/
Dockerfile.build.tmpl
166 lines (146 loc) · 4.99 KB
/
Dockerfile.build.tmpl
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
# Please refer to the USING documentation, "Dockerfile for building from source"
# Need devel version cause we need /usr/include/cudnn.h
FROM nvidia/cuda:10.1-cudnn7-devel-ubuntu18.04
ENV DEEPSPEECH_REPO=#DEEPSPEECH_REPO# \
DEEPSPEECH_SHA=#DEEPSPEECH_SHA#
# >> START Install base software
# Get basic packages
RUN apt-get update && apt-get install -y --no-install-recommends \
apt-utils \
bash-completion \
build-essential \
ca-certificates \
cmake \
curl \
g++ \
gcc \
git \
libbz2-dev \
libboost-all-dev \
libgsm1-dev \
libltdl-dev \
liblzma-dev \
libmagic-dev \
libpng-dev \
libsox-fmt-mp3 \
libsox-dev \
locales \
openjdk-8-jdk \
pkg-config \
python3 \
python3-dev \
python3-pip \
python3-wheel \
python3-numpy \
sox \
unzip \
wget \
zlib1g-dev; \
update-alternatives --install /usr/bin/pip pip /usr/bin/pip3 1 && \
update-alternatives --install /usr/bin/python python /usr/bin/python3 1; \
# Install Bazel \
curl -LO "https://github.com/bazelbuild/bazel/releases/download/3.1.0/bazel_3.1.0-linux-x86_64.deb" && dpkg -i bazel_*.deb; \
# Try and free some space \
rm -rf /var/lib/apt/lists/* bazel_*.deb
# << END Install base software
# >> START Configure Tensorflow Build
# GPU Environment Setup
ENV TF_NEED_ROCM=0 \
TF_NEED_OPENCL_SYCL=0 \
TF_NEED_OPENCL=0 \
TF_NEED_CUDA=1 \
TF_CUDA_PATHS="/usr,/usr/local/cuda-10.1,/usr/lib/x86_64-linux-gnu/" \
TF_CUDA_VERSION=10.1 \
TF_CUDNN_VERSION=7.6 \
TF_CUDA_COMPUTE_CAPABILITIES=6.0 \
TF_NCCL_VERSION=2.8 \
# Common Environment Setup \
TF_BUILD_CONTAINER_TYPE=GPU \
TF_BUILD_OPTIONS=OPT \
TF_BUILD_DISABLE_GCP=1 \
TF_BUILD_ENABLE_XLA=0 \
TF_BUILD_PYTHON_VERSION=PYTHON3 \
TF_BUILD_IS_OPT=OPT \
TF_BUILD_IS_PIP=PIP \
# Build client.cc and install Python client and decoder bindings \
TFDIR=/DeepSpeech/tensorflow \
# Allow Python printing utf-8 \
PYTHONIOENCODING=UTF-8 \
# Other Parameters \
CC_OPT_FLAGS="-mavx -mavx2 -msse4.1 -msse4.2 -mfma" \
TF_NEED_GCP=0 \
TF_NEED_HDFS=0 \
TF_NEED_JEMALLOC=1 \
TF_NEED_OPENCL=0 \
TF_CUDA_CLANG=0 \
TF_NEED_MKL=0 \
TF_ENABLE_XLA=0 \
TF_NEED_AWS=0 \
TF_NEED_KAFKA=0 \
TF_NEED_NGRAPH=0 \
TF_DOWNLOAD_CLANG=0 \
TF_NEED_TENSORRT=0 \
TF_NEED_GDR=0 \
TF_NEED_VERBS=0 \
TF_NEED_OPENCL_SYCL=0 \
PYTHON_BIN_PATH=/usr/bin/python3.6 \
PYTHON_LIB_PATH=/usr/local/lib/python3.6/dist-packages
# << END Configure Tensorflow Build
# >> START Configure Bazel
# Running bazel inside a `docker build` command causes trouble, cf:
# https://github.com/bazelbuild/bazel/issues/134
# The easiest solution is to set up a bazelrc file forcing --batch.
# Similarly, we need to workaround sandboxing issues:
# https://github.com/bazelbuild/bazel/issues/418
RUN echo "startup --batch" >>/etc/bazel.bazelrc; \
echo "build --spawn_strategy=standalone --genrule_strategy=standalone" >> /etc/bazel.bazelrc
# << END Configure Bazel
WORKDIR /
RUN git clone --recursive $DEEPSPEECH_REPO DeepSpeech && \
cd /DeepSpeech && \
git fetch origin $DEEPSPEECH_SHA && git checkout $DEEPSPEECH_SHA; \
git submodule sync tensorflow/ && git submodule update --init tensorflow/; \
git submodule sync kenlm/ && git submodule update --init kenlm/
# >> START Build and bind
# Fix for not found script https://github.com/tensorflow/tensorflow/issues/471
# Using CPU optimizations:
# -mtune=generic -march=x86-64 -msse -msse2 -msse3 -msse4.1 -msse4.2 -mavx.
# Adding --config=cuda flag to build using CUDA.
# passing LD_LIBRARY_PATH is required cause Bazel doesn't pickup it from environment
# Build DeepSpeech
RUN cd /DeepSpeech/tensorflow && ./configure && bazel build \
--workspace_status_command="bash native_client/bazel_workspace_status_cmd.sh" \
--config=monolithic \
--config=cuda \
-c opt \
--copt=-O3 \
--copt="-D_GLIBCXX_USE_CXX11_ABI=0" \
--copt=-mtune=generic \
--copt=-march=x86-64 \
--copt=-msse \
--copt=-msse2 \
--copt=-msse3 \
--copt=-msse4.1 \
--copt=-msse4.2 \
--copt=-mavx \
--copt=-fvisibility=hidden \
//native_client:libdeepspeech.so \
--verbose_failures \
--action_env=LD_LIBRARY_PATH=${LD_LIBRARY_PATH} && \
cp bazel-bin/native_client/libdeepspeech.so /DeepSpeech/native_client/ && \
rm -fr /root/.cache/*
RUN cd /DeepSpeech/native_client && make NUM_PROCESSES=$(nproc) deepspeech ; \
cd /DeepSpeech/native_client/python && make NUM_PROCESSES=$(nproc) bindings; \
pip3 install --upgrade dist/*.whl; \
cd /DeepSpeech/native_client/ctcdecode && make NUM_PROCESSES=$(nproc) bindings; \
pip3 install --upgrade dist/*.whl
# << END Build and bind
# Build KenLM in /DeepSpeech/kenlm folder
WORKDIR /DeepSpeech/kenlm
RUN wget -O - https://gitlab.com/libeigen/eigen/-/archive/3.3.8/eigen-3.3.8.tar.bz2 | tar xj; \
mkdir -p build && \
cd build && \
EIGEN3_ROOT=/DeepSpeech/kenlm/eigen-3.3.8 cmake .. && \
make -j $(nproc)
# Done
WORKDIR /DeepSpeech