Introduce code from Rust monorepo. This is a mess

tts/NeMo/examples/nlp/text2sparql/evaluate_text2sparql.py

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+# Copyright (c) 2020, MeetKai Inc.  All rights reserved.
+# Copyright (c) 2020, 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 contains an example on how to evaluate a NeuralMachineTranslationModel.
+To load the example Text2Sparql dataset, please refer to ./data/import_datasets.py.
+To train a model, please refer to text2sparql.py.
+
+
+***Setting the configs***
+This script uses the `/examples/nlp/text2sparql/conf/text2sparql_config.yaml` config file by default.
+You may update the config file from the file directly or by using the command line arguments.
+Another other option is to set another config file via command line arguments by `--config-name=CONFIG_FILE_PATH'.
+
+Please refer to text2sparql.py for detailed instructions on setting the configuration.
+
+
+***How to run the script?***
+- To reload and evaluate the model, run:
+
+python evaluate_text2sparql.py \
+    model.test_ds.filepath="$TGT_DATA_DIR"/test_easy.tsv \
+    model.batch_size=16 \
+    model.nemo_path=./NeMo_logs/bart.nemo \
+    exp_manager.exp_dir=./NeMo_logs
+"""
+
+import os
+
+import pytorch_lightning as pl
+from omegaconf import DictConfig, OmegaConf
+
+from nemo.collections.nlp.models.neural_machine_translation import NeuralMachineTranslationModel
+from nemo.core.config import hydra_runner
+from nemo.utils import logging
+
+
+@hydra_runner(config_path="conf", config_name="text2sparql_config")
+def main(cfg: DictConfig) -> None:
+    logging.info(f"Config:\n {OmegaConf.to_yaml(cfg)}")
+    trainer = pl.Trainer(gpus=cfg.trainer.gpus)
+    nmt_model = NeuralMachineTranslationModel.restore_from(restore_path=cfg.model.nemo_path)
+    nmt_model.setup_test_data(cfg.model.test_ds)
+    results = trainer.test(nmt_model)
+
+    with open(cfg.model.test_ds.filepath, "r") as f:
+        lines = f.readlines()
+
+    lines[0] = lines[0].strip() + f"\tpredictions\n"
+    for i, res in enumerate(results[0]["texts"]):
+        lines[i + 1] = lines[i + 1].strip() + f"\t{res}\n"
+
+    savepath = os.path.join(cfg.exp_manager.exp_dir, os.path.basename(cfg.model.test_ds.filepath))
+    with open(savepath, "w") as f:
+        f.writelines(lines)
+        logging.info(f"Predictions saved to {savepath}")
+
+
+if __name__ == "__main__":
+    main()