update

.github/workflows/update_test_file_ratings.yml

@@ -5,6 +5,9 @@ on:
     paths:
       - ".github/workflows/update_test_file_ratings.yml"
       - "torchci/scripts/calculate_file_test_rating.py"
+      - "torchci/scripts/test_calculate_file_test_rating.py"
+      - "torchci/scripts/td_heuristic_historical_edited_files.py"
+      - "torchci/scripts/td_heuristic_profiling.py"
       - "torchci/scripts/get_merge_base_info.py"
   schedule:
     - cron: 5 11 * * *  # At 11:05 UTC every day or about 4am PT
@@ -46,6 +49,10 @@ jobs:
       - name: Generate file test ratings
         run: |
           python3 test-infra/torchci/scripts/calculate_file_test_rating.py
+          python3 test-infra/torchci/scripts/td_heuristic_historical_edited_files.py
+          # Do not run this one, it won't change
+          # python3 test-infra/torchci/scripts/td_heuristic_profiling.py
+
         env:
           ROCKSET_API_KEY: ${{ secrets.ROCKSET_API_KEY }}
 
@@ -76,3 +83,17 @@ jobs:
           user_email: "[email protected]"
           user_name: "Pytorch Test Infra"
           commit_message: "Updating file to test class correlations"
+
+      - name: Push historical edited files heuristic to test-infra repository
+        if: github.event_name != 'pull_request'
+        uses: dmnemec/copy_file_to_another_repo_action@eebb594efdf52bc12e1b461988d7254322dac131
+        env:
+          API_TOKEN_GITHUB: ${{ secrets.GITHUB_TOKEN }}
+        with:
+          source_file: "td_heuristic_historical_edited_files.json"
+          destination_repo: "pytorch/test-infra"
+          destination_folder: "stats"
+          destination_branch: generated-stats
+          user_email: "[email protected]"
+          user_name: "Pytorch Test Infra"
+          commit_message: "Updating TD heuristic: historical edited files"

.gitignore

@@ -125,3 +125,6 @@ docs/_build/
 
 # Pyenv
 .python-version
+
+# torchci caching utils
+.torchci_python_utils_cache

torchci/scripts/get_merge_base_info.py

@@ -1,9 +1,15 @@
 import subprocess
 from datetime import datetime
-from multiprocessing import Pool
 from pathlib import Path
 from typing import List
 
+from pathlib import Path
+
+from utils_td_heuristics import (
+    list_past_year_shas,
+    run_command,
+)
+
 from rockset_utils import query_rockset, remove_from_rockset, upload_to_rockset
 
 REPO_ROOT = Path(__file__).resolve().parent.parent.parent
@@ -19,6 +25,16 @@
     mb.merge_base is null
 """
 
+NOT_IN_MERGE_BASES_TABLE = """
+select
+    shas.sha as head_sha
+from
+    unnest(SPLIT(:shas, ',') as sha) as shas
+    left outer join commons.merge_bases mb on mb.sha = shas.sha
+where
+    mb.sha is null
+    or mb.repo is null
+"""
 
 DUP_MERGE_BASE_INFO = """
 select
@@ -99,18 +115,20 @@ def upload_merge_base_info(shas: List[str]) -> None:
     print(
         f"There are {len(failed_test_shas)} shas, uploading in intervals of {interval}"
     )
-    pool = Pool(20)
-    errors = []
     for i in range(0, len(failed_test_shas), interval):
         pull_shas(failed_test_shas[i : i + interval])
-        errors.append(
-            pool.apply_async(
-                upload_merge_base_info, args=(failed_test_shas[i : i + interval],)
+        upload_merge_base_info(failed_test_shas[i : i + interval])
+
+    interval = 500
+    main_branch_shas = list_past_year_shas()
+    print(f"There are {len(main_branch_shas)} shas, uploading in batches of {interval}")
+    for i in range(0, len(main_branch_shas), interval):
+        shas = [
+            x["head_sha"]
+            for x in query_rockset(
+                NOT_IN_MERGE_BASES_TABLE,
+                {"shas": ",".join(main_branch_shas[i : i + interval])},
             )
-        )
-    print("done pulling")
-    pool.close()
-    pool.join()
-    for i in errors:
-        if i.get() is not None:
-            print(i.get())
+        ]
+        upload_merge_base_info(shas)
+        print(f"{i} to {i + interval} done")

torchci/scripts/rockset_utils.py

@@ -2,7 +2,9 @@
 import os
 from typing import Any, Dict, List, Optional
 
-import rockset  # type: ignore[import]
+import rockset
+
+from utils import cache_json  # type: ignore[import]
 
 
 @lru_cache
@@ -13,16 +15,16 @@ def get_rockset_client():
 
 
 def query_rockset(
-    query: str, params: Optional[Dict[str, Any]] = None
+    query: str, params: Optional[Dict[str, Any]] = None, use_cache: bool = False
 ) -> List[Dict[str, Any]]:
-    res: List[Dict[str, Any]] = (
-        rockset.RocksetClient(
-            host="api.rs2.usw2.rockset.com", api_key=os.environ["ROCKSET_API_KEY"]
-        )
-        .sql(query, params=params)
-        .results
-    )
-    return res
+    if not use_cache:
+        return get_rockset_client().sql(query, params=params).results
+
+    @cache_json
+    def cache_query_rockset(query, params):
+        return get_rockset_client().sql(query, params=params).results
+
+    return cache_query_rockset(query, params)
 
 
 def upload_to_rockset(

torchci/scripts/td_heuristic_historical_edited_files.py

@@ -0,0 +1,61 @@
+import json
+from collections import defaultdict
+from typing import Dict
+
+from utils_td_heuristics import (
+    cache_json,
+    evaluate,
+    get_all_invoking_files,
+    get_filtered_failed_tests,
+    get_merge_bases_dict,
+    list_past_year_shas,
+    query_rockset,
+)
+
+CHANGED_FILES_QUERY = """
+select
+    sha,
+    changed_files
+from
+    commons.merge_bases
+where
+    ARRAY_CONTAINS(SPLIT(:shas, ','), sha)
+"""
+
+
+@cache_json
+def gen_correlation_dict() -> Dict[str, Dict[str, float]]:
+    shas = list_past_year_shas()
+
+    interval = 500
+    commits = []
+    for i in range(0, len(shas), interval):
+        commits.extend(
+            query_rockset(
+                CHANGED_FILES_QUERY,
+                params={"shas": ",".join(shas[i : i + interval])},
+                use_cache=True,
+            )
+        )
+
+    invoking_files = get_all_invoking_files()
+
+    d = defaultdict(lambda: defaultdict(float))
+    for commit in commits:
+        changed_files = commit["changed_files"]
+        test_files = [x[5:-3] for x in changed_files if x[5:-3] in invoking_files]
+        for test_file in test_files:
+            for file in changed_files:
+                d[file][test_file] += 1 / len(changed_files)
+    return d
+
+
+if __name__ == "__main__":
+    correlation_dict = gen_correlation_dict()
+    merge_bases = get_merge_bases_dict()
+    filtered_tests = get_filtered_failed_tests()
+
+    evaluate(filtered_tests, merge_bases, correlation_dict)
+
+    with open("td_heuristic_historical_edited_files.json", mode="w") as file:
+        json.dump(correlation_dict, file, sort_keys=True, indent=2)

torchci/scripts/td_heuristic_profiling.py

@@ -0,0 +1,26 @@
+import json
+
+import requests
+from utils_td_heuristics import evaluate, get_filtered_failed_tests, get_merge_bases_dict
+
+
+def get_profiling_dict():
+    # The dict should be generated elsewhere and this function modified to
+    # retrieve the data.
+    url = "https://raw.githubusercontent.com/pytorch/test-infra/generated-stats/stats/td_heuristic_profiling.json"
+    return json.loads(requests.get(url).text)
+
+
+def main() -> None:
+    correlation_dict = get_profiling_dict()
+    merge_bases = get_merge_bases_dict()
+    filtered_tests = get_filtered_failed_tests()
+
+    evaluate(filtered_tests, merge_bases, correlation_dict)
+
+    with open("td_heuristic_profiling.json", mode="w") as file:
+        json.dump(correlation_dict, file, sort_keys=True, indent=2)
+
+
+if __name__ == "__main__":
+    main()

torchci/scripts/utils.py

@@ -0,0 +1,68 @@
+import datetime
+from hashlib import sha256
+import json
+import os
+import pathlib
+import subprocess
+from typing import List, Union
+
+
+FILE_CACHE_LIFESPAN_SECONDS = 60 * 60 * 24  # 1 day
+REPO_ROOT = pathlib.Path(__file__).parent.parent.parent
+CACHE_FOLDER = REPO_ROOT / ".torchci_python_utils_cache"
+
+
+def js_beautify(obj):
+    # Like json.dumps with indent=2, but only at the first level.  Nice for
+    # dictionaries of str -> really long list
+    import jsbeautifier
+
+    opts = jsbeautifier.default_options()
+    opts.indent_size = 2
+    return jsbeautifier.beautify(json.dumps(obj), opts)
+
+
+def run_command(command: Union[str, List[str]]) -> str:
+    # Runs command in pytorch folder.  Assumes test-infra and pytorch are in the
+    # same folder.
+    if isinstance(command, str):
+        command = command.split(" ")
+    cwd = REPO_ROOT / ".." / "pytorch"
+    return (
+        subprocess.check_output(
+            command,
+            cwd=cwd,
+        )
+        .decode("utf-8")
+        .strip()
+    )
+
+
+def cache_json(func):
+    # Requires that both input and output but json serializable.
+    # Decorator for caching function results into a file so it can be reused betwen runs.
+    os.makedirs(CACHE_FOLDER, exist_ok=True)
+
+    def wrapper(*args, **kwargs):
+        os.makedirs(CACHE_FOLDER, exist_ok=True)
+        args_key = sha256(json.dumps(args).encode("utf-8")).hexdigest()
+        kwargs_key = sha256(
+            json.dumps(kwargs, sort_keys=True).encode("utf-8")
+        ).hexdigest()
+        file_name = f"{func.__name__} args={args_key} kwargs={kwargs_key}.json"
+
+        if os.path.exists(CACHE_FOLDER / file_name):
+            now = datetime.datetime.now()
+            mtime = datetime.datetime.fromtimestamp(
+                (CACHE_FOLDER / file_name).stat().st_mtime
+            )
+            diff = now - mtime
+            if diff.total_seconds() < FILE_CACHE_LIFESPAN_SECONDS:
+                return json.load(open(CACHE_FOLDER / file_name))
+
+        res = func(*args, **kwargs)
+        with open(CACHE_FOLDER / file_name, "w") as f:
+            f.write(json.dumps(res))
+        return res
+
+    return wrapper