AttributeError: объект 'module' не имеет атрибута 'histogram' при использовании tf-quick-rcnn

Question

Пожалуйста, взгляните на эту проблему и сообщите мне, знаете ли вы, как ее исправить? Вот ссылка на оригинальное репо: https://github.com/endernewton/tf-faster-rcnn

mona@pascal:~/computer_vision/tf-faster-rcnn$ ./experiments/scripts/test_vgg16.sh $GPU_ID pascal_voc 
+ set -e 
+ export PYTHONUNBUFFERED=True 
+ PYTHONUNBUFFERED=True 
+ GPU_ID=0 
+ DATASET=pascal_voc 
+ array=($@) 
+ len=2 
+ EXTRA_ARGS= 
+ EXTRA_ARGS_SLUG= 
+ case ${DATASET} in 
+ TRAIN_IMDB=voc_2007_trainval 
+ TEST_IMDB=voc_2007_test 
+ ITERS=70000 
++ date +%Y-%m-%d_%H-%M-%S 
+ LOG=experiments/logs/test_vgg16_voc_2007_trainval_.txt.2017-02-13_21-29-30 
+ exec 
++ tee -a experiments/logs/test_vgg16_voc_2007_trainval_.txt.2017-02-13_21-29-30 
tee: experiments/logs/test_vgg16_voc_2007_trainval_.txt.2017-02-13_21-29-30: No such file or directory 
+ echo Logging output to experiments/logs/test_vgg16_voc_2007_trainval_.txt.2017-02-13_21-29-30 
Logging output to experiments/logs/test_vgg16_voc_2007_trainval_.txt.2017-02-13_21-29-30 
+ set +x 
+ [[ ! -z '' ]] 
+ CUDA_VISIBLE_DEVICES=0 
+ time python ./tools/test_vgg16_net.py --imdb voc_2007_test --weight data/imagenet_weights/vgg16.weights --model output/vgg16/voc_2007_trainval/default/vgg16_faster_rcnn_iter_70000.ckpt --cfg experiments/cfgs/vgg16.yml --set 
I tensorflow/stream_executor/dso_loader.cc:111] successfully opened CUDA library libcublas.so.8.0 locally 
I tensorflow/stream_executor/dso_loader.cc:111] successfully opened CUDA library libcudnn.so.5.0 locally 
I tensorflow/stream_executor/dso_loader.cc:111] successfully opened CUDA library libcufft.so.8.0 locally 
I tensorflow/stream_executor/dso_loader.cc:111] successfully opened CUDA library libcuda.so.1 locally 
I tensorflow/stream_executor/dso_loader.cc:111] successfully opened CUDA library libcurand.so.8.0 locally 
Called with args: 
Namespace(cfg_file='experiments/cfgs/vgg16.yml', comp_mode=False, imdb_name='voc_2007_test', max_per_image=100, model='output/vgg16/voc_2007_trainval/default/vgg16_faster_rcnn_iter_70000.ckpt', set_cfgs=[], tag='', weight='data/imagenet_weights/vgg16.weights') 
Using config: 
{'DATA_DIR': '/home/mona/computer_vision/tf-faster-rcnn/data', 
'DEDUP_BOXES': 0.0625, 
'EPS': 1e-14, 
'EXP_DIR': 'vgg16', 
'GPU_ID': 0, 
'MATLAB': 'matlab', 
'PIXEL_MEANS': array([[[ 102.9801, 115.9465, 122.7717]]]), 
'POOLING_MODE': 'crop', 
'RNG_SEED': 3, 
'ROOT_DIR': '/home/mona/computer_vision/tf-faster-rcnn', 
'TEST': {'BBOX_REG': True, 
      'HAS_RPN': True, 
      'MAX_SIZE': 1000, 
      'MODE': 'nms', 
      'NMS': 0.3, 
      'PROPOSAL_METHOD': 'selective_search', 
      'RPN_NMS_THRESH': 0.7, 
      'RPN_POST_NMS_TOP_N': 300, 
      'RPN_PRE_NMS_TOP_N': 6000, 
      'RPN_TOP_N': 5000, 
      'SCALES': [600], 
      'SVM': False}, 
'TRAIN': {'ASPECT_GROUPING': False, 
      'BATCH_SIZE': 256, 
      'BBOX_INSIDE_WEIGHTS': [1.0, 1.0, 1.0, 1.0], 
      'BBOX_NORMALIZE_MEANS': [0.0, 0.0, 0.0, 0.0], 
      'BBOX_NORMALIZE_STDS': [0.1, 0.1, 0.2, 0.2], 
      'BBOX_NORMALIZE_TARGETS': True, 
      'BBOX_NORMALIZE_TARGETS_PRECOMPUTED': True, 
      'BBOX_REG': True, 
      'BBOX_THRESH': 0.5, 
      'BG_THRESH_HI': 0.5, 
      'BG_THRESH_LO': 0.0, 
      'BIAS_DECAY': False, 
      'DISPLAY': 20, 
      'DOUBLE_BIAS': True, 
      'FG_FRACTION': 0.25, 
      'FG_THRESH': 0.5, 
      'GAMMA': 0.1, 
      'HAS_RPN': True, 
      'IMS_PER_BATCH': 1, 
      'LEARNING_RATE': 0.001, 
      'MAX_SIZE': 1000, 
      'MOMENTUM': 0.9, 
      'PROPOSAL_METHOD': 'gt', 
      'RPN_BATCHSIZE': 256, 
      'RPN_BBOX_INSIDE_WEIGHTS': [1.0, 1.0, 1.0, 1.0], 
      'RPN_CLOBBER_POSITIVES': False, 
      'RPN_FG_FRACTION': 0.5, 
      'RPN_NEGATIVE_OVERLAP': 0.3, 
      'RPN_NMS_THRESH': 0.7, 
      'RPN_POSITIVE_OVERLAP': 0.7, 
      'RPN_POSITIVE_WEIGHT': -1.0, 
      'RPN_POST_NMS_TOP_N': 2000, 
      'RPN_PRE_NMS_TOP_N': 12000, 
      'SCALES': [600], 
      'SNAPSHOT_ITERS': 5000, 
      'SNAPSHOT_KEPT': 3, 
      'SNAPSHOT_PREFIX': 'vgg16_faster_rcnn', 
      'STEPSIZE': 30000, 
      'SUMMARY_INTERVAL': 180, 
      'TRUNCATED': False, 
      'USE_FLIPPED': True, 
      'USE_GT': False, 
      'WEIGHT_DECAY': 0.0005}, 
'USE_GPU_NMS': True} 
I tensorflow/core/common_runtime/gpu/gpu_device.cc:951] Found device 0 with properties: 
name: Tesla K40c 
major: 3 minor: 5 memoryClockRate (GHz) 0.8755 
pciBusID 0000:03:00.0 
Total memory: 11.92GiB 
Free memory: 11.85GiB 
I tensorflow/core/common_runtime/gpu/gpu_device.cc:972] DMA: 0 
I tensorflow/core/common_runtime/gpu/gpu_device.cc:982] 0: Y 
I tensorflow/core/common_runtime/gpu/gpu_device.cc:1041] Creating TensorFlow device (/gpu:0) -> (device: 0, name: Tesla K40c, pci bus id: 0000:03:00.0) 
Loading caffe weights... 
Done! 
Traceback (most recent call last): 
    File "./tools/test_vgg16_net.py", line 89, in <module> 
    tag='default', anchor_scales=anchors) 
    File "/home/mona/computer_vision/tf-faster-rcnn/tools/../lib/nets/vgg16.py", line 503, in create_architecture 
    self._add_score_summary(key, var) 
    File "/home/mona/computer_vision/tf-faster-rcnn/tools/../lib/nets/vgg16.py", line 45, in _add_score_summary 
    tf.summary.histogram('SCORE/' + tensor.op.name + '/' + key + '/scores', tensor) 
AttributeError: 'module' object has no attribute 'histogram' 
Command exited with non-zero status 1 
5.56user 4.11system 0:07.12elapsed 135%CPU (0avgtext+0avgdata 2082508maxresident)k 
0inputs+32outputs (0major+212277minor)pagefaults 0swaps 
Environment info 

Операционная система:

$ uname -a; lsb_release -a 
Linux pascal 3.13.0-62-generiC#102-Ubuntu SMP Tue Aug 11 14:29:36 UTC 2015 x86_64 x86_64 x86_64 GNU/Linux 
No LSB modules are available. 
Distributor ID: Ubuntu 
Description: Ubuntu 14.04.5 LTS 
Release: 14.04 
Codename: trusty 
Version of TF: 

mona@pascal:~/computer_vision/tf-faster-rcnn$ python -c "import tensorflow; print(tensorflow.__version__)" 
I tensorflow/stream_executor/dso_loader.cc:111] successfully opened CUDA library libcublas.so.8.0 locally 
I tensorflow/stream_executor/dso_loader.cc:111] successfully opened CUDA library libcudnn.so.5.0 locally 
I tensorflow/stream_executor/dso_loader.cc:111] successfully opened CUDA library libcufft.so.8.0 locally 
I tensorflow/stream_executor/dso_loader.cc:111] successfully opened CUDA library libcuda.so.1 locally 
I tensorflow/stream_executor/dso_loader.cc:111] successfully opened CUDA library libcurand.so.8.0 locally 
0.10.0 

Выход Базэла версии

$ bazel version 
Extracting Bazel installation... 
Build label: 0.4.3 
Build target: bazel-out/local-fastbuild/bin/src/main/java/com/google/devtools/build/lib/bazel/BazelServer_deploy.jar 
Build time: Thu Dec 22 12:31:25 2016 (1482409885) 
Build timestamp: 1482409885 
Build timestamp as int: 1482409885 

Answer 1

Согласно ответа я получил в вопросах GitHub, Я использую очень старую версию TensorFlow. Это решило проблему:

$ sudo pip2 install tensorflow-gpu 

Или

$ sudo pip2 install tensorflow 

Для других.

Answer 2

Вы используете старую версию тензорного потока. Старая версия была tf.histogram_summary. Вы можете увидеть список изменений API в нашем upgrade script.