moved images to github
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@ -94,7 +94,7 @@
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"\n",
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"\n",
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"Don't worry if this is still unclear now! You'll go over this in more detail later in the notebook.\n",
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"Don't worry if this is still unclear now! You'll go over this in more detail later in the notebook.\n",
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"\n",
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"\n",
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"![Same- and cross-domain interaction of encoders and decoders](https://drive.google.com/uc?id=1gi5rHPiBdYtkLLok8ImSefnvUloScxm4)\n",
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"![Same- and cross-domain interaction of encoders and decoders](https://github.com/https-deeplearning-ai/GANs-Public/blob/master/MUNIT-Domains.png?raw=true)\n",
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"\n",
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"\n",
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"*Model overview, taken from Figure 2 of [Multimodal Unsupervised Image-to-Image Translation](https://arxiv.org/abs/1804.04732) (Huang et al. 2018). The red and blue arrows denote encoders-decoder pairs within the same domain. Left: same domain image reconstruction. Right: cross-domain latent (content and style) vector reconstruction.*"
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"*Model overview, taken from Figure 2 of [Multimodal Unsupervised Image-to-Image Translation](https://arxiv.org/abs/1804.04732) (Huang et al. 2018). The red and blue arrows denote encoders-decoder pairs within the same domain. Left: same domain image reconstruction. Right: cross-domain latent (content and style) vector reconstruction.*"
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]
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]
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@ -384,7 +384,7 @@
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"\n",
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"\n",
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"Now that you're all set up and implemented some basic building blocks, let's take a look at the content encoder, style encoder, and decoder! These will be used in the generator.\n",
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"Now that you're all set up and implemented some basic building blocks, let's take a look at the content encoder, style encoder, and decoder! These will be used in the generator.\n",
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"\n",
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"\n",
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"![Same- and cross-domain interaction of encoders and decoders](https://drive.google.com/uc?id=15y07M9dgnk8_HtatlDfEpN5mM-BFBnMG)\n",
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"![Same- and cross-domain interaction of encoders and decoders](https://github.com/https-deeplearning-ai/GANs-Public/blob/master/MUNIT-Generator.png?raw=true)\n",
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"\n",
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"\n",
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"*Generator architecture, taken from Figure 3 of [Multimodal Unsupervised Image-to-Image Translation](https://arxiv.org/abs/1804.04732) (Huang et al. 2018). Content encoder: generates a downsampled representation of the original. Style encoder: generates a style code from the original. Decoder: synthesizes a fake image from content code, infused with style info.*\n",
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"*Generator architecture, taken from Figure 3 of [Multimodal Unsupervised Image-to-Image Translation](https://arxiv.org/abs/1804.04732) (Huang et al. 2018). Content encoder: generates a downsampled representation of the original. Style encoder: generates a style code from the original. Decoder: synthesizes a fake image from content code, infused with style info.*\n",
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"\n",
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"\n",
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@ -1060,11 +1060,11 @@
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"cell_type": "code",
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"cell_type": "code",
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"metadata": {
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"metadata": {
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"id": "-9d8AneYxuuT",
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"id": "-9d8AneYxuuT",
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"outputId": "dd07c208-3565-4aa7-b5ef-d526885fd3f5",
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"colab": {
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"colab": {
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"base_uri": "https://localhost:8080/",
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"base_uri": "https://localhost:8080/",
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"height": 1000
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"height": 1000
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}
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},
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"outputId": "dd07c208-3565-4aa7-b5ef-d526885fd3f5"
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},
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},
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"source": [
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"source": [
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"# Parse torch version for autocast\n",
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"# Parse torch version for autocast\n",
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