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https://github.com/librempeg/librempeg
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convert_from_tensorflow.py: add option to dump graph for visualization in tensorboard
Signed-off-by: Guo, Yejun <yejun.guo@intel.com> Signed-off-by: Pedro Arthur <bygrandao@gmail.com>
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@ -27,6 +27,7 @@ def get_arguments():
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parser.add_argument('--outdir', type=str, default='./', help='where to put generated files')
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parser.add_argument('--outdir', type=str, default='./', help='where to put generated files')
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parser.add_argument('--infmt', type=str, default='tensorflow', help='format of the deep learning model')
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parser.add_argument('--infmt', type=str, default='tensorflow', help='format of the deep learning model')
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parser.add_argument('infile', help='path to the deep learning model with weights')
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parser.add_argument('infile', help='path to the deep learning model with weights')
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parser.add_argument('--dump4tb', type=str, default='no', help='dump file for visualization in tensorboard')
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return parser.parse_args()
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return parser.parse_args()
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@ -44,9 +45,12 @@ def main():
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basefile = os.path.split(args.infile)[1]
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basefile = os.path.split(args.infile)[1]
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basefile = os.path.splitext(basefile)[0]
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basefile = os.path.splitext(basefile)[0]
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outfile = os.path.join(args.outdir, basefile) + '.model'
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outfile = os.path.join(args.outdir, basefile) + '.model'
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dump4tb = False
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if args.dump4tb.lower() in ('yes', 'true', 't', 'y', '1'):
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dump4tb = True
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if args.infmt == 'tensorflow':
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if args.infmt == 'tensorflow':
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convert_from_tensorflow(args.infile, outfile)
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convert_from_tensorflow(args.infile, outfile, dump4tb)
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if __name__ == '__main__':
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if __name__ == '__main__':
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main()
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main()
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@ -24,10 +24,11 @@ import sys, struct
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__all__ = ['convert_from_tensorflow']
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__all__ = ['convert_from_tensorflow']
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class TFConverter:
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class TFConverter:
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def __init__(self, graph_def, nodes, outfile):
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def __init__(self, graph_def, nodes, outfile, dump4tb):
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self.graph_def = graph_def
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self.graph_def = graph_def
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self.nodes = nodes
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self.nodes = nodes
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self.outfile = outfile
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self.outfile = outfile
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self.dump4tb = dump4tb
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self.layer_number = 0
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self.layer_number = 0
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self.output_names = []
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self.output_names = []
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self.name_node_dict = {}
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self.name_node_dict = {}
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@ -42,8 +43,8 @@ class TFConverter:
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def dump_for_tensorboard(self):
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def dump_for_tensorboard(self):
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graph = tf.get_default_graph()
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graph = tf.get_default_graph()
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tf.import_graph_def(self.graph_def, name="")
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tf.import_graph_def(self.graph_def, name="")
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# tensorboard --logdir=/tmp/graph
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tf.summary.FileWriter('/tmp/graph', graph)
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tf.summary.FileWriter('/tmp/graph', graph)
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print('graph saved, run "tensorboard --logdir=/tmp/graph" to see it')
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def get_conv2d_params(self, node):
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def get_conv2d_params(self, node):
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@ -197,18 +198,18 @@ class TFConverter:
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self.remove_identity()
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self.remove_identity()
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self.generate_edges()
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self.generate_edges()
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#check the graph with tensorboard with human eyes
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if self.dump4tb:
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#self.dump_for_tensorboard()
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self.dump_for_tensorboard()
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self.dump_to_file()
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self.dump_to_file()
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def convert_from_tensorflow(infile, outfile):
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def convert_from_tensorflow(infile, outfile, dump4tb):
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with open(infile, 'rb') as f:
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with open(infile, 'rb') as f:
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# read the file in .proto format
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# read the file in .proto format
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graph_def = tf.GraphDef()
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graph_def = tf.GraphDef()
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graph_def.ParseFromString(f.read())
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graph_def.ParseFromString(f.read())
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nodes = graph_def.node
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nodes = graph_def.node
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converter = TFConverter(graph_def, nodes, outfile)
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converter = TFConverter(graph_def, nodes, outfile, dump4tb)
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converter.run()
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converter.run()
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