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Add max_decoder_steps, streamline Dockerfile

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This commit is contained in:
Brandon Thomas
2022-11-17 21:38:14 -05:00
parent 5163650b86
commit c7a880924f
5 changed files with 144 additions and 15 deletions
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.gitignore
+21 -8
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@@ -1,23 +1,36 @@
*.pyc
*.swo
*.swp
# Dot env (and secrets!)
*secret*sh
*~
.env
.env-secrets
.idea/
__pycache__/
models/Wav2Lip/python/
models/tacotron2/python/
production_database_secret_connect.sh
production_database_secret_query.sh
secrets.toml
secrets.yaml
# Vim cruft
*.swo
*.swp
*~
# Python cruft
*.pyc
__pycache__/
# Virtual environments
models/Wav2Lip/python/
models/tacotron2/python/
tts/python/
# Rust build
target/
# IntelliJ
.idea/
# Models for testing
future-todo/ControllableTalkNet/models
tts/hifigan/hifisr
# Other garbage to prune/remove
tts/hifigan/LJSpeech-1.1/
Dockerfile
+95 -5
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@@ -1,6 +1,91 @@
# ==================== Python Build Base ====================
FROM ghcr.io/storytold/docker-base-images-nvidia-cuda-experimental:080f96bc7087 as pybuild-base
# Experimental NVidia CUDA
# - ubuntu 20.04
# - nvidia-384
# - multiple python versions (3.6, 3.8)
# THIS IS NOT VERIFIED TO WORK YET (2021-05-30)
#FROM nvidia/cuda:10.1-devel-ubuntu18.04 as pybuild-base
FROM nvidia/cuda:11.3.0-devel-ubuntu20.04 as pybuild-base
# tzdata install hangs without presetting the time zone
ENV TZ=UTC
RUN ln -snf /usr/share/zoneinfo/$TZ /etc/localtime && echo $TZ > /etc/timezone
# NB(2021-05-30): This is the image that Tacotron 2's Dockerfile specifies.
# I have not tried this, but it might be necessary.
#FROM pytorch/pytorch:nightly-devel-cuda10.0-cudnn7
#ENV PATH /usr/local/nvidia/bin:/usr/local/cuda/bin:${PATH}
# NB: https://github.com/NVIDIA/nvidia-docker/issues/864#issuecomment-439848887
# NB: We do not install ffmpeg, since the version is 3.8.* series and we need 4.2.*
#
# NB(2021-05-30): We need to install `cython3` for building modern Tacotron 2
# dependencies (ie. protoc) on old Ubuntu
# RUN apt-get update \
# && apt-get install -y \
RUN apt-get update
#RUN apt-cache search python3.8
# NB: Here we install nvidia drivers
# NB: Avoid keyboard prompt
RUN DEBIAN_FRONTEND=noninteractive apt-get install -y \
nvidia-384 \
--no-install-recommends
# Notes on packages:
# * software-properties-common - needed for `apt-add-repository`
# * pciutils - needed for `lspci | grep -i nvidia`
RUN apt-get install -y \
build-essential \
curl \
cython3 \
ffmpeg \
g++-7 \
gcc-7 \
git \
htop \
imagemagick \
libc++-7-dev \
libffi-dev \
libgcc-7-dev \
libmagic1 \
libsm6 \
libsndfile1 \
libssl-dev \
libxext6 \
libxrender-dev \
netcat \
pciutils \
pkg-config \
python-dev \
python3-pip \
python3.8 \
python3.8-dev \
python3.8-venv\
redis-tools \
silversearcher-ag \
software-properties-common \
sox \
tmux \
unzip \
vim \
wget
# Wav2Lip needs Python3.6
# NB: we install python3-virtualenv as `python3.6 -m venv` won't work anymore
RUN add-apt-repository ppa:deadsnakes/ppa
RUN apt-get update
RUN apt-get install -y \
python3.6 \
python3.6-dev \
python3.6-venv
RUN python3.6 --version
RUN python3.8 --version
#FROM ghcr.io/storytold/docker-base-images-nvidia-cuda-experimental:080f96bc7087 as pybuild-base
## Authenticating with GHCR locally:
## https://docs.github.com/en/packages/working-with-a-github-packages-registry/migrating-to-the-container-registry-from-the-docker-registry
@@ -117,7 +202,10 @@ FROM pybuild-base as pybuild-requirements
WORKDIR /
COPY ./tts ./models/tts
RUN mkdir -p /models/tts
COPY ./tts/requirements-tacotron-python36.txt ./models/tts
WORKDIR models/tts
# NB: Not sure if we need Python3.6 for Tacotron2, but Python3.8 gave me trouble.
@@ -129,11 +217,10 @@ RUN . python/bin/activate \
&& pip install torch torchvision torchaudio --extra-index-url https://download.pytorch.org/whl/cu113 \
&& deactivate
# Final image
# FROM ubuntu:xenial
FROM pybuild-requirements as final
#FROM pybuild-requirements as final
WORKDIR /
#COPY scripts/ ./scripts
@@ -189,3 +276,6 @@ RUN pip3 install gdown
# NB(echelon,2022-07-14): Run a newer version of pytorch which will support RTX3090.
# Fixes bug, "NVIDIA GeForce RTX 3080 with CUDA capability sm_86 is not compatible with the current PyTorch installation."
#RUN pip3 install torch torchvision torchaudio --extra-index-url https://download.pytorch.org/whl/cu113
COPY ./tts ./models/tts
tts/tacotron2/model.py
+3
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@@ -469,6 +469,9 @@ class Tacotron2(nn.Module):
self.encoder = Encoder(hparams)
self.decoder = Decoder(hparams)
self.postnet = Postnet(hparams)
def fakeyou_set_max_decoder_steps(self, max_decoder_steps):
self.decoder.max_decoder_steps = max_decoder_steps
def parse_batch(self, batch):
text_padded, input_lengths, mel_padded, gate_padded, \
tts/vocodes_common.py
+11
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@@ -99,6 +99,14 @@ ENGLISH_ESPEAK_PIPELINE = EspeakPipeline(lang='en')
ENGLISH_PIPELINE_V1 = EnglishPipelineV1(EnglishPhonetization(CMUDict(DEFAULT_CMUDICT_PATH)))
LEGACY_FAKEYOU_PIPELINE = LegacyFakeYouPipeline()
def parse_int_or_default(maybe_int, default_int):
if maybe_int:
try:
return int(maybe_int)
except:
pass
return default_int
def preprocess_text(raw_user_text: str, text_pipeline_type: str):
integer_sequence = []
@@ -278,6 +286,7 @@ class TacotronWaveglowPipeline:
assert('output_audio_filename' in args)
assert('output_spectrogram_filename' in args)
assert('output_metadata_filename' in args)
assert('max_decoder_steps' in args)
LOGGER.info(f"raw inference text: {args['raw_text']}")
@@ -285,6 +294,8 @@ class TacotronWaveglowPipeline:
tacotron = self.tacotron_model_cache[args['synthesizer_checkpoint_path']]
tacotron.fakeyou_set_max_decoder_steps(args['max_decoder_steps'])
LOGGER.info("running inference...")
with torch.no_grad():
tts/vocodes_server.py
+14 -2
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@@ -25,10 +25,11 @@ from falcon_multipart.middleware import MultipartMiddleware
from wsgiref import simple_server
from vocodes_common import TacotronWaveglowPipeline
from vocodes_common import print_gpu_info
from vocodes_common import load_hifigan_model
from vocodes_common import load_tacotron_model
from vocodes_common import load_waveglow_model
from vocodes_common import load_hifigan_model
from vocodes_common import parse_int_or_default
from vocodes_common import print_gpu_info
from logger import LOGGER
@@ -221,6 +222,8 @@ class ApiHandler():
LOGGER.info(f"TTS Request: {raw_data}")
# ========== RUST SERVICE ARGUMENTS ==========
# Request parameters
synthesizer_checkpoint_path = raw_data.get('synthesizer_checkpoint_path')
text_pipeline_type = raw_data.get('text_pipeline_type')
@@ -233,10 +236,15 @@ class ApiHandler():
output_spectrogram_filename = raw_data.get('output_spectrogram_filename')
output_metadata_filename = raw_data.get('output_metadata_filename')
# Temporarily optional request parameters
maybe_max_decoder_steps = raw_data.get('max_decoder_steps')
# Optional request parameters
maybe_clear_synthesizer_checkpoint_path = \
raw_data.get('maybe_clear_synthesizer_checkpoint_path')
# ========== INFERENCE ==========
pipeline.maybe_load_waveglow_model(waveglow_vocoder_checkpoint_path)
pipeline.maybe_load_hifigan(hifigan_vocoder_checkpoint_path)
pipeline.maybe_load_hifigan_super_resolution(hifigan_superres_vocoder_checkpoint_path)
@@ -246,6 +254,9 @@ class ApiHandler():
pipeline.maybe_load_tacotron_model_to_cache(synthesizer_checkpoint_path)
# NB: 1000 is the default and is roughly 12 seconds.
max_decoder_steps = parse_int_or_default(maybe_max_decoder_steps, 1000)
inference_args = {
'raw_text': inference_text,
'synthesizer_checkpoint_path': synthesizer_checkpoint_path,
@@ -254,6 +265,7 @@ class ApiHandler():
'output_audio_filename': output_audio_filename,
'output_spectrogram_filename': output_spectrogram_filename,
'output_metadata_filename': output_metadata_filename,
'max_decoder_steps': max_decoder_steps,
}
LOGGER.info(f"running inference with args: {inference_args}")