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NotFoundError: encountered while running function tf.train.latest_checkpoint() in predict.py #13

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bhanu-sharma opened this issue Oct 9, 2017 · 3 comments

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@bhanu-sharma
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Both the model and the checkpoints exist in the same directory. This is the error i encounter when i try to run the file.

NotFoundError                    Traceback (most recent call last)
<ipython-input-60-8de4d687f60c> in <module>()
  5     checkpoint_dir += '/'
  6 print (checkpoint_dir + 'checkpoints')
  ----> 7 checkpoint_file = tf.train.latest_checkpoint(checkpoint_dir +    'checkpoints')
  8 print (checkpoint_file)

  /usr/local/lib/python3.5/dist-packages/tensorflow/python/training/saver.py in latest_checkpoint(checkpoint_dir, latest_filename)
 1612     v1_path = _prefix_to_checkpoint_path(ckpt.model_checkpoint_path,
 1613                                          saver_pb2.SaverDef.V1)
 -> 1614     if file_io.get_matching_files(v2_path) or     file_io.get_matching_files(
 1615         v1_path):
 1616       return ckpt.model_checkpoint_path

 /usr/local/lib/python3.5/dist-packages/tensorflow/python/lib/io/file_io.py in get_matching_files(filename)
 330           # Convert the filenames to string from bytes.
 331           compat.as_str_any(matching_filename)
 --> 332           for single_filename in filename
 333           for matching_filename in pywrap_tensorflow.GetMatchingFiles(
 334               compat.as_bytes(single_filename), status)

/usr/lib/python3.5/contextlib.py in __exit__(self, type, value, traceback)
 64         if type is None:
 65             try:
 ---> 66                 next(self.gen)
 67             except StopIteration:
 68                 return

/usr/local/lib/python3.5/dist-packages/tensorflow/python/framework/errors_impl.py in raise_exception_on_not_ok_status()
464           None, None,
465           compat.as_text(pywrap_tensorflow.TF_Message(status)),
--> 466           pywrap_tensorflow.TF_GetCode(status))
467   finally:
468     pywrap_tensorflow.TF_DeleteStatus(status)

NotFoundError: /home/user/cnn-model/trained_model_1506946529/checkpoints

@jiegzhan
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jiegzhan commented Nov 1, 2017

~/Desktop/multi-class-text-classification-cnn/trained_model_1509570669/checkpoints$ ls
checkpoint model-1000.meta model-1200.meta model-1400.meta model-600.meta model-800.meta
model-1000.data-00000-of-00001 model-1200.data-00000-of-00001 model-1400.data-00000-of-00001 model-600.data-00000-of-00001 model-800.data-00000-of-00001
model-1000.index model-1200.index model-1400.index model-600.index model-800.index
~/Desktop/multi-class-text-classification-cnn/trained_model_1509570669/checkpoints$ ls ../../trained_model_1479757124/

Got a trained_model_1509570669 folder.

@jiegzhan
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jiegzhan commented Nov 1, 2017

~/Desktop/multi-class-text-classification-cnn$ python3 predict.py ./trained_model_1509570669/ ./data/small_samples.json
CRITICAL:root:Loaded the trained model: /home/ai-admin/Desktop/multi-class-text-classification-cnn/trained_model_1509570669/checkpoints/model-1400
INFO:root:The number of x_test: 1000
INFO:root:The number of y_test: 1000
2017-11-01 21:30:05.576209: W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use SSE4.1 instructions, but these are available on your machine and could speed up CPU computations.
2017-11-01 21:30:05.576240: W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use SSE4.2 instructions, but these are available on your machine and could speed up CPU computations.
2017-11-01 21:30:05.576247: W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use AVX instructions, but these are available on your machine and could speed up CPU computations.
2017-11-01 21:30:05.576258: W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use AVX2 instructions, but these are available on your machine and could speed up CPU computations.
2017-11-01 21:30:05.576268: W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use FMA instructions, but these are available on your machine and could speed up CPU computations.
NVIDIA: no NVIDIA devices found
2017-11-01 21:30:05.585781: E tensorflow/stream_executor/cuda/cuda_driver.cc:406] failed call to cuInit: CUDA_ERROR_UNKNOWN
2017-11-01 21:30:05.585827: I tensorflow/stream_executor/cuda/cuda_diagnostics.cc:145] kernel driver does not appear to be running on this host: /proc/driver/nvidia/version does not exist
INFO:tensorflow:Restoring parameters from /home/ai-admin/Desktop/multi-class-text-classification-cnn/trained_model_1509570669/checkpoints/model-1400
INFO:tensorflow:Restoring parameters from /home/ai-admin/Desktop/multi-class-text-classification-cnn/trained_model_1509570669/checkpoints/model-1400
CRITICAL:root:The accuracy is: 0.741

@bhanu-sharma
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bhanu-sharma commented Nov 3, 2017

Thank you. Though i saved the model as a ckpt file and to call the model ran these commands

saver = tf.train.import_meta_graph(checkpoint_dir + 'checkpoints/generator.ckpt.meta')  
saver.restore(sess, tf.train.latest_checkpoint(checkpoint_dir + 'checkpoints'))   

The prediction script worked for me then.
You can now close the issue if you like, it's resolved from my side.

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