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Integrating custom metrics and inference parameters (#82)
Signed-off-by: Gerald Shen <geshen@nvidia.com> Signed-off-by: Igor Gitman <igitman@nvidia.com> Co-authored-by: Gerald Shen <geshen@nvidia.com> Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com> Co-authored-by: Olivier Delalleau <507137+odelalleau@users.noreply.github.com> Co-authored-by: Gerald Shen <119401249+gshennvm@users.noreply.github.com>
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| # Copyright (c) 2023, 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. | ||
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| # importing all available metrics here to make it easier to import from the config | ||
| from nemo_aligner.metrics.common import InferenceMetricsHandler |
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| # Copyright (c) 2023, 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. | ||
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| # A couple of common metrics as well as a handler class to provide a unified interface. | ||
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| from typing import Dict, Optional | ||
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| import hydra | ||
| from omegaconf import DictConfig | ||
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| class InferenceMetricsHandler: | ||
| """A wrapper around metrics objects that will call update/compute/reset on all registered metrics. | ||
| If metrics_config is None, then all methods become no-ops and compute will return an empty dict. | ||
| """ | ||
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| def __init__(self, metrics_config: Optional[DictConfig]): | ||
| if metrics_config is None: | ||
| metrics_config = {} | ||
| self.metrics = hydra.utils.instantiate(metrics_config) | ||
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| def has_metrics(self) -> bool: | ||
| """Returns True if there are metrics to compute.""" | ||
| return len(self.metrics) > 0 | ||
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| def update(self, batch: Dict, generation_output: Dict): | ||
| """Calling .update on all metrics. | ||
| Batch and generation output are coming directly from | ||
| validation dataloader and model.generate respectively. | ||
| """ | ||
| for metric in self.metrics.values(): | ||
| metric.update(batch, generation_output) | ||
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| def compute(self) -> Dict[str, float]: | ||
| """Returns a dictionary with finalized metric values.""" | ||
| return {name: metric.compute() for name, metric in self.metrics.items()} | ||
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| def reset(self): | ||
| """Will reset state of all metrics to prepare for the next validation run.""" | ||
| for metric in self.metrics.values(): | ||
| metric.reset() |
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