diff --git a/python/paddle/fluid/layers/io.py b/python/paddle/fluid/layers/io.py
index a9075045a2d5282ecded1681bc9835feb15298ea..8e18a6e784bab98bb8b5a89ec1b0399479ab5769 100644
--- a/python/paddle/fluid/layers/io.py
+++ b/python/paddle/fluid/layers/io.py
@@ -347,72 +347,70 @@ def _copy_reader_create_op_(block, op):
     return new_op
 
 
-if os.name != 'nt':
-
-    @templatedoc(op_type='create_recordio_file_reader')
-    def open_recordio_file(filename,
-                           shapes,
-                           lod_levels,
-                           dtypes,
-                           pass_num=1,
-                           for_parallel=True):
-        """
-        ${comment}
-
-        Args:
-           filename(${filename_type}): ${filename_comment}.
-           shapes(list): List of tuples which declaring data shapes.
-           lod_levels(${lod_levels_type}): ${lod_levels_comment}.
-           dtypes(list): List of strs which declaring data type.
-           pass_num(int): Number of passes to run.
-           for_parallel(Bool): Set it as True if you are going to run
-                subsequent operators in parallel.
-
-        Returns:
-           ${out_comment}.
-
-        Examples:
-
-            >>> import paddle.fluid as fluid
-            >>> reader = fluid.layers.io.open_recordio_file(
-            >>>                               filename='./data.recordio',
-            >>>                               shapes=[(3,224,224), (1)],
-            >>>                               lod_levels=[0, 0],
-            >>>                               dtypes=['float32', 'int64'])
-            >>> # Via the reader, we can use 'read_file' layer to get data:
-            >>> image, label = fluid.layers.io.read_file(reader)
-        """
-        dtypes = [convert_np_dtype_to_dtype_(dt) for dt in dtypes]
-        shape_concat = []
-        ranks = []
+@templatedoc(op_type='create_recordio_file_reader')
+def open_recordio_file(filename,
+                       shapes,
+                       lod_levels,
+                       dtypes,
+                       pass_num=1,
+                       for_parallel=True):
+    """
+    ${comment}
 
-        for shape in shapes:
-            shape_concat.extend(shape)
-            ranks.append(len(shape))
+    Args:
+       filename(${filename_type}): ${filename_comment}.
+       shapes(list): List of tuples which declaring data shapes.
+       lod_levels(${lod_levels_type}): ${lod_levels_comment}.
+       dtypes(list): List of strs which declaring data type.
+       pass_num(int): Number of passes to run.
+       for_parallel(Bool): Set it as True if you are going to run
+            subsequent operators in parallel.
 
-        var_name = unique_name('open_recordio_file')
+    Returns:
+       ${out_comment}.
 
-        startup_blk = default_startup_program().current_block()
-        startup_var = startup_blk.create_var(name=var_name)
-        startup_blk.append_op(
-            type='create_recordio_file_reader',
-            outputs={'Out': [startup_var]},
-            attrs={
-                'shape_concat': shape_concat,
-                'lod_levels': lod_levels,
-                'filename': filename,
-                'ranks': ranks
-            })
+    Examples:
 
-        startup_var.desc.set_dtypes(dtypes)
-        startup_var.persistable = True
-        main_prog_var = _copy_reader_var_(
-            default_main_program().current_block(), startup_var)
+        >>> import paddle.fluid as fluid
+        >>> reader = fluid.layers.io.open_recordio_file(
+        >>>                               filename='./data.recordio',
+        >>>                               shapes=[(3,224,224), (1)],
+        >>>                               lod_levels=[0, 0],
+        >>>                               dtypes=['float32', 'int64'])
+        >>> # Via the reader, we can use 'read_file' layer to get data:
+        >>> image, label = fluid.layers.io.read_file(reader)
+    """
+    dtypes = [convert_np_dtype_to_dtype_(dt) for dt in dtypes]
+    shape_concat = []
+    ranks = []
+
+    for shape in shapes:
+        shape_concat.extend(shape)
+        ranks.append(len(shape))
 
-        if pass_num > 1:
-            main_prog_var = multi_pass(reader=main_prog_var, pass_num=pass_num)
+    var_name = unique_name('open_recordio_file')
 
-        return monkey_patch_reader_methods(main_prog_var)
+    startup_blk = default_startup_program().current_block()
+    startup_var = startup_blk.create_var(name=var_name)
+    startup_blk.append_op(
+        type='create_recordio_file_reader',
+        outputs={'Out': [startup_var]},
+        attrs={
+            'shape_concat': shape_concat,
+            'lod_levels': lod_levels,
+            'filename': filename,
+            'ranks': ranks
+        })
+
+    startup_var.desc.set_dtypes(dtypes)
+    startup_var.persistable = True
+    main_prog_var = _copy_reader_var_(
+        default_main_program().current_block(), startup_var)
+
+    if pass_num > 1:
+        main_prog_var = multi_pass(reader=main_prog_var, pass_num=pass_num)
+
+    return monkey_patch_reader_methods(main_prog_var)
 
 
 def random_data_generator(low, high, shapes, lod_levels, for_parallel=True):