tips:keras [Galileo Labs]

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====== Keras ======

===== tensorflow =====

  * yay bazelisk

<code>
pip install -U pip six numpy wheel setuptools mock
pip install -U keras_applications --no-deps
pip install -U keras_preprocessing --no-deps

# tf 2
git clone https://github.com/tensorflow/tensorflow.git
cd tensorflow

# tf 1.15
wget https://github.com/tensorflow/tensorflow/archive/v1.15.0.tar.gz
tar zxvf v1.15.0.tar.gz
</code>

only for tf 2
<code>
wget https://git.archlinux.org/svntogit/community.git/plain/trunk/Add-grpc-fix-for-gettid.patch\?h\=packages/tensorflow -O Add-grpc-fix-for-gettid.patch
patch -Np1  -i Add-grpc-fix-for-gettid.patch
</code>

<code>
export TF_IGNORE_MAX_BAZEL_VERSION=1
export TF_NEED_CUDA=1
./configure
</code>

for atf 1.15
<code>
echo 0.26.1 > .bazelversion
</code>

this produce .tf_configure.bazelrc
<code>
build --action_env PYTHON_BIN_PATH="/lab/gianoobserver/lib/bin/python"
build --action_env PYTHON_LIB_PATH="/lab/gianoobserver/lib/lib/python3.8/site-packages"
build --python_path="/lab/gianoobserver/lib/bin/python"
build:xla --define with_xla_support=true
build --config=xla
build --action_env CUDA_TOOLKIT_PATH="/usr/local/cuda"
build --action_env TF_CUDA_COMPUTE_CAPABILITIES="6.1"
build --action_env LD_LIBRARY_PATH="/lab/dnn/lib/lib"
build --action_env GCC_HOST_COMPILER_PATH="/usr/bin/gcc-8"
build --config=cuda
build:opt --copt=-march=native
build:opt --copt=-Wno-sign-compare
build:opt --host_copt=-march=native
build:opt --define with_default_optimizations=true
test --flaky_test_attempts=3
test --test_size_filters=small,medium
test --test_tag_filters=-benchmark-test,-no_oss,-gpu,-oss_serial
test --build_tag_filters=-benchmark-test,-no_oss,-gpu
build --action_env TF_CONFIGURE_IOS="0"
</code>

compile
<code>
bazel build //tensorflow/tools/pip_package:build_pip_package

# ???
bazelisk \
    build --config=opt \
      //tensorflow:libtensorflow.so \
      //tensorflow:libtensorflow_cc.so \
      //tensorflow:install_headers \
      //tensorflow/tools/pip_package:build_pip_package
./bazel-bin/tensorflow/tools/pip_package/build_pip_package /tmp/tensorflow_pkg
pip install /tmp/tensorflow_pkg/tensorflow*.whl
</code>

===== from keras to opencv  =====

  * https://github.com/adoval4/keras_to_OpenCV_tensorflow



===== Export protobuf =====

prereq
<code>
bazel build tensorflow/python/tools:freeze_graph
</code>

<code>
import argparse
ap = argparse.ArgumentParser()
ap.add_argument('--input', required=True)
ap.add_argument('--output', default="/tmp/model/ckpt")
args = ap.parse_args()

from keras import backend as K
from keras.models import load_model
import tensorflow as tf

K.set_learning_phase(0)

# create model and load weights or ...
# model = create_model()
# model.load_weights(args.input)

# ... load h5 model
load_model(args.input)

saver = tf.train.Saver()
saver.save(K.get_session(), args.default)
print("Output node needed in freeze_graph: %s" % model.output.op.name)
print("Model created in: %s" % args.output)
</code>

result
<code>
/tmp/model
├── checkpoint
├── ckpt.data-00000-of-00001
├── ckpt.index
└── ckpt.meta
</code>

freeze 
<code>
bazel-bin/tensorflow/python/tools/freeze_graph \
--input_meta_graph=/tmp/model/ckpt.meta  \
--input_checkpoint=/tmp/model/ckpt \
--output_graph=frozen_graph.pb \
--input_binary \
--output_node_names="previous output node name"
</code>