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  1. .gitattributes +2 -0
  2. .gitignore +5 -0
  3. .gitmodules +21 -0
  4. README.md +20 -0
  5. croissant.json +1468 -0
  6. data/babyai-sr/code/.gitignore +1 -0
  7. data/babyai-sr/code/environment.editable.yml +14 -0
  8. data/babyai-sr/code/environment.yml +94 -0
  9. data/babyai-sr/code/helper.py +227 -0
  10. data/babyai-sr/code/repo +1 -0
  11. data/babyai-sr/code/run.sh +65 -0
  12. data/babyai-sr/code/util.py +1 -0
  13. data/babyai-sr/data/GoToObj/corpus.json +3 -0
  14. data/babyai-sr/data/GoToObj/corpus.jsonl +3 -0
  15. data/babyai-sr/data/GoToObj/corpus.structured.jsonl +3 -0
  16. data/babyai-sr/data/GoToObj/metadata.json +25 -0
  17. data/babyai-sr/data/GoToObjLocked/corpus.json +3 -0
  18. data/babyai-sr/data/GoToObjLocked/corpus.jsonl +3 -0
  19. data/babyai-sr/data/GoToObjLocked/corpus.structured.jsonl +3 -0
  20. data/babyai-sr/data/GoToObjLocked/metadata.json +25 -0
  21. data/babyai-sr/data/GoToObjLocked_ambiguous-freq_1/corpus.json +3 -0
  22. data/babyai-sr/data/GoToObjLocked_ambiguous-freq_1/corpus.jsonl +3 -0
  23. data/babyai-sr/data/GoToObjLocked_ambiguous-freq_1/corpus.structured.jsonl +3 -0
  24. data/babyai-sr/data/GoToObjLocked_ambiguous-freq_1/metadata.json +25 -0
  25. data/babyai-sr/data/GoToObjLocked_ambiguous-freq_2/corpus.json +3 -0
  26. data/babyai-sr/data/GoToObjLocked_ambiguous-freq_2/corpus.jsonl +3 -0
  27. data/babyai-sr/data/GoToObjLocked_ambiguous-freq_2/corpus.structured.jsonl +3 -0
  28. data/babyai-sr/data/GoToObjLocked_ambiguous-freq_2/metadata.json +25 -0
  29. data/babyai-sr/data/GoToObjLocked_ambiguous-freq_32/corpus.json +3 -0
  30. data/babyai-sr/data/GoToObjLocked_ambiguous-freq_32/corpus.jsonl +3 -0
  31. data/babyai-sr/data/GoToObjLocked_ambiguous-freq_32/corpus.structured.jsonl +3 -0
  32. data/babyai-sr/data/GoToObjLocked_ambiguous-freq_32/metadata.json +25 -0
  33. data/babyai-sr/data/GoToObjLocked_ambiguous-freq_4/corpus.json +3 -0
  34. data/babyai-sr/data/GoToObjLocked_ambiguous-freq_4/corpus.jsonl +3 -0
  35. data/babyai-sr/data/GoToObjLocked_ambiguous-freq_4/corpus.structured.jsonl +3 -0
  36. data/babyai-sr/data/GoToObjLocked_ambiguous-freq_4/metadata.json +25 -0
  37. data/babyai-sr/data/GoToObjLocked_ambiguous-msg_16/corpus.json +3 -0
  38. data/babyai-sr/data/GoToObjLocked_ambiguous-msg_16/corpus.jsonl +3 -0
  39. data/babyai-sr/data/GoToObjLocked_ambiguous-msg_16/corpus.structured.jsonl +3 -0
  40. data/babyai-sr/data/GoToObjLocked_ambiguous-msg_16/metadata.json +25 -0
  41. data/babyai-sr/data/GoToObjLocked_ambiguous-msg_32/corpus.json +3 -0
  42. data/babyai-sr/data/GoToObjLocked_ambiguous-msg_32/corpus.jsonl +3 -0
  43. data/babyai-sr/data/GoToObjLocked_ambiguous-msg_32/corpus.structured.jsonl +3 -0
  44. data/babyai-sr/data/GoToObjLocked_ambiguous-msg_32/metadata.json +25 -0
  45. data/babyai-sr/data/GoToObjLocked_ambiguous-msg_4/corpus.json +3 -0
  46. data/babyai-sr/data/GoToObjLocked_ambiguous-msg_4/corpus.jsonl +3 -0
  47. data/babyai-sr/data/GoToObjLocked_ambiguous-msg_4/corpus.structured.jsonl +3 -0
  48. data/babyai-sr/data/GoToObjLocked_ambiguous-msg_4/metadata.json +25 -0
  49. data/babyai-sr/data/GoToObjLocked_ambiguous/corpus.json +3 -0
  50. data/babyai-sr/data/GoToObjLocked_ambiguous/corpus.jsonl +3 -0
.gitattributes ADDED
@@ -0,0 +1,2 @@
 
 
 
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+ corpus*.jsonl filter=lfs diff=lfs merge=lfs -text
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+ corpus*.json filter=lfs diff=lfs merge=lfs -text
.gitignore ADDED
@@ -0,0 +1,5 @@
 
 
 
 
 
 
1
+ output-data/
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+ input-data/
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+ .direnv/
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+ .envrc
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+ __pycache__/
.gitmodules ADDED
@@ -0,0 +1,21 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ [submodule "library/egg-discrimination/code/EGG"]
2
+ path = data/egg-discrimination/code/repo
3
+ url = https://github.com/facebookresearch/EGG
4
+ [submodule "library/generalizations-mu-goodman/code/repo"]
5
+ path = data/generalizations-mu-goodman/code/repo
6
+ url = https://github.com/brendon-boldt/emergent-generalization
7
+ [submodule "library/ec-at-scale/emergent_communication_at_scale"]
8
+ path = data/ec-at-scale/code/emergent_communication_at_scale
9
+ url = https://github.com/brendon-boldt/emergent_communication_at_scale
10
+ [submodule "library/corpus-transfer-yao-et-al/repo"]
11
+ path = data/corpus-transfer-yao-et-al/code/repo
12
+ url = https://github.com/brendon-boldt/ec-nl
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+ [submodule "library/rlupus/repo"]
14
+ path = data/rlupus/code/repo
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+ url = https://github.com/brendon-boldt/rl_werewolf
16
+ [submodule "library/comon-iccv/code/repo"]
17
+ path = library/comon-iccv/code/repo
18
+ url = https://github.com/saimwani/CoMON
19
+ [submodule "library/babyai-sr/code/repo"]
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+ path = data/babyai-sr/code/repo
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+ url = https://github.com/brendon-boldt/babyai_sr
README.md ADDED
@@ -0,0 +1,20 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ # Emergent Language Library
2
+
3
+
4
+ ## Running code
5
+
6
+ For each emergent language entry, we provide wrapper code to create
7
+ a reproducible environment and run the emergent language-generating code.
8
+ Environments are specified precisely in the `environment.yml` file; if you wish
9
+ to edit the dependencies manually, it may be easier to start with
10
+ `environment.editable.yml` instead, if it exists.
11
+
12
+ ### Git submodules
13
+ This project uses git submodules to manage external dependencies. Submodules
14
+ do not always operate in an intuitive way, so we provide a brief explanation of
15
+ how to use them here. By default, submodules are not "init-ed" which means
16
+ that they will be empty after you clone the project. If you would like to
17
+ populate a submodule (i.e., the directory pointing to another repo) to see or
18
+ use its code, run `git submodule init path/to/submodule` to mark it as init-ed.
19
+ Second, run `git submodule update` to populated init-ed submodules. Run `git
20
+ submodule deinit -f path/to/submodule` to make the submodule empty again.
croissant.json ADDED
@@ -0,0 +1,1468 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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+ {
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+ "@language": "en",
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+ "@vocab": "https://schema.org/",
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+ "citeAs": "cr:citeAs",
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+ "column": "cr:column",
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+ "conformsTo": "dct:conformsTo",
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+ "cr": "http://mlcommons.org/croissant/",
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+ "rai": "http://mlcommons.org/croissant/RAI/",
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+ "data": {
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+ "@id": "cr:data",
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+ "@type": "@json"
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+ },
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+ "dataType": {
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+ "@id": "cr:dataType",
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+ "@type": "@vocab"
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+ },
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+ "dct": "http://purl.org/dc/terms/",
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+ "examples": {
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+ "@id": "cr:examples",
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+ "@type": "@json"
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+ },
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+ "extract": "cr:extract",
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+ "field": "cr:field",
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+ "fileProperty": "cr:fileProperty",
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+ "fileObject": "cr:fileObject",
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+ "fileSet": "cr:fileSet",
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+ "format": "cr:format",
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+ "includes": "cr:includes",
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+ "isLiveDataset": "cr:isLiveDataset",
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+ "jsonPath": "cr:jsonPath",
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+ "key": "cr:key",
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+ "md5": "cr:md5",
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+ "parentField": "cr:parentField",
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+ "path": "cr:path",
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+ "recordSet": "cr:recordSet",
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+ "references": "cr:references",
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+ "regex": "cr:regex",
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+ "repeated": "cr:repeated",
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+ "replace": "cr:replace",
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+ "sc": "https://schema.org/",
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+ "separator": "cr:separator",
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+ "source": "cr:source",
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+ "subField": "cr:subField",
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+ "transform": "cr:transform"
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+ },
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+ "@type": "sc:Dataset",
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+ "name": "ELCC",
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+ "description": "ELCC is a collection of emergent language corpora with accompanying metadata and analyses.",
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+ "conformsTo": "http://mlcommons.org/croissant/1.0",
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+ "citeAs": " @misc{boldt2024elcc,\n title = \"{ELCC}: the Emergent Language Corpus Collection\",\n author = \"Brendon Boldt and David Mortensen\",\n year = 2024,\n url = \"\",\n}",
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+ "datePublished": "2024-06-05 22:14:16.853626+00:00",
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+ "keywords": [
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+ "emergent communication",
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+ "emergent language",
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+ "corpus"
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+ ],
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+ "license": "https://creativecommons.org/licenses/by/4.0/",
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+ "url": "https://huggingface.co/datasets/bboldt/elcc/",
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+ "version": "0.1.0",
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+ "distribution": [
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1316
+ }
1317
+ }
1318
+ ]
1319
+ },
1320
+ {
1321
+ "@type": "cr:RecordSet",
1322
+ "@id": "rlupus/9-player.run-2",
1323
+ "name": "rlupus/9-player.run-2",
1324
+ "field": [
1325
+ {
1326
+ "@type": "cr:Field",
1327
+ "@id": "rlupus/9-player.run-2/content",
1328
+ "name": "content",
1329
+ "dataType": "sc:Text",
1330
+ "source": {
1331
+ "fileObject": {
1332
+ "@id": "data/rlupus/data/9-player.run-2/corpus.json"
1333
+ },
1334
+ "extract": {
1335
+ "fileProperty": "content"
1336
+ }
1337
+ }
1338
+ }
1339
+ ]
1340
+ },
1341
+ {
1342
+ "@type": "cr:RecordSet",
1343
+ "@id": "rlupus/21-player.run-1",
1344
+ "name": "rlupus/21-player.run-1",
1345
+ "field": [
1346
+ {
1347
+ "@type": "cr:Field",
1348
+ "@id": "rlupus/21-player.run-1/content",
1349
+ "name": "content",
1350
+ "dataType": "sc:Text",
1351
+ "source": {
1352
+ "fileObject": {
1353
+ "@id": "data/rlupus/data/21-player.run-1/corpus.json"
1354
+ },
1355
+ "extract": {
1356
+ "fileProperty": "content"
1357
+ }
1358
+ }
1359
+ }
1360
+ ]
1361
+ },
1362
+ {
1363
+ "@type": "cr:RecordSet",
1364
+ "@id": "rlupus/9-player.run-1",
1365
+ "name": "rlupus/9-player.run-1",
1366
+ "field": [
1367
+ {
1368
+ "@type": "cr:Field",
1369
+ "@id": "rlupus/9-player.run-1/content",
1370
+ "name": "content",
1371
+ "dataType": "sc:Text",
1372
+ "source": {
1373
+ "fileObject": {
1374
+ "@id": "data/rlupus/data/9-player.run-1/corpus.json"
1375
+ },
1376
+ "extract": {
1377
+ "fileProperty": "content"
1378
+ }
1379
+ }
1380
+ }
1381
+ ]
1382
+ },
1383
+ {
1384
+ "@type": "cr:RecordSet",
1385
+ "@id": "egg-discrimination/6-attr_6-val_9-dist_10-vocab_10-len",
1386
+ "name": "egg-discrimination/6-attr_6-val_9-dist_10-vocab_10-len",
1387
+ "field": [
1388
+ {
1389
+ "@type": "cr:Field",
1390
+ "@id": "egg-discrimination/6-attr_6-val_9-dist_10-vocab_10-len/content",
1391
+ "name": "content",
1392
+ "dataType": "sc:Text",
1393
+ "source": {
1394
+ "fileObject": {
1395
+ "@id": "data/egg-discrimination/data/6-attr_6-val_9-dist_10-vocab_10-len/corpus.json"
1396
+ },
1397
+ "extract": {
1398
+ "fileProperty": "content"
1399
+ }
1400
+ }
1401
+ }
1402
+ ]
1403
+ },
1404
+ {
1405
+ "@type": "cr:RecordSet",
1406
+ "@id": "egg-discrimination/8-attr_8-val_3-dist_10-vocab_10-len",
1407
+ "name": "egg-discrimination/8-attr_8-val_3-dist_10-vocab_10-len",
1408
+ "field": [
1409
+ {
1410
+ "@type": "cr:Field",
1411
+ "@id": "egg-discrimination/8-attr_8-val_3-dist_10-vocab_10-len/content",
1412
+ "name": "content",
1413
+ "dataType": "sc:Text",
1414
+ "source": {
1415
+ "fileObject": {
1416
+ "@id": "data/egg-discrimination/data/8-attr_8-val_3-dist_10-vocab_10-len/corpus.json"
1417
+ },
1418
+ "extract": {
1419
+ "fileProperty": "content"
1420
+ }
1421
+ }
1422
+ }
1423
+ ]
1424
+ },
1425
+ {
1426
+ "@type": "cr:RecordSet",
1427
+ "@id": "egg-discrimination/4-attr_4-val_3-dist_10-vocab_10-len",
1428
+ "name": "egg-discrimination/4-attr_4-val_3-dist_10-vocab_10-len",
1429
+ "field": [
1430
+ {
1431
+ "@type": "cr:Field",
1432
+ "@id": "egg-discrimination/4-attr_4-val_3-dist_10-vocab_10-len/content",
1433
+ "name": "content",
1434
+ "dataType": "sc:Text",
1435
+ "source": {
1436
+ "fileObject": {
1437
+ "@id": "data/egg-discrimination/data/4-attr_4-val_3-dist_10-vocab_10-len/corpus.json"
1438
+ },
1439
+ "extract": {
1440
+ "fileProperty": "content"
1441
+ }
1442
+ }
1443
+ }
1444
+ ]
1445
+ },
1446
+ {
1447
+ "@type": "cr:RecordSet",
1448
+ "@id": "egg-discrimination/6-attr_6-val_3-dist_10-vocab_10-len",
1449
+ "name": "egg-discrimination/6-attr_6-val_3-dist_10-vocab_10-len",
1450
+ "field": [
1451
+ {
1452
+ "@type": "cr:Field",
1453
+ "@id": "egg-discrimination/6-attr_6-val_3-dist_10-vocab_10-len/content",
1454
+ "name": "content",
1455
+ "dataType": "sc:Text",
1456
+ "source": {
1457
+ "fileObject": {
1458
+ "@id": "data/egg-discrimination/data/6-attr_6-val_3-dist_10-vocab_10-len/corpus.json"
1459
+ },
1460
+ "extract": {
1461
+ "fileProperty": "content"
1462
+ }
1463
+ }
1464
+ }
1465
+ ]
1466
+ }
1467
+ ]
1468
+ }
data/babyai-sr/code/.gitignore ADDED
@@ -0,0 +1 @@
 
 
1
+ /save/
data/babyai-sr/code/environment.editable.yml ADDED
@@ -0,0 +1,14 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ name: babyai-sr
2
+ channels:
3
+ - pytorch
4
+ - conda-forge
5
+ dependencies:
6
+ - python==3.7.*
7
+ - matplotlib<=3.1.3
8
+ - pytorch==1.5.1
9
+ - tensorboardx
10
+ - numpy==1.15.4
11
+ - pip:
12
+ - gym==0.9.6
13
+ - gym_minigrid@git+https://github.com/thomasaunger/gym-minigrid
14
+ - babyai@git+https://github.com/brendon-boldt/babyai-thomasaunger
data/babyai-sr/code/environment.yml ADDED
@@ -0,0 +1,94 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ name: babyai-sr
2
+ channels:
3
+ - pytorch
4
+ - conda-forge
5
+ dependencies:
6
+ - _libgcc_mutex=0.1=conda_forge
7
+ - _openmp_mutex=4.5=2_kmp_llvm
8
+ - blas=2.122=mkl
9
+ - blas-devel=3.9.0=22_linux64_mkl
10
+ - ca-certificates=2024.2.2=hbcca054_0
11
+ - cudatoolkit=10.2.89=hdec6ad0_13
12
+ - cycler=0.11.0=pyhd8ed1ab_0
13
+ - dbus=1.13.6=hfdff14a_1
14
+ - expat=2.6.2=h59595ed_0
15
+ - fontconfig=2.14.2=h14ed4e7_0
16
+ - freetype=2.12.1=h267a509_2
17
+ - gettext=0.22.5=h59595ed_2
18
+ - gettext-tools=0.22.5=h59595ed_2
19
+ - glib=2.66.3=h58526e2_0
20
+ - gst-plugins-base=1.14.5=h0935bb2_2
21
+ - gstreamer=1.14.5=h36ae1b5_2
22
+ - icu=64.2=he1b5a44_1
23
+ - jpeg=9e=h0b41bf4_3
24
+ - kiwisolver=1.4.4=py37h7cecad7_0
25
+ - ld_impl_linux-64=2.40=hf3520f5_1
26
+ - libasprintf=0.22.5=h661eb56_2
27
+ - libasprintf-devel=0.22.5=h661eb56_2
28
+ - libblas=3.9.0=22_linux64_mkl
29
+ - libcblas=3.9.0=22_linux64_mkl
30
+ - libclang=9.0.1=default_hb4e5071_5
31
+ - libexpat=2.6.2=h59595ed_0
32
+ - libffi=3.2.1=he1b5a44_1007
33
+ - libgcc-ng=13.2.0=h77fa898_7
34
+ - libgettextpo=0.22.5=h59595ed_2
35
+ - libgettextpo-devel=0.22.5=h59595ed_2
36
+ - libgfortran-ng=13.2.0=h69a702a_7
37
+ - libgfortran5=13.2.0=hca663fb_7
38
+ - libglib=2.66.3=hbe7bbb4_0
39
+ - libiconv=1.17=hd590300_2
40
+ - liblapack=3.9.0=22_linux64_mkl
41
+ - liblapacke=3.9.0=22_linux64_mkl
42
+ - libllvm9=9.0.1=default_hc23dcda_7
43
+ - libpng=1.6.43=h2797004_0
44
+ - libprotobuf=3.20.1=h6239696_4
45
+ - libsqlite=3.45.3=h2797004_0
46
+ - libstdcxx-ng=13.2.0=hc0a3c3a_7
47
+ - libuuid=2.38.1=h0b41bf4_0
48
+ - libxcb=1.16=hd590300_0
49
+ - libxkbcommon=0.10.0=he1b5a44_0
50
+ - libxml2=2.9.10=hee79883_0
51
+ - libzlib=1.2.13=h4ab18f5_6
52
+ - llvm-openmp=18.1.6=ha31de31_0
53
+ - matplotlib=3.1.3=py37_0
54
+ - matplotlib-base=3.1.3=py37h250f245_0
55
+ - mkl=2024.1.0=ha957f24_693
56
+ - mkl-devel=2024.1.0=ha770c72_693
57
+ - mkl-include=2024.1.0=ha957f24_693
58
+ - ncurses=6.5=h59595ed_0
59
+ - ninja=1.12.1=h297d8ca_0
60
+ - nspr=4.35=h27087fc_0
61
+ - nss=3.100=hca3bf56_0
62
+ - numpy=1.15.4=py37h8b7e671_1002
63
+ - openssl=1.1.1w=hd590300_0
64
+ - pcre=8.45=h9c3ff4c_0
65
+ - pip=24.0=pyhd8ed1ab_0
66
+ - protobuf=3.20.1=py37hd23a5d3_0
67
+ - pthread-stubs=0.4=h36c2ea0_1001
68
+ - pyparsing=3.1.2=pyhd8ed1ab_0
69
+ - pyqt=5.12.3=py37h8685d9f_3
70
+ - python=3.7.8=h8bdb77d_2_cpython
71
+ - python-dateutil=2.9.0=pyhd8ed1ab_0
72
+ - python_abi=3.7=4_cp37m
73
+ - pytorch=1.5.1=py3.7_cuda10.2.89_cudnn7.6.5_0
74
+ - qt=5.12.5=hd8c4c69_1
75
+ - readline=8.2=h8228510_1
76
+ - setuptools=69.0.3=pyhd8ed1ab_0
77
+ - six=1.16.0=pyh6c4a22f_0
78
+ - sqlite=3.45.3=h2c6b66d_0
79
+ - tbb=2021.7.0=h924138e_0
80
+ - tensorboardx=2.5.1=pyhd8ed1ab_0
81
+ - tk=8.6.13=noxft_h4845f30_101
82
+ - tornado=6.2=py37h540881e_0
83
+ - typing-extensions=4.7.1=hd8ed1ab_0
84
+ - typing_extensions=4.7.1=pyha770c72_0
85
+ - wheel=0.42.0=pyhd8ed1ab_0
86
+ - xorg-libxau=1.0.11=hd590300_0
87
+ - xorg-libxdmcp=1.1.3=h7f98852_0
88
+ - xz=5.2.6=h166bdaf_0
89
+ - zlib=1.2.13=h4ab18f5_6
90
+ - zstd=1.5.6=ha6fb4c9_0
91
+ - pip:
92
+ - gym==0.9.6
93
+ - gym_minigrid@git+https://github.com/thomasaunger/gym-minigrid
94
+ - babyai@git+https://github.com/brendon-boldt/babyai-thomasaunger
data/babyai-sr/code/helper.py ADDED
@@ -0,0 +1,227 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ from argparse import Namespace
2
+ import json
3
+ from pathlib import Path
4
+ from typing import Tuple, List, Dict
5
+
6
+ import gym
7
+ import torch
8
+ import numpy as np
9
+
10
+ import babyai.utils as utils
11
+ import babyai_sr.utils as utils_sr
12
+ from babyai_sr.arguments import ArgumentParser
13
+ from babyai_sr.rl.algos import TestAlgo, BaseAlgo
14
+ from babyai_sr.rl.utils import ParallelEnv
15
+ import util as lib_util
16
+
17
+ ##### based on repo/babyai_sr/rl/algos/test.py #####
18
+
19
+ SENDER = 0
20
+ RECEIVER = 1
21
+
22
+
23
+ def extract_messages(message, done, active) -> List[List[int]]:
24
+ argmax_messages = message.argmax(-1)[:, :, SENDER]
25
+ done_np = done.cpu().numpy()
26
+ done_idxs = np.argwhere(done_np)
27
+ message_list = []
28
+ for i in range(done_idxs.shape[0]):
29
+ prev_end = done_idxs[i - 1] if i > 0 else [0, -1]
30
+ end = done_idxs[i]
31
+ # If we are spanning the border between procs, adjust the prev_end
32
+ # to start at the end's proc.
33
+ if prev_end[0] != end[0]:
34
+ prev_end = [end[0], -1]
35
+ # Take messages from the given proc and
36
+ indexer = np.s_[prev_end[0], prev_end[1] + 1 : (end[1] + 1)]
37
+ ep_messages = argmax_messages[indexer]
38
+ # We only want messages for when the sender is active since the
39
+ # message is just repeated for the receiver until the sender is
40
+ # active again.
41
+ ep_active = active[indexer][:, SENDER]
42
+ final_ep_messages = ep_messages[ep_active]
43
+ message_list.append(final_ep_messages.cpu().tolist())
44
+ return message_list
45
+
46
+
47
+ class TestAlgo(BaseAlgo):
48
+ def __init__(
49
+ self,
50
+ env,
51
+ models,
52
+ num_frames_per_proc=40,
53
+ discount=0.99,
54
+ gae_lambda=0.99,
55
+ preprocess_obss=None,
56
+ reshape_reward=None,
57
+ use_comm=True,
58
+ conventional=False,
59
+ argmax=True,
60
+ ):
61
+
62
+ super().__init__(
63
+ env,
64
+ models,
65
+ num_frames_per_proc,
66
+ discount,
67
+ gae_lambda,
68
+ preprocess_obss,
69
+ reshape_reward,
70
+ use_comm,
71
+ conventional,
72
+ argmax,
73
+ )
74
+
75
+ def collect_episodes(self, episodes):
76
+ # Collect experiences.
77
+ exps, _ = self.collect_experiences()
78
+ batch = 1
79
+
80
+ shape_prefix = (self.num_procs, self.num_frames_per_proc)
81
+
82
+ active = exps.active.view(*shape_prefix, *exps.active.shape[1:])
83
+ done = exps.done.view(*shape_prefix, *exps.done.shape[1:])
84
+ message = exps.message.view(*shape_prefix, *exps.message.shape[1:])
85
+ reward = exps.reward.view(*shape_prefix, *exps.reward.shape[1:])
86
+
87
+ log = {
88
+ "return_per_episode": [],
89
+ }
90
+
91
+ proc = 0
92
+ frame = [0] * self.num_procs
93
+ episodes_done = 0
94
+ while True:
95
+ if done[proc, frame[proc]]:
96
+ episodes_done += 1
97
+ log["return_per_episode"].append(
98
+ reward[proc, frame[proc], RECEIVER].item()
99
+ )
100
+ if episodes_done == episodes:
101
+ break
102
+ frame[proc] += 1
103
+ proc = (proc + 1) % self.num_procs
104
+ else:
105
+ frame[proc] += 1
106
+
107
+ if frame[proc] == batch * self.num_frames_per_proc:
108
+ exps, _ = self.collect_experiences()
109
+ batch += 1
110
+
111
+ next_active = exps.active.view(*shape_prefix, *exps.active.shape[1:])
112
+ next_done = exps.done.view(*shape_prefix, *exps.done.shape[1:])
113
+ next_message = exps.message.view(*shape_prefix, *exps.message.shape[1:])
114
+ next_reward = exps.reward.view(*shape_prefix, *exps.reward.shape[1:])
115
+
116
+ active = torch.cat((active, next_active), 1)
117
+ done = torch.cat((done, next_done), 1)
118
+ message = torch.cat((message, next_message), 1)
119
+ reward = torch.cat((reward, next_reward), 1)
120
+
121
+ message_list = extract_messages(message, done, active)
122
+
123
+ return message_list, log
124
+
125
+
126
+ ##### based on repo/babyai_sr/scripts/test_rl.py #####
127
+
128
+
129
+ def parse_args() -> Namespace:
130
+ parser = ArgumentParser()
131
+ parser.add_argument("--name", help="name of the configuration")
132
+ parser.add_argument("--sender", default=None, help="name of the sender (REQUIRED)")
133
+ parser.add_argument(
134
+ "--receiver", default=None, help="name of the receiver (REQUIRED)"
135
+ )
136
+ parser.add_argument(
137
+ "--sample",
138
+ action="store_true",
139
+ default=False,
140
+ help="sample messages instead of using argmax",
141
+ )
142
+ parser.add_argument(
143
+ "--episodes",
144
+ type=int,
145
+ default=1000,
146
+ help="number of episodes to test on (default: 1000)",
147
+ )
148
+ parser.add_argument("--len-message", default=None, help="dummy")
149
+ parser.add_argument("--num-symbols", default=None, help="dummy")
150
+ return parser.parse_args()
151
+
152
+
153
+ def get_episodes(args: Namespace) -> Tuple[List, Dict]:
154
+ utils.seed(args.seed)
155
+ envs = []
156
+ for i in range(args.procs):
157
+ env = gym.make(args.env)
158
+ env.seed(100 * args.seed + i)
159
+ envs.append(env)
160
+ penv = ParallelEnv(
161
+ envs, args.n, args.conventional, args.archimedean, args.informed_sender
162
+ )
163
+
164
+ sender = utils.load_model(args.sender)
165
+ receiver = utils.load_model(args.receiver)
166
+ sender.eval()
167
+ receiver.eval()
168
+ if torch.cuda.is_available():
169
+ sender.cuda()
170
+ receiver.cuda()
171
+
172
+ reshape_reward = lambda _0, _1, reward, _2: args.reward_scale * reward
173
+ obss_preprocessor = utils_sr.MultiObssPreprocessor(
174
+ [args.sender, args.receiver], [envs[0].observation_space] * 2
175
+ )
176
+ test_algo = TestAlgo(
177
+ penv,
178
+ [sender, receiver],
179
+ args.frames_per_proc,
180
+ args.discount,
181
+ args.gae_lambda,
182
+ obss_preprocessor,
183
+ reshape_reward,
184
+ not args.no_comm,
185
+ args.conventional,
186
+ not args.sample,
187
+ )
188
+
189
+ return test_algo.collect_episodes(args.episodes)
190
+
191
+
192
+ def write_results(args: Namespace, message_list: List, logs: Dict) -> None:
193
+ out_path = Path(f"../../data/{args.name}")
194
+ out_path.mkdir(exist_ok=True, parents=True)
195
+
196
+ return_per_episode = utils.synthesize(logs["return_per_episode"])
197
+ success_per_episode = utils.synthesize(
198
+ [1 if r > 0 else 0 for r in logs["return_per_episode"]]
199
+ )
200
+
201
+ metrics = {
202
+ "success_rate": success_per_episode["mean"],
203
+ "success_rate_std": success_per_episode["std"],
204
+ "reward_per_episode": return_per_episode["mean"],
205
+ "reward_per_episode_std": return_per_episode["std"],
206
+ }
207
+ lib_util.write_system_metrics(out_path, metrics)
208
+
209
+ with (out_path / "corpus.jsonl").open("w") as fo:
210
+ for message in message_list:
211
+ flat = [x for y in message for x in y]
212
+ json.dump(flat, fo, indent=None)
213
+ fo.write("\n")
214
+ with (out_path / "corpus.structured.jsonl").open("w") as fo:
215
+ for message in message_list:
216
+ json.dump(message, fo, indent=None)
217
+ fo.write("\n")
218
+
219
+
220
+ def main() -> None:
221
+ args = parse_args()
222
+ message_list, logs = get_episodes(args)
223
+ write_results(args, message_list, logs)
224
+
225
+
226
+ if __name__ == "__main__":
227
+ main()
data/babyai-sr/code/repo ADDED
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+ Subproject commit d4a3cb757614bc3b343608f751500eeb31f7db7a
data/babyai-sr/code/run.sh ADDED
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1
+ #!/usr/bin/env bash
2
+
3
+ set -xe
4
+
5
+ export PYTHONPATH=$(realpath repo/)
6
+
7
+ args_arr=(
8
+ "--name GoToObj --n 8 --env BabyAI-GoToObj-v0"
9
+ "--name GoToObjLocked --n 8 --env BabyAI-GoToObjLocked-v0"
10
+
11
+ "--name GoToObjUnlocked-freq_1 --n 1 --env BabyAI-GoToObjUnlocked-v0"
12
+ "--name GoToObjUnlocked-freq_2 --n 2 --env BabyAI-GoToObjUnlocked-v0"
13
+ "--name GoToObjUnlocked-freq_4 --n 4 --env BabyAI-GoToObjUnlocked-v0"
14
+ "--name GoToObjUnlocked --n 8 --env BabyAI-GoToObjUnlocked-v0"
15
+ "--name GoToObjUnlocked-freq_32 --n 32 --env BabyAI-GoToObjUnlocked-v0"
16
+ "--name GoToObjLocked_ambiguous-freq_1 --n 1 --env BabyAI-GoToObjLocked_ambiguous-v0"
17
+ "--name GoToObjLocked_ambiguous-freq_2 --n 2 --env BabyAI-GoToObjLocked_ambiguous-v0"
18
+ "--name GoToObjLocked_ambiguous-freq_4 --n 4 --env BabyAI-GoToObjLocked_ambiguous-v0"
19
+ "--name GoToObjLocked_ambiguous --n 8 --env BabyAI-GoToObjLocked_ambiguous-v0"
20
+ "--name GoToObjLocked_ambiguous-freq_32 --n 32 --env BabyAI-GoToObjLocked_ambiguous-v0"
21
+
22
+ "--name GoToObjUnlocked-msg_4 --len-message 4 --num-symbols 4 --n 8 --env BabyAI-GoToObjUnlocked-v0"
23
+ "--name GoToObjUnlocked-msg_16 --len-message 16 --num-symbols 16 --n 8 --env BabyAI-GoToObjUnlocked-v0"
24
+ "--name GoToObjUnlocked-msg_32 --len-message 32 --num-symbols 32 --n 8 --env BabyAI-GoToObjUnlocked-v0"
25
+ "--name GoToObjLocked_ambiguous-msg_4 --len-message 4 --num-symbols 4 --n 8 --env BabyAI-GoToObjLocked_ambiguous-v0"
26
+ "--name GoToObjLocked_ambiguous-msg_16 --len-message 16 --num-symbols 16 --n 8 --env BabyAI-GoToObjLocked_ambiguous-v0"
27
+ "--name GoToObjLocked_ambiguous-msg_32 --len-message 32 --num-symbols 32 --n 8 --env BabyAI-GoToObjLocked_ambiguous-v0"
28
+ )
29
+
30
+ function get_model_path {
31
+ sr=$1
32
+ mod=$(ls models | grep ".*ppo_expert.*$sr" | sort | tail -n1)
33
+ echo -n $mod
34
+ }
35
+
36
+ for idx in $(seq 0 $((${#args_arr[@]} - 1))); do
37
+ cd repo
38
+ args=${args_arr[$idx]}
39
+ # Remove the leading --name arg which is not in the train_rl.py script.
40
+ train_args=$(echo $args | cut -d' ' -f3-)
41
+ name=$(echo $args | cut -d' ' -f2)
42
+
43
+ # Be careful about running this in parallel because the code does not use
44
+ # assign unique names to configurations, so get_model_path might get the
45
+ # wrong path if multiple instances of this are run in parallel.
46
+ eval python scripts/train_rl.py \
47
+ --seed 1 \
48
+ --frames 5e7 \
49
+ --tb \
50
+ $train_args
51
+
52
+ orig_sender=$(get_model_path sender)
53
+ orig_receiver=$(get_model_path receiver)
54
+ sender=$name-sender
55
+ receiver=$name-receiver
56
+ mv -n models/{$orig_sender,$sender}
57
+ mv -n models/{$orig_receiver,$receiver}
58
+
59
+ eval python ../helper.py \
60
+ --episodes 5000 \
61
+ --sender $sender \
62
+ --receiver $receiver \
63
+ $args
64
+ cd ..
65
+ done
data/babyai-sr/code/util.py ADDED
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