Skip to content

Commit d0c47fc

Browse files
author
The TensorFlow Datasets Authors
committed
Automated metadata update.
PiperOrigin-RevId: 735313500
1 parent 23f2be0 commit d0c47fc

File tree

10 files changed

+684
-0
lines changed

10 files changed

+684
-0
lines changed

‎tensorflow_datasets/testing/metadata/asimov_dilemmas_auto_val/0.1.0/dataset_info.json

+26
Original file line numberDiff line numberDiff line change
@@ -0,0 +1,26 @@
1+
{
2+
"citation": "@article{Sermanet2025RobotConstitutions,\n author = {Pierre Sermanet and Anirudha Majumdar and Alex Irpan and Dmitry Kalashnikov and Vikas Sindhwani},\n title = {Generating Robot Constitutions & Benchmarks for Semantic Safety},\n journal = {arXiv preprint arXiv:FIXME},\n url = {https://arxiv.org/abs/FIXME},\n year = {2025},\n}",
3+
"description": "Binary dilemma questions generated from counterfactual situations used to auto-amend generated constitutions (validation set).",
4+
"fileFormat": "array_record",
5+
"location": {
6+
"urls": [
7+
"https://asimov-benchmark.github.io/"
8+
]
9+
},
10+
"moduleName": "tensorflow_datasets.robotics.asimov.asimov",
11+
"name": "asimov_dilemmas_auto_val",
12+
"releaseNotes": {
13+
"0.1.0": "Initial release."
14+
},
15+
"splits": [
16+
{
17+
"filepathTemplate": "{DATASET}-{SPLIT}.{FILEFORMAT}-{SHARD_X_OF_Y}",
18+
"name": "val",
19+
"numBytes": "885552",
20+
"shardLengths": [
21+
"34"
22+
]
23+
}
24+
],
25+
"version": "0.1.0"
26+
}

‎tensorflow_datasets/testing/metadata/asimov_dilemmas_auto_val/0.1.0/features.json

+67
Original file line numberDiff line numberDiff line change
@@ -0,0 +1,67 @@
1+
{
2+
"featuresDict": {
3+
"features": {
4+
"answer": {
5+
"pythonClassName": "tensorflow_datasets.core.features.text_feature.Text",
6+
"text": {}
7+
},
8+
"prompt_with_constitution": {
9+
"pythonClassName": "tensorflow_datasets.core.features.text_feature.Text",
10+
"text": {}
11+
},
12+
"prompt_with_constitution_antijailbreak": {
13+
"pythonClassName": "tensorflow_datasets.core.features.text_feature.Text",
14+
"text": {}
15+
},
16+
"prompt_with_constitution_antijailbreak_adversary": {
17+
"pythonClassName": "tensorflow_datasets.core.features.text_feature.Text",
18+
"text": {}
19+
},
20+
"prompt_with_constitution_antijailbreak_adversary_parts": {
21+
"pythonClassName": "tensorflow_datasets.core.features.sequence_feature.Sequence",
22+
"sequence": {
23+
"feature": {
24+
"pythonClassName": "tensorflow_datasets.core.features.text_feature.Text",
25+
"text": {}
26+
},
27+
"length": "-1"
28+
}
29+
},
30+
"prompt_with_constitution_antijailbreak_parts": {
31+
"pythonClassName": "tensorflow_datasets.core.features.sequence_feature.Sequence",
32+
"sequence": {
33+
"feature": {
34+
"pythonClassName": "tensorflow_datasets.core.features.text_feature.Text",
35+
"text": {}
36+
},
37+
"length": "-1"
38+
}
39+
},
40+
"prompt_with_constitution_parts": {
41+
"pythonClassName": "tensorflow_datasets.core.features.sequence_feature.Sequence",
42+
"sequence": {
43+
"feature": {
44+
"pythonClassName": "tensorflow_datasets.core.features.text_feature.Text",
45+
"text": {}
46+
},
47+
"length": "-1"
48+
}
49+
},
50+
"prompt_without_constitution": {
51+
"pythonClassName": "tensorflow_datasets.core.features.text_feature.Text",
52+
"text": {}
53+
},
54+
"prompt_without_constitution_parts": {
55+
"pythonClassName": "tensorflow_datasets.core.features.sequence_feature.Sequence",
56+
"sequence": {
57+
"feature": {
58+
"pythonClassName": "tensorflow_datasets.core.features.text_feature.Text",
59+
"text": {}
60+
},
61+
"length": "-1"
62+
}
63+
}
64+
}
65+
},
66+
"pythonClassName": "tensorflow_datasets.core.features.features_dict.FeaturesDict"
67+
}

‎tensorflow_datasets/testing/metadata/asimov_dilemmas_scifi_train/0.1.0/dataset_info.json

+29
Original file line numberDiff line numberDiff line change
@@ -0,0 +1,29 @@
1+
{
2+
"citation": "@article{Sermanet2025RobotConstitutions,\n author = {Pierre Sermanet and Anirudha Majumdar and Alex Irpan and Dmitry Kalashnikov and Vikas Sindhwani},\n title = {Generating Robot Constitutions & Benchmarks for Semantic Safety},\n journal = {arXiv preprint arXiv:FIXME},\n url = {https://arxiv.org/abs/FIXME},\n year = {2025},\n}",
3+
"description": "Multiple-choice ethical questions (with desirable and undesirable answers) based on situations inspired from Science Fiction literature (training set).",
4+
"fileFormat": "array_record",
5+
"location": {
6+
"urls": [
7+
"https://asimov-benchmark.github.io/"
8+
]
9+
},
10+
"moduleName": "tensorflow_datasets.robotics.asimov.asimov",
11+
"name": "asimov_dilemmas_scifi_train",
12+
"releaseNotes": {
13+
"0.1.0": "Initial release."
14+
},
15+
"splits": [
16+
{
17+
"filepathTemplate": "{DATASET}-{SPLIT}.{FILEFORMAT}-{SHARD_X_OF_Y}",
18+
"name": "val",
19+
"numBytes": "446072205",
20+
"shardLengths": [
21+
"2207",
22+
"2335",
23+
"2216",
24+
"2246"
25+
]
26+
}
27+
],
28+
"version": "0.1.0"
29+
}

‎tensorflow_datasets/testing/metadata/asimov_dilemmas_scifi_train/0.1.0/features.json

+112
Original file line numberDiff line numberDiff line change
@@ -0,0 +1,112 @@
1+
{
2+
"featuresDict": {
3+
"features": {
4+
"acting_character": {
5+
"pythonClassName": "tensorflow_datasets.core.features.text_feature.Text",
6+
"text": {}
7+
},
8+
"characters": {
9+
"pythonClassName": "tensorflow_datasets.core.features.text_feature.Text",
10+
"text": {}
11+
},
12+
"possible_actions": {
13+
"pythonClassName": "tensorflow_datasets.core.features.sequence_feature.Sequence",
14+
"sequence": {
15+
"feature": {
16+
"featuresDict": {
17+
"features": {
18+
"action": {
19+
"pythonClassName": "tensorflow_datasets.core.features.text_feature.Text",
20+
"text": {}
21+
},
22+
"is_original_scifi_decision": {
23+
"pythonClassName": "tensorflow_datasets.core.features.tensor_feature.Tensor",
24+
"tensor": {
25+
"dtype": "bool",
26+
"encoding": "none",
27+
"shape": {}
28+
}
29+
},
30+
"key": {
31+
"pythonClassName": "tensorflow_datasets.core.features.text_feature.Text",
32+
"text": {}
33+
}
34+
}
35+
},
36+
"pythonClassName": "tensorflow_datasets.core.features.features_dict.FeaturesDict"
37+
},
38+
"length": "-1"
39+
}
40+
},
41+
"prompt_with_constitution": {
42+
"pythonClassName": "tensorflow_datasets.core.features.text_feature.Text",
43+
"text": {}
44+
},
45+
"prompt_with_constitution_antijailbreak": {
46+
"pythonClassName": "tensorflow_datasets.core.features.text_feature.Text",
47+
"text": {}
48+
},
49+
"prompt_with_constitution_antijailbreak_adversary": {
50+
"pythonClassName": "tensorflow_datasets.core.features.text_feature.Text",
51+
"text": {}
52+
},
53+
"prompt_with_constitution_antijailbreak_adversary_parts": {
54+
"pythonClassName": "tensorflow_datasets.core.features.sequence_feature.Sequence",
55+
"sequence": {
56+
"feature": {
57+
"pythonClassName": "tensorflow_datasets.core.features.text_feature.Text",
58+
"text": {}
59+
},
60+
"length": "-1"
61+
}
62+
},
63+
"prompt_with_constitution_antijailbreak_parts": {
64+
"pythonClassName": "tensorflow_datasets.core.features.sequence_feature.Sequence",
65+
"sequence": {
66+
"feature": {
67+
"pythonClassName": "tensorflow_datasets.core.features.text_feature.Text",
68+
"text": {}
69+
},
70+
"length": "-1"
71+
}
72+
},
73+
"prompt_with_constitution_parts": {
74+
"pythonClassName": "tensorflow_datasets.core.features.sequence_feature.Sequence",
75+
"sequence": {
76+
"feature": {
77+
"pythonClassName": "tensorflow_datasets.core.features.text_feature.Text",
78+
"text": {}
79+
},
80+
"length": "-1"
81+
}
82+
},
83+
"prompt_without_constitution": {
84+
"pythonClassName": "tensorflow_datasets.core.features.text_feature.Text",
85+
"text": {}
86+
},
87+
"prompt_without_constitution_parts": {
88+
"pythonClassName": "tensorflow_datasets.core.features.sequence_feature.Sequence",
89+
"sequence": {
90+
"feature": {
91+
"pythonClassName": "tensorflow_datasets.core.features.text_feature.Text",
92+
"text": {}
93+
},
94+
"length": "-1"
95+
}
96+
},
97+
"reference_domain": {
98+
"pythonClassName": "tensorflow_datasets.core.features.text_feature.Text",
99+
"text": {}
100+
},
101+
"reference_moment": {
102+
"pythonClassName": "tensorflow_datasets.core.features.text_feature.Text",
103+
"text": {}
104+
},
105+
"reference_scifi": {
106+
"pythonClassName": "tensorflow_datasets.core.features.text_feature.Text",
107+
"text": {}
108+
}
109+
}
110+
},
111+
"pythonClassName": "tensorflow_datasets.core.features.features_dict.FeaturesDict"
112+
}

‎tensorflow_datasets/testing/metadata/asimov_dilemmas_scifi_val/0.1.0/dataset_info.json

+26
Original file line numberDiff line numberDiff line change
@@ -0,0 +1,26 @@
1+
{
2+
"citation": "@article{Sermanet2025RobotConstitutions,\n author = {Pierre Sermanet and Anirudha Majumdar and Alex Irpan and Dmitry Kalashnikov and Vikas Sindhwani},\n title = {Generating Robot Constitutions & Benchmarks for Semantic Safety},\n journal = {arXiv preprint arXiv:FIXME},\n url = {https://arxiv.org/abs/FIXME},\n year = {2025},\n}",
3+
"description": "Multiple-choice ethical questions (with desirable and undesirable answers) based on situations inspired from Science Fiction literature (validation set).",
4+
"fileFormat": "array_record",
5+
"location": {
6+
"urls": [
7+
"https://asimov-benchmark.github.io/"
8+
]
9+
},
10+
"moduleName": "tensorflow_datasets.robotics.asimov.asimov",
11+
"name": "asimov_dilemmas_scifi_val",
12+
"releaseNotes": {
13+
"0.1.0": "Initial release."
14+
},
15+
"splits": [
16+
{
17+
"filepathTemplate": "{DATASET}-{SPLIT}.{FILEFORMAT}-{SHARD_X_OF_Y}",
18+
"name": "val",
19+
"numBytes": "2070165",
20+
"shardLengths": [
21+
"51"
22+
]
23+
}
24+
],
25+
"version": "0.1.0"
26+
}

‎tensorflow_datasets/testing/metadata/asimov_dilemmas_scifi_val/0.1.0/features.json

+120
Original file line numberDiff line numberDiff line change
@@ -0,0 +1,120 @@
1+
{
2+
"featuresDict": {
3+
"features": {
4+
"acting_character": {
5+
"pythonClassName": "tensorflow_datasets.core.features.text_feature.Text",
6+
"text": {}
7+
},
8+
"characters": {
9+
"pythonClassName": "tensorflow_datasets.core.features.text_feature.Text",
10+
"text": {}
11+
},
12+
"possible_actions": {
13+
"pythonClassName": "tensorflow_datasets.core.features.sequence_feature.Sequence",
14+
"sequence": {
15+
"feature": {
16+
"featuresDict": {
17+
"features": {
18+
"action": {
19+
"pythonClassName": "tensorflow_datasets.core.features.text_feature.Text",
20+
"text": {}
21+
},
22+
"is_original_scifi_decision": {
23+
"pythonClassName": "tensorflow_datasets.core.features.tensor_feature.Tensor",
24+
"tensor": {
25+
"dtype": "bool",
26+
"encoding": "none",
27+
"shape": {}
28+
}
29+
},
30+
"key": {
31+
"pythonClassName": "tensorflow_datasets.core.features.text_feature.Text",
32+
"text": {}
33+
},
34+
"undesirable_groundtruth_answer": {
35+
"pythonClassName": "tensorflow_datasets.core.features.tensor_feature.Tensor",
36+
"tensor": {
37+
"dtype": "bool",
38+
"encoding": "none",
39+
"shape": {}
40+
}
41+
}
42+
}
43+
},
44+
"pythonClassName": "tensorflow_datasets.core.features.features_dict.FeaturesDict"
45+
},
46+
"length": "-1"
47+
}
48+
},
49+
"prompt_with_constitution": {
50+
"pythonClassName": "tensorflow_datasets.core.features.text_feature.Text",
51+
"text": {}
52+
},
53+
"prompt_with_constitution_antijailbreak": {
54+
"pythonClassName": "tensorflow_datasets.core.features.text_feature.Text",
55+
"text": {}
56+
},
57+
"prompt_with_constitution_antijailbreak_adversary": {
58+
"pythonClassName": "tensorflow_datasets.core.features.text_feature.Text",
59+
"text": {}
60+
},
61+
"prompt_with_constitution_antijailbreak_adversary_parts": {
62+
"pythonClassName": "tensorflow_datasets.core.features.sequence_feature.Sequence",
63+
"sequence": {
64+
"feature": {
65+
"pythonClassName": "tensorflow_datasets.core.features.text_feature.Text",
66+
"text": {}
67+
},
68+
"length": "-1"
69+
}
70+
},
71+
"prompt_with_constitution_antijailbreak_parts": {
72+
"pythonClassName": "tensorflow_datasets.core.features.sequence_feature.Sequence",
73+
"sequence": {
74+
"feature": {
75+
"pythonClassName": "tensorflow_datasets.core.features.text_feature.Text",
76+
"text": {}
77+
},
78+
"length": "-1"
79+
}
80+
},
81+
"prompt_with_constitution_parts": {
82+
"pythonClassName": "tensorflow_datasets.core.features.sequence_feature.Sequence",
83+
"sequence": {
84+
"feature": {
85+
"pythonClassName": "tensorflow_datasets.core.features.text_feature.Text",
86+
"text": {}
87+
},
88+
"length": "-1"
89+
}
90+
},
91+
"prompt_without_constitution": {
92+
"pythonClassName": "tensorflow_datasets.core.features.text_feature.Text",
93+
"text": {}
94+
},
95+
"prompt_without_constitution_parts": {
96+
"pythonClassName": "tensorflow_datasets.core.features.sequence_feature.Sequence",
97+
"sequence": {
98+
"feature": {
99+
"pythonClassName": "tensorflow_datasets.core.features.text_feature.Text",
100+
"text": {}
101+
},
102+
"length": "-1"
103+
}
104+
},
105+
"reference_domain": {
106+
"pythonClassName": "tensorflow_datasets.core.features.text_feature.Text",
107+
"text": {}
108+
},
109+
"reference_moment": {
110+
"pythonClassName": "tensorflow_datasets.core.features.text_feature.Text",
111+
"text": {}
112+
},
113+
"reference_scifi": {
114+
"pythonClassName": "tensorflow_datasets.core.features.text_feature.Text",
115+
"text": {}
116+
}
117+
}
118+
},
119+
"pythonClassName": "tensorflow_datasets.core.features.features_dict.FeaturesDict"
120+
}

0 commit comments

Comments
 (0)