'csqa': {

'train': './data/csqa/train_rand_split.jsonl',

'dev': './data/csqa/dev_rand_split.jsonl',

'test': './data/csqa/test_rand_split_no_answers.jsonl',

},

'obqa': {

'train': './data/obqa/OpenBookQA-V1-Sep2018/Data/Additional/train_complete.jsonl',

'dev': './data/obqa/OpenBookQA-V1-Sep2018/Data/Additional/dev_complete.jsonl',

'test': './data/obqa/OpenBookQA-V1-Sep2018/Data/Additional/test_complete.jsonl',

},

'cpnet': {

'csv': './data/cpnet/conceptnet-assertions-5.6.0.csv',

},

'cpnet': {

'csv': './data/cpnet/conceptnet.en.csv',

'vocab': './data/cpnet/concept.txt',

'patterns': './data/cpnet/matcher_patterns.json',

'unpruned-graph': './data/cpnet/conceptnet.en.unpruned.graph',

'pruned-graph': './data/cpnet/conceptnet.en.pruned.graph',

},

'csqa': {

'statement': {

'train': './data/csqa/statement/train.statement.jsonl',

'dev': './data/csqa/statement/dev.statement.jsonl',

'test': './data/csqa/statement/test.statement.jsonl',

},

'grounded': {

'train': './data/csqa/grounded/train.grounded.jsonl',

'dev': './data/csqa/grounded/dev.grounded.jsonl',

'test': './data/csqa/grounded/test.grounded.jsonl',

},

'graph': {

'adj-train': './data/csqa/graph/train.graph.adj.pk',

'adj-dev': './data/csqa/graph/dev.graph.adj.pk',

'adj-test': './data/csqa/graph/test.graph.adj.pk',

},

},

'obqa': {

'statement': {

'train': './data/obqa/statement/train.statement.jsonl',

'dev': './data/obqa/statement/dev.statement.jsonl',

'test': './data/obqa/statement/test.statement.jsonl',

'train-fairseq': './data/obqa/fairseq/official/train.jsonl',

'dev-fairseq': './data/obqa/fairseq/official/valid.jsonl',

'test-fairseq': './data/obqa/fairseq/official/test.jsonl',

},

'grounded': {

'train': './data/obqa/grounded/train.grounded.jsonl',

'dev': './data/obqa/grounded/dev.grounded.jsonl',

'test': './data/obqa/grounded/test.grounded.jsonl',

},

'graph': {

'adj-train': './data/obqa/graph/train.graph.adj.pk',

'adj-dev': './data/obqa/graph/dev.graph.adj.pk',

'adj-test': './data/obqa/graph/test.graph.adj.pk',

},

},

parser = argparse.ArgumentParser()

parser.add_argument('--run', default=['common', 'csqa', 'obqa'], choices=['common', 'csqa', 'obqa'], nargs='+')

parser.add_argument('-p', '--nprocs', type=int, default=cpu_count(), help='number of processes to use')

parser.add_argument('--debug', action='store_true', help='enable debug mode')

args = parser.parse_args()

if args.debug:

raise NotImplementedError()

routines = {

'common': [

{'func': extract_english, 'args': (input_paths['cpnet']['csv'], output_paths['cpnet']['csv'], output_paths['cpnet']['vocab'])},

{'func': construct_graph, 'args': (output_paths['cpnet']['csv'], output_paths['cpnet']['vocab'],

output_paths['cpnet']['unpruned-graph'], False)},

{'func': construct_graph, 'args': (output_paths['cpnet']['csv'], output_paths['cpnet']['vocab'],

output_paths['cpnet']['pruned-graph'], True)},

{'func': create_matcher_patterns, 'args': (output_paths['cpnet']['vocab'], output_paths['cpnet']['patterns'])},

],

'csqa': [

{'func': convert_to_entailment, 'args': (input_paths['csqa']['train'], output_paths['csqa']['statement']['train'])},

{'func': convert_to_entailment, 'args': (input_paths['csqa']['dev'], output_paths['csqa']['statement']['dev'])},

{'func': convert_to_entailment, 'args': (input_paths['csqa']['test'], output_paths['csqa']['statement']['test'])},

{'func': ground, 'args': (output_paths['csqa']['statement']['train'], output_paths['cpnet']['vocab'],

output_paths['cpnet']['patterns'], output_paths['csqa']['grounded']['train'], args.nprocs)},

{'func': ground, 'args': (output_paths['csqa']['statement']['dev'], output_paths['cpnet']['vocab'],

output_paths['cpnet']['patterns'], output_paths['csqa']['grounded']['dev'], args.nprocs)},

{'func': ground, 'args': (output_paths['csqa']['statement']['test'], output_paths['cpnet']['vocab'],

output_paths['cpnet']['patterns'], output_paths['csqa']['grounded']['test'], args.nprocs)},

{'func': generate_adj_data_from_grounded_concepts__use_LM, 'args': (output_paths['csqa']['grounded']['train'], output_paths['cpnet']['pruned-graph'], output_paths['cpnet']['vocab'], output_paths['csqa']['graph']['adj-train'], args.nprocs)},

{'func': generate_adj_data_from_grounded_concepts__use_LM, 'args': (output_paths['csqa']['grounded']['dev'], output_paths['cpnet']['pruned-graph'], output_paths['cpnet']['vocab'], output_paths['csqa']['graph']['adj-dev'], args.nprocs)},

{'func': generate_adj_data_from_grounded_concepts__use_LM, 'args': (output_paths['csqa']['grounded']['test'], output_paths['cpnet']['pruned-graph'], output_paths['cpnet']['vocab'], output_paths['csqa']['graph']['adj-test'], args.nprocs)},

],

'obqa': [

{'func': convert_to_obqa_statement, 'args': (input_paths['obqa']['train'], output_paths['obqa']['statement']['train'], output_paths['obqa']['statement']['train-fairseq'])},

{'func': convert_to_obqa_statement, 'args': (input_paths['obqa']['dev'], output_paths['obqa']['statement']['dev'], output_paths['obqa']['statement']['dev-fairseq'])},

{'func': convert_to_obqa_statement, 'args': (input_paths['obqa']['test'], output_paths['obqa']['statement']['test'], output_paths['obqa']['statement']['test-fairseq'])},

{'func': ground, 'args': (output_paths['obqa']['statement']['train'], output_paths['cpnet']['vocab'],

output_paths['cpnet']['patterns'], output_paths['obqa']['grounded']['train'], args.nprocs)},

{'func': ground, 'args': (output_paths['obqa']['statement']['dev'], output_paths['cpnet']['vocab'],

output_paths['cpnet']['patterns'], output_paths['obqa']['grounded']['dev'], args.nprocs)},

{'func': ground, 'args': (output_paths['obqa']['statement']['test'], output_paths['cpnet']['vocab'],

output_paths['cpnet']['patterns'], output_paths['obqa']['grounded']['test'], args.nprocs)},

{'func': generate_adj_data_from_grounded_concepts__use_LM, 'args': (output_paths['obqa']['grounded']['train'], output_paths['cpnet']['pruned-graph'], output_paths['cpnet']['vocab'], output_paths['obqa']['graph']['adj-train'], args.nprocs)},

{'func': generate_adj_data_from_grounded_concepts__use_LM, 'args': (output_paths['obqa']['grounded']['dev'], output_paths['cpnet']['pruned-graph'], output_paths['cpnet']['vocab'], output_paths['obqa']['graph']['adj-dev'], args.nprocs)},

{'func': generate_adj_data_from_grounded_concepts__use_LM, 'args': (output_paths['obqa']['grounded']['test'], output_paths['cpnet']['pruned-graph'], output_paths['cpnet']['vocab'], output_paths['obqa']['graph']['adj-test'], args.nprocs)},

],

}

for rt in args.run:

for rt_dic in routines[rt]:

rt_dic['func'](*rt_dic['args'])