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      1 # Copyright 2016 The TensorFlow Authors. All Rights Reserved.
      2 #
      3 # Licensed under the Apache License, Version 2.0 (the "License");
      4 # you may not use this file except in compliance with the License.
      5 # You may obtain a copy of the License at
      6 #
      7 #     http://www.apache.org/licenses/LICENSE-2.0
      8 #
      9 # Unless required by applicable law or agreed to in writing, software
     10 # distributed under the License is distributed on an "AS IS" BASIS,
     11 # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
     12 # See the License for the specific language governing permissions and
     13 # limitations under the License.
     14 # ==============================================================================
     15 """Tests for TensorForestTrainer."""
     16 
     17 from __future__ import absolute_import
     18 from __future__ import division
     19 from __future__ import print_function
     20 
     21 import numpy as np
     22 
     23 from tensorflow.contrib.learn.python.learn.datasets import base
     24 from tensorflow.contrib.tensor_forest.client import random_forest
     25 from tensorflow.contrib.tensor_forest.python import tensor_forest
     26 from tensorflow.python.platform import test
     27 
     28 
     29 class TensorForestTrainerTests(test.TestCase):
     30 
     31   def testClassification(self):
     32     """Tests multi-class classification using matrix data as input."""
     33     hparams = tensor_forest.ForestHParams(
     34         num_trees=3,
     35         max_nodes=1000,
     36         num_classes=3,
     37         num_features=4,
     38         split_after_samples=20,
     39         inference_tree_paths=True)
     40     classifier = random_forest.TensorForestEstimator(hparams.fill())
     41 
     42     iris = base.load_iris()
     43     data = iris.data.astype(np.float32)
     44     labels = iris.target.astype(np.int32)
     45 
     46     classifier.fit(x=data, y=labels, steps=100, batch_size=50)
     47     classifier.evaluate(x=data, y=labels, steps=10)
     48 
     49   def testRegression(self):
     50     """Tests multi-class classification using matrix data as input."""
     51 
     52     hparams = tensor_forest.ForestHParams(
     53         num_trees=3,
     54         max_nodes=1000,
     55         num_classes=1,
     56         num_features=13,
     57         regression=True,
     58         split_after_samples=20)
     59 
     60     regressor = random_forest.TensorForestEstimator(hparams.fill())
     61 
     62     boston = base.load_boston()
     63     data = boston.data.astype(np.float32)
     64     labels = boston.target.astype(np.int32)
     65 
     66     regressor.fit(x=data, y=labels, steps=100, batch_size=50)
     67     regressor.evaluate(x=data, y=labels, steps=10)
     68 
     69 
     70 if __name__ == "__main__":
     71   test.main()
     72