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# Copyright 2023 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.
"""Flags for benchmarking models."""
from absl import flags
from official.utils.flags._conventions import help_wrap
def define_log_steps():
flags.DEFINE_integer(
name="log_steps",
default=100,
help="Frequency with which to log timing information with TimeHistory.")
return []
def define_benchmark(benchmark_log_dir=True, bigquery_uploader=True):
"""Register benchmarking flags.
Args:
benchmark_log_dir: Create a flag to specify location for benchmark logging.
bigquery_uploader: Create flags for uploading results to BigQuery.
Returns:
A list of flags for core.py to marks as key flags.
"""
key_flags = []
flags.DEFINE_enum(
name="benchmark_logger_type",
default="BaseBenchmarkLogger",
enum_values=["BaseBenchmarkLogger", "BenchmarkFileLogger"],
help=help_wrap("The type of benchmark logger to use. Defaults to using "
"BaseBenchmarkLogger which logs to STDOUT. Different "
"loggers will require other flags to be able to work."))
flags.DEFINE_string(
name="benchmark_test_id",
short_name="bti",
default=None,
help=help_wrap("The unique test ID of the benchmark run. It could be the "
"combination of key parameters. It is hardware "
"independent and could be used compare the performance "
"between different test runs. This flag is designed for "
"human consumption, and does not have any impact within "
"the system."))
define_log_steps()
if benchmark_log_dir:
flags.DEFINE_string(
name="benchmark_log_dir",
short_name="bld",
default=None,
help=help_wrap("The location of the benchmark logging."))
if bigquery_uploader:
flags.DEFINE_string(
name="gcp_project",
short_name="gp",
default=None,
help=help_wrap(
"The GCP project name where the benchmark will be uploaded."))
flags.DEFINE_string(
name="bigquery_data_set",
short_name="bds",
default="test_benchmark",
help=help_wrap(
"The Bigquery dataset name where the benchmark will be uploaded."))
flags.DEFINE_string(
name="bigquery_run_table",
short_name="brt",
default="benchmark_run",
help=help_wrap("The Bigquery table name where the benchmark run "
"information will be uploaded."))
flags.DEFINE_string(
name="bigquery_run_status_table",
short_name="brst",
default="benchmark_run_status",
help=help_wrap("The Bigquery table name where the benchmark run "
"status information will be uploaded."))
flags.DEFINE_string(
name="bigquery_metric_table",
short_name="bmt",
default="benchmark_metric",
help=help_wrap("The Bigquery table name where the benchmark metric "
"information will be uploaded."))
@flags.multi_flags_validator(
["benchmark_logger_type", "benchmark_log_dir"],
message="--benchmark_logger_type=BenchmarkFileLogger will require "
"--benchmark_log_dir being set")
def _check_benchmark_log_dir(flags_dict):
benchmark_logger_type = flags_dict["benchmark_logger_type"]
if benchmark_logger_type == "BenchmarkFileLogger":
return flags_dict["benchmark_log_dir"]
return True
return key_flags
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