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.github/actions/collect_data/src/parsers/tt_torch_model_tests_parser.py
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# SPDX-FileCopyrightText: (c) 2024 Tenstorrent AI ULC | ||
# | ||
# SPDX-License-Identifier: Apache-2.0 | ||
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import tarfile | ||
import os | ||
import json | ||
from loguru import logger | ||
from functools import partial | ||
from datetime import datetime | ||
from pydantic_models import Test | ||
from .parser import Parser | ||
from . import junit_xml_utils | ||
from enum import Enum, IntEnum | ||
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class OpCompilationStatus(IntEnum): | ||
NOT_STARTED = 0 | ||
CREATED_GRAPH = 1 | ||
CONVERTED_TO_TORCH_IR = 2 | ||
CONVERTED_TO_TORCH_BACKEND_IR = 3 | ||
CONVERTED_TO_STABLE_HLO = 4 | ||
CONVERTED_TO_TTIR = 5 | ||
CONVERTED_TO_TTNN = 6 | ||
EXECUTED = 7 | ||
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class TTTorchModelTestsParser(Parser): | ||
"""Parser for python unitest report files.""" | ||
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def can_parse(self, filepath: str): | ||
basename = os.path.basename(filepath) | ||
return basename.startswith("run") and basename.endswith(".tar") | ||
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def parse(self, filepath: str): | ||
return get_tests(filepath) | ||
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def untar(filepath): | ||
basename = os.path.basename(filepath) | ||
path = f"/tmp/{basename}" | ||
with tarfile.open(filepath, "r") as fd: | ||
fd.extractall(path=path) | ||
return path | ||
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def all_json_files(filepath): | ||
for root, dirs, files in os.walk(filepath): | ||
for file in files: | ||
if file.endswith(".json"): | ||
yield os.path.join(root, file) | ||
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def get_tests_from_json(filepath): | ||
with open(filepath, "r") as fd: | ||
data = json.load(fd) | ||
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for name, test in data.items(): | ||
yield get_pydantic_test(filepath, name, test) | ||
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def get_pydantic_test(filepath, name, test, default_timestamp=datetime.now()): | ||
status = OpCompilationStatus(test["compilation_status"]) | ||
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skipped = False | ||
failed = status < OpCompilationStatus.EXECUTED | ||
error = False | ||
success = not (failed or error) | ||
error_message = str(status).split(".")[1] | ||
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properties = {} | ||
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test_start_ts = default_timestamp | ||
test_end_ts = default_timestamp | ||
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model_name = os.path.basename(filepath).split(".")[0] | ||
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# leaving empty for now | ||
group = None | ||
owner = None | ||
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full_test_name = f"{filepath}::{name}" | ||
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# to be populated with [] if available | ||
config = None | ||
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tags = None | ||
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return Test( | ||
test_start_ts=test_start_ts, | ||
test_end_ts=test_end_ts, | ||
test_case_name=name, | ||
filepath=filepath, | ||
category="models", | ||
group=None, | ||
owner=None, | ||
frontend="tt-torch", | ||
model_name=model_name, | ||
op_name=None, | ||
framework_op_name=test["torch_name"], | ||
op_kind=None, | ||
error_message=error_message, | ||
success=success, | ||
skipped=skipped, | ||
full_test_name=full_test_name, | ||
config=config, | ||
tags=tags, | ||
) | ||
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def flatten(list_of_lists): | ||
return [item for sublist in list_of_lists for item in sublist] | ||
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def get_tests(filepath): | ||
untar_path = untar(filepath) | ||
tests = map(get_tests_from_json, all_json_files(untar_path)) | ||
return flatten(tests) |
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