I'm learning at www.coursera.org/learn/sequence-models-tensorflow-gcp/gradedLti/tKjLT/qwiklabs-using-linear-models-for-sequences. I followed the instruction to setup the Qwiklabs/GCP and when I reached following code block, an error encountered. Tried to re-setup the env, switch python 2/3 sinewaves.ipynb, still not working.
WARNING:tensorflow:From sinemodel/model.py:23: The name tf.logging.set_verbosity is deprecated. Please use tf.compat.v1.logging.set_verbosity instead.
WARNING:tensorflow:From sinemodel/model.py:23: The name tf.logging.INFO is deprecated. Please use tf.compat.v1.logging.INFO instead.
WARNING:tensorflow:From sinemodel/model.py:212: The name tf.summary.FileWriterCache is deprecated. Please use tf.compat.v1.summary.FileWriterCache instead.
INFO:tensorflow:TF_CONFIG environment variable: {u'environment': u'cloud', u'cluster': {}, u'job': {u'args': [u'--train_data_path=/home/jupyter/training-data-analyst/courses/machine_learning/deepdive/09_sequence/labs/data/sines/train-1.csv', u'--eval_data_path=/home/jupyter/training-data-analyst/courses/machine_learning/deepdive/09_sequence/labs/data/sines/valid-1.csv', u'--output_dir=/home/jupyter/training-data-analyst/courses/machine_learning/deepdive/09_sequence/labs/trained/sines', u'--model=dnn', u'--train_steps=10', u'--sequence_length=50'], u'job_name': u'sinemodel.task'}, u'task': {}}
INFO:tensorflow:Using config: {'_save_checkpoints_secs': 60, '_num_ps_replicas': 0, '_keep_checkpoint_max': 5, '_task_type': 'worker', '_global_id_in_cluster': 0, '_is_chief': True, '_cluster_spec': <tensorflow.python.training.server_lib.ClusterSpec object at 0x7f163ba32d50>, '_model_dir': '/home/jupyter/training-data-analyst/courses/machine_learning/deepdive/09_sequence/labs/trained/sines/', '_protocol': None, '_save_checkpoints_steps': None, '_keep_checkpoint_every_n_hours': 10000, '_service': None, '_session_config': allow_soft_placement: true
graph_options {
rewrite_options {
meta_optimizer_iterations: ONE
}
}
, '_tf_random_seed': None, '_save_summary_steps': 100, '_device_fn': None, '_experimental_distribute': None, '_num_worker_replicas': 1, '_task_id': 0, '_log_step_count_steps': 100, '_experimental_max_worker_delay_secs': None, '_evaluation_master': '', '_eval_distribute': None, '_train_distribute': None, '_master': ''}
INFO:tensorflow:Not using Distribute Coordinator.
INFO:tensorflow:Running training and evaluation locally (non-distributed).
INFO:tensorflow:Start train and evaluate loop. The evaluate will happen after every checkpoint. Checkpoint frequency is determined based on RunConfig arguments: save_checkpoints_steps None or save_checkpoints_secs 60.
WARNING:tensorflow:From /usr/local/lib/python2.7/dist-packages/tensorflow/python/training/training_util.py:236: initialized_value (from tensorflow.python.ops.variables) is deprecated and will be removed in a future version.
Instructions for updating:
Use Variable.read_value. Variables in 2.X are initialized automatically both in eager and graph (inside tf.defun) contexts.
WARNING:tensorflow:From sinemodel/model.py:93: The name tf.decode_csv is deprecated. Please use tf.io.decode_csv instead.
WARNING:tensorflow:From sinemodel/model.py:112: make_one_shot_iterator (from tensorflow.python.data.ops.dataset_ops) is deprecated and will be removed in a future version.
Instructions for updating:
Use `for ... in dataset:` to iterate over a dataset. If using `tf.estimator`, return the `Dataset` object directly from your input function. As a last resort, you can use `tf.compat.v1.data.make_one_shot_iterator(dataset)`.
INFO:tensorflow:Calling model_fn.
Traceback (most recent call last):
File "/usr/lib/python2.7/runpy.py", line 174, in _run_module_as_main
"__main__", fname, loader, pkg_name)
File "/usr/lib/python2.7/runpy.py", line 72, in _run_code
exec code in run_globals
File "/home/jupyter/training-data-analyst/courses/machine_learning/deepdive/09_sequence/labs/sinemodel/task.py", line 123, in <module>
model.train_and_evaluate(output_dir, hparams)
File "sinemodel/model.py", line 233, in train_and_evaluate
tf.estimator.train_and_evaluate(estimator, train_spec, eval_spec)
File "/usr/local/lib/python2.7/dist-packages/tensorflow_estimator/python/estimator/training.py", line 473, in train_and_evaluate
return executor.run()
File "/usr/local/lib/python2.7/dist-packages/tensorflow_estimator/python/estimator/training.py", line 613, in run
return self.run_local()
File "/usr/local/lib/python2.7/dist-packages/tensorflow_estimator/python/estimator/training.py", line 714, in run_local
saving_listeners=saving_listeners)
File "/usr/local/lib/python2.7/dist-packages/tensorflow_estimator/python/estimator/estimator.py", line 367, in train
loss = self._train_model(input_fn, hooks, saving_listeners)
File "/usr/local/lib/python2.7/dist-packages/tensorflow_estimator/python/estimator/estimator.py", line 1158, in _train_model
return self._train_model_default(input_fn, hooks, saving_listeners)
File "/usr/local/lib/python2.7/dist-packages/tensorflow_estimator/python/estimator/estimator.py", line 1188, in _train_model_default
features, labels, ModeKeys.TRAIN, self.config)
File "/usr/local/lib/python2.7/dist-packages/tensorflow_estimator/python/estimator/estimator.py", line 1146, in _call_model_fn
model_fn_results = self._model_fn(features=features, **kwargs)
File "sinemodel/model.py", line 175, in sequence_regressor
loss, rmse = compute_errors(features, labels, predictions)
File "sinemodel/model.py", line 134, in compute_errors
if predictions.shape[1] == 1:
AttributeError: 'NoneType' object has no attribute 'shape'
imp8468
commented
4 years ago
I'm learning at
www.coursera.org/learn/sequence-models-tensorflow-gcp/gradedLti/tKjLT/qwiklabs-using-linear-models-for-sequences. I followed the instruction to setup the Qwiklabs/GCP and when I reached following code block, an error encountered. Tried to re-setup the env, switch python 2/3 sinewaves.ipynb, still not working.filepath:
training-data-analyst/courses/machine_learning/deepdive/09_sequence/labs/sinewaves.ipynbcode block