Fix Dockerfile, make it more convenient and efficient

.dockerignore

@@ -0,0 +1,3 @@
+docker_data
+build
+*.pyc

.gitignore

@@ -132,4 +132,7 @@ dmypy.json
 .models/*
 .custom/*
 results/*
-debug_states/*
+debug_states/*
+
+# Ignore docker data files
+docker_data

Dockerfile

@@ -1,7 +1,5 @@
 FROM nvidia/cuda:12.2.0-base-ubuntu22.04
 
-COPY . /app
-
 RUN apt-get update && \
     apt-get install -y --allow-unauthenticated --no-install-recommends \
     wget \
@@ -10,12 +8,10 @@ RUN apt-get update && \
     && apt-get clean -y \
     && rm -rf /var/lib/apt/lists/*
 
-ENV HOME "/root"
-ENV CONDA_DIR "${HOME}/miniconda"
+ENV HOME="/root"
+ENV CONDA_DIR="${HOME}/miniconda"
 ENV PATH="$CONDA_DIR/bin":$PATH
 ENV CONDA_AUTO_UPDATE_CONDA=false
-ENV PIP_DOWNLOAD_CACHE="$HOME/.pip/cache"
-ENV TORTOISE_MODELS_DIR
 
 RUN wget https://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-x86_64.sh -O /tmp/miniconda3.sh \
     && bash /tmp/miniconda3.sh -b -p "${CONDA_DIR}" -f -u \
@@ -30,5 +26,16 @@ RUN conda create --name tortoise python=3.9 numba inflect \
     && conda activate tortoise \
     && conda install pytorch torchvision torchaudio pytorch-cuda=11.7 -c pytorch -c nvidia \
     && conda install transformers=4.29.2 \
-    && cd /app \
-    && python setup.py install
+    && conda clean --all \
+    && echo "conda activate tortoise; cd /app" >> "${HOME}/.bashrc"
+
+# Cache the pip deps after all the slow Conda deps
+COPY requirements.txt /app/requirements.txt
+WORKDIR /app
+RUN conda activate tortoise \
+    && pip install -r requirements.txt --no-cache-dir
+
+# and finally copy the source over
+COPY . /app/
+RUN conda activate tortoise \
+    && pip install . --no-cache-dir

README.md

@@ -99,15 +99,7 @@ An easy way to hit the ground running and a good jumping off point depending on
 git clone https://github.com/neonbjb/tortoise-tts.git
 cd tortoise-tts
 
-docker build . -t tts
-
-docker run --gpus all \
-    -e TORTOISE_MODELS_DIR=/models \
-    -v /mnt/user/data/tortoise_tts/models:/models \
-    -v /mnt/user/data/tortoise_tts/results:/results \
-    -v /mnt/user/data/.cache/huggingface:/root/.cache/huggingface \
-    -v /root:/work \
-    -it tts
+./scripts/run_docker.sh
 ```
 This gives you an interactive terminal in an environment that's ready to do some tts. Now you can explore the different interfaces that tortoise exposes for tts.
 

scripts/run_docker.sh

@@ -0,0 +1,15 @@
+#!/bin/bash
+
+set -e
+
+docker build . -t tts
+
+pwd=$(pwd)
+
+docker run --gpus all \
+    -e TORTOISE_MODELS_DIR=/models \
+    -v $pwd/docker_data/models:/models \
+    -v $pwd/docker_data/results:/results \
+    -v $pwd/docker_data/.cache/huggingface:/root/.cache/huggingface \
+    -v $pwd/docker_data/work:/work \
+    -it tts