2, | |
| "outputs": [ | |
| { | |
| "output_type": "stream", | |
| "text": [ | |
| "Requirement already satisfied: nupic.torch from git+https://github.com/numenta/nupic.torch.git#egg=nupic.torch in /usr/local/lib/python3.6/dist-packages (0.0.1.dev0)\n", | |
| "Requirement already satisfied: torch==1.6 in /usr/local/lib/python3.6/dist-packages (from nupic.torch) (1.6.0+cu101)\n", | |
| "Requirement already satisfied: numpy in /usr/local/lib/python3.6/dist-packages (from torch==1.6->nupic.torch) (1.18.5)\n", | |
| "Requirement already satisfied: future in /usr/local/lib/python3.6/dist-packages (from torch==1.6->nupic.torch) (0.16.0)\n" | |
| ], | |
| "name": "stdout" | |
| } | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "metadata": { | |
| "id": "67vdcJX88-Sh", | |
| "colab_type": "code", | |
| "colab": { | |
| "base_uri": "https://localhost:8080/", | |
| "height": 34 | |
| }, | |
| "outputId": "e0171de6-5caf-4611-c093-49fc7994c17b" | |
| }, | |
| "source": [ | |
| "%reload_ext autoreload\n", | |
| "%autoreload 2\n", | |
| "%matplotlib\n", | |
| "\n", | |
| "from fastai.script import *\n", | |
| "from fastai.vision import *\n", | |
| "from fastai.callbacks import *\n", | |
| "from fastai.distributed import *\n", | |
| "from fastprogress import fastprogress" | |
| ], | |
| "execution_count": 3, | |
| "outputs": [ | |
| { | |
| "output_type": "stream", | |
| "text": [ | |
| "Using matplotlib backend: agg\n" | |
| ], | |
| "name": "stdout" | |
| } | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "metadata": { | |
| "id": "49J3XiGKAk1S", | |
| "colab_type": "code", | |
| "colab": {} | |
| }, | |
| "source": [ | |
| "#config\n", | |
| "# gpu=None\n", | |
| "woof=0\n", | |
| "lr=1e-3\n", | |
| "size=128\n", | |
| "alpha=0.99\n", | |
| "mom=0.9\n", | |
| "eps=1e-6\n", | |
| "epochs=5\n", | |
| "bs=256\n", | |
| "mixup=0.\n", | |
| "opt='adam'\n", | |
| "dump=0" | |
| ], | |
| "execution_count": 4, | |
| "outputs": [] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "metadata": { | |
| "id": "r57Jv0iW8-Sp", | |
| "colab_type": "text" | |
| }, | |
| "source": [ | |
| "# Data Loading" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "metadata": { | |
| "id": "ya7XKVAS8-Sq", | |
| "colab_type": "code", | |
| "colab": {} | |
| }, | |
| "source": [ | |
| "def get_data(size, woof, bs, workers=None):\n", | |
| " path = URLs.IMAGEWOOF if woof else URLs.IMAGENETTE\n", | |
| " path = untar_data(path)\n", | |
| "\n", | |
| " n_gpus = num_distrib() or 1\n", | |
| " if workers is None: workers = min(8, num_cpus()//n_gpus)\n", | |
| "\n", | |
| " return (ImageList.from_folder(path).split_by_folder(valid='val')\n", | |
| " .label_from_folder().transform(([flip_lr(p=0.5)], []), size=size)\n", | |
| " .databunch(bs=bs, num_workers=workers)\n", | |
| " .presize(size, scale=(0.35,1))\n", | |
| " .normalize(imagenet_stats))" | |
| ], | |
| "execution_count": 5, | |
| "outputs": [] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "metadata": { | |
| "id": "Tz3uFJDE8-Su", | |
| "colab_type": "code", | |
| "colab": { | |
| "base_uri": "https://localhost:8080/", | |
| "height": 1000 | |
| }, | |
| "outputId": "e2fbc8f4-1cb0-45f7-9064-460ffedb5979" | |
| }, | |
| "source": [ | |
| "# gpu = setup_distrib(gpu)\n", | |
| "# if gpu is None: bs *= torch.cuda.device_count()\n", | |
| "# if opt=='adam' : opt_func = partial(optim.Adam, betas=(mom,alpha), eps=eps)\n", | |
| "# elif opt=='rms' : opt_func = partial(optim.RMSprop, alpha=alpha, eps=eps)\n", | |
| "# elif opt=='sgd' : opt_func = partial(optim.SGD, momentum=mom)\n", | |
| "\n", | |
| "data = get_data(size, woof, bs)\n", | |
| "# bs_rat = bs/256\n", | |
| "# if gpu is not None: bs_rat *= num_distrib()\n", | |
| "# if not gpu: print(f'lr: {lr}; eff_lr: {lr*bs_rat}; size: {size}; alpha: {alpha}; mom: {mom}; eps: {eps}')\n", | |
| "# lr *= bs_rat\n", | |
| "\n", | |
| "# data.show_batch(4)" | |
| ], | |
| "execution_count": 6, | |
| "outputs": [ | |
| { | |
| "output_type": "stream", | |
| "text": [ | |
| "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. \n", | |
| " warnings.warn(\"The default behavior for interpolate/upsample with float scale_factor changed \"\n", | |
| "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. \n", | |
| " warnings.warn(\"The default behavior for interpolate/upsample with float scale_factor changed \"\n", | |
| "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. \n", | |
| " warnings.warn(\"The default behavior for interpolate/upsample with float scale_factor changed \"\n", | |
| "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. \n", | |
| " warnings.warn(\"The default behavior for interpolate/upsample with float scale_factor changed \"\n", | |
| "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. \n", | |
| " warnings.warn(\"The default behavior for interpolate/upsample with float scale_factor changed \"\n", | |
| "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. \n", | |
| " warnings.warn(\"The default behavior for interpolate/upsample with float scale_factor changed \"\n", | |
| "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. \n", | |
| " warnings.warn(\"The default behavior for interpolate/upsample with float scale_factor changed \"\n", | |
| "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. \n", | |
| " warnings.warn(\"The default behavior for interpolate/upsample with float scale_factor changed \"\n", | |
| "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. \n", | |
| " warnings.warn(\"The default behavior for interpolate/upsample with float scale_factor changed \"\n", | |
| "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. \n", | |
| " warnings.warn(\"The default behavior for interpolate/upsample with float scale_factor changed \"\n", | |
| "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. \n", | |
| " warnings.warn(\"The default behavior for interpolate/upsample with float scale_factor changed \"\n", | |
| "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. \n", | |
| " warnings.warn(\"The default behavior for interpolate/upsample with float scale_factor changed \"\n", | |
| "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. \n", | |
| " warnings.warn(\"The default behavior for interpolate/upsample with float scale_factor changed \"\n", | |
| "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. \n", | |
| " warnings.warn(\"The default behavior for interpolate/upsample with float scale_factor changed \"\n", | |
| "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. \n", | |
| " warnings.warn(\"The default behavior for interpolate/upsample with float scale_factor changed \"\n", | |
| "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. \n", | |
| " warnings.warn(\"The default behavior for interpolate/upsample with float scale_factor changed \"\n", | |
| "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. \n", | |
| " warnings.warn(\"The default behavior for interpolate/upsample with float scale_factor changed \"\n", | |
| "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. \n", | |
| " warnings.warn(\"The default behavior for interpolate/upsample with float scale_factor changed \"\n", | |
| "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. \n", | |
| " warnings.warn(\"The default behavior for interpolate/upsample with float scale_factor changed \"\n", | |
| "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. \n", | |
| " warnings.warn(\"The default behavior for interpolate/upsample with float scale_factor changed \"\n", | |
| "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. \n", | |
| " warnings.warn(\"The default behavior for interpolate/upsample with float scale_factor changed \"\n", | |
| "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. \n", | |
| " warnings.warn(\"The default behavior for interpolate/upsample with float scale_factor changed \"\n", | |
| "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. \n", | |
| " warnings.warn(\"The default behavior for interpolate/upsample with float scale_factor changed \"\n", | |
| "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. \n", | |
| " warnings.warn(\"The default behavior for interpolate/upsample with float scale_factor changed \"\n", | |
| "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. \n", | |
| " warnings.warn(\"The default behavior for interpolate/upsample with float scale_factor changed \"\n", | |
| "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. \n", | |
| " warnings.warn(\"The default behavior for interpolate/upsample with float scale_factor changed \"\n", | |
| "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. \n", | |
| " warnings.warn(\"The default behavior for interpolate/upsample with float scale_factor changed \"\n", | |
| "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. \n", | |
| " warnings.warn(\"The default behavior for interpolate/upsample with float scale_factor changed \"\n", | |
| "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. \n", | |
| " warnings.warn(\"The default behavior for interpolate/upsample with float scale_factor changed \"\n", | |
| "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. \n", | |
| " warnings.warn(\"The default behavior for interpolate/upsample with float scale_factor changed \"\n", | |
| "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. \n", | |
| " warnings.warn(\"The default behavior for interpolate/upsample with float scale_factor changed \"\n", | |
| "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. \n", | |
| " warnings.warn(\"The default behavior for interpolate/upsample with float scale_factor changed \"\n", | |
| "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. \n", | |
| " warnings.warn(\"The default behavior for interpolate/upsample with float scale_factor changed \"\n", | |
| "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. \n", | |
| " warnings.warn(\"The default behavior for interpolate/upsample with float scale_factor changed \"\n", | |
| "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. \n", | |
| " warnings.warn(\"The default behavior for interpolate/upsample with float scale_factor changed \"\n", | |
| "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. \n", | |
| " warnings.warn(\"The default behavior for interpolate/upsample with float scale_factor changed \"\n", | |
| "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. \n", | |
| " warnings.warn(\"The default behavior for interpolate/upsample with float scale_factor changed \"\n", | |
| "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. \n", | |
| " warnings.warn(\"The default behavior for interpolate/upsample with float scale_factor changed \"\n", | |
| "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. \n", | |
| " warnings.warn(\"The default behavior for interpolate/upsample with float scale_factor changed \"\n", | |
| "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. \n", | |
| " warnings.warn(\"The default behavior for interpolate/upsample with float scale_factor changed \"\n", | |
| "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. \n", | |
| " warnings.warn(\"The default behavior for interpolate/upsample with float scale_factor changed \"\n", | |
| "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. \n", | |
| " warnings.warn(\"The default behavior for interpolate/upsample with float scale_factor changed \"\n", | |
| "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. \n", | |
| " warnings.warn(\"The default behavior for interpolate/upsample with float scale_factor changed \"\n", | |
| "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. \n", | |
| " warnings.warn(\"The default behavior for interpolate/upsample with float scale_factor changed \"\n", | |
| "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. \n", | |
| " warnings.warn(\"The default behavior for interpolate/upsample with float scale_factor changed \"\n", | |
| "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. \n", | |
| " warnings.warn(\"The default behavior for interpolate/upsample with float scale_factor changed \"\n", | |
| "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. \n", | |
| " warnings.warn(\"The default behavior for interpolate/upsample with float scale_factor changed \"\n", | |
| "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. \n", | |
| " warnings.warn(\"The default behavior for interpolate/upsample with float scale_factor changed \"\n", | |
| "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. \n", | |
| " warnings.warn(\"The default behavior for interpolate/upsample with float scale_factor changed \"\n", | |
| "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. \n", | |
| " warnings.warn(\"The default behavior for interpolate/upsample with float scale_factor changed \"\n", | |
| "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. \n", | |
| " warnings.warn(\"The default behavior for interpolate/upsample with float scale_factor changed \"\n", | |
| "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. \n", | |
| " warnings.warn(\"The default behavior for interpolate/upsample with float scale_factor changed \"\n", | |
| "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. \n", | |
| " warnings.warn(\"The default behavior for interpolate/upsample with float scale_factor changed \"\n", | |
| "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. \n", | |
| " warnings.warn(\"The default behavior for interpolate/upsample with float scale_factor changed \"\n", | |
| "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. \n", | |
| " warnings.warn(\"The default behavior for interpolate/upsample with float scale_factor changed \"\n", | |
| "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. \n", | |
| " warnings.warn(\"The default behavior for interpolate/upsample with float scale_factor changed \"\n", | |
| "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. \n", | |
| " warnings.warn(\"The default behavior for interpolate/upsample with float scale_factor changed \"\n", | |
| "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. \n", | |
| " warnings.warn(\"The default behavior for interpolate/upsample with float scale_factor changed \"\n", | |
| "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. \n", | |
| " warnings.warn(\"The default behavior for interpolate/upsample with float scale_factor changed \"\n", | |
| "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. \n", | |
| " warnings.warn(\"The default behavior for interpolate/upsample with float scale_factor changed \"\n", | |
| "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. \n", | |
| " warnings.warn(\"The default behavior for interpolate/upsample with float scale_factor changed \"\n", | |
| "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. \n", | |
| " warnings.warn(\"The default behavior for interpolate/upsample with float scale_factor changed \"\n", | |
| "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. \n", | |
| " warnings.warn(\"The default behavior for interpolate/upsample with float scale_factor changed \"\n", | |
| "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. \n", | |
| " warnings.warn(\"The default behavior for interpolate/upsample with float scale_factor changed \"\n", | |
| "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. \n", | |
| " warnings.warn(\"The default behavior for interpolate/upsample with float scale_factor changed \"\n", | |
| "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. \n", | |
| " warnings.warn(\"The default behavior for interpolate/upsample with float scale_factor changed \"\n", | |
| "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. \n", | |
| " warnings.warn(\"The default behavior for interpolate/upsample with float scale_factor changed \"\n", | |
| "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. \n", | |
| " warnings.warn(\"The default behavior for interpolate/upsample with float scale_factor changed \"\n", | |
| "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. \n", | |
| " warnings.warn(\"The default behavior for interpolate/upsample with float scale_factor changed \"\n", | |
| "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. \n", | |
| " warnings.warn(\"The default behavior for interpolate/upsample with float scale_factor changed \"\n", | |
| "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. \n", | |
| " warnings.warn(\"The default behavior for interpolate/upsample with float scale_factor changed \"\n", | |
| "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. \n", | |
| " warnings.warn(\"The default behavior for interpolate/upsample with float scale_factor changed \"\n", | |
| "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. \n", | |
| " warnings.warn(\"The default behavior for interpolate/upsample with float scale_factor changed \"\n", | |
| "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. \n", | |
| " warnings.warn(\"The default behavior for interpolate/upsample with float scale_factor changed \"\n", | |
| "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. \n", | |
| " warnings.warn(\"The default behavior for interpolate/upsample with float scale_factor changed \"\n", | |
| "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. \n", | |
| " warnings.warn(\"The default behavior for interpolate/upsample with float scale_factor changed \"\n", | |
| "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. \n", | |
| " warnings.warn(\"The default behavior for interpolate/upsample with float scale_factor changed \"\n", | |
| "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. \n", | |
| " warnings.warn(\"The default behavior for interpolate/upsample with float scale_factor changed \"\n", | |
| "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. \n", | |
| " warnings.warn(\"The default behavior for interpolate/upsample with float scale_factor changed \"\n", | |
| "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. \n", | |
| " warnings.warn(\"The default behavior for interpolate/upsample with float scale_factor changed \"\n", | |
| "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. \n", | |
| " warnings.warn(\"The default behavior for interpolate/upsample with float scale_factor changed \"\n", | |
| "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. \n", | |
| " warnings.warn(\"The default behavior for interpolate/upsample with float scale_factor changed \"\n", | |
| "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. \n", | |
| " warnings.warn(\"The default behavior for interpolate/upsample with float scale_factor changed \"\n", | |
| "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. \n", | |
| " warnings.warn(\"The default behavior for interpolate/upsample with float scale_factor changed \"\n", | |
| "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. \n", | |
| " warnings.warn(\"The default behavior for interpolate/upsample with float scale_factor changed \"\n", | |
| "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. \n", | |
| " warnings.warn(\"The default behavior for interpolate/upsample with float scale_factor changed \"\n", | |
| "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. \n", | |
| " warnings.warn(\"The default behavior for interpolate/upsample with float scale_factor changed \"\n", | |
| "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. \n", | |
| " warnings.warn(\"The default behavior for interpolate/upsample with float scale_factor changed \"\n", | |
| "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. \n", | |
| " warnings.warn(\"The default behavior for interpolate/upsample with float scale_factor changed \"\n", | |
| "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. \n", | |
| " warnings.warn(\"The default behavior for interpolate/upsample with float scale_factor changed \"\n", | |
| "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. \n", | |
| " warnings.warn(\"The default behavior for interpolate/upsample with float scale_factor changed \"\n", | |
| "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. \n", | |
| " warnings.warn(\"The default behavior for interpolate/upsample with float scale_factor changed \"\n", | |
| "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. \n", | |
| " warnings.warn(\"The default behavior for interpolate/upsample with float scale_factor changed \"\n", | |
| "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. \n", | |
| " warnings.warn(\"The default behavior for interpolate/upsample with float scale_factor changed \"\n", | |
| "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. \n", | |
| " warnings.warn(\"The default behavior for interpolate/upsample with float scale_factor changed \"\n", | |
| "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. \n", | |
| " warnings.warn(\"The default behavior for interpolate/upsample with float scale_factor changed \"\n", | |
| "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. \n", | |
| " warnings.warn(\"The default behavior for interpolate/upsample with float scale_factor changed \"\n", | |
| "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. \n", | |
| " warnings.warn(\"The default behavior for interpolate/upsample with float scale_factor changed \"\n", | |
| "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. \n", | |
| " warnings.warn(\"The default behavior for interpolate/upsample with float scale_factor changed \"\n", | |
| "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. \n", | |
| " warnings.warn(\"The default behavior for interpolate/upsample with float scale_factor changed \"\n", | |
| "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. \n", | |
| " warnings.warn(\"The default behavior for interpolate/upsample with float scale_factor changed \"\n", | |
| "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. \n", | |
| " warnings.warn(\"The default behavior for interpolate/upsample with float scale_factor changed \"\n", | |
| "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. \n", | |
| " warnings.warn(\"The default behavior for interpolate/upsample with float scale_factor changed \"\n", | |
| "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. \n", | |
| " warnings.warn(\"The default behavior for interpolate/upsample with float scale_factor changed \"\n", | |
| "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. \n", | |
| " warnings.warn(\"The default behavior for interpolate/upsample with float scale_factor changed \"\n", | |
| "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. \n", | |
| " warnings.warn(\"The default behavior for interpolate/upsample with float scale_factor changed \"\n", | |
| "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. \n", | |
| " warnings.warn(\"The default behavior for interpolate/upsample with float scale_factor changed \"\n", | |
| "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. \n", | |
| " warnings.warn(\"The default behavior for interpolate/upsample with float scale_factor changed \"\n", | |
| "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. \n", | |
| " warnings.warn(\"The default behavior for interpolate/upsample with float scale_factor changed \"\n", | |
| "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. \n", | |
| " warnings.warn(\"The default behavior for interpolate/upsample with float scale_factor changed \"\n", | |
| "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. \n", | |
| " warnings.warn(\"The default behavior for interpolate/upsample with float scale_factor changed \"\n", | |
| "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. \n", | |
| " warnings.warn(\"The default behavior for interpolate/upsample with float scale_factor changed \"\n", | |
| "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. \n", | |
| " warnings.warn(\"The default behavior for interpolate/upsample with float scale_factor changed \"\n", | |
| "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. \n", | |
| " warnings.warn(\"The default behavior for interpolate/upsample with float scale_factor changed \"\n", | |
| "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. \n", | |
| " warnings.warn(\"The default behavior for interpolate/upsample with float scale_factor changed \"\n", | |
| "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. \n", | |
| " warnings.warn(\"The default behavior for interpolate/upsample with float scale_factor changed \"\n", | |
| "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. \n", | |
| " warnings.warn(\"The default behavior for interpolate/upsample with float scale_factor changed \"\n", | |
| "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. \n", | |
| " warnings.warn(\"The default behavior for interpolate/upsample with float scale_factor changed \"\n", | |
| "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. \n", | |
| " warnings.warn(\"The default behavior for interpolate/upsample with float scale_factor changed \"\n", | |
| "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. \n", | |
| " warnings.warn(\"The default behavior for interpolate/upsample with float scale_factor changed \"\n", | |
| "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. \n", | |
| " warnings.warn(\"The default behavior for interpolate/upsample with float scale_factor changed \"\n", | |
| "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. \n", | |
| " warnings.warn(\"The default behavior for interpolate/upsample with float scale_factor changed \"\n", | |
| "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. \n", | |
| " warnings.warn(\"The default behavior for interpolate/upsample with float scale_factor changed \"\n", | |
| "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. \n", | |
| " warnings.warn(\"The default behavior for interpolate/upsample with float scale_factor changed \"\n", | |
| "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. \n", | |
| " warnings.warn(\"The default behavior for interpolate/upsample with float scale_factor changed \"\n", | |
| "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. \n", | |
| " warnings.warn(\"The default behavior for interpolate/upsample with float scale_factor changed \"\n", | |
| "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. \n", | |
| " warnings.warn(\"The default behavior for interpolate/upsample with float scale_factor changed \"\n", | |
| "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. \n", | |
| " warnings.warn(\"The default behavior for interpolate/upsample with float scale_factor changed \"\n", | |
| "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. \n", | |
| " warnings.warn(\"The default behavior for interpolate/upsample with float scale_factor changed \"\n", | |
| "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. \n", | |
| " warnings.warn(\"The default behavior for interpolate/upsample with float scale_factor changed \"\n", | |
| "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. \n", | |
| " warnings.warn(\"The default behavior for interpolate/upsample with float scale_factor changed \"\n", | |
| "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. \n", | |
| " warnings.warn(\"The default behavior for interpolate/upsample with float scale_factor changed \"\n", | |
| "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. \n", | |
| " warnings.warn(\"The default behavior for interpolate/upsample with float scale_factor changed \"\n", | |
| "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. \n", | |
| " warnings.warn(\"The default behavior for interpolate/upsample with float scale_factor changed \"\n", | |
| "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. \n", | |
| " warnings.warn(\"The default behavior for interpolate/upsample with float scale_factor changed \"\n", | |
| "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. \n", | |
| " warnings.warn(\"The default behavior for interpolate/upsample with float scale_factor changed \"\n", | |
| "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. \n", | |
| " warnings.warn(\"The default behavior for interpolate/upsample with float scale_factor changed \"\n", | |
| "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. \n", | |
| " warnings.warn(\"The default behavior for interpolate/upsample with float scale_factor changed \"\n", | |
| "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. \n", | |
| " warnings.warn(\"The default behavior for interpolate/upsample with float scale_factor changed \"\n", | |
| "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. \n", | |
| " warnings.warn(\"The default behavior for interpolate/upsample with float scale_factor changed \"\n", | |
| "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. \n", | |
| " warnings.warn(\"The default behavior for interpolate/upsample with float scale_factor changed \"\n", | |
| "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. \n", | |
| " warnings.warn(\"The default behavior for interpolate/upsample with float scale_factor changed \"\n", | |
| "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. \n", | |
| " warnings.warn(\"The default behavior for interpolate/upsample with float scale_factor changed \"\n", | |
| "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. \n", | |
| " warnings.warn(\"The default behavior for interpolate/upsample with float scale_factor changed \"\n", | |
| "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. \n", | |
| " warnings.warn(\"The default behavior for interpolate/upsample with float scale_factor changed \"\n", | |
| "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. \n", | |
| " warnings.warn(\"The default behavior for interpolate/upsample with float scale_factor changed \"\n", | |
| "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. \n", | |
| " warnings.warn(\"The default behavior for interpolate/upsample with float scale_factor changed \"\n", | |
| "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. \n", | |
| " warnings.warn(\"The default behavior for interpolate/upsample with float scale_factor changed \"\n", | |
| "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. \n", | |
| " warnings.warn(\"The default behavior for interpolate/upsample with float scale_factor changed \"\n", | |
| "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. \n", | |
| " warnings.warn(\"The default behavior for interpolate/upsample with float scale_factor changed \"\n", | |
| "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. \n", | |
| " warnings.warn(\"The default behavior for interpolate/upsample with float scale_factor changed \"\n", | |
| "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. \n", | |
| " warnings.warn(\"The default behavior for interpolate/upsample with float scale_factor changed \"\n", | |
| "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. \n", | |
| " warnings.warn(\"The default behavior for interpolate/upsample with float scale_factor changed \"\n", | |
| "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. \n", | |
| " warnings.warn(\"The default behavior for interpolate/upsample with float scale_factor changed \"\n", | |
| "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. \n", | |
| " warnings.warn(\"The default behavior for interpolate/upsample with float scale_factor changed \"\n", | |
| "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. \n", | |
| " warnings.warn(\"The default behavior for interpolate/upsample with float scale_factor changed \"\n", | |
| "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. \n", | |
| " warnings.warn(\"The default behavior for interpolate/upsample with float scale_factor changed \"\n", | |
| "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. \n", | |
| " warnings.warn(\"The default behavior for interpolate/upsample with float scale_factor changed \"\n", | |
| "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. \n", | |
| " warnings.warn(\"The default behavior for interpolate/upsample with float scale_factor changed \"\n", | |
| "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. \n", | |
| " warnings.warn(\"The default behavior for interpolate/upsample with float scale_factor changed \"\n", | |
| "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. \n", | |
| " warnings.warn(\"The default behavior for interpolate/upsample with float scale_factor changed \"\n", | |
| "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. \n", | |
| " warnings.warn(\"The default behavior for interpolate/upsample with float scale_factor changed \"\n", | |
| "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. \n", | |
| " warnings.warn(\"The default behavior for interpolate/upsample with float scale_factor changed \"\n", | |
| "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. \n", | |
| " warnings.warn(\"The default behavior for interpolate/upsample with float scale_factor changed \"\n", | |
| "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. \n", | |
| " warnings.warn(\"The default behavior for interpolate/upsample with float scale_factor changed \"\n", | |
| "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. \n", | |
| " warnings.warn(\"The default behavior for interpolate/upsample with float scale_factor changed \"\n", | |
| "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. \n", | |
| " warnings.warn(\"The default behavior for interpolate/upsample with float scale_factor changed \"\n", | |
| "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. \n", | |
| " warnings.warn(\"The default behavior for interpolate/upsample with float scale_factor changed \"\n", | |
| "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. \n", | |
| " warnings.warn(\"The default behavior for interpolate/upsample with float scale_factor changed \"\n", | |
| "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. \n", | |
| " warnings.warn(\"The default behavior for interpolate/upsample with float scale_factor changed \"\n", | |
| "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. \n", | |
| " warnings.warn(\"The default behavior for interpolate/upsample with float scale_factor changed \"\n", | |
| "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. \n", | |
| " warnings.warn(\"The default behavior for interpolate/upsample with float scale_factor changed \"\n", | |
| "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. \n", | |
| " warnings.warn(\"The default behavior for interpolate/upsample with float scale_factor changed \"\n", | |
| "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. \n", | |
| " warnings.warn(\"The default behavior for interpolate/upsample with float scale_factor changed \"\n", | |
| "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. \n", | |
| " warnings.warn(\"The default behavior for interpolate/upsample with float scale_factor changed \"\n", | |
| "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. \n", | |
| " warnings.warn(\"The default behavior for interpolate/upsample with float scale_factor changed \"\n", | |
| "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. \n", | |
| " warnings.warn(\"The default behavior for interpolate/upsample with float scale_factor changed \"\n", | |
| "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. \n", | |
| " warnings.warn(\"The default behavior for interpolate/upsample with float scale_factor changed \"\n", | |
| "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. \n", | |
| " warnings.warn(\"The default behavior for interpolate/upsample with float scale_factor changed \"\n", | |
| "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. \n", | |
| " warnings.warn(\"The default behavior for interpolate/upsample with float scale_factor changed \"\n", | |
| "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. \n", | |
| " warnings.warn(\"The default behavior for interpolate/upsample with float scale_factor changed \"\n", | |
| "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. \n", | |
| " warnings.warn(\"The default behavior for interpolate/upsample with float scale_factor changed \"\n", | |
| "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. \n", | |
| " warnings.warn(\"The default behavior for interpolate/upsample with float scale_factor changed \"\n", | |
| "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. \n", | |
| " warnings.warn(\"The default behavior for interpolate/upsample with float scale_factor changed \"\n", | |
| "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. \n", | |
| " warnings.warn(\"The default behavior for interpolate/upsample with float scale_factor changed \"\n", | |
| "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. \n", | |
| " warnings.warn(\"The default behavior for interpolate/upsample with float scale_factor changed \"\n", | |
| "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. \n", | |
| " warnings.warn(\"The default behavior for interpolate/upsample with float scale_factor changed \"\n", | |
| "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. \n", | |
| " warnings.warn(\"The default behavior for interpolate/upsample with float scale_factor changed \"\n", | |
| "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. \n", | |
| " warnings.warn(\"The default behavior for interpolate/upsample with float scale_factor changed \"\n", | |
| "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. \n", | |
| " warnings.warn(\"The default behavior for interpolate/upsample with float scale_factor changed \"\n", | |
| "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. \n", | |
| " warnings.warn(\"The default behavior for interpolate/upsample with float scale_factor changed \"\n", | |
| "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. \n", | |
| " warnings.warn(\"The default behavior for interpolate/upsample with float scale_factor changed \"\n", | |
| "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. \n", | |
| " warnings.warn(\"The default behavior for interpolate/upsample with float scale_factor changed \"\n", | |
| "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. \n", | |
| " warnings.warn(\"The default behavior for interpolate/upsample with float scale_factor changed \"\n", | |
| "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. \n", | |
| " warnings.warn(\"The default behavior for interpolate/upsample with float scale_factor changed \"\n", | |
| "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. \n", | |
| " warnings.warn(\"The default behavior for interpolate/upsample with float scale_factor changed \"\n", | |
| "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. \n", | |
| " warnings.warn(\"The default behavior for interpolate/upsample with float scale_factor changed \"\n", | |
| "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. \n", | |
| " warnings.warn(\"The default behavior for interpolate/upsample with float scale_factor changed \"\n", | |
| "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. \n", | |
| " warnings.warn(\"The default behavior for interpolate/upsample with float scale_factor changed \"\n", | |
| "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. \n", | |
| " warnings.warn(\"The default behavior for interpolate/upsample with float scale_factor changed \"\n", | |
| "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. \n", | |
| " warnings.warn(\"The default behavior for interpolate/upsample with float scale_factor changed \"\n", | |
| "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. \n", | |
| " warnings.warn(\"The default behavior for interpolate/upsample with float scale_factor changed \"\n", | |
| "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. \n", | |
| " warnings.warn(\"The default behavior for interpolate/upsample with float scale_factor changed \"\n", | |
| "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. \n", | |
| " warnings.warn(\"The default behavior for interpolate/upsample with float scale_factor changed \"\n", | |
| "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. \n", | |
| " warnings.warn(\"The default behavior for interpolate/upsample with float scale_factor changed \"\n", | |
| "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. \n", | |
| " warnings.warn(\"The default behavior for interpolate/upsample with float scale_factor changed \"\n", | |
| "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. \n", | |
| " warnings.warn(\"The default behavior for interpolate/upsample with float scale_factor changed \"\n", | |
| "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. \n", | |
| " warnings.warn(\"The default behavior for interpolate/upsample with float scale_factor changed \"\n", | |
| "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. \n", | |
| " warnings.warn(\"The default behavior for interpolate/upsample with float scale_factor changed \"\n", | |
| "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. \n", | |
| " warnings.warn(\"The default behavior for interpolate/upsample with float scale_factor changed \"\n", | |
| "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. \n", | |
| " warnings.warn(\"The default behavior for interpolate/upsample with float scale_factor changed \"\n", | |
| "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. \n", | |
| " warnings.warn(\"The default behavior for interpolate/upsample with float scale_factor changed \"\n", | |
| "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. \n", | |
| " warnings.warn(\"The default behavior for interpolate/upsample with float scale_factor changed \"\n", | |
| "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. \n", | |
| " warnings.warn(\"The default behavior for interpolate/upsample with float scale_factor changed \"\n", | |
| "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. \n", | |
| " warnings.warn(\"The default behavior for interpolate/upsample with float scale_factor changed \"\n", | |
| "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. \n", | |
| " warnings.warn(\"The default behavior for interpolate/upsample with float scale_factor changed \"\n", | |
| "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. \n", | |
| " warnings.warn(\"The default behavior for interpolate/upsample with float scale_factor changed \"\n", | |
| "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. \n", | |
| " warnings.warn(\"The default behavior for interpolate/upsample with float scale_factor changed \"\n", | |
| "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. \n", | |
| " warnings.warn(\"The default behavior for interpolate/upsample with float scale_factor changed \"\n", | |
| "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. \n", | |
| " warnings.warn(\"The default behavior for interpolate/upsample with float scale_factor changed \"\n", | |
| "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. \n", | |
| " warnings.warn(\"The default behavior for interpolate/upsample with float scale_factor changed \"\n", | |
| "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. \n", | |
| " warnings.warn(\"The default behavior for interpolate/upsample with float scale_factor changed \"\n", | |
| "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. \n", | |
| " warnings.warn(\"The default behavior for interpolate/upsample with float scale_factor changed \"\n", | |
| "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. \n", | |
| " warnings.warn(\"The default behavior for interpolate/upsample with float scale_factor changed \"\n", | |
| "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. \n", | |
| " warnings.warn(\"The default behavior for interpolate/upsample with float scale_factor changed \"\n", | |
| "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. \n", | |
| " warnings.warn(\"The default behavior for interpolate/upsample with float scale_factor changed \"\n", | |
| "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:3000: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and uses scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. \n", | |
| " warnings.warn(\"The default behavior for interpolate/upsample with float scale_factor changed \"\n" | |
| ], | |
| "name": "stderr" | |
| } | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "metadata": { | |
| "id": "HSAdoLbF8-Sk", | |
| "colab_type": "text" | |
| }, | |
| "source": [ | |
| "## Model Definition" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "metadata": { | |
| "id": "6S8PZS8K8-Sm", | |
| "colab_type": "code", | |
| "colab": {} | |
| }, | |
| "source": [ | |
| "from collections import OrderedDict\n", | |
| "\n", | |
| "from torch import nn\n", | |
| "from torch.hub import load_state_dict_from_url\n", | |
| "\n", | |
| "from nupic.torch.modules import Flatten, KWinners, KWinners2d, SparseWeights\n", | |
| "\n", | |
| "\n", | |
| "class CNN(nn.Sequential):\n", | |
| " def __init__(self,\n", | |
| " cnn_out_channels=(32, 64),\n", | |
| " cnn_percent_on=(0.087, 0.293),\n", | |
| " linear_units=700,\n", | |
| " num_classes=10\n", | |
| " ):\n", | |
| " super(CNN, self).__init__(OrderedDict([\n", | |
| " # First Sparse CNN layer\n", | |
| " (\"cnn1\", nn.Conv2d(3, cnn_out_channels[0], 5)),\n", | |
| " (\"cnn1_maxpool\", nn.MaxPool2d(2)),\n", | |
| "\n", | |
| "\n", | |
| " # Second Sparse CNN layer\n", | |
| " (\"cnn2\", nn.Conv2d(cnn_out_channels[0], cnn_out_channels[1], 5)),\n", | |
| " (\"cnn2_maxpool\", nn.MaxPool2d(2)),\n", | |
| "\n", | |
| " (\"flatten\", Flatten()),\n", | |
| "\n", | |
| " # Classifier\n", | |
| " (\"output\", nn.Linear(linear_units, out_features=num_classes)),\n", | |
| " (\"softmax\", nn.LogSoftmax(dim=1))\n", | |
| " ]))\n", | |
| "\n", | |
| "class SparseCNN(nn.Sequential):\n", | |
| " \"\"\"Sparse CNN model used to classify `MNIST` dataset as described in `How\n", | |
| " Can We Be So Dense?`_ paper.\n", | |
| " .. _`How Can We Be So Dense?`: https://arxiv.org/abs/1903.11257\n", | |
| " :param cnn_out_channels: output channels for each CNN layer\n", | |
| " :param cnn_percent_on: Percent of units allowed to remain on each convolution\n", | |
| " layer\n", | |
| " :param linear_units: Number of units in the linear layer\n", | |
| " :param linear_percent_on: Percent of units allowed to remain on the linear\n", | |
| " layer\n", | |
| " :param linear_weight_sparsity: Percent of weights that are allowed to be\n", | |
| " non-zero in the linear layer\n", | |
| " :param k_inference_factor: During inference (training=False) we increase\n", | |
| " `percent_on` in all sparse layers by this factor\n", | |
| " :param boost_strength: boost strength (0.0 implies no boosting)\n", | |
| " :param boost_strength_factor: Boost strength factor to use [0..1]\n", | |
| " :param duty_cycle_period: The period used to calculate duty cycles\n", | |
| " \"\"\"\n", | |
| "\n", | |
| " def __init__(self,\n", | |
| " cnn_out_channels=(32, 64),\n", | |
| " cnn_percent_on=(0.087, 0.293),\n", | |
| " linear_units=700,\n", | |
| " linear_percent_on=0.143,\n", | |
| " linear_weight_sparsity=0.3,\n", | |
| " boost_strength=1.5,\n", | |
| " boost_strength_factor=0.85,\n", | |
| " k_inference_factor=1.5,\n", | |
| " duty_cycle_period=1000,\n", | |
| " num_classes=10\n", | |
| " ):\n", | |
| " super(SparseCNN, self).__init__(OrderedDict([\n", | |
| " # First Sparse CNN layer\n", | |
| " (\"cnn1\", nn.Conv2d(3, cnn_out_channels[0], 5)),\n", | |
| " (\"cnn1_maxpool\", nn.MaxPool2d(2)),\n", | |
| " (\"cnn1_kwinner\", KWinners2d(channels=cnn_out_channels[0],\n", | |
| " percent_on=cnn_percent_on[0],\n", | |
| " k_inference_factor=k_inference_factor,\n", | |
| " boost_strength=boost_strength,\n", | |
| " boost_strength_factor=boost_strength_factor,\n", | |
| " duty_cycle_period=duty_cycle_period)),\n", | |
| "\n", | |
| " # Second Sparse CNN layer\n", | |
| " (\"cnn2\", nn.Conv2d(cnn_out_channels[0], cnn_out_channels[1], 5)),\n", | |
| " (\"cnn2_maxpool\", nn.MaxPool2d(2)),\n", | |
| " (\"cnn2_kwinner\", KWinners2d(channels=cnn_out_channels[1],\n", | |
| " percent_on=cnn_percent_on[1],\n", | |
| " k_inference_factor=k_inference_factor,\n", | |
| " boost_strength=boost_strength,\n", | |
| " boost_strength_factor=boost_strength_factor,\n", | |
| " duty_cycle_period=duty_cycle_period)),\n", | |
| "\n", | |
| " (\"flatten\", Flatten()),\n", | |
| "\n", | |
| " # Sparse Linear layer\n", | |
| " (\"linear\", SparseWeights(\n", | |
| " nn.Linear(16 * cnn_out_channels[1], linear_units),\n", | |
| " weight_sparsity=linear_weight_sparsity)),\n", | |
| " (\"linear_kwinner\", KWinners(n=linear_units,\n", | |
| " percent_on=linear_percent_on,\n", | |
| " k_inference_factor=k_inference_factor,\n", | |
| " boost_strength=boost_strength,\n", | |
| " boost_strength_factor=boost_strength_factor,\n", | |
| " duty_cycle_period=duty_cycle_period)),\n", | |
| "\n", | |
| " # Classifier\n", | |
| " (\"output\", nn.Linear(linear_units, out_features=num_classes)),\n", | |
| " (\"softmax\", nn.LogSoftmax(dim=1))\n", | |
| " ]))" | |
| ], | |
| "execution_count": 7, | |
| "outputs": [] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "metadata": { | |
| "id": "Ck-EDrVD8-Sy", | |
| "colab_type": "code", | |
| "colab": {} | |
| }, | |
| "source": [ | |
| "def get_cnn(pretrained=False):\n", | |
| " return nn.Sequential(*CNN(num_classes=len(data.c2i)).children())\n", | |
| "\n", | |
| "\n", | |
| "learn = cnn_learner(data, base_arch=get_cnn, wd=1e-2,\n", | |
| " metrics=[accuracy,top_k_accuracy],\n", | |
| " bn_wd=False, true_wd=True,\n", | |
| " loss_func = LabelSmoothingCrossEntropy())\n", | |
| " \n", | |
| "if dump: print(learn.model);\n", | |
| "if mixup: learn = learn.mixup(alpha=mixup)\n", | |
| "learn = learn.to_fp16(dynamic=True)\n", | |
| "# if gpu is None: learn.to_parallel()\n", | |
| "# elif num_distrib()>1: learn.to_distributed(gpu) # Requires `-m fastai.launch`" | |
| ], | |
| "execution_count": 8, | |
| "outputs": [] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "metadata": { | |
| "id": "8b-fGgR3B6Lf", | |
| "colab_type": "text" | |
| }, | |
| "source": [ | |
| "# Training CNN" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "metadata": { | |
| "id": "fZ7je2VO8-S1", | |
| "colab_type": "code", | |
| "colab": { | |
| "base_uri": "https://localhost:8080/", | |
| "height": 204 | |
| }, | |
| "outputId": "93542653-27fe-4458-d895-f6745e314e96" | |
| }, | |
| "source": [ | |
| "learn.fit_one_cycle(epochs, lr, div_factor=10, pct_start=0.3)" | |
| ], | |
| "execution_count": 9, | |
| "outputs": [ | |
| { | |
| "output_type": "display_data", | |
| "data": { | |
| "text/html": [ | |
| "<table border=\"1\" class=\"dataframe\">\n", | |
| " <thead>\n", | |
| " <tr style=\"text-align: left;\">\n", | |
| " <th>epoch</th>\n", | |
| " <th>train_loss</th>\n", | |
| " <th>valid_loss</th>\n", | |
| " <th>accuracy</th>\n", | |
| " <th>top_k_accuracy</th>\n", | |
| " <th>time</th>\n", | |
| " </tr>\n", | |
| " </thead>\n", | |
| " <tbody>\n", | |
| " <tr>\n", | |
| " <td>0</td>\n", | |
| " <td>3.242586</td>\n", | |
| " <td>2.134421</td>\n", | |
| " <td>0.292484</td>\n", | |
| " <td>0.733248</td>\n", | |
| " <td>01:05</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <td>1</td>\n", | |
| " <td>2.787031</td>\n", | |
| " <td>1.866002</td>\n", | |
| " <td>0.418599</td>\n", | |
| " <td>0.849682</td>\n", | |
| " <td>01:05</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <td>2</td>\n", | |
| " <td>2.525564</td>\n", | |
| " <td>1.787806</td>\n", | |
| " <td>0.453758</td>\n", | |
| " <td>0.864968</td>\n", | |
| " <td>01:04</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <td>3</td>\n", | |
| " <td>2.373092</td>\n", | |
| " <td>1.761256</td>\n", | |
| " <td>0.468535</td>\n", | |
| " <td>0.874395</td>\n", | |
| " <td>01:04</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <td>4</td>\n", | |
| " <td>2.282795</td>\n", | |
| " <td>1.755484</td>\n", | |
| " <td>0.471338</td>\n", | |
| " <td>0.877707</td>\n", | |
| " <td>01:05</td>\n", | |
| " </tr>\n", | |
| " </tbody>\n", | |
| "</table>" | |
| ], | |
| "text/plain": [ | |
| "<IPython.core.display.HTML object>" | |
| ] | |
| }, | |
| "metadata": { | |
| "tags": [] | |
| } | |
| } | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "metadata": { | |
| "id": "NK72XVh_8-S5", | |
| "colab_type": "code", | |
| "colab": { | |
| "base_uri": "https://localhost:8080/", | |
| "height": 34 | |
| }, | |
| "outputId": "e5969249-1821-4665-a1ec-79eb8b70fca9" | |
| }, | |
| "source": [ | |
| "accuracy(*learn.TTA())" | |
| ], | |
| "execution_count": 10, | |
| "outputs": [ | |
| { | |
| "output_type": "display_data", | |
| "data": { | |
| "text/html": [ | |
| "" | |
| ], | |
| "text/plain": [ | |
| "<IPython.core.display.HTML object>" | |
| ] | |
| }, | |
| "metadata": { | |
| "tags": [] | |
| } | |
| }, | |
| { | |
| "output_type": "display_data", | |
| "data": { | |
| "text/html": [ | |
| "" | |
| ], | |
| "text/plain": [ | |
| "<IPython.core.display.HTML object>" | |
| ] | |
| }, | |
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| "tags": [] | |
| } | |
| }, | |
| { | |
| "output_type": "execute_result", | |
| "data": { | |
| "text/plain": [ | |
| "tensor(0.4517)" | |
| ] | |
| }, | |
| "metadata": { | |
| "tags": [] | |
| }, | |
| "execution_count": 10 | |
| } | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "metadata": { | |
| "colab_type": "code", | |
| "id": "5Ibd5G_2m1eh", | |
| "colab": {} | |
| }, | |
| "source": [ | |
| "def get_sparsecnn(pretrained=False):\n", | |
| " return nn.Sequential(*SparseCNN(num_classes=len(data.c2i)).children())\n", | |
| "\n", | |
| "\n", | |
| "learn = cnn_learner(data, base_arch=get_sparsecnn, wd=1e-2,\n", | |
| " metrics=[accuracy,top_k_accuracy],\n", | |
| " bn_wd=False, true_wd=True,\n", | |
| " loss_func = LabelSmoothingCrossEntropy())\n", | |
| " \n", | |
| "if dump: print(learn.model);\n", | |
| "if mixup: learn = learn.mixup(alpha=mixup)\n", | |
| "learn = learn.to_fp16(dynamic=True)\n", | |
| "# if gpu is None: learn.to_parallel()\n", | |
| "# elif num_distrib()>1: learn.to_distributed(gpu) # Requires `-m fastai.launch`" | |
| ], | |
| "execution_count": 11, | |
| "outputs": [] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "metadata": { | |
| "colab_type": "text", | |
| "id": "rrstKP-um1eu" | |
| }, | |
| "source": [ | |
| "# Training SparseCNN" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "metadata": { | |
| "colab_type": "code", | |
| "id": "2AikTJyTm1ev", | |
| "colab": { | |
| "base_uri": "https://localhost:8080/", | |
| "height": 204 | |
| }, | |
| "outputId": "ee644f49-c73a-4a7d-d107-a334e4f6fef0" | |
| }, | |
| "source": [ | |
| "learn.fit_one_cycle(epochs, lr, div_factor=10, pct_start=0.3)" | |
| ], | |
| "execution_count": 12, | |
| "outputs": [ | |
| { | |
| "output_type": "display_data", | |
| "data": { | |
| "text/html": [ | |
| "<table border=\"1\" class=\"dataframe\">\n", | |
| " <thead>\n", | |
| " <tr style=\"text-align: left;\">\n", | |
| " <th>epoch</th>\n", | |
| " <th>train_loss</th>\n", | |
| " <th>valid_loss</th>\n", | |
| " <th>accuracy</th>\n", | |
| " <th>top_k_accuracy</th>\n", | |
| " <th>time</th>\n", | |
| " </tr>\n", | |
| " </thead>\n", | |
| " <tbody>\n", | |
| " <tr>\n", | |
| " <td>0</td>\n", | |
| " <td>3.382499</td>\n", | |
| " <td>2.279953</td>\n", | |
| " <td>0.170446</td>\n", | |
| " <td>0.651974</td>\n", | |
| " <td>01:06</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <td>1</td>\n", | |
| " <td>3.030929</td>\n", | |
| " <td>2.126004</td>\n", | |
| " <td>0.289427</td>\n", | |
| " <td>0.750318</td>\n", | |
| " <td>01:05</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <td>2</td>\n", | |
| " <td>2.773572</td>\n", | |
| " <td>2.100171</td>\n", | |
| " <td>0.301656</td>\n", | |
| " <td>0.763822</td>\n", | |
| " <td>01:05</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <td>3</td>\n", | |
| " <td>2.625630</td>\n", | |
| " <td>2.091475</td>\n", | |
| " <td>0.298599</td>\n", | |
| " <td>0.769172</td>\n", | |
| " <td>01:05</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <td>4</td>\n", | |
| " <td>2.541692</td>\n", | |
| " <td>2.085472</td>\n", | |
| " <td>0.300127</td>\n", | |
| " <td>0.770701</td>\n", | |
| " <td>01:05</td>\n", | |
| " </tr>\n", | |
| " </tbody>\n", | |
| "</table>" | |
| ], | |
| "text/plain": [ | |
| "<IPython.core.display.HTML object>" | |
| ] | |
| }, | |
| "metadata": { | |
| "tags": [] | |
| } | |
| } | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "metadata": { | |
| "colab_type": "code", | |
| "id": "JY_aXoDMm1e1", | |
| "colab": { | |
| "base_uri": "https://localhost:8080/", | |
| "height": 34 | |
| }, | |
| "outputId": "520824aa-1c97-4dc7-b710-2898c8153dc9" | |
| }, | |
| "source": [ | |
| "accuracy(*learn.TTA())" | |
| ], | |
| "execution_count": 13, | |
| "outputs": [ | |
| { | |
| "output_type": "display_data", | |
| "data": { | |
| "text/html": [ | |
| "" | |
| ], | |
| "text/plain": [ | |
| "<IPython.core.display.HTML object>" | |
| ] | |
| }, | |
| "metadata": { | |
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| } | |
| }, | |
| { | |
| "output_type": "display_data", | |
| "data": { | |
| "text/html": [ | |
| "" | |
| ], | |
| "text/plain": [ | |
| "<IPython.core.display.HTML object>" | |
| ] | |
| }, | |
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| "tags": [] | |
| } | |
| }, | |
| { | |
| "output_type": "execute_result", | |
| "data": { | |
| "text/plain": [ | |
| "tensor(0.3042)" | |
| ] | |
| }, | |
| "metadata": { | |
| "tags": [] | |
| }, | |
| "execution_count": 13 | |
| } | |
| ] | |
| } | |
| ] | |
| } |
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