8000 iris_monitors.py broken in release r1.0 due to inacurate MetricSpec namespace · Issue #7637 · tensorflow/tensorflow · GitHub
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chidochipotle opened this issue Feb 17, 2017 · 4 comments
Closed

iris_monitors.py broken in release r1.0 due to inacurate MetricSpec namespace #7637

chidochipotle opened this issue Feb 17, 2017 · 4 comments

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@chidochipotle
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chidochipotle commented Feb 17, 2017 •
edited
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tf.contrib.learn.metric_spec.MetricSpec should be changed to MetricSpec in iris_monitors.py in release 1.0.0

No need to import MetricSpec in iris_monitors.py it's already imported on line 24 in commit fa4ba830f437fdb9dc1085b4d68a3bab41a16e20:
tensorflow.contrib.learn.python.learn.metric_spec import MetricSpec

Environment info

Operating System:

tensorflow/tensorflow/examples/tutorials/monitors$ lsb_release -a
No LSB modules are available.
Distributor ID: Ubuntu
Description: Ubuntu 16.04.1 LTS
Release: 16.04
Codename: xenial
tensorflow/tensorflow/examples/tutorials/monitors$ uname -a
Linux panchito 4.4.0-62-generic-tuxonice #83~ppa1-Ubuntu SMP Thu Feb 2 23:17:45 UTC 2017 x86_64 x86_64 x86_64 GNU/Linux

Installed version of CUDA and cuDNN:
(please attach the output of ls -l /path/to/cuda/lib/libcud*):

If installed from binary pip package, provide:

  1. A link to the pip package you installed:
  2. The output from python -c "import tensorflow; print(tensorflow.__version__)".
repositories/tensorflow/tensorflow/examples/tutorials/monitors$ python -c "import tensorflow; print(tensorflow.__version__)"
1.0.0

If installed from source, provide

  1. The commit hash (git rev-parse HEAD)
  2. The output of bazel version

If possible, provide a minimal reproducible example (We usually don't have time to read hundreds of lines of your code)

repositories/tensorflow/tensorflow/examples/tutorials/monitors$ python iris_monitors.py
Traceback (most recent call last):
File "iris_monitors.py", line 116, in
tf.app.run()
File "/home/chidochipotle/anaconda3/lib/python3.5/site-packages/tensorflow/python/platform/app.py", line 44, in run
_sys.exit(main(_sys.argv[:1] + flags_passthrough))
File "iris_monitors.py", line 42, in main
tf.contrib.learn.metric_spec.MetricSpec(
AttributeError: module 'tensorflow.contrib.learn' has no attribute 'metric_spec'

What other attempted solutions have you tried?

Logs or other output that would be helpful

(If logs are large, please upload as attachment or provide link).
@chidochipotle chidochipotle changed the title iris_monitors.py broken in release 1.0.0 due to incorrect MetricSpec namespace iris_monitors.py broken in release r1.0 due to incorrect MetricSpec namespace Feb 17, 2017
@chidochipotle chidochipotle changed the title iris_monitors.py broken in release r1.0 due to incorrect MetricSpec namespace iris_monitors.py broken in release r1.0 due to inacurate MetricSpec namespace Feb 17, 2017
@chidochipotle
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chidochipotle commented Feb 17, 2017 •
edited
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Needs many more changes to work, iris_monitors.py seems to be is totally broken with r1.0 or I am just too newbie to understand what's wrong ...

After fixing a couple of more inaccurate imports I get lots of warnings when I run it:

dkor@panchito:~/repositories/tensorflow/tensorflow/examples/tutorials/monitors$ python iris_monitors.py 
WARNING:tensorflow:From /home/dkor/anaconda3/lib/python3.5/site-packages/tensorflow/contrib/learn/python/learn/monitors.py:322: BaseMonitor.__init__ (from tensorflow.contrib.learn.python.learn.monitors) is deprecated and will be removed after 2016-12-05.
Instructions for updating:
Monitors are deprecated. Please use tf.train.SessionRunHook.
WARNING:tensorflow:From /home/dkor/anaconda3/lib/python3.5/site-packages/tensorflow/contrib/learn/python/learn/monitors.py:322: BaseMonitor.__init__ (from tensorflow.contrib.learn.python.learn.monitors) is deprecated and will be removed after 2016-12-05.
Instructions for updating:
Monitors are deprecated. Please use tf.train.SessionRunHook.
INFO:tensorflow:Using config: {'_cluster_spec': <tensorflow.python.training.server_lib.ClusterSpec object at 0x7fdc67b414e0>, '_is_chief': True, '_tf_random_seed': None, '_task_type': None, '_keep_checkpoint_max': 5, '_master': '', '_keep_checkpoint_every_n_hours': 10000, '_save_summary_steps': 100, '_environment': 'local', '_save_checkpoints_secs': 1, '_num_ps_replicas': 0, '_tf_config': gpu_options {
  per_process_gpu_memory_fraction: 1
}
, '_save_checkpoints_steps': None, '_task_id': 0, '_evaluation_master': ''}
/home/dkor/anaconda3/lib/python3.5/site-packages/tensorflow/python/util/deprecation.py:247: FutureWarning: comparison to `None` will result in an elementwise object comparison in the future.
  equality = a == b
WARNING:tensorflow:From iris_monitors.py:104: calling BaseEstimator.fit (from tensorflow.contrib.learn.python.learn.estimators.estimator) with x is deprecated and will be removed after 2016-12-01.
Instructions for updating:
Estimator is decoupled from Scikit Learn interface by moving into
separate class SKCompat. Arguments x, y and batch_size are only
available in the SKCompat class, Estimator will only accept input_fn.
Example conversion:
  est = Estimator(...) -> est = SKCompat(Estimator(...))
WARNING:tensorflow:From iris_monitors.py:104: calling BaseEstimator.fit (from tensorflow.contrib.learn.python.learn.estimators.estimator) with y is deprecated and will be removed after 2016-12-01.
Instructions for updating:
Estimator is decoupled from Scikit Learn interface by moving into
separate class SKCompat. Arguments x, y and batch_size are only
available in the SKCompat class, Estimator will only accept input_fn.
Example conversion:
  est = Estimator(...) -> est = SKCompat(Estimator(...))
WARNING:tensorflow:float64 is not supported by many models, consider casting to float32.
WARNING:tensorflow:From /home/dkor/anaconda3/lib/python3.5/site-packages/tensorflow/contrib/learn/python/learn/estimators/head.py:1362: scalar_summary (from tensorflow.python.ops.logging_ops) is deprecated and will be removed after 2016-11-30.
Instructions for updating:
Please switch to tf.summary.scalar. Note that tf.summary.scalar uses the node name instead of the tag. This means that TensorFlow will automatically de-duplicate summary names based on the scope they are created in. Also, passing a tensor or list of tags to a scalar summary op is no longer supported.
INFO:tensorflow:Create CheckpointSaverHook.
W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use SSE3 instructions, but these are available on your machine and could speed up CPU computations.
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.
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.
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.
INFO:tensorflow:Saving checkpoints for 851 into /tmp/iris_model/model.ckpt.
INFO:tensorflow:loss = 0.0496295, step = 851
WARNING:tensorflow:From /home/dkor/anaconda3/lib/python3.5/site-packages/tensorflow/contrib/learn/python/learn/monitors.py:712: calling BaseEstimator.evaluate (from tensorflow.contrib.learn.python.learn.estimators.estimator) with x is deprecated and will be removed after 2016-12-01.
Instructions for updating:
Estimator is decoupled from Scikit Learn interface by moving into
separate class SKCompat. Arguments x, y and batch_size are only
available in the SKCompat class, Estimator will only accept input_fn.
Example conversion:
  est = Estimator(...) -> est = SKCompat(Estimator(...))
WARNING:tensorflow:From /home/dkor/anaconda3/lib/python3.5/site-packages/tensorflow/contrib/learn/python/learn/monitors.py:712: calling BaseEstimator.evaluate (from tensorflow.contrib.learn.python.learn.estimators.estimator) with y is deprecated and will be removed after 2016-12-01.
Instructions for updating:
Estimator is decoupled from Scikit Learn interface by moving into
separate class SKCompat. Arguments x, y and batch_size are only
available in the SKCompat class, Estimator will only accept input_fn.
Example conversion:
  est = Estimator(...) -> est = SKCompat(Estimator(...))
WARNING:tensorflow:float64 is not supported by many models, consider casting to float32.
WARNING:tensorflow:From /home/dkor/anaconda3/lib/python3.5/site-packages/tensorflow/contrib/learn/python/learn/estimators/head.py:1362: scalar_summary (from tensorflow.python.ops.logging_ops) is deprecated and will be removed after 2016-11-30.
Instructions for updating:
Please switch to tf.summary.scalar. Note that tf.summary.scalar uses the node name instead of the tag. This means that TensorFlow will automatically de-duplicate summary names based on the scope they are created in. Also, passing a tensor or list of tags to a scalar summary op is no longer supported.
INFO:tensorflow:Starting evaluation at 2017-02-17-23:21:20
INFO:tensorflow:Finished evaluation at 2017-02-17-23:21:21
INFO:tensorflow:Saving dict for global step 851: accuracy = 0.966667, auc = 0.998333, global_step = 851, loss = 0.0598002, precision = 1.0, recall = 1.0
WARNING:tensorflow:Skipping summary for global_step, must be a float or np.float32.
INFO:tensorflow:Validation (step 851): precision = 1.0, auc = 0.998333, loss = 0.0598002, recall = 1.0, accuracy = 0.966667, global_step = 851
INFO:tensorflow:Saving checkpoints for 852 into /tmp/iris_model/model.ckpt.
WARNING:tensorflow:From /home/dkor/anaconda3/lib/python3.5/site-packages/tensorflow/contrib/learn/python/learn/monitors.py:712: calling BaseEstimator.evaluate (from tensorflow.contrib.learn.python.learn.estimators.estimator) with x is deprecated and will be removed after 2016-12-01.
Instructions for updating:
Estimator is decoupled from Scikit Learn interface by moving into
separate class SKCompat. Arguments x, y and batch_size are only
available in the SKCompat class, Estimator will only accept input_fn.
Example conversion:
  est = Estimator(...) -> est = SKCompat(Estimator(...))
WARNING:tensorflow:From /home/dkor/anaconda3/lib/python3.5/site-packages/tensorflow/contrib/learn/python/learn/monitors.py:712: calling BaseEstimator.evaluate (from tensorflow.contrib.learn.python.learn.estimators.estimator) with y is deprecated and will be removed after 2016-12-01.
Instructions for updating:
Estimator is decoupled from Scikit Learn interface by moving into
separate class SKCompat. Arguments x, y and batch_size are only
available in the SKCompat class, Estimator will only accept input_fn.
Example conversion:
  est = Estimator(...) -> est = SKCompat(Estimator(...))
WARNING:tensorflow:float64 is not supported by many models, consider casting to float32.
WARNING:tensorflow:From /home/dkor/anaconda3/lib/python3.5/site-packages/tensorflow/contrib/learn/python/learn/estimators/head.py:1362: scalar_summary (from tensorflow.python.ops.logging_ops) is deprecated and will be removed after 2016-11-30.
Instructions for updating:
Please switch to tf.summary.scalar. Note that tf.summary.scalar uses the node name instead of the tag. This means that TensorFlow will automatically de-duplicate summary names based on the scope they are created in. Also, passing a tensor or list of tags to a scalar summary op is no longer supported.
INFO:tensorflow:Starting evaluation at 2017-02-17-23:21:23
INFO:tensorflow:Finished evaluation at 2017-02-17-23:21:23
INFO:tensorflow:Saving dict for global step 852: accuracy = 0.966667, auc = 0.998333, global_step = 852, loss = 0.0556784, precision = 1.0, recall = 1.0
WARNING:tensorflow:Skipping summary for global_step, must be a float or np.float32.
INFO:tensorflow:Validation (step 901): precision = 1.0, auc = 0.998333, loss = 0.0556784, recall = 1.0, accuracy = 0.966667, global_step = 852
INFO:tensorflow:Saving checkpoints for 902 into /tmp/iris_model/model.ckpt.
INFO:tensorflow:global_step/sec: 23.6534
INFO:tensorflow:loss = 0.0484522, step = 951
WARNING:tensorflow:From /home/dkor/anaconda3/lib/python3.5/site-packages/tensorflow/contrib/learn/python/learn/monitors.py:712: calling BaseEstimator.evaluate (from tensorflow.contrib.learn.python.learn.estimators.estimator) with x is deprecated and will be removed after 2016-12-01.
Instructions for updating:
Estimator is decoupled from Scikit Learn interface by moving into
separate class SKCompat. Arguments x, y and batch_size are only
available in the SKCompat class, Estimator will only accept input_fn.
Example conversion:
  est = Estimator(...) -> est = SKCompat(Estimator(...))
WARNING:tensorflow:From /home/dkor/anaconda3/lib/python3.5/site-packages/tensorflow/contrib/learn/python/learn/monitors.py:712: calling BaseEstimator.evaluate (from tensorflow.contrib.learn.python.learn.estimators.estimator) with y is deprecated and will be removed after 2016-12-01.
Instructions for updating:
Estimator is decoupled from Scikit Learn interface by moving into
separate class SKCompat. Arguments x, y and batch_size are only
available in the SKCompat class, Estimator will only accept input_fn.
Example conversion:
  est = Estimator(...) -> est = SKCompat(Estimator(...))
WARNING:tensorflow:float64 is not supported by many models, consider casting to float32.
WARNING:tensorflow:From /home/dkor/anaconda3/lib/python3.5/site-packages/tensorflow/contrib/learn/python/learn/estimators/head.py:1362: scalar_summary (from tensorflow.python.ops.logging_ops) is deprecated and will be removed after 2016-11-30.
Instructions for updating:
Please switch to tf.summary.scalar. Note that tf.summary.scalar uses the node name instead of the tag. This means that TensorFlow will automatically de-duplicate summary names based on the scope they are created in. Also, passing a tensor or list of tags to a scalar summary op is no longer supported.
INFO:tensorflow:Starting evaluation at 2017-02-17-23:21:24
INFO:tensorflow:Finished evaluation at 2017-02-17-23:21:25
INFO:tensorflow:Saving dict for global step 902: accuracy = 0.966667, auc = 0.998333, global_step = 902, loss = 0.0556355, precision = 1.0, recall = 1.0
WARNING:tensorflow:Skipping summary for global_step, must be a float or np.float32.
INFO:tensorflow:Validation (step 951): precision = 1.0, auc = 0.998333, loss = 0.0556355, recall = 1.0, accuracy = 0.966667, global_step = 902
INFO:tenso
8000
rflow:Saving checkpoints for 952 into /tmp/iris_model/model.ckpt.
WARNING:tensorflow:From /home/dkor/anaconda3/lib/python3.5/site-packages/tensorflow/contrib/learn/python/learn/monitors.py:712: calling BaseEstimator.evaluate (from tensorflow.contrib.learn.python.learn.estimators.estimator) with x is deprecated and will be removed after 2016-12-01.
Instructions for updating:
Estimator is decoupled from Scikit Learn interface by moving into
separate class SKCompat. Arguments x, y and batch_size are only
available in the SKCompat class, Estimator will only accept input_fn.
Example conversion:
  est = Estimator(...) -> est = SKCompat(Estimator(...))
WARNING:tensorflow:From /home/dkor/anaconda3/lib/python3.5/site-packages/tensorflow/contrib/learn/python/learn/monitors.py:712: calling BaseEstimator.evaluate (from tensorflow.contrib.learn.python.learn.estimators.estimator) with y is deprecated and will be removed after 2016-12-01.
Instructions for updating:
Estimator is decoupled from Scikit Learn interface by moving into
separate class SKCompat. Arguments x, y and batch_size are only
available in the SKCompat class, Estimator will only accept input_fn.
Example conversion:
  est = Estimator(...) -> est = SKCompat(Estimator(...))
WARNING:tensorflow:float64 is not supported by many models, consider casting to float32.
WARNING:tensorflow:From /home/dkor/anaconda3/lib/python3.5/site-packages/tensorflow/contrib/learn/python/learn/estimators/head.py:1362: scalar_summary (from tensorflow.python.ops.logging_ops) is deprecated and will be removed after 2016-11-30.
Instructions for updating:
Please switch to tf.summary.scalar. Note that tf.summary.scalar uses the node name instead of the tag. This means that TensorFlow will automatically de-duplicate summary names based on the scope they are created in. Also, passing a tensor or list of tags to a scalar summary op is no longer supported.
INFO:tensorflow:Starting evaluation at 2017-02-17-23:21:26
INFO:tensorflow:Finished evaluation at 2017-02-17-23:21:26
INFO:tensorflow:Saving dict for global step 952: accuracy = 0.966667, auc = 0.998333, global_step = 952, loss = 0.0556713, precision = 1.0, recall = 1.0
WARNING:tensorflow:Skipping summary for global_step, must be a float or np.float32.
INFO:tensorflow:Validation (step 1001): precision = 1.0, auc = 0.998333, loss = 0.0556713, recall = 1.0, accuracy = 0.966667, global_step = 952
INFO:tensorflow:Saving checkpoints for 1002 into /tmp/iris_model/model.ckpt.
INFO:tensorflow:global_step/sec: 31.7257
INFO:tensorflow:loss = 0.0475382, step = 1051
WARNING:tensorflow:From /home/dkor/anaconda3/lib/python3.5/site-packages/tensorflow/contrib/learn/python/learn/monitors.py:712: calling BaseEstimator.evaluate (from tensorflow.contrib.learn.python.learn.estimators.estimator) with x is deprecated and will be removed after 2016-12-01.
Instructions for updating:
Estimator is decoupled from Scikit Learn interface by moving into
separate class SKCompat. Arguments x, y and batch_size are only
available in the SKCompat class, Estimator will only accept input_fn.
Example conversion:
  est = Estimator(...) -> est = SKCompat(Estimator(...))
WARNING:tensorflow:From /home/dkor/anaconda3/lib/python3.5/site-packages/tensorflow/contrib/learn/python/learn/monitors.py:712: calling BaseEstimator.evaluate (from tensorflow.contrib.learn.python.learn.estimators.estimator) with y is deprecated and will be removed after 2016-12-01.
Instructions for updating:
Estimator is decoupled from Scikit Learn interface by moving into
separate class SKCompat. Arguments x, y and batch_size are only
available in the SKCompat class, Estimator will only accept input_fn.
Example conversion:
  est = Estimator(...) -> est = SKCompat(Estimator(...))
WARNING:tensorflow:float64 is not supported by many models, consider casting to float32.
WARNING:tensorflow:From /home/dkor/anaconda3/lib/python3.5/site-packages/tensorflow/contrib/learn/python/learn/estimators/head.py:1362: scalar_summary (from tensorflow.python.ops.logging_ops) is deprecated and will be removed after 2016-11-30.
Instructions for updating:
Please switch to tf.summary.scalar. Note that tf.summary.scalar uses the node name instead of the tag. This means that TensorFlow will automatically de-duplicate summary names based on the scope they are created in. Also, passing a tensor or list of tags to a scalar summary op is no longer supported.
INFO:tensorflow:Starting evaluation at 2017-02-17-23:21:27
INFO:tensorflow:Finished evaluation at 2017-02-17-23:21:28
INFO:tensorflow:Saving dict for global step 1002: accuracy = 0.966667, auc = 0.998333, global_step = 1002, loss = 0.0556784, precision = 1.0, recall = 1.0
WARNING:tensorflow:Skipping summary for global_step, must be a float or np.float32.
INFO:tensorflow:Validation (step 1051): precision = 1.0, auc = 0.998333, loss = 0.0556784, recall = 1.0, accuracy = 0.966667, global_step = 1002
INFO:tensorflow:Saving checkpoints for 1052 into /tmp/iris_model/model.ckpt.
WARNING:tensorflow:From /home/dkor/anaconda3/lib/python3.5/site-packages/tensorflow/contrib/learn/python/learn/monitors.py:712: calling BaseEstimator.evaluate (from tensorflow.contrib.learn.python.learn.estimators.estimator) with x is deprecated and will be removed after 2016-12-01.
Instructions for updating:
Estimator is decoupled from Scikit Learn interface by moving into
separate class SKCompat. Arguments x, y and batch_size are only
available in the SKCompat class, Estimator will only accept input_fn.
Example conversion:
  est = Estimator(...) -> est = SKCompat(Estimator(...))
WARNING:tensorflow:From /home/dkor/anaconda3/lib/python3.5/site-packages/tensorflow/contrib/learn/python/learn/monitors.py:712: calling BaseEstimator.evaluate (from tensorflow.contrib.learn.python.learn.estimators.estimator) with y is deprecated and will be removed after 2016-12-01.
Instructions for updating:
Estimator is decoupled from Scikit Learn interface by moving into
separate class SKCompat. Arguments x, y and batch_size are only
available in the SKCompat class, Estimator will only accept input_fn.
Example conversion:
  est = Estimator(...) -> est = SKCompat(Estimator(...))
WARNING:tensorflow:float64 is not supported by many models, consider casting to float32.
WARNING:tensorflow:From /home/dkor/anaconda3/lib/python3.5/site-packages/tensorflow/contrib/learn/python/learn/estimators/head.py:1362: scalar_summary (from tensorflow.python.ops.logging_ops) is deprecated and will be removed after 2016-11-30.
Instructions for updating:
Please switch to tf.summary.scalar. Note that tf.summary.scalar uses the node name instead of the tag. This means that TensorFlow will automatically de-duplicate summary names based on the scope they are created in. Also, passing a tensor or list of tags to a scalar summary op is no longer supported.
INFO:tensorflow:Starting evaluation at 2017-02-17-23:21:29
INFO:tensorflow:Finished evaluation at 2017-02-17-23:21:29
INFO:tensorflow:Saving dict for global step 1052: accuracy = 0.966667, auc = 0.998333, global_step = 1052, loss = 0.0557572, precision = 1.0, recall = 1.0
WARNING:tensorflow:Skipping summary for global_step, must be a float or np.float32.
INFO:tensorflow:Validation (step 1101): precision = 1.0, auc = 0.998333, loss = 0.0557572, recall = 1.0, accuracy = 0.966667, global_step = 1052
INFO:tensorflow:Saving checkpoints for 1102 into /tmp/iris_model/model.ckpt.
INFO:tensorflow:global_step/sec: 32.9999
INFO:tensorflow:loss = 0.0466149, step = 1151
WARNING:tensorflow:From /home/dkor/anaconda3/lib/python3.5/site-packages/tensorflow/contrib/learn/python/learn/monitors.py:712: calling BaseEstimator.evaluate (from tensorflow.contrib.learn.python.learn.estimators.estimator) with x is deprecated and will be removed after 2016-12-01.
Instructions for updating:
Estimator is decoupled from Scikit Learn interface by moving into
separate class SKCompat. Arguments x, y and batch_size are only
available in the SKCompat class, Estimator will only accept input_fn.
Example conversion:
  est = Estimator(...) -> est = SKCompat(Estimator(...))
WARNING:tensorflow:From /home/dkor/anaconda3/lib/python3.5/site-packages/tensorflow/contrib/learn/python/learn/monitors.py:712: calling BaseEstimator.evaluate (from tensorflow.contrib.learn.python.learn.estimators.estimator) with y is deprecated and will be removed after 2016-12-01.
Instructions for updating:
Estimator is decoupled from Scikit Learn interface by moving into
separate class SKCompat. Arguments x, y and batch_size are only
available in the SKCompat class, Estimator will only accept input_fn.
Example conversion:
  est = Estimator(...) -> est = SKCompat(Estimator(...))
WARNING:tensorflow:float64 is not supported by many models, consider casting to float32.
WARNING:tensorflow:From /home/dkor/anaconda3/lib/python3.5/site-packages/tensorflow/contrib/learn/python/learn/estimators/head.py:1362: scalar_summary (from tensorflow.python.ops.logging_ops) is deprecated and will be removed after 2016-11-30.
Instructions for updating:
Please switch to tf.summary.scalar. Note that tf.summary.scalar uses the node name instead of the tag. This means that TensorFlow will automatically de-duplicate summary names based on the scope they are created in. Also, passing a tensor or list of tags to a scalar summary op is no longer supported.
INFO:tensorflow:Starting evaluation at 2017-02-17-23:21:30
INFO:tensorflow:Finished evaluation at 2017-02-17-23:21:31
INFO:tensorflow:Saving dict for global step 1102: accuracy = 0.966667, auc = 0.998333, global_step = 1102, loss = 0.0559047, precision = 1.0, recall = 1.0
WARNING:tensorflow:Skipping summary for global_step, must be a float or np.float32.
INFO:tensorflow:Validation (step 1151): precision = 1.0, auc = 0.998333, loss = 0.0559047, recall = 1.0, accuracy = 0.966667, global_step = 1102
INFO:tensorflow:Stopping. Best step: 951 with loss = 0.05563554912805557.
INFO:tensorflow:Saving checkpoints for 1151 into /tmp/iris_model/model.ckpt.
INFO:tensorflow:Loss for final step: 0.0466149.
WARNING:tensorflow:From iris_monitors.py:108: calling BaseEstimator.evaluate (from tensorflow.contrib.learn.python.learn.estimators.estimator) with x is deprecated and will be removed after 2016-12-01.
Instructions for updating:
Estimator is decoupled from Scikit Learn interface by moving into
separate class SKCompat. Arguments x, y and batch_size are only
available in the SKCompat class, Estimator will only accept input_fn.
Example conversion:
  est = Estimator(...) -> est = SKCompat(Estimator(...))
WARNING:tensorflow:From iris_monitors.py:108: calling BaseEstimator.evaluate (from tensorflow.contrib.learn.python.learn.estimators.estimator) with y is deprecated and will be removed after 2016-12-01.
Instructions for updating:
Estimator is decoupled from Scikit Learn interface by moving into
separate class SKCompat. Arguments x, y and batch_size are only
available in the SKCompat class, Estimator will only accept input_fn.
Example conversion:
  est = Estimator(...) -> est = SKCompat(Estimator(...))
WARNING:tensorflow:float64 is not supported by many models, consider casting to float32.
WARNING:tensorflow:From /home/dkor/anaconda3/lib/python3.5/site-packages/tensorflow/contrib/learn/python/learn/estimators/head.py:1362: scalar_summary (from tensorflow.python.ops.logging_ops) is deprecated and will be removed after 2016-11-30.
Instructions for updating:
Please switch to tf.summary.scalar. Note that tf.summary.scalar uses the node name instead of the tag. This means that TensorFlow will automatically de-duplicate summary names based on the scope they are created in. Also, passing a tensor or list of tags to a scalar summary op is no longer supported.
INFO:tensorflow:Starting evaluation at 2017-02-17-23:21:32
INFO:tensorflow:Finished evaluation at 2017-02-17-23:21:32
INFO:tensorflow:Saving dict for global step 1151: accuracy = 0.966667, auc = 0.998333, global_step = 1151, loss = 0.0619039
WARNING:tensorflow:Skipping summary for global_step, must be a float or np.float32.
Accuracy: 0.966667
WARNING:tensorflow:From /home/dkor/anaconda3/lib/python3.5/site-packages/tensorflow/contrib/learn/python/learn/estimators/dnn.py:374: calling BaseEstimator.predict (from tensorflow.contrib.learn.python.learn.estimators.estimator) with x is deprecated and will be removed after 2016-12-01.
Instructions for updating:
Estimator is decoupled from Scikit Learn interface by moving into
separate class SKCompat. Arguments x, y and batch_size are only
available in the SKCompat class, Estimator will only accept input_fn.
Example conversion:
  est = Estimator(...) -> est = SKCompat(Estimator(...))
WARNING:tensorflow:float64 is not supported by many models, consider casting to float32.
Predictions: [1, 2]
dkor@panchito:~/repositories/tensorflow/tensorflow/examples/tutorials/monitors$

@jarlva
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jarlva commented Mar 3, 2017 •
edited
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I'm getting the errors using the latest nightly TF build (3/3/2017) with the Iris dataset. I see this issue as closed. So how was it fixed?
It worked fine prior to 1.0. Using python 3.5.1 on Windows, no gpu.
code is the same as the example in https://www.tensorflow.org/get_started/tflearn

Errors:

C:\Users\Jake\py\my_env\lib\site-packages\tensorflow\python\util\deprecation.py:248: FutureWarning: comparison to None will result in an elementwise object comparison in the future.
equality = a == b
WARNING:tensorflow:From C:\Users\Jake\py\files\Iris\Iris_TF_example.py:34: calling BaseEstimator.fit (from tensorflow.contrib.learn.python.learn.estimators.estimator) with x is deprecated and will be removed after 2016-12-01.
Instructions for updating:
Estimator is decoupled from Scikit Learn interface by moving into
separate class SKCompat. Arguments x, y and batch_size are only
available in the SKCompat class, Estimator will only accept input_fn.
Example conversion:
est = Estimator(...) -> est = SKCompat(Estimator(...))
WARNING:tensorflow:From C:\Users\Jake\py\files\Iris\Iris_TF_example.py:34: calling BaseEstimator.fit (from tensorflow.contrib.learn.python.learn.estimators.estimator) with y is deprecated and will be removed after 2016-12-01.
Instructions for updating:
Estimator is decoupled from Scikit Learn interface by moving into
separate class SKCompat. Arguments x, y and batch_size are only
available in the SKCompat class, Estimator will only accept input_fn.
Example conversion:
est = Estimator(...) -> est = SKCompat(Estimator(...))
WARNING:tensorflow:From C:\Users\Jake\py\my_env\lib\site-packages\tensorflow\contrib\learn\python\learn\estimators\head.py:527: scalar_summary (from tensorflow.python.ops.logging_ops) is deprecated and will be removed after 2016-11-30.
Instructions for updating:
Please switch to tf.summary.scalar. Note that tf.summary.scalar uses the node name instead of the tag. This means that TensorFlow will automatically de-duplicate summary names based on the scope they are created in. Also, passing a tensor or list of tags to a scalar summary op is no longer supported.
2017-03-03 09:47:24.299814: W c:\tf_jenkins\home\workspace\nightly-win\device\cpu\os\windows\tensorflow\core\platform\cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use SSE instructions, but these are available on your machine and could speed up CPU computations.
2017-03-03 09:47:24.303698: W c:\tf_jenkins\home\workspace\nightly-win\device\cpu\os\windows\tensorflow\core\platform\cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use SSE2 instructions, but these are available on your machine and could speed up CPU computations.
2017-03-03 09:47:24.305520: W c:\tf_jenkins\home\workspace\nightly-win\device\cpu\os\windows\tensorflow\core\platform\cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use SSE3 instructions, but these are available on your machine and could speed up CPU computations.
2017-03-03 09:47:24.309054: W c:\tf_jenkins\home\workspace\nightly-win\device\cpu\os\windows\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.
2017-03-03 09:47:24.311934: W c:\tf_jenkins\home\workspace\nightly-win\device\cpu\os\windows\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.
2017-03-03 09:47:24.329330: W c:\tf_jenkins\home\workspace\nightly-win\device\cpu\os\windows\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.
2017-03-03 09:47:24.330449: W c:\tf_jenkins\home\workspace\nightly-win\device\cpu\os\windows\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.
2017-03-03 09:47:24.340085: W c:\tf_jenkins\home\workspace\nightly-win\device\cpu\os\windows\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.
2017-03-03 09:47:24.891764: W c:\tf_jenkins\home\workspace\nightly-win\device\cpu\os\windows\tensorflow\core\framework\op_kernel.cc:1150] Not found: Key dnn/hiddenlayer_1/biases/denlayer_1/biases/part_0/Adagrad not found in checkpoint
2017-03-03 09:47:24.897697: W c:\tf_jenkins\home\workspace\nightly-win\device\cpu\os\windows\tensorflow\core\framework\op_kernel.cc:1150] Not found: Key dnn/hiddenlayer_0/weights/enlayer_0/weights/part_0/Adagrad not found in checkpoint
2017-03-03 09:47:24.909642: W c:\tf_jenkins\home\workspace\nightly-win\device\cpu\os\windows\tensorflow\core\framework\op_kernel.cc:1150] Not found: Key dnn/hiddenlayer_1/weights/enlayer_1/weights/part_0/Adagrad not found in checkpoint
2017-03-03 09:47:24.912938: W c:\tf_jenkins\home\workspace\nightly-win\device\cpu\os\windows\tensorflow\core\framework\op_kernel.cc:1150] Not found: Key dnn/hiddenlayer_2/biases/denlayer_2/biases/part_0/Adagrad not found in checkpoint
2017-03-03 09:47:24.917436: W c:\tf_jenkins\home\workspace\nightly-win\device\cpu\os\windows\tensorflow\core\framework\op_kernel.cc:1150] Not found: Key dnn/hiddenlayer_2/weights/enlayer_2/weights/part_0/Adagrad not found in checkpoint
2017-03-03 09:47:24.918026: W c:\tf_jenkins\home\workspace\nightly-win\device\cpu\os\windows\tensorflow\core\framework\op_kernel.cc:1150] Not found: Key dnn/hiddenlayer_0/biases/denlayer_0/biases/part_0/Adagrad not found in checkpoint
2017-03-03 09:47:24.925070: W c:\tf_jenkins\home\workspace\nightly-win\device\cpu\os\windows\tensorflow\core\framework\op_kernel.cc:1150] Not found: Key dnn/logits/biases/dnn/logits/biases/part_0/Adagrad not found in checkpoint
2017-03-03 09:47:24.930800: W c:\tf_jenkins\home\workspace\nightly-win\device\cpu\os\windows\tensorflow\core\framework\op_kernel.cc:1150] Not found: Key dnn/multi_class_head/dnn/learning_rate not found in checkpoint
2017-03-03 09:47:24.931319: W c:\tf_jenkins\home\workspace\nightly-win\device\cpu\os\windows\tensorflow\core\framework\op_kernel.cc:1150] Not found: Key dnn/logits/weights/nn/logits/weights/part_0/Adagrad not found in checkpoint
Traceback (most recent call last):
File "C:\Users\Jake\py\my_env\lib\site-packages\tensorflow\python\client\session.py", line 1024, in _do_call
return fn(*args)
File "C:\Users\Jake\py\my_env\lib\site-packages\tensorflow\python\client\session.py", line 1006, in _run_fn
status, run_metadata)
File "C:\Users\Jake\AppData\Local\Programs\Python\Python35\lib\contextlib.py", line 66, in exit
next(self.gen)
File "C:\Users\Jake\py\my_env\lib\site-packages\tensorflow\python\framework\errors_impl.py", line 466, in raise_exception_on_not_ok_status
pywrap_tensorflow.TF_GetCode(status))
tensorflow.python.framework.errors_impl.NotFoundError: Key dnn/hiddenlayer_1/biases/denlayer_1/biases/part_0/Adagrad not found in checkpoint
[[Node: save/RestoreV2_5 = RestoreV2[dtypes=[DT_FLOAT], _device="/job:localhost/replica:0/task:0/cpu:0"](_recv_save/Const_0, save/RestoreV2_5/tensor_names, save/RestoreV2_5/shape_and_slices)]]

During handling of the above exception, another excepti 8000 on occurred:

Traceback (most recent call last):
File "C:\Users\Jake\py\files\Iris\Iris_TF_example.py", line 34, in
steps=2000)
File "C:\Users\Jake\py\my_env\lib\site-packages\tensorflow\python\util\deprecation.py", line 281, in new_func
return func(*args, **kwargs)
File "C:\Users\Jake\py\my_env\lib\site-packages\tensorflow\contrib\learn\python\learn\estimators\estimator.py", line 402, in fit
SKCompat(self).fit(x, y, batch_size, steps, max_steps, monitors)
File "C:\Users\Jake\py\my_env\lib\site-packages\tensorflow\contrib\learn\python\learn\estimators\estimator.py", line 1301, in fit
monitors=all_monitors)
File "C:\Users\Jake\py\my_env\lib\site-packages\tensorflow\python\util\deprecation.py", line 281, in new_func
return func(*args, **kwargs)
File "C:\Users\Jake\py\my_env\lib\site-packages\tensorflow\contrib\learn\python\learn\estimators\estimator.py", line 418, in fit
loss = self._train_model(input_fn=input_fn, hooks=hooks)
File "C:\Users\Jake\py\my_env\lib\site-packages\tensorflow\contrib\learn\python\learn\estimators\estimator.py", line 962, in _train_model
config=config_pb2.ConfigProto(allow_soft_placement=True)
File "C:\Users\Jake\py\my_env\lib\site-packages\tensorflow\python\training\monitored_session.py", line 332, in MonitoredTrainingSession
stop_grace_period_secs=stop_grace_period_secs)
File "C:\Users\Jake\py\my_env\lib\site-packages\tensorflow\python\training\monitored_session.py", line 626, in init
stop_grace_period_secs=stop_grace_period_secs)
File "C:\Users\Jake\py\my_env\lib\site-packages\tensorflow\python\training\monitored_session.py", line 455, in init
self._sess = _RecoverableSession(self._coordinated_creator)
File "C:\Users\Jake\py\my_env\lib\site-packages\tensorflow\python\training\monitored_session.py", line 799, in init
_WrappedSession.init(self, self._create_session())
File "C:\Users\Jake\py\my_env\lib\site-packages\tensorflow\python\training\monitored_session.py", line 804, in _create_session
return self._sess_creator.create_session()
File "C:\Users\Jake\py\my_env\lib\site-packages\tensorflow\python\training\monitored_session.py", line 516, in create_session
self.tf_sess = self._session_creator.create_session()
File "C:\Users\Jake\py\my_env\lib\site-packages\tensorflow\python\training\monitored_session.py", line 392, in create_session
init_fn=self._scaffold.init_fn)
File "C:\Users\Jake\py\my_env\lib\site-packages\tensorflow\python\training\session_manager.py", line 256, in prepare_session
config=config)
File "C:\Users\Jake\py\my_env\lib\site-packages\tensorflow\python\training\session_manager.py", line 188, in _restore_checkpoint
saver.restore(sess, ckpt.model_checkpoint_path)
File "C:\Users\Jake\py\my_env\lib\site-packages\tensorflow\python\training\saver.py", line 1457, in restore
{self.saver_def.filename_tensor_name: save_path})
File "C:\Users\Jake\py\my_env\lib\site-packages\tensorflow\python\client\session.py", line 769, in run
run_metadata_ptr)
File "C:\Users\Jake\py\my_env\lib\site-packages\tensorflow\python\client\session.py", line 967, in _run
feed_dict_string, options, run_metadata)
File "C:\Users\Jake\py\my_env\lib\site-packages\tensorflow\python\client\session.py", line 1017, in _do_run
target_list, options, run_metadata)
File "C:\Users\Jake\py\my_env\lib\site-packages\tensorflow\python\client\session.py", line 1037, in _do_call
raise type(e)(node_def, op, message)
tensorflow.python.framework.errors_impl.NotFoundError: Key dnn/hiddenlayer_1/biases/denlayer_1/biases/part_0/Adagrad not found in checkpoint
[[Node: save/RestoreV2_5 = RestoreV2[dtypes=[DT_FLOAT], _device="/job:localhost/replica:0/task:0/cpu:0"](_recv_save/Const_0, save/RestoreV2_5/tensor_names, save/RestoreV2_5/shape_and_slices)]]

Caused by op 'save/RestoreV2_5', defined at:
File "C:\Users\Jake\py\files\Iris\Iris_TF_example.py", line 34, in
steps=2000)
File "C:\Users\Jake\py\my_env\lib\site-packages\tensorflow\python\util\deprecation.py", line 281, in new_func
return func(*args, **kwargs)
File "C:\Users\Jake\py\my_env\lib\site-packages\tensorflow\contrib\learn\python\learn\estimators\estimator.py", line 402, in fit
SKCompat(self).fit(x, y, batch_size, steps, max_steps, monitors)
File "C:\Users\Jake\py\my_env\lib\site-packages\tensorflow\contrib\learn\python\learn\estimators\estimator.py", line 1301, in fit
monitors=all_monitors)
File "C:\Users\Jake\py\my_env\lib\site-packages\tensorflow\python\util\deprecation.py", line 281, in new_func
return func(*args, **kwargs)
File "C:\Users\Jake\py\my_env\lib\site-packages\tensorflow\contrib\learn\python\learn\estimators\estimator.py", line 418, in fit
loss = self._train_model(input_fn=input_fn, hooks=hooks)
File "C:\Users\Jake\py\my_env\lib\site-packages\tensorflow\contrib\learn\python\learn\estimators\estimator.py", line 962, in _train_model
config=config_pb2.ConfigProto(allow_soft_placement=True)
File "C:\Users\Jake\py\my_env\lib\site-packages\tensorflow\python\training\monitored_session.py", line 332, in MonitoredTrainingSession
stop_grace_period_secs=stop_grace_period_secs)
File "C:\Users\Jake\py\my_env\lib\site-packages\tensorflow\python\training\monitored_session.py", line 626, in init
stop_grace_period_secs=stop_grace_period_secs)
File "C:\Users\Jake\py\my_env\lib\site-packages\tensorflow\python\training\monitored_session.py", line 455, in init
self._sess = _RecoverableSession(self._coordinated_creator)
File "C:\Users\Jake\py\my_env\lib\site-packages\tensorflow\python\training\monitored_session.py", line 799, in init
_WrappedSession.init(self, self._create_session())
File "C:\Users\Jake\py\my_env\lib\site-packages\tensorflow\python\training\monitored_session.py", line 804, in _create_session
return self._sess_creator.create_session()
File "C:\Users\Jake\py\my_env\lib\site-packages\tensorflow\python\training\monitored_session.py", line 516, in create_session
self.tf_sess = self._session_creator.create_session()
File "C:\Users\Jake\py\my_env\lib\site-packages\tensorflow\python\training\monitored_session.py", line 383, in create_session
self._scaffold.finalize()
File "C:\Users\Jake\py\my_env\lib\site-packages\tensorflow\python\training\monitored_session.py", line 188, in finalize
self._saver.build()
File "C:\Users\Jake\py\my_env\lib\site-packages\tensorflow\python\training\saver.py", line 1086, in build
restore_sequentially=self._restore_sequentially)
File "C:\Users\Jake\py\my_env\lib\site-packages\tensorflow\python\training\saver.py", line 687, in build
restore_sequentially, reshape)
File "C:\Users\Jake\py\my_env\lib\site-packages\tensorflow\python\training\saver.py", line 450, in _AddShardedRestoreOps
name="restore_shard"))
File "C:\Users\Jake\py\my_env\lib\site-packages\tensorflow\python\training\saver.py", line 407, in _AddRestoreOps
tensors = self.restore_op(filename_tensor, saveable, preferred_shard)
File "C:\Users\Jake\py\my_env\lib\site-packages\tensorflow\python\training\saver.py", line 247, in restore_op
[spec.tensor.dtype])[0])
File "C:\Users\Jake\py\my_env\lib\site-packages\tensorflow\python\ops\gen_io_ops.py", line 669, in restore_v2
dtypes=dtypes, name=name)
File "C:\Users\Jake\py\my_env\lib\site-packages\tensorflow\python\framework\op_def_library.py", line 768, in apply_op
op_def=op_def)
File "C:\Users\Jake\py\my_env\lib\site-packages\tensorflow\python\framework\ops.py", line 2334, in create_op
original_op=self._default_original_op, op_def=op_def)
File "C:\Users\Jake\py\my_env\lib\site-packages\tensorflow\python\framework\ops.py", line 1226, in init
self._traceback = _extract_stack()

NotFoundError (see above for traceback): Key dnn/hiddenlayer_1/biases/denlayer_1/biases/part_0/Adagrad not found in checkpoint
[[Node: save/RestoreV2_5 = RestoreV2[dtypes=[DT_FLOAT], _device="/job:localhost/replica:0/task:0/cpu:0"](_recv_save/Const_0, save/RestoreV2_5/tensor_names, save/RestoreV2_5/shape_and_slices)]]

@terrytangyuan
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Member

Use learn.MetricSpec instead

@jarlva
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jarlva commented Mar 4, 2017

I'm new to this and using the tensorflow site as a learning resource. If recent code changes break the learn example than for the sake of clear/concise learning it would require updating the tensorflow site with the corrected code. Specifically: https://www.tensorflow.org/get_started/tflearn

copybara-service bot pushed a commit that referenced this issue Dec 15, 2023
@zhenying-liu @tensorflower-gardener
PR #7637: Raise an error if it get an optimized graph as input to run…
0adc421 
… optimization passes

Imported from GitHub PR openxla/xla#7637

This is to set the right expectation that an already optimized graph shouldn't be optimized again.
Copybara import of the project:

--
61f19f6138578bb1b39d7aa517a9147394be816a by Jane Liu <janeliu@nvidia.com>:

raise an error if it get an optimized graph as input

--
150a7513a2b926eb106c21d2b4a5b67da373c936 by Jane Liu <janeliu@nvidia.com>:

fix a unit test by removing its module's is_schedule=true

Merging this change closes #7637

PiperOrigin-RevId: 591186406
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@terrytangyuan @chidochipotle @jarlva
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