Bug fix: Link operator names to the MLGraphBuilder methods

For a "reshape" reference a malformed IDL link was present. The
other references are linked as appropriately to the builder
references rather than just being styled text.

Author: inexorabletash

SpecCodingConventions.md

@@ -70,6 +70,8 @@ Example:
     1. If |shape| is a [=circle=], draw it at |shape|'s [=circle/origin=].
 ```
 
+* When referencing an operator in text (e.g. sigmoid, tanh, etc), link the operator name to the `MLGraphBuilder` methods for creating the corresponding `MLOperand` or `MLActivation`, e.g. `{{MLGraphBuilder/sigmoid()}}`. This provides consistent styling, and provides a thorough overview of the operator, even if the method itself isn't being discussed.
+
 
 ### Formatting
 

index.bs

@@ -1637,7 +1637,7 @@ partial interface MLGraphBuilder {
 <div class="note">
   <details open>
     <summary>
-    The behavior of this operation when the input tensor is 4-D of the {{MLInputOperandLayout/"nchw"}} layout and the activation is of operator type *relu* can be generically emulated from the usage of other operations as follow. However, user agents typically have a more efficient implementation for it, therefore its usage is encouraged from the performance standpoint.
+    The behavior of this operation when the input tensor is 4-D of the {{MLInputOperandLayout/"nchw"}} layout and the activation is {{MLGraphBuilder/relu()}} can be generically emulated from the usage of other operations as follow. However, user agents typically have a more efficient implementation for it, therefore its usage is encouraged from the performance standpoint.
     </summary>
     <pre highlight="js">
     const shape = [1,null,1,1];
@@ -2527,7 +2527,7 @@ partial interface MLGraphBuilder {
 </div>
 
 <div class="note">
-Although operations *greaterOrEqual* and *lesserOrEqual* can each be implemented in terms of operations *not*, *lesser*, and *greater* in other words `greater-or-equal(a, b)` is `not(lesser(a, b))`, they are specifically defined to handle NaN cases and for performance reason to avoid double comparisons.
+Although operations {{MLGraphBuilder/greaterOrEqual()}} and {{MLGraphBuilder/lesserOrEqual()}} can each be implemented in terms of operations {{MLGraphBuilder/not()}}, {{MLGraphBuilder/lesser()}}, and {{MLGraphBuilder/greater()}} in other words `builder.greaterOrEqual(a, b)` is `builder.not(builder.lesser(a, b))`, they are specifically defined to handle NaN cases and for performance reason to avoid double comparisons.
 </div>
 
 <details open algorithm>
@@ -3388,7 +3388,7 @@ partial interface MLGraphBuilder {
 <div class="note">
 <details open>
   <summary>
-    The behavior of this operation can be generically emulated via other operations as shown below, when the weight layout is the default {{MLGruWeightLayout/"zrn"}} layout, and the activation functions of the update/reset gate and new gate are of the operator types *sigmoid* and *tanh* respectively.
+    The behavior of this operation can be generically emulated via other operations as shown below, when the weight layout is the default {{MLGruWeightLayout/"zrn"}} layout, and the activation functions of the update/reset gate and new gate are of the operator types {{MLGraphBuilder/sigmoid()}} and {{MLGraphBuilder/tanh()}} respectively.
   </summary>
   <pre highlight="js">
     const one = builder.constant(1);
@@ -4397,7 +4397,7 @@ partial interface MLGraphBuilder {
 <div class="note">
 <details open>
   <summary>
-    The behavior of this operation can be generically emulated via other operations as shown below, when the weight layout is the default {{MLLstmWeightLayout/"iofg"}} layout, and the activation functions of the input/forget/output gate and the cell gate/the cell state's filter for the output hidden state are of the operator types *sigmoid* and *tanh* respectively.
+    The behavior of this operation can be generically emulated via other operations as shown below, when the weight layout is the default {{MLLstmWeightLayout/"iofg"}} layout, and the activation functions of the input/forget/output gate and the cell gate/the cell state's filter for the output hidden state are of the operator types {{MLGraphBuilder/sigmoid()}} and {{MLGraphBuilder/tanh()}} respectively.
   </summary>
   <pre highlight="js">
     const zero = builder.constant(0);
@@ -5325,7 +5325,7 @@ partial interface MLGraphBuilder {
 <div class="note">
   <details open>
     <summary>
-    Many shape-related operations such as [squeeze](https://pytorch.org/docs/stable/generated/torch.squeeze.html), [unsqueeze](https://pytorch.org/docs/stable/generated/torch.unsqueeze.html), and [flatten](https://pytorch.org/docs/stable/generated/torch.flatten.html) can be generically implemented using the *reshape*}} operation as follows:
+    Many shape-related operations such as [squeeze](https://pytorch.org/docs/stable/generated/torch.squeeze.html), [unsqueeze](https://pytorch.org/docs/stable/generated/torch.unsqueeze.html), and [flatten](https://pytorch.org/docs/stable/generated/torch.flatten.html) can be generically implemented using the {{MLGraphBuilder/reshape()}} operation as follows:
     </summary>
     <pre highlight="js">
     // Returns a tensor with all specified dimensions of input of size 1 removed.