Ошибка при последовательном экспорте двух разных графов логического вывода в API обнаружения объектов tenorflow

Question

Я использую API обнаружения объектов Tensorflow и обучил две отдельные модели (FRCNN Inception V2 и SSD Mobil enet V2). В моем потоке кода, когда обе модели были обучены, мне нужно экспортировать графы вывода. Ниже приведен код для того же самого:

# Dependencies
import tensorflow as tf
import glob
import os
import re

from google.protobuf import text_format
from object_detection import exporter
from object_detection.protos import pipeline_pb2

class ExportInferenceGraph():

    def __init__(self):

        # input parameters for exporter
        self.pipeline_config_path = None
        self.trained_checkpoint_prefix = None
        self.output_directory = None


        #############################################################################
        '''
        code used form export_inference_graph.py file from Tensorflow github
        '''
        #############################################################################

        flags = tf.app.flags

        flags.DEFINE_string('input_type', 'image_tensor', 'Type of input node. Can be '
                            'one of [`image_tensor`, `encoded_image_string_tensor`, '
                            '`tf_example`]')
        flags.DEFINE_string('input_shape', None,
                            'If input_type is `image_tensor`, this can explicitly set '
                            'the shape of this input tensor to a fixed size. The '
                            'dimensions are to be provided as a comma-separated list '
                            'of integers. A value of -1 can be used for unknown '
                            'dimensions. If not specified, for an `image_tensor, the '
                            'default shape will be partially specified as '
                            '`[None, None, None, 3]`.')
        flags.DEFINE_string('config_override', '',
                            'pipeline_pb2.TrainEvalPipelineConfig '
                            'text proto to override pipeline_config_path.')
        flags.DEFINE_boolean('write_inference_graph', False,
                            'If true, writes inference graph to disk.')
        self.FLAGS = flags.FLAGS

        #############################################################################



    # method to get latest checkpoint files
    def get_latest_checkpoints(self, trainingDir):

        # getting list of all meta files
        metaFiles = glob.glob(trainingDir + '/*.meta')

        tempList = []
        # sorting based on num_steps
        for _file in metaFiles:
            tempList.append(int(re.findall(r'[0-9]+', os.path.basename(_file))[0]))

        tempList.sort(reverse = True)

        # returning path of latest checkpoint file
        return trainingDir + '/model.ckpt-' + str(tempList[0])


    # parsing flags and exporting graphs
    def export(self, pipeline_config_path, trained_checkpoint_dir, output_directory):

        # path to store exported inference graphs
        if not os.path.exists(output_directory):
            os.makedirs(output_directory)

        # getting latest checkpoint file
        self.trained_checkpoint_prefix = self.get_latest_checkpoints(trained_checkpoint_dir)

        print(self.trained_checkpoint_prefix)

        self.pipeline_config_path = pipeline_config_path
        self.output_directory = output_directory


        #############################################################################
        '''
        code used form export_inference_graph.py file from Tensorflow
        '''
        #############################################################################

        pipeline_config = pipeline_pb2.TrainEvalPipelineConfig()

        with tf.gfile.GFile(self.pipeline_config_path, 'r') as f:
            text_format.Merge(f.read(), pipeline_config)
        text_format.Merge(self.FLAGS.config_override, pipeline_config)
        if self.FLAGS.input_shape:
            input_shape = [
                int(dim) if dim != '-1' else None
                for dim in self.FLAGS.input_shape.split(',')
            ]
        else:
            input_shape = None

        exporter.export_inference_graph(
            self.FLAGS.input_type, pipeline_config, self.trained_checkpoint_prefix,
            self.output_directory, input_shape = input_shape,
            write_inference_graph = self.FLAGS.write_inference_graph)

        #############################################################################

Это фрагмент кода, который показывает, как я вызываю методы для двух разных моделей:

export = ExportInferenceGraph()

export.export(pipeline_config_path = TRAIN_CONFIG_FILES[0], 
                trained_checkpoint_dir = MODEL_TRAIN_DIRS[0], 
                output_directory = INFERENCE_SUB_DIRS[0])

export.export(pipeline_config_path = TRAIN_CONFIG_FILES[1], 
                trained_checkpoint_dir = MODEL_TRAIN_DIRS[1], 
                output_directory = INFERENCE_SUB_DIRS[1])

Но я получаю следующее ошибка:

2020-01-22 17:42:47.520891: W tensorflow/core/framework/op_kernel.cc:1502] OP_REQUIRES failed at save_restore_v2_ops.cc:184 : Not 
found: Key BoxPredictor_0/BoxEncodingPredictor/biases not found in checkpoint
Traceback (most recent call last):
  File "C:\Users\Lenovo\Anaconda3\envs\wsp\lib\site-packages\tensorflow\python\client\session.py", line 1356, in _do_call
    return fn(*args)
  File "C:\Users\Lenovo\Anaconda3\envs\wsp\lib\site-packages\tensorflow\python\client\session.py", line 1341, in _run_fn
    options, feed_dict, fetch_list, target_list, run_metadata)
  File "C:\Users\Lenovo\Anaconda3\envs\wsp\lib\site-packages\tensorflow\python\client\session.py", line 1429, in _call_tf_sessionrun
    run_metadata)
tensorflow.python.framework.errors_impl.NotFoundError: Key BoxPredictor_0/BoxEncodingPredictor/biases not found in checkpoint     
         [[{{node save_1/RestoreV2}}]]

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
  File "C:\Users\Lenovo\Anaconda3\envs\wsp\lib\site-packages\tensorflow\python\training\saver.py", line 1286, in restore
    {self.saver_def.filename_tensor_name: save_path})
  File "C:\Users\Lenovo\Anaconda3\envs\wsp\lib\site-packages\tensorflow\python\client\session.py", line 950, in run
    run_metadata_ptr)
  File "C:\Users\Lenovo\Anaconda3\envs\wsp\lib\site-packages\tensorflow\python\client\session.py", line 1173, in _run
    feed_dict_tensor, options, run_metadata)
  File "C:\Users\Lenovo\Anaconda3\envs\wsp\lib\site-packages\tensorflow\python\client\session.py", line 1350, in _do_run
    run_metadata)
  File "C:\Users\Lenovo\Anaconda3\envs\wsp\lib\site-packages\tensorflow\python\client\session.py", line 1370, in _do_call
    raise type(e)(node_def, op, message)
tensorflow.python.framework.errors_impl.NotFoundError: Key BoxPredictor_0/BoxEncodingPredictor/biases not found in checkpoint     
         [[node save_1/RestoreV2 (defined at ../TensorFlow/models/research\object_detection\exporter.py:323) ]]

Original stack trace for 'save_1/RestoreV2':
  File "ocr_train.py", line 99, in <module>
    output_directory = INFERENCE_SUB_DIRS[1])
  File "D:\shubham\wsp\OCR\export_inference_graph.py", line 109, in export
    write_inference_graph = self.FLAGS.write_inference_graph)
  File "../TensorFlow/models/research\object_detection\exporter.py", line 489, in export_inference_graph
    write_inference_graph=write_inference_graph)
  File "../TensorFlow/models/research\object_detection\exporter.py", line 418, in _export_inference_graph
    trained_checkpoint_prefix=checkpoint_to_use)
  File "../TensorFlow/models/research\object_detection\exporter.py", line 323, in write_graph_and_checkpoint
    tf.import_graph_def(inference_graph_def, name='')
  File "C:\Users\Lenovo\Anaconda3\envs\wsp\lib\site-packages\tensorflow\python\util\deprecation.py", line 507, in new_func        
    return func(*args, **kwargs)
  File "C:\Users\Lenovo\Anaconda3\envs\wsp\lib\site-packages\tensorflow\python\framework\importer.py", line 443, in import_graph_def
    _ProcessNewOps(graph)
  File "C:\Users\Lenovo\Anaconda3\envs\wsp\lib\site-packages\tensorflow\python\framework\importer.py", line 236, in _ProcessNewOps
    for new_op in graph._add_new_tf_operations(compute_devices=False):  # pylint: disable=protected-access
  File "C:\Users\Lenovo\Anaconda3\envs\wsp\lib\site-packages\tensorflow\python\framework\ops.py", line 3751, in _add_new_tf_operations
    for c_op in c_api_util.new_tf_operations(self)
  File "C:\Users\Lenovo\Anaconda3\envs\wsp\lib\site-packages\tensorflow\python\framework\ops.py", line 3751, in <listcomp>        
    for c_op in c_api_util.new_tf_operations(self)
  File "C:\Users\Lenovo\Anaconda3\envs\wsp\lib\site-packages\tensorflow\python\framework\ops.py", line 3641, in _create_op_from_tf_operation
    ret = Operation(c_op, self)
  File "C:\Users\Lenovo\Anaconda3\envs\wsp\lib\site-packages\tensorflow\python\framework\ops.py", line 2005, in __init__
    self._traceback = tf_stack.extract_stack()


During handling of the above exception, another exception occurred:

Traceback (most recent call last):
  File "C:\Users\Lenovo\Anaconda3\envs\wsp\lib\site-packages\tensorflow\python\training\saver.py", line 1296, in restore
    names_to_keys = object_graph_key_mapping(save_path)
  File "C:\Users\Lenovo\Anaconda3\envs\wsp\lib\site-packages\tensorflow\python\training\saver.py", line 1614, in object_graph_key_mapping
    object_graph_string = reader.get_tensor(trackable.OBJECT_GRAPH_PROTO_KEY)
  File "C:\Users\Lenovo\Anaconda3\envs\wsp\lib\site-packages\tensorflow\python\pywrap_tensorflow_internal.py", line 678, in get_tensor
    return CheckpointReader_GetTensor(self, compat.as_bytes(tensor_str))
tensorflow.python.framework.errors_impl.NotFoundError: Key _CHECKPOINTABLE_OBJECT_GRAPH not found in checkpoint

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
  File "ocr_train.py", line 99, in <module>
    output_directory = INFERENCE_SUB_DIRS[1])
  File "D:\shubham\wsp\OCR\export_inference_graph.py", line 109, in export
    write_inference_graph = self.FLAGS.write_inference_graph)
  File "../TensorFlow/models/research\object_detection\exporter.py", line 489, in export_inference_graph
    write_inference_graph=write_inference_graph)
  File "../TensorFlow/models/research\object_detection\exporter.py", line 418, in _export_inference_graph
    trained_checkpoint_prefix=checkpoint_to_use)
  File "../TensorFlow/models/research\object_detection\exporter.py", line 327, in write_graph_and_checkpoint
    saver.restore(sess, trained_checkpoint_prefix)
  File "C:\Users\Lenovo\Anaconda3\envs\wsp\lib\site-packages\tensorflow\python\training\saver.py", line 1302, in restore
    err, "a Variable name or other graph key that is missing")
tensorflow.python.framework.errors_impl.NotFoundError: Restoring from checkpoint failed. This is most likely due to a Variable name or other graph key that is missing from the checkpoint. Please ensure that you have not altered the graph expected based on the 
checkpoint. Original error:

Key BoxPredictor_0/BoxEncodingPredictor/biases not found in checkpoint
         [[node save_1/RestoreV2 (defined at ../TensorFlow/models/research\object_detection\exporter.py:323) ]]

Original stack trace for 'save_1/RestoreV2':
  File "ocr_train.py", line 99, in <module>
    output_directory = INFERENCE_SUB_DIRS[1])
  File "D:\shubham\wsp\OCR\export_inference_graph.py", line 109, in export
    write_inference_graph = self.FLAGS.write_inference_graph)
  File "../TensorFlow/models/research\object_detection\exporter.py", line 489, in export_inference_graph
    write_inference_graph=write_inference_graph)
  File "../TensorFlow/models/research\object_detection\exporter.py", line 418, in _export_inference_graph
    trained_checkpoint_prefix=checkpoint_to_use)
  File "../TensorFlow/models/research\object_detection\exporter.py", line 323, in write_graph_and_checkpoint
    tf.import_graph_def(inference_graph_def, name='')
  File "C:\Users\Lenovo\Anaconda3\envs\wsp\lib\site-packages\tensorflow\python\util\deprecation.py", line 507, in new_func        
    return func(*args, **kwargs)
  File "C:\Users\Lenovo\Anaconda3\envs\wsp\lib\site-packages\tensorflow\python\framework\importer.py", line 443, in import_graph_def
    _ProcessNewOps(graph)
  File "C:\Users\Lenovo\Anaconda3\envs\wsp\lib\site-packages\tensorflow\python\framework\importer.py", line 236, in _ProcessNewOps
    for new_op in graph._add_new_tf_operations(compute_devices=False):  # pylint: disable=protected-access
  File "C:\Users\Lenovo\Anaconda3\envs\wsp\lib\site-packages\tensorflow\python\framework\ops.py", line 3751, in _add_new_tf_operations
    for c_op in c_api_util.new_tf_operations(self)
  File "C:\Users\Lenovo\Anaconda3\envs\wsp\lib\site-packages\tensorflow\python\framework\ops.py", line 3751, in <listcomp>        
    for c_op in c_api_util.new_tf_operations(self)
  File "C:\Users\Lenovo\Anaconda3\envs\wsp\lib\site-packages\tensorflow\python\framework\ops.py", line 3641, in _create_op_from_tf_operation
    ret = Operation(c_op, self)
  File "C:\Users\Lenovo\Anaconda3\envs\wsp\lib\site-packages\tensorflow\python\framework\ops.py", line 2005, in __init__
    self._traceback = tf_stack.extract_stack()

ПРИМЕЧАНИЕ. Я мог видеть, что первый график успешно экспортирован, но он выдает ошибку для второго графика. Я обменивался вызовом методов экспорта, он все еще не удался при втором экспорте.

Я все еще новичок в Tensorflow и мне нужна помощь здесь. Я предполагаю, что он использует тот же график, который он создал для первой модели.

Answer 1

Я копаю глубоко в каталог Tensorflow и дошел до метода _export_inference_graph . Путь TensorFlow / models / research / object_detection / exporter.py . Добавление этой строки в конце функции решило мою проблему.

tf.reset_default_graph()