1 # Copyright 2015 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 pandas_io.""" 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.learn_io import pandas_io 24 from tensorflow.python.framework import errors 25 from tensorflow.python.platform import test 26 from tensorflow.python.training import coordinator 27 from tensorflow.python.training import queue_runner_impl 28 29 # pylint: disable=g-import-not-at-top 30 try: 31 import pandas as pd 32 HAS_PANDAS = True 33 except ImportError: 34 HAS_PANDAS = False 35 36 37 class PandasIoTest(test.TestCase): 38 39 def makeTestDataFrame(self): 40 index = np.arange(100, 104) 41 a = np.arange(4) 42 b = np.arange(32, 36) 43 x = pd.DataFrame({'a': a, 'b': b}, index=index) 44 y = pd.Series(np.arange(-32, -28), index=index) 45 return x, y 46 47 def callInputFnOnce(self, input_fn, session): 48 results = input_fn() 49 coord = coordinator.Coordinator() 50 threads = queue_runner_impl.start_queue_runners(session, coord=coord) 51 result_values = session.run(results) 52 coord.request_stop() 53 coord.join(threads) 54 return result_values 55 56 def testPandasInputFn_IndexMismatch(self): 57 if not HAS_PANDAS: 58 return 59 x, _ = self.makeTestDataFrame() 60 y_noindex = pd.Series(np.arange(-32, -28)) 61 with self.assertRaises(ValueError): 62 pandas_io.pandas_input_fn( 63 x, y_noindex, batch_size=2, shuffle=False, num_epochs=1) 64 65 def testPandasInputFn_ProducesExpectedOutputs(self): 66 if not HAS_PANDAS: 67 return 68 with self.test_session() as session: 69 x, y = self.makeTestDataFrame() 70 input_fn = pandas_io.pandas_input_fn( 71 x, y, batch_size=2, shuffle=False, num_epochs=1) 72 73 features, target = self.callInputFnOnce(input_fn, session) 74 75 self.assertAllEqual(features['a'], [0, 1]) 76 self.assertAllEqual(features['b'], [32, 33]) 77 self.assertAllEqual(target, [-32, -31]) 78 79 def testPandasInputFn_ProducesOutputsForLargeBatchAndMultipleEpochs(self): 80 if not HAS_PANDAS: 81 return 82 with self.test_session() as session: 83 index = np.arange(100, 102) 84 a = np.arange(2) 85 b = np.arange(32, 34) 86 x = pd.DataFrame({'a': a, 'b': b}, index=index) 87 y = pd.Series(np.arange(-32, -30), index=index) 88 input_fn = pandas_io.pandas_input_fn( 89 x, y, batch_size=128, shuffle=False, num_epochs=2) 90 91 results = input_fn() 92 93 coord = coordinator.Coordinator() 94 threads = queue_runner_impl.start_queue_runners(session, coord=coord) 95 96 features, target = session.run(results) 97 self.assertAllEqual(features['a'], [0, 1, 0, 1]) 98 self.assertAllEqual(features['b'], [32, 33, 32, 33]) 99 self.assertAllEqual(target, [-32, -31, -32, -31]) 100 101 with self.assertRaises(errors.OutOfRangeError): 102 session.run(results) 103 104 coord.request_stop() 105 coord.join(threads) 106 107 def testPandasInputFn_ProducesOutputsWhenDataSizeNotDividedByBatchSize(self): 108 if not HAS_PANDAS: 109 return 110 with self.test_session() as session: 111 index = np.arange(100, 105) 112 a = np.arange(5) 113 b = np.arange(32, 37) 114 x = pd.DataFrame({'a': a, 'b': b}, index=index) 115 y = pd.Series(np.arange(-32, -27), index=index) 116 117 input_fn = pandas_io.pandas_input_fn( 118 x, y, batch_size=2, shuffle=False, num_epochs=1) 119 120 results = input_fn() 121 122 coord = coordinator.Coordinator() 123 threads = queue_runner_impl.start_queue_runners(session, coord=coord) 124 125 features, target = session.run(results) 126 self.assertAllEqual(features['a'], [0, 1]) 127 self.assertAllEqual(features['b'], [32, 33]) 128 self.assertAllEqual(target, [-32, -31]) 129 130 features, target = session.run(results) 131 self.assertAllEqual(features['a'], [2, 3]) 132 self.assertAllEqual(features['b'], [34, 35]) 133 self.assertAllEqual(target, [-30, -29]) 134 135 features, target = session.run(results) 136 self.assertAllEqual(features['a'], [4]) 137 self.assertAllEqual(features['b'], [36]) 138 self.assertAllEqual(target, [-28]) 139 140 with self.assertRaises(errors.OutOfRangeError): 141 session.run(results) 142 143 coord.request_stop() 144 coord.join(threads) 145 146 def testPandasInputFn_OnlyX(self): 147 if not HAS_PANDAS: 148 return 149 with self.test_session() as session: 150 x, _ = self.makeTestDataFrame() 151 input_fn = pandas_io.pandas_input_fn( 152 x, y=None, batch_size=2, shuffle=False, num_epochs=1) 153 154 features = self.callInputFnOnce(input_fn, session) 155 156 self.assertAllEqual(features['a'], [0, 1]) 157 self.assertAllEqual(features['b'], [32, 33]) 158 159 def testPandasInputFn_ExcludesIndex(self): 160 if not HAS_PANDAS: 161 return 162 with self.test_session() as session: 163 x, y = self.makeTestDataFrame() 164 input_fn = pandas_io.pandas_input_fn( 165 x, y, batch_size=2, shuffle=False, num_epochs=1) 166 167 features, _ = self.callInputFnOnce(input_fn, session) 168 169 self.assertFalse('index' in features) 170 171 def assertInputsCallableNTimes(self, input_fn, session, n): 172 inputs = input_fn() 173 coord = coordinator.Coordinator() 174 threads = queue_runner_impl.start_queue_runners(session, coord=coord) 175 for _ in range(n): 176 session.run(inputs) 177 with self.assertRaises(errors.OutOfRangeError): 178 session.run(inputs) 179 coord.request_stop() 180 coord.join(threads) 181 182 def testPandasInputFn_RespectsEpoch_NoShuffle(self): 183 if not HAS_PANDAS: 184 return 185 with self.test_session() as session: 186 x, y = self.makeTestDataFrame() 187 input_fn = pandas_io.pandas_input_fn( 188 x, y, batch_size=4, shuffle=False, num_epochs=1) 189 190 self.assertInputsCallableNTimes(input_fn, session, 1) 191 192 def testPandasInputFn_RespectsEpoch_WithShuffle(self): 193 if not HAS_PANDAS: 194 return 195 with self.test_session() as session: 196 x, y = self.makeTestDataFrame() 197 input_fn = pandas_io.pandas_input_fn( 198 x, y, batch_size=4, shuffle=True, num_epochs=1) 199 200 self.assertInputsCallableNTimes(input_fn, session, 1) 201 202 def testPandasInputFn_RespectsEpoch_WithShuffleAutosize(self): 203 if not HAS_PANDAS: 204 return 205 with self.test_session() as session: 206 x, y = self.makeTestDataFrame() 207 input_fn = pandas_io.pandas_input_fn( 208 x, y, batch_size=2, shuffle=True, queue_capacity=None, num_epochs=2) 209 210 self.assertInputsCallableNTimes(input_fn, session, 4) 211 212 def testPandasInputFn_RespectsEpochUnevenBatches(self): 213 if not HAS_PANDAS: 214 return 215 x, y = self.makeTestDataFrame() 216 with self.test_session() as session: 217 input_fn = pandas_io.pandas_input_fn( 218 x, y, batch_size=3, shuffle=False, num_epochs=1) 219 220 # Before the last batch, only one element of the epoch should remain. 221 self.assertInputsCallableNTimes(input_fn, session, 2) 222 223 def testPandasInputFn_Idempotent(self): 224 if not HAS_PANDAS: 225 return 226 x, y = self.makeTestDataFrame() 227 for _ in range(2): 228 pandas_io.pandas_input_fn( 229 x, y, batch_size=2, shuffle=False, num_epochs=1)() 230 for _ in range(2): 231 pandas_io.pandas_input_fn( 232 x, y, batch_size=2, shuffle=True, num_epochs=1)() 233 234 235 if __name__ == '__main__': 236 test.main() 237
