# Copyright 2016 The TensorFlow Authors. All Rights Reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. # ============================================================================== """Library for getting system information during TensorFlow tests.""" from __future__ import absolute_import from __future__ import division from __future__ import print_function import os import re import shlex import subprocess import tempfile import time from tensorflow.core.util import test_log_pb2 from tensorflow.python.platform import gfile from tensorflow.tools.test import gpu_info_lib from tensorflow.tools.test import system_info_lib class MissingLogsError(Exception): pass def get_git_commit_sha(): """Get git commit SHA for this build. Attempt to get the SHA from environment variable GIT_COMMIT, which should be available on Jenkins build agents. Returns: SHA hash of the git commit used for the build, if available """ return os.getenv("GIT_COMMIT") def process_test_logs(name, test_name, test_args, benchmark_type, start_time, run_time, log_files): """Gather test information and put it in a TestResults proto. Args: name: Benchmark target identifier. test_name: A unique bazel target, e.g. "//path/to:test" test_args: A string containing all arguments to run the target with. benchmark_type: A string representing the BenchmarkType enum; the benchmark type for this target. start_time: Test starting time (epoch) run_time: Wall time that the test ran for log_files: Paths to the log files Returns: A TestResults proto """ results = test_log_pb2.TestResults() results.name = name results.target = test_name results.start_time = start_time results.run_time = run_time results.benchmark_type = test_log_pb2.TestResults.BenchmarkType.Value( benchmark_type.upper()) # Gather source code information git_sha = get_git_commit_sha() if git_sha: results.commit_id.hash = git_sha results.entries.CopyFrom(process_benchmarks(log_files)) results.run_configuration.argument.extend(test_args) results.machine_configuration.CopyFrom( system_info_lib.gather_machine_configuration()) return results def process_benchmarks(log_files): benchmarks = test_log_pb2.BenchmarkEntries() for f in log_files: content = gfile.GFile(f, "rb").read() if benchmarks.MergeFromString(content) != len(content): raise Exception("Failed parsing benchmark entry from %s" % f) return benchmarks def run_and_gather_logs(name, test_name, test_args, benchmark_type): """Run the bazel test given by test_name. Gather and return the logs. Args: name: Benchmark target identifier. test_name: A unique bazel target, e.g. "//path/to:test" test_args: A string containing all arguments to run the target with. benchmark_type: A string representing the BenchmarkType enum; the benchmark type for this target. Returns: A tuple (test_results, mangled_test_name), where test_results: A test_log_pb2.TestResults proto test_adjusted_name: Unique benchmark name that consists of benchmark name optionally followed by GPU type. Raises: ValueError: If the test_name is not a valid target. subprocess.CalledProcessError: If the target itself fails. IOError: If there are problems gathering test log output from the test. MissingLogsError: If we couldn't find benchmark logs. """ if not (test_name and test_name.startswith("//") and ".." not in test_name and not test_name.endswith(":") and not test_name.endswith(":all") and not test_name.endswith("...") and len(test_name.split(":")) == 2): raise ValueError("Expected test_name parameter with a unique test, e.g.: " "--test_name=//path/to:test") test_executable = test_name.rstrip().strip("/").replace(":", "/") if gfile.Exists(os.path.join("bazel-bin", test_executable)): # Running in standalone mode from core of the repository test_executable = os.path.join("bazel-bin", test_executable) else: # Hopefully running in sandboxed mode test_executable = os.path.join(".", test_executable) test_adjusted_name = name gpu_config = gpu_info_lib.gather_gpu_devices() if gpu_config: gpu_name = gpu_config[0].model gpu_short_name_match = re.search(r"Tesla (K40|K80|P100|V100)", gpu_name) if gpu_short_name_match: gpu_short_name = gpu_short_name_match.group(0) test_adjusted_name = name + "|" + gpu_short_name.replace(" ", "_") temp_directory = tempfile.mkdtemp(prefix="run_and_gather_logs") mangled_test_name = (test_adjusted_name.strip("/") .replace("|", "_").replace("/", "_").replace(":", "_")) test_file_prefix = os.path.join(temp_directory, mangled_test_name) test_file_prefix = "%s." % test_file_prefix try: if not gfile.Exists(test_executable): raise ValueError("Executable does not exist: %s" % test_executable) test_args = shlex.split(test_args) # This key is defined in tf/core/util/reporter.h as # TestReporter::kTestReporterEnv. os.environ["TEST_REPORT_FILE_PREFIX"] = test_file_prefix start_time = time.time() subprocess.check_call([test_executable] + test_args) run_time = time.time() - start_time log_files = gfile.Glob("{}*".format(test_file_prefix)) if not log_files: raise MissingLogsError("No log files found at %s." % test_file_prefix) return (process_test_logs( test_adjusted_name, test_name=test_name, test_args=test_args, benchmark_type=benchmark_type, start_time=int(start_time), run_time=run_time, log_files=log_files), test_adjusted_name) finally: try: gfile.DeleteRecursively(temp_directory) except OSError: pass