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#
# Pyserini: Reproducible IR research with sparse and dense representations
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
#
from collections import defaultdict
from string import Template
import yaml
from scripts.repro_matrix.defs_mrtydi import models, languages, html_display, trec_eval_metric_definitions
def format_run_command(raw):
return raw.replace('--lang', '\\\n --lang')\
.replace('--encoder', '\\\n --encoder')\
.replace('--topics', '\\\n --topics')\
.replace('--index', '\\\n --index')\
.replace('--output ', '\\\n --output ')\
.replace('--batch ', '\\\n --batch ') \
.replace('--threads 12', '--threads 12 \\\n ')
def format_eval_command(raw):
return raw.replace('-c ', '\\\n -c ')\
.replace('run.', '\\\n run.')
def read_file(f):
fin = open(f, 'r')
text = fin.read()
fin.close()
return text
def generate_table_rows(table_id, split, metric):
row_cnt = 1
html_rows = []
for model in models:
s = Template(row_template)
keys = {}
for lang in languages:
keys[lang[0]] = f'{model}.{lang[0]}'
sum = table[keys["ar"]][split][metric] + \
table[keys["bn"]][split][metric] + \
table[keys["en"]][split][metric] + \
table[keys["fi"]][split][metric] + \
table[keys["id"]][split][metric] + \
table[keys["ja"]][split][metric] + \
table[keys["ko"]][split][metric] + \
table[keys["ru"]][split][metric] + \
table[keys["sw"]][split][metric] + \
table[keys["te"]][split][metric] + \
table[keys["th"]][split][metric]
avg = sum / 11
s = s.substitute(table_cnt=table_id,
row_cnt=row_cnt,
model=html_display[model],
ar=f'{table[keys["ar"]][split][metric]:.3f}',
bn=f'{table[keys["bn"]][split][metric]:.3f}',
en=f'{table[keys["en"]][split][metric]:.3f}',
fi=f'{table[keys["fi"]][split][metric]:.3f}',
id=f'{table[keys["id"]][split][metric]:.3f}',
ja=f'{table[keys["ja"]][split][metric]:.3f}',
ko=f'{table[keys["ko"]][split][metric]:.3f}',
ru=f'{table[keys["ru"]][split][metric]:.3f}',
sw=f'{table[keys["sw"]][split][metric]:.3f}',
te=f'{table[keys["te"]][split][metric]:.3f}',
th=f'{table[keys["th"]][split][metric]:.3f}',
avg=f'{avg:.3f}',
cmd1=f'{commands[keys["ar"]]}',
cmd2=f'{commands[keys["bn"]]}',
cmd3=f'{commands[keys["en"]]}',
cmd4=f'{commands[keys["fi"]]}',
cmd5=f'{commands[keys["id"]]}',
cmd6=f'{commands[keys["ja"]]}',
cmd7=f'{commands[keys["ko"]]}',
cmd8=f'{commands[keys["ru"]]}',
cmd9=f'{commands[keys["sw"]]}',
cmd10=f'{commands[keys["te"]]}',
cmd11=f'{commands[keys["th"]]}',
eval_cmd1=f'{eval_commands[keys["ar"]][metric]}',
eval_cmd2=f'{eval_commands[keys["bn"]][metric]}',
eval_cmd3=f'{eval_commands[keys["en"]][metric]}',
eval_cmd4=f'{eval_commands[keys["fi"]][metric]}',
eval_cmd5=f'{eval_commands[keys["id"]][metric]}',
eval_cmd6=f'{eval_commands[keys["ja"]][metric]}',
eval_cmd7=f'{eval_commands[keys["ko"]][metric]}',
eval_cmd8=f'{eval_commands[keys["ru"]][metric]}',
eval_cmd9=f'{eval_commands[keys["sw"]][metric]}',
eval_cmd10=f'{eval_commands[keys["te"]][metric]}',
eval_cmd11=f'{eval_commands[keys["th"]][metric]}'
)
html_rows.append(s)
row_cnt += 1
return html_rows
if __name__ == '__main__':
table = defaultdict(lambda: defaultdict(lambda: defaultdict(lambda: 0.0)))
commands = defaultdict(lambda: '')
eval_commands = defaultdict(lambda: defaultdict(lambda: ''))
html_template = read_file('scripts/repro_matrix/mrtydi_html.template')
table_template = read_file('scripts/repro_matrix/mrtydi_html_table.template')
row_template = read_file('scripts/repro_matrix/mrtydi_html_table_row.template')
with open('pyserini/resources/mrtydi.yaml') as f:
yaml_data = yaml.safe_load(f)
for condition in yaml_data['conditions']:
name = condition['name']
eval_key = condition['eval_key']
cmd_template = condition['command']
for splits in condition['splits']:
split = splits['split']
runfile = f'run.mrtydi.{name}.{split}.txt'
cmd = Template(cmd_template).substitute(split=split, output=runfile)
commands[name] = format_run_command(cmd)
for expected in splits['scores']:
for metric in expected:
table[name][split][metric] = expected[metric]
eval_cmd = f'python -m pyserini.eval.trec_eval ' + \
f'{trec_eval_metric_definitions[metric]} {eval_key}-{split} {runfile}'
eval_commands[name][metric] = format_eval_command(eval_cmd)
tables_html = []
# Build the table for MRR@100, test queries
html_rows = generate_table_rows(1, 'test', 'MRR@100')
all_rows = '\n'.join(html_rows)
tables_html.append(Template(table_template).substitute(desc='MRR@100, test queries', rows=all_rows))
# Build the table for R@100, test queries
html_rows = generate_table_rows(2, 'test', 'R@100')
all_rows = '\n'.join(html_rows)
tables_html.append(Template(table_template).substitute(desc='Recall@100, test queries', rows=all_rows))
print(Template(html_template).substitute(title='Mr.TyDi', tables=' '.join(tables_html)))
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