experiments/STT-tensorflow
1
0
Fork 0
Code Issues Pull Requests Projects Releases Wiki Activity

Small fix for named arguments in SparseFeature parsing.

Browse Source 
Change: 143799509
This commit is contained in:
A. Unique TensorFlower 2017-01-06 12:05:19 -08:00 committed by TensorFlower Gardener
parent 5129328062
commit 088a5df5bb
2 changed files with 11 additions and 7 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

3
tensorflow/python/kernel_tests/parsing_ops_test.py
View File

@ -363,7 +363,8 @@ class ParseExampleTest(test.TestCase):
"sp1":
parsing_ops.SparseFeature("idx", "val1", dtypes.float32, 13),
"sp2":
parsing_ops.SparseFeature("idx", "val2", dtypes.float32, 7)
parsing_ops.SparseFeature(
"idx", "val2", dtypes.float32, size=7, already_sorted=True)
}
}, expected_output)

15
tensorflow/python/ops/parsing_ops.py
View File

@ -65,9 +65,11 @@ class SparseFeature(
be `dtype` and its length must always match that of the `index_key`
feature.
dtype: Data type of the `value_key` feature.
size: Each value in the `index_key` feature must be in `[0, size)`.
already_sorted: A boolean to specify whether the values in `index_key` are
already sorted. If so skip sorting, False by default (optional).
size: A Python int to specify a dimension of the dense shape. Each value in
the `index_key` feature must be in `[0, size)`.
already_sorted: A Python boolean to specify whether the values in
`index_key` are already sorted. If so skip sorting.
False by default (optional).
"""
pass
SparseFeature.__new__.__defaults__ = (False,)
@ -225,8 +227,8 @@ def _construct_sparse_tensors_for_sparse_features(features, tensor_dict):
tensor_dict[key] = sparse_ops.sparse_merge(
sp_ids,
sp_values,
feature.size,
feature.already_sorted)
vocab_size=feature.size,
already_sorted=feature.already_sorted)
# Remove tensors from dictionary that were only used to construct
# SparseTensors for SparseFeature.
for key in set(tensor_dict.keys()) - set(features.keys()):
@ -394,7 +396,8 @@ def parse_example(serialized, features, name=None, example_names=None):
```
example_names: ["input0", "input1"],
features: {
"sparse": SparseFeature("ix", "val", tf.float32, 100),
"sparse": SparseFeature(
index_key="ix", value_key="val", dtype=tf.float32, size=100),
}
```