Datasets:

abhinavk
/

openpi_v2

	# coding=utf-8
	# Copyright 2022 The TensorFlow Datasets Authors and the HuggingFace Datasets Authors.
	#
	# 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.

	# Lint as: python3
	"""Openpi V2: A Dataset for tracking state changes in prcedural text by using an unrestricted library"""

	import json
	import os
	import sys
	import textwrap

	import numpy as np
	import datasets

	logger = datasets.logging.get_logger(__name__)

	_OPENPI_V2_CITATION = """\
	@inproceedings{
	title={{OPENPI V2}: }
	author={}
	note={}
	year={2022}
	}
	"""

	_OPENPI_V2_DESCRIPTION = """\
	TEMPORARY DESCRIPTION
	"""

	_LICENSE = "CC BY 4.0"
	_VERSION = "1.0.0"
	_HOMEPAGE = "https://allenai.org/data/openpi"
	_URL = "https://huggingface.co/datasets/abhinavk/openpi_v2/resolve/main/data/"
	_URLS = {"train": _URL + "train-data.json",
	"dev": _URL + "dev-data.json",
	"test": _URL + "test-data.json"}


	class OpenpiConfig(datasets.BuilderConfig):
	"""BuilderConfig for Openpi V2."""

	def __init__(
	self,
	features,
	data_url,
	citation,
	url,
	process_label = lambda x: x,
	**kwargs,
	):

	super(OpenpiConfig, self).__init__(version = datasets.Version(_VERSION), **kwargs)
	self.features = features
	self.data_url = data_url
	self.citation = citation
	self.url = url
	self.process_label = process_label


	class OpenpiV2(datasets.GeneratorBasedBuilder):

	BUILDER_CONFIGS = [
	OpenpiConfig(
	name = "openpi_text",
	description = textwrap.dedent(
	"""\
	"""
	),
	features = datasets.Features({
	"goal": datasets.Value("string"),
	"steps": [datasets.Value("string")],
	"topics": datasets.Value("string"),
	"image_urls": [datasets.Value("string")],
	"states": [{
	"answers_openpiv1_metadata": {
	"entity": datasets.Value("string"),
	"attribute": datasets.Value("string"),
	"answers": [datasets.Value("string")],
	"modality": [datasets.Value("string")]
	},
	"entity": datasets.Value("string"),
	"attribute": datasets.Value("string"),
	"answers": [datasets.Value("string")],
	"saliency": datasets.Value("float32")
	}]
	}),
	data_url = _URLS,
	citation = textwrap.dedent(
	"""\
	@inproceedings{
	title={},
	author={},
	booktitle={},
	year={}
	}"""
	),
	url = _HOMEPAGE
	),
	OpenpiConfig(
	name = "Task 1",
	description = textwrap.dedent(
	"""\
	Given paragraph (e.g., with 5 steps), identify entities that change
	(challenge: implicit entities, some explicit entities that don’t change)."""
	),
	features = datasets.Features({
	"steps": [datasets.Value("string")],
	"entity_changes": [[datasets.Value("string")]]
	}),
	data_url = _URLS,
	citation = textwrap.dedent(
	"""\
	@inproceedings{
	title={},
	author={},
	booktitle={},
	year={}
	}"""
	),
	url = _HOMEPAGE
	),
	OpenpiConfig(
	name = "Task 3",
	description = textwrap.dedent(
	"""\
	Given paragraph (e.g., with 5 steps), identify the attributes of entity that change
	(challenge: implicit entities, attributes & many combinations)."""
	),
	features = datasets.Features({
	"steps": [datasets.Value("string")],
	"attr_entity_changes": [datasets.Value("string")]
	}),
	data_url = _URLS,
	citation = textwrap.dedent(
	"""\
	@inproceedings{
	title={},
	author={},
	booktitle={},
	year={}
	}"""
	),
	url = _HOMEPAGE
	),
	OpenpiConfig(
	name = "Task 4",
	description = textwrap.dedent(
	"""\
	Task 4: Given paragraph & an entity, identify the sequence of attribute value changes
	(challenge: implicit attributes)."""
	),
	features = datasets.Features({
	"steps": [datasets.Value("string")],
	"entity": datasets.Value("string"),
	"attribute_changes": [[datasets.Value("string")]]
	}),
	data_url = _URLS,
	citation = textwrap.dedent(
	"""\
	@inproceedings{
	title={},
	author={},
	booktitle={},
	year={}
	}"""
	),
	url = _HOMEPAGE
	),
	OpenpiConfig(
	name = "Task 7",
	description = textwrap.dedent(
	"""\
	Task 7: Given image url, identify the visual attributes of entity and
	non-visual attributes of entity that change."""
	),
	features = datasets.Features({
	"image_url": datasets.Value("string"),
	"visual_attr": [datasets.Value("string")],
	"non_visual_attr": [datasets.Value("string")]
	}),
	data_url = _URLS,
	citation = textwrap.dedent(
	"""\
	@inproceedings{
	title={},
	author={},
	booktitle={},
	year={}
	}"""
	),
	url = _HOMEPAGE
	),
	]

	def _info(self):
	return datasets.DatasetInfo(
	description = _OPENPI_V2_DESCRIPTION,
	features = self.config.features,
	supervised_keys = None,
	homepage = self.config.url,
	citation = self.config.citation + "\n" + _OPENPI_V2_CITATION
	)

	def _split_generators(self, dl_manager):
	downloaded_files = dl_manager.download_and_extract(self.config.data_url)

	return [
	datasets.SplitGenerator(
	name = datasets.Split.TRAIN,
	gen_kwargs = {
	"filepath": downloaded_files["train"]
	},
	),
	datasets.SplitGenerator(
	name = datasets.Split.VALIDATION,
	gen_kwargs = {
	"filepath": downloaded_files["dev"]
	},
	),
	datasets.SplitGenerator(
	name = datasets.Split.TEST,
	gen_kwargs = {
	"filepath": downloaded_files["test"]
	}
	),
	]


	@staticmethod
	def change_occur(dataset):
	for step in dataset:
	if len(step) > 0:
	return True

	return False

	@staticmethod
	def find_change(key, dataset):
	res = []

	for state in dataset:
	if OpenpiV2.change_occur(state["answers"]):
	list_key = state[key].split(" \| ")
	res.append([el for el in list_key])

	return (res)

	@staticmethod
	def find_attr_entity_change(dataset):
	attr_change = []

	for state in dataset:
	if OpenpiV2.change_occur(state["answers"]):
	change_str = "[" + state["attribute"] + "] of [" + state["entity"] + "] changed"
	attr_change.append(change_str)

	return attr_change

	def _generate_examples(self, filepath):
	logger.info("generating examples from = %s", filepath)

	if self.config.name == "openpi_text":
	with open(filepath) as f:
	dataset = json.load(f)

	for id_ in dataset:
	yield int(id_), {
	"goal": dataset[id_]["goal"],
	"steps": dataset[id_]["steps"],
	"topics": dataset[id_]["topics"],
	"image_urls": dataset[id_]["image_urls"],
	"states": dataset[id_]["states"],
	}

	elif self.config.name == "Task 1":
	with open(filepath) as f:
	dataset = json.load(f)

	for id_ in dataset:
	steps_ar = dataset[id_]["steps"]
	entity_changes = OpenpiV2.find_change("entity", dataset[id_]["states"])

	yield int(id_), {
	"steps": steps_ar,
	"entity_changes": entity_changes
	}

	elif self.config.name == "Task 3":
	with open(filepath) as f:
	dataset = json.load(f)

	for id_ in dataset:
	steps_ar = dataset[id_]["steps"]
	attr_entity_changes = OpenpiV2.find_attr_entity_change(dataset[id_]["states"])

	yield int(id_), {
	"steps": steps_ar,
	"attr_entity_changes": attr_entity_changes
	}

	elif self.config.name == "Task 4":
	with open(filepath) as f:
	dataset = json.load(f)

	for id_ in dataset:
	steps_ar = dataset[id_]["steps"]

	for state in dataset[id_]["states"]:
	for el in state["entity"].split(" \| "):
	entity = el
	attribute_changes = []

	for state2 in dataset[id_]["states"]:
	flag = False

	for el2 in state2["entity"].split(" \| "):
	if entity == el2:
	flag = True
	break

	if flag == False:
	continue

	if OpenpiV2.change_occur(state2["answers"]):
	list_attribute = state2["attribute"].split(" \| ")
	attribute_changes.append([el for el in list_attribute])

	yield int(id_), {
	"steps": steps_ar,
	"entity": entity,
	"attribute_changes": attribute_changes
	}

	elif self.config.name == "Task 7":
	with open(filepath) as f:
	dataset = json.load(f)

	for id_ in dataset:
	N = len(dataset[id_]["image_urls"])

	for i in range(N):
	image_url = dataset[id_]["image_urls"][i]
	visual_attr = []
	non_visual_attr = []

	for state in dataset[id_]["states"]:
	if len(state["answers"][i]) > 0:
	visual = False
	non_visual = False

	for el in state["answers_openpiv1_metadata"]["modality"][i].split(" \| "):
	visual = (visual or (el == "with_image"))
	non_visual = (non_visual or (el == "without_image"))

	change_str = "[" + state["attribute"] + "] of [" + state["entity"] + "] changed"

	if visual:
	visual_attr.append(change_str)
	if non_visual:
	non_visual_attr.append(change_str)

	yield int(id_), {
	"image_url": image_url,
	"visual_attr": visual_attr,
	"non_visual_attr": non_visual_attr
	}