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60 lines
1.9 KiB
Python
60 lines
1.9 KiB
Python
# Copyright (c) 2025, NVIDIA CORPORATION. All rights reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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import copy
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from contextlib import contextmanager
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import librosa
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import torch
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from nemo.collections.asr.models import ASRModel
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@contextmanager
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def preserve_decoding_cfg_and_cpu_device(model: ASRModel):
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"""
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Context manager to preserve the decoding strategy and device of the model.
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This is useful for tests that modify the model's decoding strategy or device
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to avoid side effects or costly model reloading.
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"""
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backup_decoding_cfg = copy.deepcopy(model.cfg.decoding)
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try:
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yield
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finally:
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model.to(device="cpu")
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if model.cfg.decoding != backup_decoding_cfg:
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model.change_decoding_strategy(backup_decoding_cfg)
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def load_audio(file_path, target_sr=16000) -> tuple[torch.Tensor, int]:
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audio, sr = librosa.load(file_path, sr=target_sr)
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return torch.tensor(audio, dtype=torch.float32), sr
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@contextmanager
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def avoid_sync_operations(device: torch.device):
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try:
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if device.type == "cuda":
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torch.cuda.set_sync_debug_mode(2) # fail if a blocking operation
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yield
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finally:
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if device.type == "cuda":
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torch.cuda.set_sync_debug_mode(0) # default, blocking operations are allowed
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def make_preprocessor_deterministic(model: ASRModel):
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model.preprocessor.featurizer.dither = 0.0
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model.preprocessor.featurizer.pad_to = 0
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