我开始使用inception_v2_imagenet_2016_08_28预训练模型训练一个faster_rcnn_inception_v2。
fine_tune_checkpoint: "./pretrained_models/inception_v2_imagenet_2016_08_28/inception_v2.ckpt"
from_detection_checkpoint: false
我收到有关缺少参数（gamma）的警告。 比我把所有信息加倍。
INFO:tensorflow:global step 435766: loss = 0.7736 (0.27 sec/step)
INFO:tensorflow:global step 435766: loss = 0.7736 (0.27 sec/step)
为什么呢？有解决方案吗？ 感谢。
答案 0 :(得分：0)
我找到了解决这个问题的方法！
该错误位于https://github.com/tensorflow/models/blob/master/research/object_detection/utils/variables_helper.py中的def get_variables_available_in_checkpoint(variables, checkpoint_path):
"""Returns the subset of variables available in the checkpoint.
Inspects given checkpoint and returns the subset of variables that are
available in it.
TODO: force input and output to be a dictionary.
Args:
variables: a list or dictionary of variables to find in checkpoint.
checkpoint_path: path to the checkpoint to restore variables from.
Returns:
A list or dictionary of variables.
Raises:
ValueError: if `variables` is not a list or dict.
"""
if isinstance(variables, list):
variable_names_map = {variable.op.name: variable for variable in variables}
elif isinstance(variables, dict):
variable_names_map = variables
else:
raise ValueError('`variables` is expected to be a list or dict.')
ckpt_reader = tf.train.NewCheckpointReader(checkpoint_path)
ckpt_vars = ckpt_reader.get_variable_to_shape_map().keys()
vars_in_ckpt = {}
for variable_name, variable in sorted(variable_names_map.items()):
if variable_name in ckpt_vars:
vars_in_ckpt[variable_name] = variable
else:
logging.warning('Variable [%s] not available in checkpoint',
variable_name)
if isinstance(variables, list):
return vars_in_ckpt.values()
return vars_in_ckpt
函数中：
# else:
# logging.warning('Variable [%s] not available in checkpoint',
# variable_name)
我对此部分进行了评论，培训期间的信息仅显示一次。
var params = {
CollectionId: collectionId,
Image: {
Bytes: new Buffer(imageBytes, 'base64')
}
};