Bran Stewart wenfahu

Overall process

This toolset provides channel level pruning of inception-renet v2 model( the details of inception resnet v2 model, please refer to .. _Inception-ResnetV2: https://arxiv.org/abs/1602.07261

python inf.py [meta] [ckpt] [output_mask] --threshold [threshold] : get the indices (mask) for the convolutional channel weights under the threshold.
python freeze_graph.py [model_dir] [output_file]: freeze the model weights
simplify the tensorflow graph using .. GTT: https://github.com/tensorflow/tensorflow/blob/master/tensorflow/tools/graph_transforms/README.md#optimizing-for-deployment
python conv_travser.py [graph_path] [mask_path] [output_graph] [output_mask]: prune the model based on the dependency of inception resnet v2, the output_graph is the pruned model and the output_mask is used for further training.

	layer {
	name: "train-data"
	type: "Data"
	top: "data"
	top: "label"
	include {
	phase: TRAIN
	}
	transform_param {
	mirror: true

	def triplet_loss(anchor, positive, negative, alpha):
	"""Calculate the triplet loss according to the FaceNet paper

	Args:
	anchor: the embeddings for the anchor images.
	positive: the embeddings for the positive images.
	negative: the embeddings for the negative images.

	Returns:
	the triplet loss according to the FaceNet paper as a float tensor.

	def triplet_loss_soft(anchor, positive, negative, m=1):
	"""Calculate the triplet loss according to the FaceNet paper

	Args:
	anchor: the embeddings for the anchor images.
	positive: the embeddings for the positive images.
	negative: the embeddings for the negative images.

	Returns:
	the triplet loss according to the FaceNet paper as a float tensor.

	from collections import defaultdict
	import numpy as np
	import pdb
	from IPython import embed


	sky = defaultdict(list)

	def find_tuple(pts, tgts):
	idx = []

	from __future__ import absolute_import
	from __future__ import division
	from __future__ import print_function

	import tensorflow as tf
	import numpy as np
	import pickle
	from tensorflow.core.framework import attr_value_pb2
	from tensorflow.core.framework import graph_pb2
	from tensorflow.core.framework import node_def_pb2