def testStringInput(self): with self.assertRaisesRegexp( ValueError, 'on integer or non floating types are not supported'): # pylint: disable=g-long-lambda estimator.infer_real_valued_columns_from_input( np.array([['%d.0' % i for i in xrange(8)] for _ in xrange(7)]))
def testInvalidArgs(self): with self.assertRaisesRegexp(ValueError, 'x or input_fn must be provided'): estimator.infer_real_valued_columns_from_input(None) with self.assertRaisesRegexp(ValueError, 'cannot be tensors'): estimator.infer_real_valued_columns_from_input( constant_op.constant(1.0))
def testBoolInput(self): with self.assertRaisesRegexp( ValueError, 'on integer or non floating types are not supported'): estimator.infer_real_valued_columns_from_input( np.array([[False for _ in xrange(8)] for _ in xrange(7)]))
def testFloat64Input(self): feature_columns = estimator.infer_real_valued_columns_from_input( np.ones(shape=[7, 8], dtype=np.float64)) self._assert_single_feature_column([8], dtypes.float64, feature_columns)
def testInt32Input(self): feature_columns = estimator.infer_real_valued_columns_from_input( np.ones(shape=[7, 8], dtype=np.int32)) self._assert_single_feature_column([8], dtypes.int32, feature_columns)
def testStringInput(self): with self.assertRaisesRegexp( ValueError, 'on integer or non floating types are not supported'): # pylint: disable=g-long-lambda estimator.infer_real_valued_columns_from_input( np.array([['%d.0' % i for i in xrange(8)] for _ in xrange(7)]))
def testBoolInput(self): with self.assertRaisesRegexp( ValueError, 'on integer or non floating types are not supported'): estimator.infer_real_valued_columns_from_input( np.array([[False for _ in xrange(8)] for _ in xrange(7)]))
def testFloat64Input(self): feature_columns = estimator.infer_real_valued_columns_from_input( np.ones( shape=[7, 8], dtype=np.float64)) self._assert_single_feature_column([8], dtypes.float64, feature_columns)
def testInt32Input(self): feature_columns = estimator.infer_real_valued_columns_from_input( np.ones( shape=[7, 8], dtype=np.int32)) self._assert_single_feature_column([8], dtypes.int32, feature_columns)
def testInvalidArgs(self): with self.assertRaisesRegexp(ValueError, 'x or input_fn must be provided'): estimator.infer_real_valued_columns_from_input(None) with self.assertRaisesRegexp(ValueError, 'cannot be tensors'): estimator.infer_real_valued_columns_from_input(constant_op.constant(1.0))