Tensorflow Version Hatası


#1

win 7 64 bit ve tensorflow 1.5 cpu üzerinde alıyorum hatayı 1.9 ve üst versiyonlarında DLL hatası alıyorum yine aynı şekilde tensorflow-gpu 1.4 ve üstü için denedim çalışanlar 1.4 ,1.5,.1.12 fakat hepsinde farklı farklı hatalar alıyorum venv üzerinde çalışıyorum kanser etti bundan sonra yeni ismi canserflow.

    (tensorflow1) C:\tensorflow1\models\research\object_detection>python train.py --
    logtostderr --train_dir=training/ --pipeline_config_path=training/faster_rcnn_in
    ception_v2_pets.config
    WARNING:tensorflow:From C:\Users\WEAP\Anaconda3\envs\tensorflow1\lib\site-packag
    es\tensorflow\python\platform\app.py:124: main (from __main__) is deprecated and
     will be removed in a future version.
    Instructions for updating:
    Use object_detection/model_main.py.
    W1111 18:52:05.496925  6636 tf_logging.py:118] From C:\Users\WEAP\Anaconda3\envs
    \tensorflow1\lib\site-packages\tensorflow\python\platform\app.py:124: main (from
     __main__) is deprecated and will be removed in a future version.
    Instructions for updating:
    Use object_detection/model_main.py.
    WARNING:tensorflow:From C:\tensorflow1\models\research\object_detection\legacy\t
    rainer.py:265: create_global_step (from tensorflow.contrib.framework.python.ops.
    variables) is deprecated and will be removed in a future version.
    Instructions for updating:
    Please switch to tf.train.create_global_step
    W1111 18:52:05.619932  6636 tf_logging.py:118] From C:\tensorflow1\models\resear
    ch\object_detection\legacy\trainer.py:265: create_global_step (from tensorflow.c
    ontrib.framework.python.ops.variables) is deprecated and will be removed in a fu
    ture version.
    Instructions for updating:
    Please switch to tf.train.create_global_step
    WARNING:tensorflow:num_readers has been reduced to 1 to match input file shards.

    W1111 18:52:05.644933  6636 tf_logging.py:118] num_readers has been reduced to 1
     to match input file shards.
    INFO:tensorflow:Scale of 0 disables regularizer.
    I1111 18:52:07.784056  6636 tf_logging.py:110] Scale of 0 disables regularizer.
    INFO:tensorflow:Scale of 0 disables regularizer.
    I1111 18:52:07.799057  6636 tf_logging.py:110] Scale of 0 disables regularizer.
    INFO:tensorflow:depth of additional conv before box predictor: 0
    I1111 18:52:07.800057  6636 tf_logging.py:110] depth of additional conv before b
    ox predictor: 0
    Traceback (most recent call last):
      File "train.py", line 184, in <module>
        tf.app.run()
      File "C:\Users\WEAP\Anaconda3\envs\tensorflow1\lib\site-packages\tensorflow\py
    thon\platform\app.py", line 124, in run
        _sys.exit(main(argv))
      File "C:\Users\WEAP\Anaconda3\envs\tensorflow1\lib\site-packages\tensorflow\py
    thon\util\deprecation.py", line 136, in new_func
        return func(*args, **kwargs)
      File "train.py", line 180, in main
        graph_hook_fn=graph_rewriter_fn)
      File "C:\tensorflow1\models\research\object_detection\legacy\trainer.py", line
     290, in train
        clones = model_deploy.create_clones(deploy_config, model_fn, [input_queue])
      File "C:\tensorflow1\models\research\slim\deployment\model_deploy.py", line 19
    3, in create_clones
        outputs = model_fn(*args, **kwargs)
      File "C:\tensorflow1\models\research\object_detection\legacy\trainer.py", line
     203, in _create_losses
        prediction_dict = detection_model.predict(images, true_image_shapes)
      File "C:\tensorflow1\models\research\object_detection\meta_architectures\faste
    r_rcnn_meta_arch.py", line 688, in predict
        self._anchors.get(), image_shape, true_image_shapes))
      File "C:\tensorflow1\models\research\object_detection\meta_architectures\faste
    r_rcnn_meta_arch.py", line 775, in _predict_second_stage
        anchors, image_shape_2d, true_image_shapes)
      File "C:\tensorflow1\models\research\object_detection\meta_architectures\faste
    r_rcnn_meta_arch.py", line 1285, in _postprocess_rpn
        clip_window=clip_window)
      File "C:\tensorflow1\models\research\object_detection\core\post_processing.py"
    , line 478, in batch_multiclass_non_max_suppression
        parallel_iterations=parallel_iterations)
      File "C:\tensorflow1\models\research\object_detection\utils\shape_utils.py", l
    ine 228, in static_or_dynamic_map_fn
        return tf.map_fn(fn, elems, dtype, parallel_iterations, back_prop)
      File "C:\Users\WEAP\Anaconda3\envs\tensorflow1\lib\site-packages\tensorflow\py
    thon\ops\functional_ops.py", line 409, in map_fn
        swap_memory=swap_memory)
      File "C:\Users\WEAP\Anaconda3\envs\tensorflow1\lib\site-packages\tensorflow\py
    thon\ops\control_flow_ops.py", line 2934, in while_loop
        result = loop_context.BuildLoop(cond, body, loop_vars, shape_invariants)
      File "C:\Users\WEAP\Anaconda3\envs\tensorflow1\lib\site-packages\tensorflow\py
    thon\ops\control_flow_ops.py", line 2720, in BuildLoop
        pred, body, original_loop_vars, loop_vars, shape_invariants)
      File "C:\Users\WEAP\Anaconda3\envs\tensorflow1\lib\site-packages\tensorflow\py
    thon\ops\control_flow_ops.py", line 2662, in _BuildLoop
        body_result = body(*packed_vars_for_body)
      File "C:\Users\WEAP\Anaconda3\envs\tensorflow1\lib\site-packages\tensorflow\py
    thon\ops\functional_ops.py", line 399, in compute
        packed_fn_values = fn(packed_values)
      File "C:\tensorflow1\models\research\object_detection\core\post_processing.py"
    , line 452, in _single_image_nms_fn
        additional_fields=per_image_additional_fields)
      File "C:\tensorflow1\models\research\object_detection\core\post_processing.py"
    , line 170, in multiclass_non_max_suppression
        score_threshold=score_thresh)
    TypeError: non_max_suppression() got an unexpected keyword argument 'score_thres
    hold'

#2

DLL hatasının sebebini görmeden bir şey diyemem ama gönderdiğin hatanın sebebi, non_max_suppression() metodunun score_threshold diye bir parametresi olmaması yüzünden patlıyorsun. tf’da şaşırtmayan bir hatadır, versiyondan versiyona zibilyon değişiklik olduğundan. Yani sebepsizce tf’in son versiyonuna geçicem gibi bir inadınız varsa bu tip olayları göz önüne almak lazım. Bir diğer alternatif de sadece yeni projeleri güncel tf versiyonunda kodlamak olur, akıl ve ruh sağlığı için.


#3

Efem amaç güncel tf versiyonu kullanmak değil eğitim için 1.9 ve üst versiyonlarda çalıştığını belirtmiş fakat benim cihazımda sadece venv de değil normal kurulumdada 1.4 1.5 çalışıyor diğerlerinde dll hatası alıyorum