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@ -47,9 +47,10 @@ The user must also specify a --model, the variants of which are described in det
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#### Logging directory
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Finally, a --base_log_dir should be specified (it defaults to the current directory).
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The output of the model and log files will be stored in a subdirectory of the base_log_dir.
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The path to the logged data will be of the form `<sup/unsup>-<data_prefix>/graphsage-<model_description>/`.
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The supervised model will output F1 scores, while the unsupervised model will train embeddings and store them.
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The unsupervised embeddings will be stored at val.npy with val.txt specifying the order of embeddings as a per-line list of node ids.
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Note that the full log outputs and stored embeddings can be 5-10Gb in size (on the full data).
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The unsupervised embeddings will be stored in a numpy formated file named val.npy with val.txt specifying the order of embeddings as a per-line list of node ids.
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Note that the full log outputs and stored embeddings can be 5-10Gb in size (on the full data when running with the unsupervised variant).
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#### Using the output of the unsupervised models
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