Merge branch 'master' into webqs

lm_eval/tasks/triviaqa.py

 import os
 import json
 import random
-from lm_eval.base import Dataset, mean, rf
+from lm_eval.base import Task, mean, rf
 from ..utils import sh
 
-class TriviaQA(Dataset):
+class TriviaQA(Task):
     def download(self):
         if not os.path.exists('data/triviaqa'):
             sh("""
@@ -21,7 +21,7 @@ class TriviaQA(Dataset):
         return True
 
     def has_test_docs(self):
-        return True
+        return False
 
     def training_docs(self):
         return json.load(open('data/triviaqa/triviaqa-unfiltered/unfiltered-web-train.json'))['Data']
@@ -74,4 +74,4 @@ class TriviaQA(Dataset):
     def higher_is_better(self):
         return {
             "acc": True
-        }
+        }
\ No newline at end of file

lm_eval/tasks/wikitext.py

@@ -14,9 +14,11 @@ class WikiText103(NLP_TASK):
 
     def doc_to_text(self, doc):
         # TODO: implement
+        pass
 
     def doc_to_target(self, doc):
         # TODO: implement
+        pass
 
     def construct_requests(self, doc, ctx):
         """ Uses RequestFactory to construct Requests and returns an iterable of 
@@ -74,9 +76,11 @@ class WikiText2(NLP_TASK):
 
     def doc_to_text(self, doc):
         # TODO: implement
+        pass
 
     def doc_to_target(self, doc):
         # TODO: implement
+        pass
 
     def construct_requests(self, doc, ctx):
         """ Uses RequestFactory to construct Requests and returns an iterable of 
@@ -121,4 +125,4 @@ class WikiText2(NLP_TASK):
             whether a higher value of the submetric is better
         """
         # TODO: implement evaluation.
-        raise NotImplementedError('Evaluation not implemented')
+        raise NotImplementedError('Evaluation not implemented')
\ No newline at end of file

lm_eval/tasks/winogrande.py

@@ -90,4 +90,4 @@ class Winogrande(HFTask):
             whether a higher value of the submetric is better
         """
         # TODO: implement evaluation.
-        raise NotImplementedError('Evaluation not implemented')
+        raise NotImplementedError('Evaluation not implemented')
\ No newline at end of file

lm_eval/tasks/wsc273.py

 import json
 import random
 import os
-from lm_eval.base import Dataset
+from lm_eval.base import Task
 from ..utils import sh
 
 
-class WinogradSchemaChallenge273(Dataset):    
+class WinogradSchemaChallenge273(Task):    
     def __init__(self):
         super().__init__()
 

lm_eval/utils.py

@@ -28,4 +28,4 @@ def simple_parse_args_string(args_string):
 
 def join_iters(iters):
     for iter in iters:
-        yield from iter
+        yield from iter
\ No newline at end of file

lm_eval/utils_stream.py

@@ -5,11 +5,13 @@ from tqdm import tqdm
 import json
 
 
-class ExitCodeError(Exception): pass
+class ExitCodeError(Exception):
+    pass
 
 
 def sh(x):
-    if os.system(x): raise ExitCodeError()
+    if os.system(x):
+        raise ExitCodeError()
 
 def ls(x):
     return [x + '/' + fn for fn in os.listdir(x)]
@@ -64,7 +66,8 @@ class join:
         self.sep = sep
 
     def __rrshift__(self, other):
-        if other is None: return
+        if other is None:
+            return
         try:
             return self.sep.join(other)
         except:
@@ -156,4 +159,4 @@ def comp(*fs):
     return _f
 
 
-X = Reflective()
+X = Reflective()
\ No newline at end of file

setup.py

+import setuptools
+
+with open("README.md", "r", encoding="utf-8") as fh:
+    long_description = fh.read()
+
+setuptools.setup(
+    name="lm_eval_harness",
+    version="0.0.1",
+    author="Leo Gao",
+    author_email="lg@eleuther.ai",
+    description="A framework for evaluating autoregressive language models",
+    long_description=long_description,
+    long_description_content_type="text/markdown",
+    url="https://github.com/EleutherAI/lm-evaluation-harness",
+    packages=setuptools.find_packages(),
+    classifiers=[
+        "Programming Language :: Python :: 3",
+        "License :: OSI Approved :: MIT License",
+        "Operating System :: OS Independent",
+    ],
+    python_requires='>=3.6',
+)

tests/test_all_sanitycheck.py

+import lm_eval.tasks as tasks
+import lm_eval.base as base
+from unittest.mock import MagicMock
+from itertools import islice
+import pytest
+
+
+@pytest.mark.parametrize("taskname,Task", tasks.TASK_REGISTRY.items())
+def test_basic_interface(taskname, Task):
+    print('Evaluating task', taskname)
+    dl = Task.download
+    Task.download = MagicMock()
+    task = Task()
+    Task.download = dl
+
+    assert task.has_training_docs() in [True, False]
+    assert task.has_validation_docs() in [True, False]
+    assert task.has_test_docs() in [True, False]
+
+    assert isinstance(task.aggregation(), dict)
+    assert isinstance(task.higher_is_better(), dict)
+    assert task.aggregation().keys() == task.higher_is_better().keys()
+
+    for v in task.higher_is_better().values(): assert v in [True, False]
+
+
+@pytest.mark.parametrize("taskname,Task", tasks.TASK_REGISTRY.items())
+def test_documents_and_requests(taskname, Task):
+    print('Evaluating task', taskname)
+    task = Task()
+    fns = []
+    if task.has_training_docs(): fns.append(task.training_docs)
+    if task.has_validation_docs(): fns.append(task.validation_docs)
+    # test doce might not have labels
+    #if task.has_test_docs(): fns.append(task.test_docs)
+
+    for fn in fns:
+        #print(list(islice(fn(), 10)))
+        for doc in islice(fn(), 10):
+            
+            txt = task.doc_to_text(doc)
+            tgt = task.doc_to_target(doc)
+
+            assert isinstance(txt, str)
+            assert isinstance(tgt, str)
+
+            reqs = task.construct_requests(doc, txt)
+
+            # todo: mock lm by pluggin what's currently in main.py in here
+            for req in reqs:
+                assert isinstance(req, base.Request)
\ No newline at end of file