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@@ -44,8 +44,8 @@ For example, to pre-process the dtd dataset and train a PGAN model on a host
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with CUDA 10.2 you could run the following commands.
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```bash
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-singularity exec pytorch_GAN_zoo.sif datasets.py dtd <path to dtd dataset>/images/
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-singularity exec pytorch_GAN_zoo.sif --nv --app cu102 train.py PGAN -c config_dtd.json --restart --no_vis -n dtd
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+singularity exec --app cu102 pytorch_GAN_zoo.sif datasets.py dtd <path to dtd dataset>/images/
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+singularity exec --nv --app cu102 pytorch_GAN_zoo.sif train.py PGAN -c config_dtd.json --restart --no_vis -n dtd
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```
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### Models
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@@ -68,8 +68,8 @@ The DTD dataset requires no preprocessing, so the datasets script simply creates
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a configuration file.
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```bash
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-singularity exec pytorch_GAN_zoo.sif datasets.py dtd <path to dtd>/images
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-singularity exec pytorch_GAN_zoo.sif --nv --app cu102 train.py PGAN -c config_dtd.json --restart --no_vis -n dtd
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+singularity exec --app cu102 pytorch_GAN_zoo.sif datasets.py dtd <path to dtd>/images
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+singularity exec --nv --app cu102 pytorch_GAN_zoo.sif train.py PGAN -c config_dtd.json --restart --no_vis -n dtd
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```
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Where `<path to dtd>` is the path of the directory extracted from the dtd
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@@ -82,8 +82,8 @@ A processed dataset will be written to a directory delcared using the `-o` flag,
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`cifar-10` n this example.
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```bash
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-singularity exec pytorch_GAN_zoo.sif datasets.py cifar10 <path to cifar-10> -o cifar10
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-singularity exec pytorch_GAN_zoo.sif --nv --app cu102 train.py -c config_cifar10.json --restart --no_vis -n cifar10
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+singularity exec --app cu102 pytorch_GAN_zoo.sif datasets.py cifar10 <path to cifar-10> -o cifar10
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+singularity exec --nv --app cu102 pytorch_GAN_zoo.sif train.py -c config_cifar10.json --restart --no_vis -n cifar10
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```
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Where `<path to cifar-10>` is the path of the directory containing the pickle
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