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README.md DELETED
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- # Numerical Reasoning
 
 
arithmetic_addition/numerical_reasoning-test.parquet ADDED
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+ version https://git-lfs.github.com/spec/v1
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arithmetic_multiplication/numerical_reasoning-test.parquet ADDED
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+ version https://git-lfs.github.com/spec/v1
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numerical_reasoning.py DELETED
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- # Copyright 2020 The HuggingFace Datasets Authors and the current dataset script contributor.
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- #
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- # Licensed under the Apache License, Version 2.0 (the "License");
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- # you may not use this file except in compliance with the License.
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- # You may obtain a copy of the License at
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- #
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- # http://www.apache.org/licenses/LICENSE-2.0
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- #
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- # Unless required by applicable law or agreed to in writing, software
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- # distributed under the License is distributed on an "AS IS" BASIS,
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- # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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- # See the License for the specific language governing permissions and
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- # limitations under the License.
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- # TODO: Address all TODOs and remove all explanatory comments
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- """TODO: Add a description here."""
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-
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-
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- import csv
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- import json
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- import os
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-
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- import datasets
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-
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-
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- # TODO: Add BibTeX citation
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- # Find for instance the citation on arxiv or on the dataset repo/website
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- _CITATION = """\
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-
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- """
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-
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- # TODO: Add description of the dataset here
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- # You can copy an official description
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- _DESCRIPTION = """\
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- Generated dataset for testing numerical reasoning
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- """
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-
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- # TODO: Add a link to an official homepage for the dataset here
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- _HOMEPAGE = ""
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-
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- # TODO: Add the licence for the dataset here if you can find it
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- _LICENSE = ""
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-
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- # TODO: Add link to the official dataset URLs here
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- # The HuggingFace Datasets library doesn't host the datasets but only points to the original files.
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- # This can be an arbitrary nested dict/list of URLs (see below in `_split_generators` method)
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- _URLS = {
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- "first_domain": "https://huggingface.co/great-new-dataset-first_domain.zip",
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- "second_domain": "https://huggingface.co/great-new-dataset-second_domain.zip",
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- }
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-
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-
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- # TODO: Name of the dataset usually matches the script name with CamelCase instead of snake_case
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- class NewDataset(datasets.GeneratorBasedBuilder):
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- """TODO: Short description of my dataset."""
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-
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- VERSION = datasets.Version("0.1.0")
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-
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- BUILDER_CONFIGS = [
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- datasets.BuilderConfig(name="arithmetic_multiplication", version=VERSION, description="x1 x x2 = y"),
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- datasets.BuilderConfig(name="arithmetic_addition", version=VERSION, description="x1 + x2 = y"),
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- datasets.BuilderConfig(name="op_infer_mult", version=VERSION, description="x1 # x2 = y, must infer that # is multiplication"),
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- datasets.BuilderConfig(name="op_infer_add", version=VERSION, description="x1 # x2 = y, must infer that # is addition"),
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- datasets.BuilderConfig(name="time_unit_min_sec", version=VERSION, description="x minutes equals y seconds"),
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- datasets.BuilderConfig(name="time_unit_hour_min", version=VERSION, description="x hours equals y minutes"),
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- datasets.BuilderConfig(name="time_unit_day_hour", version=VERSION, description="x days equals y hours"),
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- datasets.BuilderConfig(name="time_unit_week_day", version=VERSION, description="x minutes equals y seconds"),
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- datasets.BuilderConfig(name="time_unit_month_week", version=VERSION, description="x months equals y weeks"),
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- datasets.BuilderConfig(name="time_unit_year_month", version=VERSION, description="x years equals y months"),
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- datasets.BuilderConfig(name="time_unit_decade_year", version=VERSION, description="x decades equals y years"),
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- ]
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-
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- DEFAULT_CONFIG_NAME = "first_domain" # It's not mandatory to have a default configuration. Just use one if it make sense.
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-
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- def _info(self):
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- if ("arithmetic" in self.config.name) or ("op_infer" in self.config.name): # This is the name of the configuration selected in BUILDER_CONFIGS above
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- features = datasets.Features(
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- {
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- "x1": datasets.Value("int32"),
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- "x2": datasets.Value("int32"),
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- "y": datasets.Value("int32")
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- }
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- )
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- else:
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- features = datasets.Features(
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- {
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- "x1": datasets.Value("int32"),
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- "time_unit": datasets.Value("string"),
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- "y": datasets.Value("int32")
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- }
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- )
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- return datasets.DatasetInfo(
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- description=_DESCRIPTION,
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- features=features, # Here we define them above because they are different between the two configurations
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- homepage=_HOMEPAGE,
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- license=_LICENSE,
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- citation=_CITATION,
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- )
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-
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- def _split_generators(self, dl_manager):
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- return [
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- datasets.SplitGenerator(
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- name=datasets.Split.TEST,
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- # These kwargs will be passed to _generate_examples
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- gen_kwargs={
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- "split": "test"
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- },
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- ),
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- ]
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-
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- def _generate_examples(self, split):
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-
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- if ("arithmetic" in self.config.name) or ("op_infer" in self.config.name):
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- key = 0
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- for x1 in range(0,100):
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- for x2 in range(1,51):
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- key += 1
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- # Yields examples as (key, example) tuples
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- yield key, {
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- "x1": x1,
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- "x2": x2,
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- "y": x1*x2,
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- }
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- else:
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- if "min_sec" in self.config.name:
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- time_unit = "minutes"
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- multiplier = 60
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-
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- elif "hour_min" in self.config.name:
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- time_unit = "hours"
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- multiplier = 60
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-
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- elif "day_hour" in self.config.name:
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- time_unit = "days"
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- multiplier = 24
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-
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- elif "week_day" in self.config.name:
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- time_unit = "weeks"
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- multiplier = 7
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-
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- elif "month_week" in self.config.name:
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- time_unit = "months"
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- multiplier = 30
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-
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- elif "year_month" in self.config.name:
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- time_unit = "years"
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- multiplier = 12
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-
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- elif "decade_year" in self.config.name:
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- time_unit = "decades"
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- multiplier = 10
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-
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- for key, x1 in enumerate(range(0, 100)):
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- yield key, {
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- "x1": x1,
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- "time_unit": time_unit,
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- "y": multiplier*x1,
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- }
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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