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Experiment Workspace: Expt

Expt is the workspace for our experiments. Initially, it contains the following 3 main folders, We breifly give an overview of each of them, and the subfolders in them.

mrp_scripts

It contains all the bash scripts that organize the running of our

experiments. Worth to menthion, our principle of running neural experiments is seperating the reciept from its cook tool. Hence, all cook tools are placed in mrp_scripts/commands/, and all cook receipts are placed in mrp_scripts/configs.

During developing, build the core of cook tools in tensorflow code directory, and then wrap that as a configurable bash script in mrp_scrpts/commands. Then, write various receipts by setting different switch or hyperparamters. Finally, a cook tool(command) feeded by a receipt(config) will build a model as you wish.

Worth to mention, a `env.sh` in commands folder is a special

initialization code, which will set the important global variables that will used in our model. It will be fine to run the code without any customization on env.sh However, please check the details in Expt/commands/env.sh script, which contains the global variables in our model. Once you checkout the code, all the environment varibles will be set with the relative path in the env.sh script

data

  • mrp_data_ro
It is a folder for read-only data, once data generated in this

folder, it will keep unchanged, e.g. glove pretrained embedding, original data set, data splits etc.

  • mrp_data

It the proprocessed data for traning, including dictionaries, tokenization, prepared training data. In our case, we will generate seperate folders for different MRP datasets

pre_logs

logs fiels for preprocessing all the datasets

workdir

It is folder to store all the experiment results organized by per folder one modeling receipt.

  • training.log or training_restore.log

generated from ./train.sh or ./train_restore.sh, it shows all the training logs. Each dataset will have a seperate folders, which are corresponding to the folder structure of the config files in mrp_scripts

  • results
It will store the results for dev and test set, and the their evluation scores by mtool.
  • models
models will save all the best models.
  • summary

This folder is for writing event and all kinds summaries, that can be read by tensorboard.