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Merge pull request #23 from ornew/develop
Add Converter Tools
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# coding: utf-8 | ||
# Copyright (c) 2018 Arata Furukawa | ||
# | ||
# Permission is hereby granted, free of charge, to any person obtaining a copy | ||
# of this software and associated documentation files (the "Software"), to deal | ||
# in the Software without restriction, including without limitation the rights | ||
# to use, copy, modify, merge, publish, distribute, sublicense, and/or sell | ||
# copies of the Software, and to permit persons to whom the Software is | ||
# furnished to do so, subject to the following conditions: | ||
# | ||
# The above copyright notice and this permission notice shall be included in all | ||
# copies or substantial portions of the Software. | ||
# | ||
# THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR | ||
# IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, | ||
# FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE | ||
# AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER | ||
# LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, | ||
# OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE | ||
# SOFTWARE. | ||
|
||
import tensorflow as tf | ||
from tensorflowjs import quantization | ||
from tensorflowjs.converters import tf_saved_model_conversion | ||
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DEFAULT_TAGS = [tf.saved_model.tag_constants.SERVING] | ||
DEFAULT_SIGNATURE = tf.saved_model.signature_constants.DEFAULT_SERVING_SIGNATURE_DEF_KEY | ||
DEFAULT_INPUTS = ['image'] | ||
DEFAULT_OUTPUTS = ['classes','probabilities'] | ||
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def convert_to_tfjs( | ||
savedmodel_dir, | ||
output_dir, | ||
tags, | ||
signature, | ||
inputs, | ||
outputs, | ||
quantization_dtype, | ||
skip_op_check, | ||
strip_debug_ops | ||
): | ||
with tf.Graph().as_default() as graph, tf.Session(graph=graph) as sess: | ||
meta_graph = tf.saved_model.loader.load(sess, tags, savedmodel_dir) | ||
meta = meta_graph.signature_def[signature] | ||
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output_node_names = [ | ||
meta.outputs[key].name for key in outputs | ||
] | ||
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# Getting input/output tensor name from signature for information. | ||
input_tensors = [ | ||
graph.get_tensor_by_name(meta.inputs[key].name) for key in inputs | ||
] | ||
output_tensors = [ | ||
graph.get_tensor_by_name(name) for name in output_node_names | ||
] | ||
print('input tensors:') | ||
for i, t in enumerate(input_tensors): | ||
print(' {}: "{}" {}'.format(i, t.name, t.shape.as_list())) | ||
print('output tensors:') | ||
for i, t in enumerate(output_tensors): | ||
print(' {}: "{}" {}'.format(i, t.name, t.shape.as_list())) | ||
|
||
tf_saved_model_conversion.convert_tf_saved_model( | ||
savedmodel_dir, | ||
output_node_names=','.join([n.split(':')[0] for n in output_node_names]), | ||
output_dir=output_dir, | ||
saved_model_tags=','.join(tags), | ||
quantization_dtype=quantization_dtype, | ||
skip_op_check=skip_op_check, | ||
strip_debug_ops=strip_debug_ops) | ||
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if __name__ == '__main__': | ||
import argparse | ||
p = argparse.ArgumentParser() | ||
p.add_argument('savedmodel_dir') | ||
p.add_argument('output_dir') | ||
p.add_argument('--tags', default=DEFAULT_TAGS) | ||
p.add_argument('--signature', default=DEFAULT_SIGNATURE) | ||
p.add_argument('--inputs', default=DEFAULT_INPUTS) | ||
p.add_argument('--outputs', default=DEFAULT_OUTPUTS) | ||
p.add_argument('--quantization_bytes', type=int, choices=set(quantization.QUANTIZATION_BYTES_TO_DTYPES.keys())) | ||
p.add_argument('--skip_op_check', default=False) | ||
p.add_argument('--strip_debug_ops', default=True) | ||
args = p.parse_args() | ||
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quantization_dtype = ( | ||
quantization.QUANTIZATION_BYTES_TO_DTYPES[args.quantization_bytes] | ||
if args.quantization_bytes else None) | ||
convert_to_tfjs( | ||
args.savedmodel_dir, | ||
args.output_dir, | ||
args.tags, | ||
args.signature, | ||
args.inputs, | ||
args.outputs, | ||
quantization_dtype, | ||
args.skip_op_check, | ||
args.strip_debug_ops | ||
) | ||
|
||
|
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@@ -0,0 +1,106 @@ | ||
# coding: utf-8 | ||
# Copyright (c) 2018 Arata Furukawa | ||
# | ||
# Permission is hereby granted, free of charge, to any person obtaining a copy | ||
# of this software and associated documentation files (the "Software"), to deal | ||
# in the Software without restriction, including without limitation the rights | ||
# to use, copy, modify, merge, publish, distribute, sublicense, and/or sell | ||
# copies of the Software, and to permit persons to whom the Software is | ||
# furnished to do so, subject to the following conditions: | ||
# | ||
# The above copyright notice and this permission notice shall be included in all | ||
# copies or substantial portions of the Software. | ||
# | ||
# THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR | ||
# IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, | ||
# FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE | ||
# AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER | ||
# LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, | ||
# OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE | ||
# SOFTWARE. | ||
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import tensorflow as tf | ||
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# Workaround for bugs. Details refer below: | ||
# https://github.com/tensorflow/tensorflow/issues/15410 | ||
import tempfile | ||
import subprocess | ||
tf.contrib.lite.tempfile = tempfile | ||
tf.contrib.lite.subprocess = subprocess | ||
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DEFAULT_TAGS = [tf.saved_model.tag_constants.SERVING] | ||
DEFAULT_SIGNATURE = tf.saved_model.signature_constants.DEFAULT_SERVING_SIGNATURE_DEF_KEY | ||
DEFAULT_INPUTS = ['image'] | ||
# Not using `classes` because TFLite not support ArgMax. | ||
DEFAULT_OUTPUTS = ['probabilities'] | ||
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def convert_to_tflite( | ||
savedmodel_dir, | ||
output_path, | ||
tags, | ||
signature, | ||
inputs, | ||
outputs | ||
): | ||
with tf.Graph().as_default() as graph, tf.Session(graph=graph) as sess: | ||
meta_graph = tf.saved_model.loader.load(sess, tags, savedmodel_dir) | ||
meta = meta_graph.signature_def[signature] | ||
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# Freeze variables. | ||
output_node_names = [ | ||
meta.outputs[key].name for key in outputs | ||
] | ||
frozen_graph_def = tf.graph_util.convert_variables_to_constants( | ||
sess, sess.graph_def, [ | ||
n.split(':')[0] for n in output_node_names | ||
]) | ||
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def fix_shape(t): | ||
if not t.shape.is_fully_defined(): | ||
t.set_shape([ | ||
d if d is not None else 1 for d in t.shape.as_list() | ||
]) | ||
return t | ||
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# Getting input/output tensor name from signature. | ||
input_tensors = map(fix_shape, [ | ||
graph.get_tensor_by_name(meta.inputs[key].name) for key in inputs | ||
]) | ||
output_tensors = [ | ||
graph.get_tensor_by_name(name) for name in output_node_names | ||
] | ||
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print('input tensors:') | ||
for i, t in enumerate(input_tensors): | ||
print(' {}: "{}" {}'.format(i, t.name, t.shape.as_list())) | ||
print('output tensors:') | ||
for i, t in enumerate(output_tensors): | ||
print(' {}: "{}" {}'.format(i, t.name, t.shape.as_list())) | ||
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# Convert to FlatBuffers by TOCO. | ||
tflite_model = tf.contrib.lite.toco_convert( | ||
frozen_graph_def, input_tensors, output_tensors) | ||
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# Save | ||
with open(output_path, 'wb') as f: | ||
f.write(tflite_model) | ||
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if __name__ == '__main__': | ||
import argparse | ||
p = argparse.ArgumentParser() | ||
p.add_argument('savedmodel_dir') | ||
p.add_argument('output_path') | ||
p.add_argument('--tags', default=DEFAULT_TAGS) | ||
p.add_argument('--signature', default=DEFAULT_SIGNATURE) | ||
p.add_argument('--inputs', default=DEFAULT_INPUTS) | ||
p.add_argument('--outputs', default=DEFAULT_OUTPUTS) | ||
args = p.parse_args() | ||
convert_to_tflite( | ||
args.savedmodel_dir, | ||
args.output_path, | ||
args.tags, | ||
args.signature, | ||
args.inputs, | ||
args.outputs | ||
) | ||
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