diff options
author | A. Unique TensorFlower <gardener@tensorflow.org> | 2018-03-22 11:12:10 -0700 |
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committer | TensorFlower Gardener <gardener@tensorflow.org> | 2018-03-22 11:14:40 -0700 |
commit | 1a6752dddf387d280a6a13c2dc7e2bebf69dab2f (patch) | |
tree | 7c88d9d18b4baade07f96156dd6add0927275fc7 /tensorflow/contrib/feature_column | |
parent | 6fa811a94f3da0c49d69db9b15ea424f84a6431f (diff) |
Adds remaining validations in sequence_numeric_column.
PiperOrigin-RevId: 190094883
Diffstat (limited to 'tensorflow/contrib/feature_column')
-rw-r--r-- | tensorflow/contrib/feature_column/python/feature_column/sequence_feature_column.py | 32 | ||||
-rw-r--r-- | tensorflow/contrib/feature_column/python/feature_column/sequence_feature_column_test.py | 26 |
2 files changed, 57 insertions, 1 deletions
diff --git a/tensorflow/contrib/feature_column/python/feature_column/sequence_feature_column.py b/tensorflow/contrib/feature_column/python/feature_column/sequence_feature_column.py index e60116966f..555beddeaa 100644 --- a/tensorflow/contrib/feature_column/python/feature_column/sequence_feature_column.py +++ b/tensorflow/contrib/feature_column/python/feature_column/sequence_feature_column.py @@ -166,6 +166,10 @@ def sequence_categorical_column_with_identity( Returns: A `_SequenceCategoricalColumn`. + + Raises: + ValueError: if `num_buckets` is less than one. + ValueError: if `default_value` is not in range `[0, num_buckets)`. """ return fc._SequenceCategoricalColumn( fc.categorical_column_with_identity( @@ -205,6 +209,10 @@ def sequence_categorical_column_with_hash_bucket( Returns: A `_SequenceCategoricalColumn`. + + Raises: + ValueError: `hash_bucket_size` is not greater than 1. + ValueError: `dtype` is neither string nor integer. """ return fc._SequenceCategoricalColumn( fc.categorical_column_with_hash_bucket( @@ -257,6 +265,13 @@ def sequence_categorical_column_with_vocabulary_file( Returns: A `_SequenceCategoricalColumn`. + + Raises: + ValueError: `vocabulary_file` is missing or cannot be opened. + ValueError: `vocabulary_size` is missing or < 1. + ValueError: `num_oov_buckets` is a negative integer. + ValueError: `num_oov_buckets` and `default_value` are both specified. + ValueError: `dtype` is neither string nor integer. """ return fc._SequenceCategoricalColumn( fc.categorical_column_with_vocabulary_file( @@ -311,6 +326,12 @@ def sequence_categorical_column_with_vocabulary_list( Returns: A `_SequenceCategoricalColumn`. + + Raises: + ValueError: if `vocabulary_list` is empty, or contains duplicate keys. + ValueError: `num_oov_buckets` is a negative integer. + ValueError: `num_oov_buckets` and `default_value` are both specified. + ValueError: if `dtype` is not integer or string. """ return fc._SequenceCategoricalColumn( fc.categorical_column_with_vocabulary_list( @@ -352,8 +373,17 @@ def sequence_numeric_column( Returns: A `_SequenceNumericColumn`. + + Raises: + TypeError: if any dimension in shape is not an int. + ValueError: if any dimension in shape is not a positive integer. + ValueError: if `dtype` is not convertible to `tf.float32`. """ - # TODO(b/73160931): Add validations. + shape = fc._check_shape(shape=shape, key=key) + if not (dtype.is_integer or dtype.is_floating): + raise ValueError('dtype must be convertible to float. ' + 'dtype: {}, key: {}'.format(dtype, key)) + return _SequenceNumericColumn( key, shape=shape, diff --git a/tensorflow/contrib/feature_column/python/feature_column/sequence_feature_column_test.py b/tensorflow/contrib/feature_column/python/feature_column/sequence_feature_column_test.py index b64f086376..88f5d53516 100644 --- a/tensorflow/contrib/feature_column/python/feature_column/sequence_feature_column_test.py +++ b/tensorflow/contrib/feature_column/python/feature_column/sequence_feature_column_test.py @@ -662,6 +662,32 @@ class SequenceIndicatorColumnTest(test.TestCase): class SequenceNumericColumnTest(test.TestCase): + def test_defaults(self): + a = sfc.sequence_numeric_column('aaa') + self.assertEqual('aaa', a.key) + self.assertEqual('aaa', a.name) + self.assertEqual('aaa', a._var_scope_name) + self.assertEqual((1,), a.shape) + self.assertEqual(0., a.default_value) + self.assertEqual(dtypes.float32, a.dtype) + + def test_shape_saved_as_tuple(self): + a = sfc.sequence_numeric_column('aaa', shape=[1, 2]) + self.assertEqual((1, 2), a.shape) + + def test_shape_must_be_positive_integer(self): + with self.assertRaisesRegexp(TypeError, 'shape dimensions must be integer'): + sfc.sequence_numeric_column('aaa', shape=[1.0]) + + with self.assertRaisesRegexp( + ValueError, 'shape dimensions must be greater than 0'): + sfc.sequence_numeric_column('aaa', shape=[0]) + + def test_dtype_is_convertible_to_float(self): + with self.assertRaisesRegexp( + ValueError, 'dtype must be convertible to float'): + sfc.sequence_numeric_column('aaa', dtype=dtypes.string) + def test_get_sequence_dense_tensor(self): sparse_input = sparse_tensor.SparseTensorValue( # example 0, values [[0.], [1]] |