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# 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
}
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