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# Copyright (c) 2021, NVIDIA CORPORATION. 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.
"""
This script runs model parallel text classification evaluation.
"""
import pytorch_lightning as pl
from omegaconf import DictConfig, OmegaConf
from nemo.collections.nlp.models.text_classification import TextClassificationModel
from nemo.collections.nlp.parts.nlp_overrides import NLPDDPStrategy
from nemo.core.config import hydra_runner
from nemo.utils import logging
from nemo.utils.exp_manager import exp_manager
@hydra_runner(config_path="conf", config_name="text_classification_config")
def main(cfg: DictConfig) -> None:
logging.info(f'\nConfig Params:\n{OmegaConf.to_yaml(cfg)}')
trainer = pl.Trainer(strategy=NLPDDPStrategy(), **cfg.trainer)
exp_manager(trainer, cfg.get("exp_manager", None))
# TODO: can we drop strict=False
model = TextClassificationModel.restore_from(cfg.model.nemo_path, trainer=trainer, strict=False)
model.setup_test_data(test_data_config=cfg.model.test_ds)
trainer.test(model=model, ckpt_path=None)
if __name__ == '__main__':
main()
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