Я следую этому уроку https://hackernoon.com/object-detection-in-google-colab-with-custom-dataset-5a7bb2b0e97e от RomRoc, и столкнулся с проблемой из lookup_ops.py (для Python 2.7 из TensorFlow 1.12).Кто-нибудь знает, как работает эта часть TensorFlow и может подсказать, что может быть не так?Вот вызов model_main.py, который выдает ошибку,
!python ~/models/research/object_detection/model_main.py \
--pipeline_config_path=/root/models/research/object_detection/samples/configs/faster_rcnn_inception_v2_pets.config \
--model_dir=/root/datalab/trained \
--alsologtostderr \
--num_train_steps=3000 \
--num_eval_steps=500
И трассировка стека,
/root/datalab
/root/models/research/object_detection/utils/visualization_utils.py:26: UserWarning:
This call to matplotlib.use() has no effect because the backend has already
been chosen; matplotlib.use() must be called *before* pylab, matplotlib.pyplot,
or matplotlib.backends is imported for the first time.
The backend was *originally* set to 'module://ipykernel.pylab.backend_inline' by the following code:
File "/root/models/research/object_detection/model_main.py", line 26, in <module>
from object_detection import model_lib
File "/root/models/research/object_detection/model_lib.py", line 27, in <module>
from object_detection import eval_util
File "/root/models/research/object_detection/eval_util.py", line 27, in <module>
from object_detection.metrics import coco_evaluation
File "/root/models/research/object_detection/metrics/coco_evaluation.py", line 20, in <module>
from object_detection.metrics import coco_tools
File "/root/models/research/object_detection/metrics/coco_tools.py", line 47, in <module>
from pycocotools import coco
File "/usr/local/lib/python2.7/dist-packages/pycocotools/coco.py", line 49, in <module>
import matplotlib.pyplot as plt
File "/usr/local/lib/python2.7/dist-packages/matplotlib/pyplot.py", line 72, in <module>
from matplotlib.backends import pylab_setup
File "/usr/local/lib/python2.7/dist-packages/matplotlib/backends/__init__.py", line 14, in <module>
line for line in traceback.format_stack()
import matplotlib; matplotlib.use('Agg') # pylint: disable=multiple-statements
WARNING:tensorflow:Forced number of epochs for all eval validations to be 1.
WARNING:tensorflow:Expected number of evaluation epochs is 1, but instead encountered `eval_on_train_input_config.num_epochs` = 0. Overwriting `num_epochs` to 1.
WARNING:tensorflow:Estimator's model_fn (<function model_fn at 0x7f0dbdee1230>) includes params argument, but params are not passed to Estimator.
/root/models/research/object_detection/utils/label_map_util.py:138: RuntimeWarning: Unexpected end-group tag: Not all data was converted
label_map.ParseFromString(label_map_string)
WARNING:tensorflow:num_readers has been reduced to 1 to match input file shards.
WARNING:tensorflow:From /root/models/research/object_detection/builders/dataset_builder.py:80: parallel_interleave (from tensorflow.contrib.data.python.ops.interleave_ops) is deprecated and will be removed in a future version.
Instructions for updating:
Use `tf.data.experimental.parallel_interleave(...)`.
WARNING:tensorflow:From /usr/local/lib/python2.7/dist-packages/tensorflow/python/ops/sparse_ops.py:1165: sparse_to_dense (from tensorflow.python.ops.sparse_ops) is deprecated and will be removed in a future version.
Instructions for updating:
Create a `tf.sparse.SparseTensor` and use `tf.sparse.to_dense` instead.
Traceback (most recent call last):
File "/root/models/research/object_detection/model_main.py", line 109, in <module>
tf.app.run()
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/platform/app.py", line 125, in run
_sys.exit(main(argv))
File "/root/models/research/object_detection/model_main.py", line 105, in main
tf.estimator.train_and_evaluate(estimator, train_spec, eval_specs[0])
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/estimator/training.py", line 471, in train_and_evaluate
return executor.run()
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/estimator/training.py", line 610, in run
return self.run_local()
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/estimator/training.py", line 711, in run_local
saving_listeners=saving_listeners)
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/estimator/estimator.py", line 354, in train
loss = self._train_model(input_fn, hooks, saving_listeners)
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/estimator/estimator.py", line 1207, in _train_model
return self._train_model_default(input_fn, hooks, saving_listeners)
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/estimator/estimator.py", line 1234, in _train_model_default
input_fn, model_fn_lib.ModeKeys.TRAIN))
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/estimator/estimator.py", line 1075, in _get_features_and_labels_from_input_fn
self._call_input_fn(input_fn, mode))
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/estimator/estimator.py", line 1162, in _call_input_fn
return input_fn(**kwargs)
File "/root/models/research/object_detection/inputs.py", line 488, in _train_input_fn
batch_size=params['batch_size'] if params else train_config.batch_size)
File "/root/models/research/object_detection/builders/dataset_builder.py", line 145, in build
num_parallel_calls=num_parallel_calls)
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/data/ops/dataset_ops.py", line 1040, in map
return ParallelMapDataset(self, map_func, num_parallel_calls)
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/data/ops/dataset_ops.py", line 2649, in __init__
use_inter_op_parallelism)
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/data/ops/dataset_ops.py", line 2611, in __init__
map_func, "Dataset.map()", input_dataset)
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/data/ops/dataset_ops.py", line 1860, in __init__
self._function.add_to_graph(ops.get_default_graph())
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/framework/function.py", line 479, in add_to_graph
self._create_definition_if_needed()
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/framework/function.py", line 335, in _create_definition_if_needed
self._create_definition_if_needed_impl()
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/framework/function.py", line 344, in _create_definition_if_needed_impl
self._capture_by_value, self._caller_device)
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/framework/function.py", line 864, in func_graph_from_py_func
outputs = func(*func_graph.inputs)
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/data/ops/dataset_ops.py", line 1794, in tf_data_structured_function_wrapper
ret = func(*nested_args)
File "/root/models/research/object_detection/builders/dataset_builder.py", line 127, in process_fn
processed_tensors = decoder.decode(value)
File "/root/models/research/object_detection/data_decoders/tf_example_decoder.py", line 363, in decode
tensors = decoder.decode(serialized_example, items=keys)
File "/usr/local/lib/python2.7/dist-packages/tensorflow/contrib/slim/python/slim/data/tfexample_decoder.py", line 525, in decode
outputs.append(handler.tensors_to_item(keys_to_tensors))
File "/root/models/research/object_detection/data_decoders/tf_example_decoder.py", line 117, in tensors_to_item
item = self._handler.tensors_to_item(keys_to_tensors)
File "/root/models/research/object_detection/data_decoders/tf_example_decoder.py", line 86, in tensors_to_item
return tf.maximum(self._name_to_id_table.lookup(unmapped_tensor),
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/ops/lookup_ops.py", line 224, in lookup
(self._key_dtype, keys.dtype))
TypeError: Signature mismatch. Keys must be dtype <dtype: 'float32'>, got <dtype: 'string'>.
Вот код из учебника: https://github.com/RomRoc/objdet_train_tensorflow_colab/blob/master/objdet_custom_tf_colab.ipynb
Я точно следовал учебному пособию, но использовал свои собственные данные тренировок.Мне пришлось внести некоторые изменения в create_pet_tf_record.py, чтобы заставить эту часть работать.Можете ли вы помочь мне понять, как это отладить?Спасибо!
Вот значение keys, которое передается функции lookup() в lookup_ops.py, вызывающей проблему:
Tensor("SparseToDense:0", shape=(?,), dtype=string, device=/device:CPU:0)
РЕДАКТИРОВАТЬ: Может быть потому, что он должен использовать GPU?Обнаружен графический процессор ...
from tensorflow.python.client import device_lib
device_lib.list_local_devices()
[name: "/device:CPU:0"
device_type: "CPU"
memory_limit: 268435456
locality {
}
incarnation: 6030853355760210263, name: "/device:XLA_CPU:0"
device_type: "XLA_CPU"
memory_limit: 17179869184
locality {
}
incarnation: 8061591699314310064
physical_device_desc: "device: XLA_CPU device", name: "/device:XLA_GPU:0"
device_type: "XLA_GPU"
memory_limit: 17179869184
locality {
}
incarnation: 1730080795414704681
physical_device_desc: "device: XLA_GPU device", name: "/device:GPU:0"
device_type: "GPU"
memory_limit: 11281553818
locality {
bus_id: 1
links {
}
}
incarnation: 5476104669001907939
physical_device_desc: "device: 0, name: Tesla K80, pci bus id: 0000:00:04.0, compute capability: 3.7"]