nemo/collections/tts/modules/adapters.py

# 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)