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author | Anthony Wang | 2021-08-24 20:27:14 -0500 |
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committer | Anthony Wang | 2021-08-24 20:27:14 -0500 |
commit | b8133346a4a626451436883f35477c8014de4a4b (patch) | |
tree | 4d90baa08f94f8f62c0f8575f319f96e39ae2595 /fashion-mnist-with-pytorch-93-accuracy.ipynb | |
parent | 8816c54f44c615481a712fa14e494ae9c91c6f91 (diff) |
Add latest code
Diffstat (limited to 'fashion-mnist-with-pytorch-93-accuracy.ipynb')
-rw-r--r-- | fashion-mnist-with-pytorch-93-accuracy.ipynb | 34 |
1 files changed, 12 insertions, 22 deletions
diff --git a/fashion-mnist-with-pytorch-93-accuracy.ipynb b/fashion-mnist-with-pytorch-93-accuracy.ipynb index 79f6923..5f98a1f 100644 --- a/fashion-mnist-with-pytorch-93-accuracy.ipynb +++ b/fashion-mnist-with-pytorch-93-accuracy.ipynb @@ -19,7 +19,7 @@ }, { "cell_type": "code", - "execution_count": 5, + "execution_count": 1, "metadata": { "colab": {}, "colab_type": "code", @@ -53,7 +53,7 @@ }, { "cell_type": "code", - "execution_count": 6, + "execution_count": 2, "metadata": { "colab": {}, "colab_type": "code", @@ -219,22 +219,13 @@ }, { "cell_type": "code", - "execution_count": 8, + "execution_count": 4, "metadata": { "colab": {}, "colab_type": "code", "id": "zM618_wYGM0n" }, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/ta180m/git/PyTorch/.venv/lib/python3.9/site-packages/torchvision/datasets/mnist.py:498: UserWarning: The given NumPy array is not writeable, and PyTorch does not support non-writeable tensors. This means you can write to the underlying (supposedly non-writeable) NumPy array using the tensor. You may want to copy the array to protect its data or make it writeable before converting it to a tensor. This type of warning will be suppressed for the rest of this program. (Triggered internally at /pytorch/torch/csrc/utils/tensor_numpy.cpp:180.)\n", - " return torch.from_numpy(parsed.astype(m[2], copy=False)).view(*s)\n" - ] - } - ], + "outputs": [], "source": [ "\n", "train_set = torchvision.datasets.FashionMNIST(\"./data\", download=True, transform=\n", @@ -246,7 +237,7 @@ }, { "cell_type": "code", - "execution_count": 9, + "execution_count": 5, "metadata": { "colab": {}, "colab_type": "code", @@ -279,7 +270,7 @@ }, { "cell_type": "code", - "execution_count": 10, + "execution_count": 6, "metadata": { "colab": {}, "colab_type": "code", @@ -415,7 +406,7 @@ }, { "cell_type": "code", - "execution_count": 13, + "execution_count": 7, "metadata": { "colab": { "base_uri": "https://localhost:8080/", @@ -427,11 +418,10 @@ }, "outputs": [ { - "name": "stdout", "output_type": "stream", + "name": "stdout", "text": [ - "<class 'torch.Tensor'> <class 'torch.Tensor'>\n", - "torch.Size([10, 1, 28, 28]) torch.Size([10])\n" + "<class 'torch.Tensor'> <class 'torch.Tensor'>\ntorch.Size([10, 1, 28, 28]) torch.Size([10])\n" ] } ], @@ -525,7 +515,7 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": 8, "metadata": { "colab": {}, "colab_type": "code", @@ -998,9 +988,9 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.9.6" + "version": "3.9.6-final" } }, "nbformat": 4, "nbformat_minor": 4 -} +}
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