1 files changed, 60 insertions, 60 deletions
diff --git a/tensorflow/docs_src/api_guides/python/array_ops.md b/tensorflow/docs_src/api_guides/python/array_ops.md
index a34f01f073..ddeea80c56 100644
--- a/tensorflow/docs_src/api_guides/python/array_ops.md
+++ b/tensorflow/docs_src/api_guides/python/array_ops.md
@@ -1,7 +1,7 @@
 # Tensor Transformations
 
 Note: Functions taking `Tensor` arguments can also take anything accepted by
-@{tf.convert_to_tensor}.
+`tf.convert_to_tensor`.
 
 [TOC]
 
@@ -10,78 +10,78 @@ Note: Functions taking `Tensor` arguments can also take anything accepted by
 TensorFlow provides several operations that you can use to cast tensor data
 types in your graph.
 
-*   @{tf.string_to_number}
-*   @{tf.to_double}
-*   @{tf.to_float}
-*   @{tf.to_bfloat16}
-*   @{tf.to_int32}
-*   @{tf.to_int64}
-*   @{tf.cast}
-*   @{tf.bitcast}
-*   @{tf.saturate_cast}
+*   `tf.string_to_number`
+*   `tf.to_double`
+*   `tf.to_float`
+*   `tf.to_bfloat16`
+*   `tf.to_int32`
+*   `tf.to_int64`
+*   `tf.cast`
+*   `tf.bitcast`
+*   `tf.saturate_cast`
 
 ## Shapes and Shaping
 
 TensorFlow provides several operations that you can use to determine the shape
 of a tensor and change the shape of a tensor.
 
-*   @{tf.broadcast_dynamic_shape}
-*   @{tf.broadcast_static_shape}
-*   @{tf.shape}
-*   @{tf.shape_n}
-*   @{tf.size}
-*   @{tf.rank}
-*   @{tf.reshape}
-*   @{tf.squeeze}
-*   @{tf.expand_dims}
-*   @{tf.meshgrid}
+*   `tf.broadcast_dynamic_shape`
+*   `tf.broadcast_static_shape`
+*   `tf.shape`
+*   `tf.shape_n`
+*   `tf.size`
+*   `tf.rank`
+*   `tf.reshape`
+*   `tf.squeeze`
+*   `tf.expand_dims`
+*   `tf.meshgrid`
 
 ## Slicing and Joining
 
 TensorFlow provides several operations to slice or extract parts of a tensor,
 or join multiple tensors together.
 
-*   @{tf.slice}
-*   @{tf.strided_slice}
-*   @{tf.split}
-*   @{tf.tile}
-*   @{tf.pad}
-*   @{tf.concat}
-*   @{tf.stack}
-*   @{tf.parallel_stack}
-*   @{tf.unstack}
-*   @{tf.reverse_sequence}
-*   @{tf.reverse}
-*   @{tf.reverse_v2}
-*   @{tf.transpose}
-*   @{tf.extract_image_patches}
-*   @{tf.space_to_batch_nd}
-*   @{tf.space_to_batch}
-*   @{tf.required_space_to_batch_paddings}
-*   @{tf.batch_to_space_nd}
-*   @{tf.batch_to_space}
-*   @{tf.space_to_depth}
-*   @{tf.depth_to_space}
-*   @{tf.gather}
-*   @{tf.gather_nd}
-*   @{tf.unique_with_counts}
-*   @{tf.scatter_nd}
-*   @{tf.dynamic_partition}
-*   @{tf.dynamic_stitch}
-*   @{tf.boolean_mask}
-*   @{tf.one_hot}
-*   @{tf.sequence_mask}
-*   @{tf.dequantize}
-*   @{tf.quantize_v2}
-*   @{tf.quantized_concat}
-*   @{tf.setdiff1d}
+*   `tf.slice`
+*   `tf.strided_slice`
+*   `tf.split`
+*   `tf.tile`
+*   `tf.pad`
+*   `tf.concat`
+*   `tf.stack`
+*   `tf.parallel_stack`
+*   `tf.unstack`
+*   `tf.reverse_sequence`
+*   `tf.reverse`
+*   `tf.reverse_v2`
+*   `tf.transpose`
+*   `tf.extract_image_patches`
+*   `tf.space_to_batch_nd`
+*   `tf.space_to_batch`
+*   `tf.required_space_to_batch_paddings`
+*   `tf.batch_to_space_nd`
+*   `tf.batch_to_space`
+*   `tf.space_to_depth`
+*   `tf.depth_to_space`
+*   `tf.gather`
+*   `tf.gather_nd`
+*   `tf.unique_with_counts`
+*   `tf.scatter_nd`
+*   `tf.dynamic_partition`
+*   `tf.dynamic_stitch`
+*   `tf.boolean_mask`
+*   `tf.one_hot`
+*   `tf.sequence_mask`
+*   `tf.dequantize`
+*   `tf.quantize_v2`
+*   `tf.quantized_concat`
+*   `tf.setdiff1d`
 
 ## Fake quantization
 Operations used to help train for better quantization accuracy.
 
-*   @{tf.fake_quant_with_min_max_args}
-*   @{tf.fake_quant_with_min_max_args_gradient}
-*   @{tf.fake_quant_with_min_max_vars}
-*   @{tf.fake_quant_with_min_max_vars_gradient}
-*   @{tf.fake_quant_with_min_max_vars_per_channel}
-*   @{tf.fake_quant_with_min_max_vars_per_channel_gradient}
+*   `tf.fake_quant_with_min_max_args`
+*   `tf.fake_quant_with_min_max_args_gradient`
+*   `tf.fake_quant_with_min_max_vars`
+*   `tf.fake_quant_with_min_max_vars_gradient`
+*   `tf.fake_quant_with_min_max_vars_per_channel`
+*   `tf.fake_quant_with_min_max_vars_per_channel_gradient`