Add TensorFlow model converter

build-tools/make/build-with-docker.mk

@@ -31,6 +31,7 @@ DOCKER_IMAGE_DOC ?= $(DOCKER_IMAGE_NAME_BASE)-doc:$(shell md5sum $(NNABLA_DIRECT
 DOCKER_IMAGE_BUILD ?= $(DOCKER_IMAGE_NAME_BASE)-build$(ARCH_SUFFIX):$(shell md5sum $(NNABLA_DIRECTORY)/docker/development/Dockerfile.build$(ARCH_SUFFIX) |cut -d \  -f 1)
 DOCKER_IMAGE_NNABLA ?= $(DOCKER_IMAGE_NAME_BASE)-nnabla:$(shell md5sum $(NNABLA_DIRECTORY)/docker/development/Dockerfile.build |cut -d \  -f 1)
 DOCKER_IMAGE_ONNX_TEST ?= $(DOCKER_IMAGE_NAME_BASE)-onnx-test$(ARCH_SUFFIX):$(shell md5sum $(NNABLA_DIRECTORY)/docker/development/Dockerfile.onnx-test$(ARCH_SUFFIX) |cut -d \  -f 1)
+DOCKER_IMAGE_TF_TEST ?= $(DOCKER_IMAGE_NAME_BASE)-tf-test$(ARCH_SUFFIX):$(shell md5sum $(NNABLA_DIRECTORY)/docker/development/Dockerfile.tf-test |cut -d \  -f 1)
 
 ########################################################################################################################
 # Docker images
@@ -63,6 +64,12 @@ docker_image_onnx_test$(DOCKER_IMAGE_TARGET_SUFFIX):
 		(cd $(NNABLA_DIRECTORY) && docker build $(DOCKER_BUILD_ARGS) -t $(DOCKER_IMAGE_ONNX_TEST) -f docker/development/Dockerfile.onnx-test$(ARCH_SUFFIX) .) \
 	fi
 
+.PHONY: docker_image_tf_test$(DOCKER_IMAGE_TARGET_SUFFIX)
+docker_image_tf_test$(DOCKER_IMAGE_TARGET_SUFFIX):
+	if ! docker image inspect $(DOCKER_IMAGE_TF_TEST) >/dev/null 2>/dev/null; then \
+		docker pull $(shell cat $(NNABLA_DIRECTORY)/docker/development/Dockerfile.tf-test$(ARCH_SUFFIX) |grep ^FROM |awk '{print $$2}') && \
+		(cd $(NNABLA_DIRECTORY) && docker build $(DOCKER_BUILD_ARGS) -t $(DOCKER_IMAGE_TF_TEST) -f docker/development/Dockerfile.tf-test$(ARCH_SUFFIX) .) \
+	fi
 
 
 # for Android

docker/development/Dockerfile.tf-test

@@ -0,0 +1,133 @@
+# Copyright (c) 2017 Sony Corporation. 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 ubuntu:16.04
+
+ENV LC_ALL C
+ENV LANG C
+ENV LANGUAGE C
+
+RUN apt-get update \
+    && apt-get install -y --no-install-recommends \
+       build-essential \
+       bzip2 \
+       ca-certificates \
+       ccache \
+       clang-format-3.8 \
+       cmake \
+       curl \
+       g++ \
+       git \
+       libarchive-dev \
+       libgoogle-glog-dev \
+       libgtest-dev \
+       libhdf5-dev \
+       libiomp-dev \
+       libleveldb-dev \
+       liblmdb-dev \
+       libopencv-dev \
+       libopenmpi-dev \
+       libprotobuf-dev \
+       libsnappy-dev \
+       libssl-dev \
+       make \
+       openmpi-bin \
+       openmpi-doc \
+       openssl \
+       unzip \
+       wget \
+       zip \
+       graphviz \
+    && apt-get clean \
+    && rm -rf /var/lib/apt/lists/*
+
+RUN cd /tmp \
+    && curl -L https://www.libarchive.org/downloads/libarchive-3.3.2.tar.gz -o libarchive-3.3.2.tar.gz \
+    && tar xfa libarchive-3.3.2.tar.gz \
+    && mkdir libarchive-build \
+    && cd libarchive-build \
+    && cmake \
+        -DCMAKE_POSITION_INDEPENDENT_CODE=ON \
+        -DENABLE_NETTLE=FALSE \
+        -DENABLE_OPENSSL=FALSE \
+        -DENABLE_LZO=FALSE \
+        -DENABLE_LZMA=FALSE \
+        -DENABLE_BZip2=FALSE \
+        -DENABLE_LIBXML2=FALSE \
+        -DENABLE_EXPAT=FALSE \
+        -DENABLE_PCREPOSIX=FALSE \
+        -DENABLE_LibGCC=FALSE \
+        -DENABLE_CNG=FALSE \
+        -DENABLE_TAR=FALSE \
+        -DENABLE_TAR_SHARED=FALSE \
+        -DENABLE_CPIO=FALSE \
+        -DENABLE_CPIO_SHARED=FALSE \
+        -DENABLE_CAT=FALSE \
+        -DENABLE_CAT_SHARED=FALSE \
+        -DENABLE_XATTR=FALSE \
+        -DENABLE_ACL=FALSE \
+        -DENABLE_ICONV=FALSE \
+        -DENABLE_TEST=FALSE \
+        ../libarchive-3.3.2 \
+    && make \
+    && make install \
+    && cd / \
+    && rm -rf /tmp/*
+
+ARG PYTHON_VERSION_MAJOR
+ARG PYTHON_VERSION_MINOR
+ENV PYVERNAME=${PYTHON_VERSION_MAJOR}.${PYTHON_VERSION_MINOR}
+
+ENV PATH /opt/miniconda3/bin:$PATH
+ENV LD_LIBRARY_PATH /opt/miniconda3/lib:$LD_LIBRARY_PATH
+
+RUN set -xe \
+    && umask 0 \
+    && wget https://repo.continuum.io/miniconda/Miniconda3-latest-Linux-x86_64.sh \
+    && bash Miniconda3-latest-Linux-x86_64.sh -b -p /opt/miniconda3 \
+    && rm -rf Miniconda3-latest-Linux-x86_64.sh \
+    && if test ${PYTHON_VERSION_MAJOR} -eq 3 -a ${PYTHON_VERSION_MINOR} -eq 5; \
+       then \
+            conda install -y conda=4.5.11 python=${PYVERNAME}; \
+       else \
+            conda install -y python=${PYVERNAME}; \
+            conda update -y --all; \
+       fi \
+    && conda install -y \
+        boto3 \
+        future \
+        h5py \
+        ipython \
+        mako \
+        'numpy<1.16' \
+        opencv \
+        pip \
+        protobuf \
+        pytest \
+        scikit-image \
+        scipy \
+        tqdm \
+        wheel \
+        virtualenv \
+    && pip install pyyaml onnx==1.3.0 future Cython autopep8 requests \
+        graphviz tensorflow onnx_tf \
+    && pip install cntk || true \
+    && conda install -y -c pytorch pytorch-nightly-cpu \
+    && rm -rf /opt/miniconda3/pkgs
+
+RUN cd /tmp \
+    && git clone https://github.com/onnx/tensorflow-onnx.git \
+    && cd tensorflow-onnx \
+    && python setup.py install \
+    && rm -rf /tmp/tensorflow-onnx

python/setup.py

@@ -247,6 +247,7 @@ def extopts(library_name, library_dir):
                 'nnabla.utils.converter.nnabla',
                 'nnabla.utils.converter.nnablart',
                 'nnabla.utils.converter.onnx',
+                'nnabla.utils.converter.tensorflow',
                 'nnabla.utils.factorization',
                 'nnabla.utils.image_utils',
                 'nnabla_ext',

python/src/nnabla/utils/converter/commands.py

@@ -26,19 +26,32 @@
 
 
 def _import_file(args, ifiles):
-    if len(ifiles) == 1 and os.path.splitext(ifiles[0])[1] == '.nnp':
-        args.import_format = 'NNP'
-    if len(ifiles) == 1 and os.path.splitext(ifiles[0])[1] == '.onnx':
-        args.import_format = 'ONNX'
+    if len(ifiles) == 1:
+        ext = os.path.splitext(ifiles[0])[1]
+        if ext == '.nnp':
+            args.import_format = 'NNP'
+        elif ext == '.onnx':
+            args.import_format = 'ONNX'
+        elif ext == '.pb':
+            args.import_format = "TF_PB"
+        elif ext == '.ckpt':
+            args.import_format = "TF_CKPT"
+
     if args.import_format == 'NNP':
         # Input file that has unsupported extension store into output nnp
         # archive or directory.
         return NnpImporter(*ifiles,
                            expand_network=not args.nnp_no_expand_network,
                            executor_index=args.nnp_import_executor_index).execute()
+
     elif args.import_format == 'ONNX':
         from .onnx import OnnxImporter
         return OnnxImporter(*ifiles).execute()
+
+    elif args.import_format == 'TF_PB' or \
+            args.import_format == 'TF_CKPT':
+        from .tensorflow import TensorflowImporter
+        return TensorflowImporter(*ifiles, tf_format=args.import_format).execute()
     return None
 
 
@@ -152,6 +165,9 @@ def _export_from_nnp(args, nnp, output, output_ext):
             OnnxExporter(nnp, args.batch_size, opset=opset).execute(output)
         else:
             OnnxExporter(nnp, args.batch_size).execute(output)
+    elif output_ext == '.pb':
+        from .tensorflow import TensorflowExporter
+        TensorflowExporter(nnp, args.batch_size).execute(output)
     else:
         print('Output file ({})'.format(output_ext) +
               ' is not supported or output directory does not exist.')
@@ -284,7 +300,7 @@ def convert_files(args, ifiles, output):
         else:
             return _export_from_nnp(args, nnp, output, output_ext)
     else:
-        print('Import from [{}] failed.'.format(ifiles))
+        print('Import from {} failed.'.format(ifiles))
         return False
 
 

python/src/nnabla/utils/converter/onnx/exporter.py

@@ -1541,6 +1541,11 @@ def dump_graph(self):
                         print("{} : {}".format(i, in_d[i]))
             print(node)
 
+    def export_model_proto(self):
+        self.create_model()
+        self.create_graph()
+        return self._model_proto
+
     def execute(self, file_path):
         # if debug, please uncomment it.
         # self.dump_nnp(file_path)

python/src/nnabla/utils/converter/onnx/importer.py

@@ -440,7 +440,7 @@ def add_tensor_as_parameter(pb, tensor):
 
 
 class OnnxImporter:
-    def __init__(self, file_path):
+    def __init__(self, file_path=''):
         self._file_path = file_path
 
         # We use an OrderedDict and not a set
@@ -1722,6 +1722,12 @@ class nnp:
         nnp.other_files = []
         return nnp
 
+    def import_from_onnx_model(self, onnx_model):
+        self._ir_version = onnx_model.ir_version
+        self._graph = onnx_model.graph
+        self._opset_import = onnx_model.opset_import
+
     def execute(self):
-        self.get_onnx_graph_info()
+        if self._file_path != '':
+            self.get_onnx_graph_info()
         return self.onnx_model_to_nnp_protobuf()

python/src/nnabla/utils/converter/supported_info.py

@@ -16,7 +16,7 @@
 
 _SupportedInfo = collections.namedtuple(
     '_SupportedInfo', 'import_name export_name')
-extensions = _SupportedInfo(import_name=['.nnp', '.onnx'], export_name=[
-                            '.nnp', '.nnb', '.onnx'])
-formats = _SupportedInfo(import_name=['NNP', 'ONNX'], export_name=[
-                         'NNP', 'NNB', 'CSRC', 'ONNX'])
+extensions = _SupportedInfo(import_name=['.nnp', '.onnx', '.ckpt', '.pb'], export_name=[
+                            '.nnp', '.nnb', '.onnx', '.ckpt', '.pb'])
+formats = _SupportedInfo(import_name=['NNP', 'ONNX', 'TF_CKPT', 'TF_PB'], export_name=[
+                         'NNP', 'NNB', 'CSRC', 'ONNX', 'TF_CKPT', 'TF_PB'])

python/src/nnabla/utils/converter/tensorflow/__init__.py

@@ -0,0 +1,16 @@
+# Copyright (c) 2017 Sony Corporation. 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 .importer import TensorflowImporter
+from .exporter import TensorflowExporter

python/src/nnabla/utils/converter/tensorflow/exporter.py

@@ -0,0 +1,28 @@
+# Copyright (c) 2019 Sony Corporation. 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 ..onnx import OnnxExporter
+from onnx_tf.backend import prepare
+
+
+class TensorflowExporter:
+    def __init__(self, nnp, batch_size):
+        self._nnp = nnp
+        self._batch_size = batch_size
+
+    def execute(self, output):
+        onnx_model = OnnxExporter(
+            self._nnp, self._batch_size).export_model_proto()
+        tf_rep = prepare(onnx_model)
+        tf_rep.export_graph(output)