Assign to both shape and dimensions when creating MLTensors

egalli · Sep 18, 2024 · 7bc892d · 7bc892d
1 parent 5b3ceec
commit 7bc892d
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Showing 3 changed files with 13 additions and 1 deletion.
diff --git a/js/web/lib/wasm/jsep/webnn/tensor-manager.ts b/js/web/lib/wasm/jsep/webnn/tensor-manager.ts
@@ -145,7 +145,13 @@ class TensorTracker {
     LOG_DEBUG('verbose', () => `[WebNN] MLContext.createTensor {dataType: ${dataType}, shape: ${shape}}`);
     // eslint-disable-next-line no-bitwise
     const usage = MLTensorUsage.READ | MLTensorUsage.WRITE;
-    const tensor = await this.context.createTensor({ dataType, shape, usage });
+    const tensor = await this.context.createTensor({
+      dataType,
+      shape,
+      // Assign both shape and dimensions while transitioning to new API.
+      dimensions: shape,
+      usage,
+    });
     this.tensorEntry = [tensor, dataType, shape];
     this.tensorCache.push(this.tensorEntry);
 

diff --git a/js/web/lib/wasm/jsep/webnn/webnn.d.ts b/js/web/lib/wasm/jsep/webnn/webnn.d.ts
@@ -33,6 +33,8 @@ type MLOperandDataType = 'float32'|'float16'|'int32'|'uint32'|'int64'|'uint64'|'
 interface MLOperandDescriptor {
   dataType: MLOperandDataType;
   shape?: readonly number[];
+  /** @deprecated Use shape instead of dimensions */
+  dimensions?: readonly number[];
 }
 interface MLOperand {
   dataType(): MLOperandDataType;

diff --git a/js/web/test/test-runner.ts b/js/web/test/test-runner.ts
@@ -664,6 +664,8 @@ async function createMLTensorForOutput(mlContext: MLContext, type: ort.Tensor.Ty
   const mlTensor = await mlContext.createTensor({
     dataType,
     shape: dims as number[],
+    // Assign both shape and dimensions while transitioning to new API.
+    dimensions: dims as number[],
     usage: MLTensorUsage.READ,
   });
 
@@ -686,6 +688,8 @@ async function createMLTensorForInput(mlContext: MLContext, cpuTensor: ort.Tenso
   const mlTensor = await mlContext.createTensor({
     dataType,
     shape: cpuTensor.dims as number[],
+    // Assign both shape and dimensions while transitioning to new API.
+    dimensions: cpuTensor.dims as number[],
     usage: MLTensorUsage.WRITE,
   });
   mlContext.writeTensor(mlTensor, cpuTensor.data);