WebNN: Support rankRange for op output tensors in opSupportLimits

This CL prototypes WebNN spec change [1] that supports tensor rank
range for graph input, constant, output and each operation's output.

This CL adds new shape rank validation according to allowed output
tensor rank of expand and reshape operations.

The sequence output of gru and cell operations has different rank,
this CL extends context properties to support them.

For logical ops, the output rank ranges are set to each op's input
rank ranges, while the output data types are set to unified logical
output data type of context properties.

[1]: webmachinelearning/webnn#857

Bug: 442209350
Change-Id: Ie5ca5c794cebb4586bcccaaa8d237be1dffea458
Reviewed-on: https://chromium-review.googlesource.com/c/chromium/src/+/6903617
Reviewed-by: Reilly Grant <reillyg@chromium.org>
Reviewed-by: Alex Gough <ajgo@chromium.org>
Commit-Queue: ningxin hu <ningxin.hu@intel.com>
Cr-Commit-Position: refs/heads/main@{#1516982}

Author: huningxin

webnn/validation_tests/expand.https.any.js

@@ -17,7 +17,7 @@ multi_builder_test(async (t, builder, otherBuilder) => {
 }, '[expand] throw if input is from another builder');
 
 const label = 'xxx_expand';
-const regrexp = new RegExp('\\[' + label + '\\]');
+const regexp = new RegExp('\\[' + label + '\\]');
 const tests = [
   {
     name: '[expand] Test with 0-D scalar to 3-D tensor.',
@@ -77,7 +77,7 @@ tests.forEach(
         const options = {...test.options};
         if (options.label) {
           assert_throws_with_label(
-              () => builder.expand(input, test.newShape, options), regrexp);
+              () => builder.expand(input, test.newShape, options), regexp);
         } else {
           assert_throws_js(
               TypeError, () => builder.expand(input, test.newShape, options));
@@ -113,5 +113,19 @@ promise_test(async t => {
 
   const options = {label};
   assert_throws_with_label(
-      () => builder.expand(input, newShape, options), regrexp);
+      () => builder.expand(input, newShape, options), regexp);
 }, '[expand] throw if the output tensor byte length exceeds limit');
+
+promise_test(async t => {
+  const builder = new MLGraphBuilder(context);
+
+  const input = builder.input('input', {dataType: 'float32', shape: [2]});
+  const newShape =
+      new Array(context.opSupportLimits().expand.output.rankRange.max + 1)
+          .fill(1);
+  newShape[newShape.length - 1] = 2;
+
+  const options = {label};
+  assert_throws_with_label(
+      () => builder.expand(input, newShape, options), regexp);
+}, '[expand] throw if new shape rank exceeds limit');

webnn/validation_tests/reshape.https.any.js

@@ -82,3 +82,19 @@ tests.forEach(
             () => builder.reshape(input, test.newShape, options), regrexp);
       }
     }, test.name));
+
+promise_test(async t => {
+  const builder = new MLGraphBuilder(context);
+
+  const input = builder.input('input', {dataType: 'float32', shape: [2]});
+  const newShape =
+      new Array(context.opSupportLimits().expand.output.rankRange.max + 1)
+          .fill(1);
+  newShape[0] = 2;
+
+  const label = 'reshape_xxx';
+  const options = {label};
+  const regrexp = new RegExp('\\[' + label + '\\]');
+  assert_throws_with_label(
+      () => builder.reshape(input, newShape, options), regrexp);
+}, '[expand] throw if new shape rank exceeds limit');