In [1]:

    

"""Example of DNNClassifier for Iris plant dataset."""

from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
from sklearn import cross_validation
from sklearn import metrics
import tensorflow as tf


    

    




/usr/local/lib/python3.5/site-packages/sklearn/cross_validation.py:44: DeprecationWarning: This module was deprecated in version 0.18 in favor of the model_selection module into which all the refactored classes and functions are moved. Also note that the interface of the new CV iterators are different from that of this module. This module will be removed in 0.20.
  "This module will be removed in 0.20.", DeprecationWarning)

In [7]:

    

# load data
iris = tf.contrib.learn.datasets.load_dataset('iris')
x_train, x_test, y_train, y_test = cross_validation.train_test_split(
    iris.data, iris.target, test_size=0.2, random_state=42)

# build 3 layers DNN with 10, 20, 10 units respectively.
feature_columns = tf.contrib.learn.infer_real_valued_columns_from_input(x_train)
classifier = tf.contrib.learn.DNNClassifier(feature_columns=feature_columns, hidden_units=[20,30,10,10], n_classes=3)

# Fit and predict
classifier.fit(x_train, y_train, steps=200)
predictions = list(classifier.predict(x_test, as_iterable=True))
score = metrics.accuracy_score(y_test, predictions)

print('Accurary: {0:f}'.format(score))


    

    




WARNING:tensorflow:float64 is not supported by many models, consider casting to float32.
WARNING:tensorflow:Using temporary folder as model directory: /var/folders/4n/dvmcx9mx3sgcp8mk0r_3xkhm0000gn/T/tmpxxetbc9i
INFO:tensorflow:Using default config.
INFO:tensorflow:Using config: {'_save_checkpoints_secs': 600, '_evaluation_master': '', '_save_summary_steps': 100, '_task_id': 0, '_save_checkpoints_steps': None, '_keep_checkpoint_every_n_hours': 10000, '_keep_checkpoint_max': 5, '_tf_random_seed': None, '_num_ps_replicas': 0, '_is_chief': True, '_master': '', '_environment': 'local', '_cluster_spec': <tensorflow.python.training.server_lib.ClusterSpec object at 0x111691550>, '_task_type': None, '_tf_config': gpu_options {
  per_process_gpu_memory_fraction: 1
}
}
WARNING:tensorflow:From <ipython-input-7-61190a75637f>:11: 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 <ipython-input-7-61190a75637f>:11: 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:float64 is not supported by many models, consider casting to float32.
WARNING:tensorflow:From /usr/local/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.






    




/usr/local/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






    




INFO:tensorflow:Create CheckpointSaverHook.
INFO:tensorflow:Saving checkpoints for 1 into /var/folders/4n/dvmcx9mx3sgcp8mk0r_3xkhm0000gn/T/tmpxxetbc9i/model.ckpt.
INFO:tensorflow:step = 1, loss = 1.13631
INFO:tensorflow:global_step/sec: 639.255
INFO:tensorflow:step = 101, loss = 0.141485
INFO:tensorflow:Saving checkpoints for 200 into /var/folders/4n/dvmcx9mx3sgcp8mk0r_3xkhm0000gn/T/tmpxxetbc9i/model.ckpt.
INFO:tensorflow:Loss for final step: 0.132648.
WARNING:tensorflow:From /usr/local/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.
Accurary: 0.933333

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