Fix discrepancy between docs and registered kernels for `tf.ones_like…

…`/`tf.zeros_like` (tensorflow#13598) * Fix discrepancy between docs and registered kernels for `tf.ones_like` This fix tries to address the discrepancy between docs and registered kernels for `tf.ones_like`. From the implementation the OnesLike is registered with all POD types. However, in the documentation several data types are missing (uint8, int8, uint16, int16, bool). This fix addresses the issue by adding missing types to documentation. Signed-off-by: Yong Tang <[email protected]> * Fix python docs for `tf.ones_like` This commit fixes python docs for `tf.ones_like` Signed-off-by: Yong Tang <[email protected]> * Fix python docs for `tf.zeros_like` This commit fixes python docs for `tf.zeros_like` Signed-off-by: Yong Tang <[email protected]> * Add test cases for different dtypes on `tf.ones_like` and `tf.zeros_like` Signed-off-by: Yong Tang <[email protected]>
leod · Nov 2, 2017 · 6a8322f · 6a8322f
1 parent 0288097
commit 6a8322f
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Showing 3 changed files with 15 additions and 10 deletions.
diff --git a/tensorflow/core/ops/array_ops.cc b/tensorflow/core/ops/array_ops.cc
@@ -723,7 +723,9 @@ y: a tensor of the same shape and type as x but filled with zeros.
 REGISTER_OP("OnesLike")
     .Input("x: T")
     .Output("y: T")
-    .Attr("T: {float, double, int32, int64, complex64, complex128}")
+    .Attr(
+        "T: {float, double, int8, uint8, int16, uint16, int32, int64, "
+        "complex64, complex128, bool}")
     .SetShapeFn(shape_inference::UnchangedShape)
     .Doc(R"doc(
 Returns a tensor of ones with the same shape and type as x.

diff --git a/tensorflow/python/kernel_tests/constant_op_test.py b/tensorflow/python/kernel_tests/constant_op_test.py
@@ -439,9 +439,10 @@ def _compareZeros(self, dtype, fully_defined_shape, use_gpu):
 
   def testZerosLikeCPU(self):
     for dtype in [
-        dtypes_lib.float32, dtypes_lib.float64, dtypes_lib.int32,
-        dtypes_lib.uint8, dtypes_lib.int16, dtypes_lib.int8,
-        dtypes_lib.complex64, dtypes_lib.complex128, dtypes_lib.int64,
+        dtypes_lib.float32, dtypes_lib.float64,
+        dtypes_lib.int8, dtypes_lib.uint8, dtypes_lib.int16, dtypes_lib.uint16,
+        dtypes_lib.int32, dtypes_lib.int64, dtypes_lib.bool,
+        dtypes_lib.complex64, dtypes_lib.complex128,
         dtypes_lib.string
     ]:
       self._compareZeros(dtype, fully_defined_shape=False, use_gpu=False)
@@ -573,9 +574,10 @@ class OnesLikeTest(test.TestCase):
 
   def testOnesLike(self):
     for dtype in [
-        dtypes_lib.float32, dtypes_lib.float64, dtypes_lib.int32,
-        dtypes_lib.uint8, dtypes_lib.int16, dtypes_lib.int8,
-        dtypes_lib.complex64, dtypes_lib.complex128, dtypes_lib.int64
+        dtypes_lib.float32, dtypes_lib.float64,
+        dtypes_lib.int8, dtypes_lib.uint8, dtypes_lib.int16, dtypes_lib.uint16,
+        dtypes_lib.int32, dtypes_lib.int64, dtypes_lib.bool,
+        dtypes_lib.complex64, dtypes_lib.complex128
     ]:
       numpy_dtype = dtype.as_numpy_dtype
       with self.test_session():

diff --git a/tensorflow/python/ops/array_ops.py b/tensorflow/python/ops/array_ops.py
@@ -1495,7 +1495,8 @@ def zeros_like(tensor, dtype=None, name=None, optimize=True):
   Args:
     tensor: A `Tensor`.
     dtype: A type for the returned `Tensor`. Must be `float32`, `float64`,
-    `int8`, `int16`, `int32`, `int64`, `uint8`, `complex64`, or `complex128`.
+      `int8`, `uint8`, `int16`, `uint16`, int32`, `int64`,
+      `complex64`, `complex128` or `bool`.
     name: A name for the operation (optional).
     optimize: if true, attempt to statically determine the shape of 'tensor'
     and encode it as a constant.
@@ -1546,8 +1547,8 @@ def ones_like(tensor, dtype=None, name=None, optimize=True):
   Args:
     tensor: A `Tensor`.
     dtype: A type for the returned `Tensor`. Must be `float32`, `float64`,
-      `int8`, `int16`, `int32`, `int64`, `uint8`, `complex64`, `complex128` or
-      `bool`.
+      `int8`, `uint8`, `int16`, `uint16`, int32`, `int64`,
+      `complex64`, `complex128` or `bool`.
     name: A name for the operation (optional).
     optimize: if true, attempt to statically determine the shape of 'tensor'
     and encode it as a constant.