# Copyright (c) 2023, NVIDIA CORPORATION & AFFILIATES. 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. from typing import List, Optional from omegaconf import DictConfig from nemo.collections.asr.parts.utils import adapter_utils from nemo.collections.tts.modules.aligner import AlignmentEncoder from nemo.collections.tts.modules.fastpitch import TemporalPredictor from nemo.collections.tts.modules.transformer import FFTransformerDecoder, FFTransformerEncoder from nemo.core.classes import adapter_mixins class FFTransformerDecoderAdapter(FFTransformerDecoder, adapter_mixins.AdapterModuleMixin): """ Inherit from FFTransformerDecoder and add support for adapter""" def add_adapter(self, name: str, cfg: dict): cfg = self._update_adapter_cfg_input_dim(cfg) for fft_layer in self.layers: # type: adapter_mixins.AdapterModuleMixin fft_layer.add_adapter(name, cfg) def is_adapter_available(self) -> bool: return any([FFT_layer.is_adapter_available() for FFT_layer in self.layers]) def set_enabled_adapters(self, name: Optional[str] = None, enabled: bool = True): for FFT_layer in self.layers: # type: adapter_mixins.AdapterModuleMixin FFT_layer.set_enabled_adapters(name=name, enabled=enabled) def get_enabled_adapters(self) -> List[str]: names = set([]) for FFT_layer in self.layers: # type: adapter_mixins.AdapterModuleMixin names.update(FFT_layer.get_enabled_adapters()) names = sorted(list(names)) return names def _update_adapter_cfg_input_dim(self, cfg: DictConfig): cfg = adapter_utils.update_adapter_cfg_input_dim(self, cfg, module_dim=self.d_model) return cfg class FFTransformerEncoderAdapter( FFTransformerDecoderAdapter, FFTransformerEncoder, adapter_mixins.AdapterModuleMixin ): """ Inherit from FFTransformerEncoder and add support for adapter""" pass class AlignmentEncoderAdapter(AlignmentEncoder, adapter_mixins.AdapterModuleMixin): """ Inherit from AlignmentEncoder and add support for adapter""" def add_adapter(self, name: str, cfg: dict): for i, conv_layer in enumerate(self.key_proj): if i % 2 == 0: cfg = self._update_adapter_cfg_input_dim(cfg, conv_layer.conv.out_channels) conv_layer.add_adapter(name, cfg) for i, conv_layer in enumerate(self.query_proj): if i % 2 == 0: cfg = self._update_adapter_cfg_input_dim(cfg, conv_layer.conv.out_channels) conv_layer.add_adapter(name, cfg) def is_adapter_available(self) -> bool: return any( [conv_layer.is_adapter_available() for i, conv_layer in enumerate(self.key_proj) if i % 2 == 0] + [conv_layer.is_adapter_available() for i, conv_layer in enumerate(self.query_proj) if i % 2 == 0] ) def set_enabled_adapters(self, name: Optional[str] = None, enabled: bool = True): for i, conv_layer in enumerate(self.key_proj): if i % 2 == 0: conv_layer.set_enabled_adapters(name=name, enabled=enabled) for i, conv_layer in enumerate(self.query_proj): if i % 2 == 0: conv_layer.set_enabled_adapters(name=name, enabled=enabled) def get_enabled_adapters(self) -> List[str]: names = set([]) for i, conv_layer in enumerate(self.key_proj): if i % 2 == 0: names.update(conv_layer.get_enabled_adapters()) for i, conv_layer in enumerate(self.query_proj): if i % 2 == 0: names.update(conv_layer.get_enabled_adapters()) names = sorted(list(names)) return names def _update_adapter_cfg_input_dim(self, cfg: DictConfig, module_dim: int): cfg = adapter_utils.update_adapter_cfg_input_dim(self, cfg, module_dim=module_dim) return cfg class TemporalPredictorAdapter(TemporalPredictor, adapter_mixins.AdapterModuleMixin): """ Inherit from TemporalPredictor and add support for adapter""" def add_adapter(self, name: str, cfg: dict): cfg = self._update_adapter_cfg_input_dim(cfg) for conv_layer in self.layers: # type: adapter_mixins.AdapterModuleMixin conv_layer.add_adapter(name, cfg) def is_adapter_available(self) -> bool: return any([conv_layer.is_adapter_available() for conv_layer in self.layers]) def set_enabled_adapters(self, name: Optional[str] = None, enabled: bool = True): for conv_layer in self.layers: # type: adapter_mixins.AdapterModuleMixin conv_layer.set_enabled_adapters(name=name, enabled=enabled) def get_enabled_adapters(self) -> List[str]: names = set([]) for conv_layer in self.layers: # type: adapter_mixins.AdapterModuleMixin names.update(conv_layer.get_enabled_adapters()) names = sorted(list(names)) return names def _update_adapter_cfg_input_dim(self, cfg: DictConfig): cfg = adapter_utils.update_adapter_cfg_input_dim(self, cfg, module_dim=self.filter_size) return cfg """Register any additional information""" if adapter_mixins.get_registered_adapter(FFTransformerEncoder) is None: adapter_mixins.register_adapter(base_class=FFTransformerEncoder, adapter_class=FFTransformerEncoderAdapter) if adapter_mixins.get_registered_adapter(FFTransformerDecoder) is None: adapter_mixins.register_adapter(base_class=FFTransformerDecoder, adapter_class=FFTransformerDecoderAdapter) if adapter_mixins.get_registered_adapter(AlignmentEncoder) is None: adapter_mixins.register_adapter(base_class=AlignmentEncoder, adapter_class=AlignmentEncoderAdapter) if adapter_mixins.get_registered_adapter(TemporalPredictor) is None: adapter_mixins.register_adapter(base_class=TemporalPredictor, adapter_class=TemporalPredictorAdapter)