diff --git a/ERNIE/.run_ce.sh b/ERNIE/.run_ce.sh new file mode 100644 index 0000000000000000000000000000000000000000..b139a818b5664c2e3f944953e4c658bcde2a2c69 --- /dev/null +++ b/ERNIE/.run_ce.sh @@ -0,0 +1,43 @@ +set -eux + +export FLAGS_sync_nccl_allreduce=1 +MODEL_PATH=ERNIE_1.0.1 +TASK_DATA_PATH=task_data + +train() { +python -u run_classifier.py \ + --use_cuda true \ + --do_train true \ + --do_val true \ + --do_test true \ + --verbose true \ + --batch_size 8192 \ + --in_tokens true \ + --init_pretraining_params ${MODEL_PATH}/params \ + --train_set ${TASK_DATA_PATH}/xnli/train.tsv \ + --dev_set ${TASK_DATA_PATH}/xnli/dev.tsv \ + --test_set ${TASK_DATA_PATH}/xnli/test.tsv \ + --vocab_path config/vocab.txt \ + --label_map ${TASK_DATA_PATH}/xnli/label_map.json \ + --ernie_config_path config/ernie_config.json \ + --checkpoints ./checkpoints \ + --save_steps 2000 \ + --weight_decay 0.01 \ + --warmup_proportion 0.0 \ + --validation_steps 25 \ + --epoch 1 \ + --max_seq_len 512 \ + --learning_rate 1e-4 \ + --skip_steps 10 \ + --num_iteration_per_drop_scope 1 \ + --num_labels 3 \ + --random_seed 100 \ + --enable_ce \ + --shuffle false +} + +export CUDA_VISIBLE_DEVICES=0 +train | python _ce.py + +export CUDA_VISIBLE_DEVICES=0,1,2,3 +train | python _ce.py diff --git a/ERNIE/__init__.py b/ERNIE/__init__.py new file mode 100644 index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391 diff --git a/ERNIE/_ce.py b/ERNIE/_ce.py new file mode 100644 index 0000000000000000000000000000000000000000..97089c3b11724d7c748808e02665342a61866a96 --- /dev/null +++ b/ERNIE/_ce.py @@ -0,0 +1,67 @@ +####this file is only used for continuous evaluation test! + +import os +import sys +sys.path.insert(0, os.environ['ceroot']) +from kpi import CostKpi, DurationKpi, AccKpi + +#### NOTE kpi.py should shared in models in some way!!!! + +train_loss_card1_kpi = CostKpi('train_loss_card1', 0.03, 0, actived=True) +train_acc_card1_kpi = AccKpi('train_acc_card1', 0.06, 0, actived=True) +train_duration_card1_kpi = DurationKpi( + 'train_duration_card1', 0.01, 0, actived=True) +train_loss_card4_kpi = CostKpi('train_loss_card4', 0.01, 0, actived=True) +train_acc_card4_kpi = AccKpi('train_acc_card4', 0.02, 0, actived=True) +train_duration_card4_kpi = DurationKpi( + 'train_duration_card4', 0.02, 0, actived=True) + +tracking_kpis = [ + train_loss_card1_kpi, + train_acc_card1_kpi, + train_duration_card1_kpi, + train_loss_card4_kpi, + train_acc_card4_kpi, + train_duration_card4_kpi, +] + + +def parse_log(log): + ''' + This method should be implemented by model developers. + The suggestion: + each line in the log should be key, value, for example: + " + train_loss\t1.0 + test_loss\t1.0 + train_loss\t1.0 + train_acc\t1.2 + " + ''' + for line in log.split('\n'): + fs = line.strip().split('\t') + print(fs) + if len(fs) == 3 and fs[0] == 'kpis': + print("-----%s" % fs) + kpi_name = fs[1] + kpi_value = float(fs[2]) + yield kpi_name, kpi_value + + +def log_to_ce(log): + kpi_tracker = {} + for kpi in tracking_kpis: + kpi_tracker[kpi.name] = kpi + + for (kpi_name, kpi_value) in parse_log(log): + print(kpi_name, kpi_value) + kpi_tracker[kpi_name].add_record(kpi_value) + kpi_tracker[kpi_name].persist() + + +if __name__ == '__main__': + log = sys.stdin.read() + print("*****") + print(log) + print("****") + log_to_ce(log) diff --git a/ERNIE/finetune_args.py b/ERNIE/finetune_args.py index f25e5ab0cc0d76d18838437423aed8499d605e18..0a19a1aafa4148f3302ca28cb8ba839b3ba0882b 100644 --- a/ERNIE/finetune_args.py +++ b/ERNIE/finetune_args.py @@ -74,4 +74,7 @@ run_type_g.add_arg("do_train", bool, True, "Whether to pe run_type_g.add_arg("do_val", bool, True, "Whether to perform evaluation on dev data set.") run_type_g.add_arg("do_test", bool, True, "Whether to perform evaluation on test data set.") run_type_g.add_arg("metrics", bool, True, "Whether to perform evaluation on test data set.") +run_type_g.add_arg("shuffle", bool, True, "") + +parser.add_argument("--enable_ce", action='store_true', help="The flag indicating whether to run the task for continuous evaluation.") # yapf: enable diff --git a/ERNIE/run_classifier.py b/ERNIE/run_classifier.py index 61fda8f7d48421da90a7f499ad1e72bc2cc792b7..fbc9fdb12d9486e162c52b05a675c9b979b5ca7b 100644 --- a/ERNIE/run_classifier.py +++ b/ERNIE/run_classifier.py @@ -29,6 +29,7 @@ from finetune.classifier import create_model, evaluate from optimization import optimization from utils.args import print_arguments, check_cuda from utils.init import init_pretraining_params, init_checkpoint +from utils.cards import get_cards from finetune_args import parser args = parser.parse_args() @@ -67,7 +68,7 @@ def main(args): input_file=args.train_set, batch_size=args.batch_size, epoch=args.epoch, - shuffle=True, + shuffle=args.shuffle, phase="train") num_train_examples = reader.get_num_examples(args.train_set) @@ -85,6 +86,8 @@ def main(args): print("Num warmup steps: %d" % warmup_steps) train_program = fluid.Program() + if args.random_seed is not None and args.enable_ce: + train_program.random_seed = args.random_seed with fluid.program_guard(train_program, startup_prog): with fluid.unique_name.guard(): @@ -187,6 +190,7 @@ def main(args): if warmup_steps > 0: graph_vars["learning_rate"] = scheduled_lr + ce_info = [] time_begin = time.time() while True: try: @@ -213,6 +217,7 @@ def main(args): (current_epoch, current_example, num_train_examples, steps, outputs["loss"], outputs["accuracy"], args.skip_steps / used_time)) + ce_info.append([outputs["loss"], outputs["accuracy"], used_time]) time_begin = time.time() if steps % args.save_steps == 0: @@ -246,6 +251,24 @@ def main(args): fluid.io.save_persistables(exe, save_path, train_program) train_pyreader.reset() break + if args.enable_ce: + card_num = get_cards() + ce_loss = 0 + ce_acc = 0 + ce_time = 0 + try: + ce_loss = ce_info[-2][0] + ce_acc = ce_info[-2][1] + ce_time = ce_info[-2][2] + except: + print("ce info error") + print("kpis\ttrain_duration_card%s\t%s" % + (card_num, ce_time)) + print("kpis\ttrain_loss_card%s\t%f" % + (card_num, ce_loss)) + print("kpis\ttrain_acc_card%s\t%f" % + (card_num, ce_acc)) + # final eval on dev set if args.do_val: diff --git a/ERNIE/utils/cards.py b/ERNIE/utils/cards.py new file mode 100644 index 0000000000000000000000000000000000000000..9ba9aa6d2ee81eebfc8c02bdef5d50dff7d96f6e --- /dev/null +++ b/ERNIE/utils/cards.py @@ -0,0 +1,28 @@ +# Copyright (c) 2019 PaddlePaddle 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. + + +import os + +def get_cards(): + """ + get gpu cards number + """ + num = 0 + cards = os.environ.get('CUDA_VISIBLE_DEVICES', '') + if cards != '': + num = len(cards.split(",")) + return num + +