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constants.py
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constants.py
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# Copyright 2019 MLBenchmark Group. 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.
# ==============================================================================
"""Master list of constants in MLPerf log
"""
# NOTE: Keep string values in alphabetical order under each section.
# Constant values - log settings
DEFAULT_LOGGER_NAME = "mllog_default"
DEFAULT_NAMESPACE = ""
# Constant values - log event type
INTERVAL_END = "INTERVAL_END"
INTERVAL_START = "INTERVAL_START"
POINT_IN_TIME = "POINT_IN_TIME"
# Constant values - submission division
CLOSED = "closed"
OPEN = "open"
# Constant values - submission status
ONPREM = "onprem"
CLOUD = "cloud"
RESEARCH = "research"
# Constant values - benchmark name
GNMT = "gnmt"
MASKRCNN = "maskrcnn"
MINIGO = "minigo"
NCF = "ncf"
RESNET = "resnet"
SSD = "ssd"
TRANSFORMER = "transformer"
RNNT = "rnnt"
UNET3D = "unet3d"
BERT ="bert"
# Constant values - model info
ADAM = "adam"
LARS = "lars"
LAZY_ADAM = "lazy_adam"
SGD = "sgd"
LAMB ="lamb"
# Constant values - metadata info
ABORTED = "aborted"
SUCCESS = "success"
# Log keys - submission info
SUBMISSION_BENCHMARK = "submission_benchmark"
SUBMISSION_DIVISION = "submission_division"
SUBMISSION_ENTRY = "submission_entry"
SUBMISSION_ORG = "submission_org"
SUBMISSION_PLATFORM = "submission_platform"
SUBMISSION_POC_NAME = "submission_poc_name"
SUBMISSION_POC_EMAIL = "submission_poc_email"
SUBMISSION_STATUS = "submission_status"
# Log keys - timing info
BLOCK_START = "block_start"
BLOCK_STOP = "block_stop"
EPOCH_START = "epoch_start"
EPOCH_STOP = "epoch_stop"
EVAL_START = "eval_start"
EVAL_STOP = "eval_stop"
INIT_START = "init_start"
INIT_STOP = "init_stop"
STAGING_START = "staging_start"
STAGING_STOP = "staging_stop"
RUN_START = "run_start"
RUN_STOP = "run_stop"
# Log keys - common run info
CACHE_CLEAR = "cache_clear"
EVAL_ACCURACY = "eval_accuracy"
EVAL_SAMPLES = "eval_samples"
SEED = "seed"
TRAIN_SAMPLES = "train_samples"
WEIGHTS_INITIALIZATION = "weights_initialization"
# Log kyes - model hyperparameters
GLOBAL_BATCH_SIZE = "global_batch_size"
GRADIENT_ACCUMULATION_STEPS = "gradient_accumulation_steps"
LARS_EPSILON = "lars_epsilon"
LARS_OPT_END_LR = "lars_opt_end_learning_rate"
LARS_OPT_LR_DECAY_POLY_POWER = "lars_opt_learning_rate_decay_poly_power"
LARS_OPT_LR_DECAY_STEPS = "lars_opt_learning_rate_decay_steps"
LARS_OPT_WEIGHT_DECAY = "lars_opt_weight_decay"
MAX_IMAGE_SIZE = "max_image_size"
MAX_SAMPLES = "max_samples"
MAX_SEQUENCE_LENGTH = "max_sequence_length"
MIN_IMAGE_SIZE = "min_image_size"
MODEL_BN_SPAN = "model_bn_span"
NUM_IMAGE_CANDIDATES = "num_image_candidates"
NUM_WARMUP_STEPS = "num_warmup_steps"
OPT_ADAM_BETA_1 = "opt_adam_beta_1"
OPT_ADAM_BETA_2 = "opt_adam_beta_2"
OPT_ADAM_EPSILON = "opt_adam_epsilon"
OPT_NAME = "opt_name"
OPT_BASE_LR = "opt_base_learning_rate"
OPT_LAMB_LR_MIN = "opt_lamb_learning_rate_min"
OPT_LAMB_LR_DECAY_POLY_POWER = "opt_lamb_learning_rate_decay_poly_power"
OPT_LAMB_WEIGHT_DECAY = "opt_lamb_weight_decay_rate"
OPT_LAMB_BETA_1 = "opt_lamb_beta_1"
OPT_LAMB_BETA_2 = "opt_lamb_beta_2"
OPT_LAMB_EPSILON = "opt_lamb_epsilon"
OPT_LAMB_LR_HOLD_EPOCHS = "opt_lamb_learning_rate_hold_epochs"
OPT_LR_ALT_DECAY_FUNC = "opt_learning_rate_alt_decay_func"
OPT_LR_ALT_WARMUP_FUNC = "opt_learning_rate_alt_warmup_func"
OPT_LR_DECAY_BOUNDARY_EPOCHS = "opt_learning_rate_decay_boundary_epochs"
OPT_LR_DECAY_BOUNDARY_STEPS = "opt_learning_rate_decay_boundary_steps"
OPT_LR_DECAY_FACTOR = "opt_learning_rate_decay_factor"
OPT_LR_DECAY_INTERVAL = "opt_learning_rate_decay_interval"
OPT_LR_DECAY_START_STEP = "opt_learning_rate_decay_start_step"
OPT_LR_DECAY_STEPS = "opt_learning_rate_decay_steps"
OPT_LR_REMAIN_STEPS = "opt_learning_rate_remain_steps"
OPT_LR_TRAINING_STEPS = "opt_learning_rate_training_steps"
OPT_LR_WARMUP_EPOCHS = "opt_learning_rate_warmup_epochs"
OPT_LR_WARMUP_FACTOR = "opt_learning_rate_warmup_factor"
OPT_LR_WARMUP_STEPS = "opt_learning_rate_warmup_steps"
OPT_WEIGHT_DECAY = "opt_weight_decay"
OPT_GRADIENT_CLIP_NORM = "opt_gradient_clip_norm"
DATA_SPEED_PERTURBATON_MAX = "data_speed_perturbaton_max"
DATA_SPEED_PERTURBATON_MIN = "data_speed_perturbaton_min"
DATA_SPEC_AUGMENT_FREQ_N = "data_spec_augment_freq_n"
DATA_SPEC_AUGMENT_FREQ_MIN = "data_spec_augment_freq_min"
DATA_SPEC_AUGMENT_FREQ_MAX = "data_spec_augment_freq_max"
DATA_SPEC_AUGMENT_TIME_N = "data_spec_augment_time_n"
DATA_SPEC_AUGMENT_TIME_MIN = "data_spec_augment_time_min"
DATA_SPEC_AUGMENT_TIME_MAX = "data_spec_augment_time_max"
DATA_TRAIN_NUM_BUCKETS = "data_train_num_buckets"
DATA_TRAIN_MAX_DURATION = "data_train_max_duration"
DATA_NUM_BUCKETS = "data_num_buckets"
MODEL_EVAL_EMA_FACTOR = "model_eval_ema_factor"
MODEL_WEIGHTS_INITIALIZATION_SCALE = "model_weights_initialization_scale"
EVAL_MAX_PREDICTION_SYMBOLS = "eval_max_prediction_symbols"
START_WARMUP_STEP ="start_warmup_step"
# Log keys - misc.
BBOX = "bbox"
SEGM = "segm"
# Log metadata keys
EPOCH_COUNT = "epoch_count"
EPOCH_NUM = "epoch_num"
FIRST_EPOCH_NUM = "first_epoch_num"
STATUS = "status"