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README.md +14 -10
build/webgpu/bench.json +0 -1
build/webgpu/manifest.json +6 -38
build/webgpu/metadata.json +7 -7
build/webgpu/shape.wgsl.jinja +3 -3
build/webgpu/test.json +12 -13

README.md CHANGED Viewed

@@ -18,15 +18,15 @@ See the [ONNX `Shape` spec](https://onnx.ai/onnx/operators/onnx__Shape.html) for
 ## Inputs
-| Name | Bind key | Logical dtype | Rank | Shape | Description | Presence |
-| --- | --- | --- | --- | --- | --- | --- |
-| `data` | `data` | `T` | — | — | The input tensor whose shape is computed. | required |
 ## Outputs
-| Name | Bind key | Logical dtype | WebGPU storage | Rank | Shape | Description | Presence |
-| --- | --- | --- | --- | --- | --- | --- | --- |
-| `shape` | `shape` | `S` | `uint32` | `1` | derived; see description | Logical int64 1-D tensor of dimension sizes for the selected axes of the input; WebGPU emits bounded uint32 values. | required |
 ## Attributes
@@ -34,8 +34,8 @@ Attributes and default values (overridable per request):
 | Attribute | Default | Description |
 | --- | --- | --- |
-| `start` | `0` | First axis (inclusive) of the shape slice; negative values count from the back, default is 0. |
 | `end` | — | Last axis (exclusive) of the shape slice; negative values count from the back; if omitted, all axes through the last are included. |
 ## Type constraints
@@ -46,7 +46,7 @@ Attributes and default values (overridable per request):
 ## Files
-- [`metadata.json`](build/webgpu/metadata.json) — kernel metadata (id, digests, provenance)
 - [`manifest.json`](build/webgpu/manifest.json) — the op contract (source of truth)
 - [`test.json`](build/webgpu/test.json) — correctness cases
 - [`bench.json`](build/webgpu/bench.json) — benchmark + tuning cases
@@ -54,10 +54,14 @@ Attributes and default values (overridable per request):
 ## Use with `@huggingface/kernels`
-The loader derives every required output's shape and logical dtype from the manifest contract and this call.
-It then allocates the result tensors automatically.
 The `version: 1` option selects the published kernel contract; it is independent of any operator opset, contrib `since_version`, or model version.
 Replace each `*Data` placeholder with a typed array containing the corresponding input data.

 ## Inputs
+| Name | Logical dtype | Rank | Shape | Description | Presence |
+| --- | --- | --- | --- | --- | --- |
+| `data` | `T` | — | — | The input tensor whose shape is computed. | required |
 ## Outputs
+| Name | Logical dtype | WebGPU storage | Rank | Shape | Description | Presence |
+| --- | --- | --- | --- | --- | --- | --- |
+| `shape` | `S` | `uint32` | `1` | derived | Logical int64 1-D tensor of dimension sizes for the selected axes of the input; WebGPU emits bounded uint32 values. | required |
 ## Attributes
 | Attribute | Default | Description |
 | --- | --- | --- |
 | `end` | — | Last axis (exclusive) of the shape slice; negative values count from the back; if omitted, all axes through the last are included. |
+| `start` | `0` | First axis (inclusive) of the shape slice; negative values count from the back, default is 0. |
 ## Type constraints
 ## Files
+- [`metadata.json`](build/webgpu/metadata.json) — kernel metadata (id, digests, per-variant templates, provenance)
 - [`manifest.json`](build/webgpu/manifest.json) — the op contract (source of truth)
 - [`test.json`](build/webgpu/test.json) — correctness cases
 - [`bench.json`](build/webgpu/bench.json) — benchmark + tuning cases
 ## Use with `@huggingface/kernels`
+```sh
+npm install --save-exact @huggingface/kernels@0.0.1-preview.2
+```
+Required output shapes and logical data types are inferred from the supplied inputs and attributes; result tensors are allocated automatically.
 The `version: 1` option selects the published kernel contract; it is independent of any operator opset, contrib `since_version`, or model version.
+It follows the `v1` branch as fixes land. To pin exact artifact bytes, pass a 40-character commit `revision` instead of `version`.
 Replace each `*Data` placeholder with a typed array containing the corresponding input data.

build/webgpu/bench.json CHANGED Viewed

@@ -1,5 +1,4 @@
 {
-  "op": "ai.onnx.Shape",
   "cases": [
     {
       "name": "rank4",

 {
   "cases": [
     {
       "name": "rank4",

build/webgpu/manifest.json CHANGED Viewed

@@ -2,30 +2,13 @@
   "domain": "ai.onnx",
   "name": "Shape",
   "sinceVersion": 15,
-  "description": "Returns a 1-D tensor containing the shape of the input tensor. Optional `start` and `end` attributes select a slice of the shape axes; negative values count from the back, and axes are clamped to `[0, rank]`.",
-  "inputs": [{ "role": "data", "dtype": "T", "description": "The input tensor whose shape is computed." }],
-  "outputs": [
-    {
-      "role": "shape",
-      "dtype": "S",
-      "rank": 1,
-      "description": "Logical int64 1-D tensor of dimension sizes for the selected axes of the input; WebGPU emits bounded uint32 values.",
-      "shape": ["max(0, endAxis - startAxis)"]
-    }
-  ],
-  "attributes": { "start": 0 },
-  "attributeDescriptions": {
-    "start": "First axis (inclusive) of the shape slice; negative values count from the back, default is 0.",
-    "end": "Last axis (exclusive) of the shape slice; negative values count from the back; if omitted, all axes through the last are included."
-  },
   "typeConstraints": {
     "T": ["float32", "float16", "int32", "int16", "uint32", "int8", "uint8", "bool"],
     "S": ["int64"]
   },
-  "args": {
-    "data": { "kind": "tensor", "semantic": "data", "role": "input" },
-    "shape": { "kind": "tensor", "semantic": "shape", "role": "output", "dtype": "uint32" }
-  },
   "derive": {
     "startAxis": "max(0, min(ranks.data, attrs.start + (ranks.data if attrs.start < 0 else 0)))",
     "endParam": "attrs.end if has(attrs, \"end\") else ranks.data",
@@ -39,24 +22,9 @@
         {
           "id": "main",
           "name": "Shape",
-          "source": {
-            "shader": "shape.wgsl.jinja",
-            "inputs": {
-              "inputShape": "shapes.data",
-              "rank": "ranks.data",
-              "start": "startAxis",
-              "outputRank": "dim(shapes.shape, 0)"
-            }
-          },
-          "bindings": [
-            {
-              "name": "shape",
-              "arg": "shape",
-              "semantic": "shape",
-              "buffer": { "type": "storage" },
-              "elementType": "u32"
-            }
-          ],
           "dispatch": { "x": 1 }
         }
       ]

   "domain": "ai.onnx",
   "name": "Shape",
   "sinceVersion": 15,
+  "inputs": { "data": { "dtype": "T" } },
+  "outputs": { "shape": { "dtype": "S", "rank": 1, "shape": ["max(0, endAxis - startAxis)"], "storage": "uint32" } },
+  "attributes": { "start": { "default": 0 }, "end": {} },
   "typeConstraints": {
     "T": ["float32", "float16", "int32", "int16", "uint32", "int8", "uint8", "bool"],
     "S": ["int64"]
   },
   "derive": {
     "startAxis": "max(0, min(ranks.data, attrs.start + (ranks.data if attrs.start < 0 else 0)))",
     "endParam": "attrs.end if has(attrs, \"end\") else ranks.data",
         {
           "id": "main",
           "name": "Shape",
+          "shader": "shape.wgsl.jinja",
+          "derive": { "inputShape": "shapes.data", "start": "startAxis", "outputRank": "dim(shapes.shape, 0)" },
+          "bindings": ["shape"],
           "dispatch": { "x": 1 }
         }
       ]

build/webgpu/metadata.json CHANGED Viewed

@@ -1,18 +1,18 @@
 {
   "name": "ai.onnx.Shape",
-  "id": "_ai_onnx_shape_webgpu_353de3d",
   "version": 1,
   "license": "Apache-2.0",
   "backend": { "type": "webgpu" },
   "digest": {
     "algorithm": "sha256",
     "files": {
-      "bench.json": "kiw8iMiBPBGaaz6TKqd9RaaOn38QOi/xilG0TXGnttQ=",
-      "manifest.json": "Y8kEIxBXPtwm8XOQcctfW9bFg8RGzmi1r7HwvpwrEPY=",
-      "shape.wgsl.jinja": "J1oIMamgxFx04z+NWiHv6zFj8vclOHR99dd4R/GsPzY=",
-      "test.json": "U5HvTdgN4iqjYIRxu51OW8NZCuqqj/oRlYrEEruggIM="
     }
   },
-  "provenance": { "kernel": { "sha": "2e7068faf55e7f43df740015f6d1ee49391a41c5", "dirty": false } },
-  "webgpu": { "manifestSpec": "1.0", "specialized": true, "opPath": "ops/ai.onnx.Shape" }
 }

 {
   "name": "ai.onnx.Shape",
+  "id": "_ai_onnx_shape_webgpu_5a9b5b0",
   "version": 1,
   "license": "Apache-2.0",
   "backend": { "type": "webgpu" },
   "digest": {
     "algorithm": "sha256",
     "files": {
+      "bench.json": "R7qQRulG0ZYBXID+7lefm4MMiRSotddmA7zkoCnxAsQ=",
+      "manifest.json": "1disq05Dn+ENQNGqLwxbl1S5KHhAizkNtqMKAXDaEC0=",
+      "shape.wgsl.jinja": "6VyYYEl2JqmSVGNpab59uvRysZnhLgkw4QlAZHhLPuM=",
+      "test.json": "CY1CD4C9jPFMmdxqKd9PY4TbKI0vUgRvBY79x5eekt4="
     }
   },
+  "provenance": { "kernel": { "sha": "91d990483a174128daf7673f3f37a7c890493ae1", "dirty": false } },
+  "webgpu": { "manifestSpec": "2.0", "variants": { "full_shape": ["shape.wgsl.jinja"] } }
 }

build/webgpu/shape.wgsl.jinja CHANGED Viewed

@@ -5,9 +5,9 @@ fn main(@builtin(global_invocation_id) gid: vec3<u32>) {
   if (gid.x != 0u) {
     return;
   }
-{% for dim in source.inputShape %}
-{% if loop.index0 >= source.start and loop.index0 < source.start + source.outputRank %}
-  shape[{{ loop.index0 - source.start }}u] = {{ dim }}u;
 {% endif %}
 {% endfor %}
 }

   if (gid.x != 0u) {
     return;
   }
+{% for dim in inputShape %}
+{% if loop.index0 >= start and loop.index0 < start + outputRank %}
+  shape[{{ loop.index0 - start }}u] = {{ dim }}u;
 {% endif %}
 {% endfor %}
 }

build/webgpu/test.json CHANGED Viewed

@@ -1,5 +1,4 @@
 {
-  "op": "ai.onnx.Shape",
   "cases": [
     {
       "name": "rank3_f32",
@@ -241,7 +240,7 @@
       "name": "onnx_backend_shape",
       "provenance": {
         "source": "cmake/external/onnx/onnx/backend/test/data/node/test_shape",
-        "notes": "ONNX shape/size outputs are int64; this framework uses uint32 shape/index storage."
       },
       "inputs": { "data": { "dtype": "float32", "shape": [3, 4, 5] } },
       "outputs": { "shape": { "dtype": "uint32", "shape": [3], "tolerance": 0 } }
@@ -250,7 +249,7 @@
       "name": "onnx_backend_shape_clip_end",
       "provenance": {
         "source": "cmake/external/onnx/onnx/backend/test/data/node/test_shape_clip_end",
-        "notes": "ONNX shape/size outputs are int64; this framework uses uint32 shape/index storage."
       },
       "attrs": { "end": 10 },
       "inputs": { "data": { "dtype": "float32", "shape": [3, 4, 5] } },
@@ -260,7 +259,7 @@
       "name": "onnx_backend_shape_clip_start",
       "provenance": {
         "source": "cmake/external/onnx/onnx/backend/test/data/node/test_shape_clip_start",
-        "notes": "ONNX shape/size outputs are int64; this framework uses uint32 shape/index storage."
       },
       "attrs": { "start": -10 },
       "inputs": { "data": { "dtype": "float32", "shape": [3, 4, 5] } },
@@ -270,7 +269,7 @@
       "name": "onnx_backend_shape_end_1",
       "provenance": {
         "source": "cmake/external/onnx/onnx/backend/test/data/node/test_shape_end_1",
-        "notes": "ONNX shape/size outputs are int64; this framework uses uint32 shape/index storage."
       },
       "attrs": { "end": 1 },
       "inputs": { "data": { "dtype": "float32", "shape": [3, 4, 5] } },
@@ -280,7 +279,7 @@
       "name": "onnx_backend_shape_end_negative_1",
       "provenance": {
         "source": "cmake/external/onnx/onnx/backend/test/data/node/test_shape_end_negative_1",
-        "notes": "ONNX shape/size outputs are int64; this framework uses uint32 shape/index storage."
       },
       "attrs": { "end": -1 },
       "inputs": { "data": { "dtype": "float32", "shape": [3, 4, 5] } },
@@ -290,7 +289,7 @@
       "name": "onnx_backend_shape_example",
       "provenance": {
         "source": "cmake/external/onnx/onnx/backend/test/data/node/test_shape_example",
-        "notes": "ONNX shape/size outputs are int64; this framework uses uint32 shape/index storage."
       },
       "inputs": { "data": { "dtype": "float32", "shape": [2, 3] } },
       "outputs": { "shape": { "dtype": "uint32", "shape": [2], "tolerance": 0 } }
@@ -299,7 +298,7 @@
       "name": "onnx_backend_shape_start_1",
       "provenance": {
         "source": "cmake/external/onnx/onnx/backend/test/data/node/test_shape_start_1",
-        "notes": "ONNX shape/size outputs are int64; this framework uses uint32 shape/index storage."
       },
       "attrs": { "start": 1 },
       "inputs": { "data": { "dtype": "float32", "shape": [3, 4, 5] } },
@@ -309,7 +308,7 @@
       "name": "onnx_backend_shape_start_1_end_2",
       "provenance": {
         "source": "cmake/external/onnx/onnx/backend/test/data/node/test_shape_start_1_end_2",
-        "notes": "ONNX shape/size outputs are int64; this framework uses uint32 shape/index storage."
       },
       "attrs": { "end": 2, "start": 1 },
       "inputs": { "data": { "dtype": "float32", "shape": [3, 4, 5] } },
@@ -319,7 +318,7 @@
       "name": "onnx_backend_shape_start_1_end_negative_1",
       "provenance": {
         "source": "cmake/external/onnx/onnx/backend/test/data/node/test_shape_start_1_end_negative_1",
-        "notes": "ONNX shape/size outputs are int64; this framework uses uint32 shape/index storage."
       },
       "attrs": { "end": -1, "start": 1 },
       "inputs": { "data": { "dtype": "float32", "shape": [3, 4, 5] } },
@@ -329,7 +328,7 @@
       "name": "onnx_backend_shape_start_greater_than_end",
       "provenance": {
         "source": "cmake/external/onnx/onnx/backend/test/data/node/test_shape_start_greater_than_end",
-        "notes": "ONNX shape/size outputs are int64; this framework uses uint32 shape/index storage."
       },
       "attrs": { "end": 1, "start": 2 },
       "inputs": { "data": { "dtype": "float32", "shape": [3, 4, 5] } },
@@ -339,7 +338,7 @@
       "name": "onnx_backend_shape_start_negative_1",
       "provenance": {
         "source": "cmake/external/onnx/onnx/backend/test/data/node/test_shape_start_negative_1",
-        "notes": "ONNX shape/size outputs are int64; this framework uses uint32 shape/index storage."
       },
       "attrs": { "start": -1 },
       "inputs": { "data": { "dtype": "float32", "shape": [3, 4, 5] } },
@@ -382,7 +381,7 @@
       "name": "rank7_full_shape",
       "provenance": {
         "source": "onnx spec: Shape returns the input tensor dimensions",
-        "notes": "Small rank-7 sentinel. ORT CPU returns [1,2,1,3,1,4,1]; full_shape is rank-agnostic, and rank8_full_shape covers the band above it."
       },
       "inputs": { "data": { "dtype": "float32", "shape": [1, 2, 1, 3, 1, 4, 1] } },
       "outputs": {

 {
   "cases": [
     {
       "name": "rank3_f32",
       "name": "onnx_backend_shape",
       "provenance": {
         "source": "cmake/external/onnx/onnx/backend/test/data/node/test_shape",
+        "notes": "ONNX Shape and Size return int64 values; this package stores representable shape values in uint32 slots."
       },
       "inputs": { "data": { "dtype": "float32", "shape": [3, 4, 5] } },
       "outputs": { "shape": { "dtype": "uint32", "shape": [3], "tolerance": 0 } }
       "name": "onnx_backend_shape_clip_end",
       "provenance": {
         "source": "cmake/external/onnx/onnx/backend/test/data/node/test_shape_clip_end",
+        "notes": "ONNX Shape and Size return int64 values; this package stores representable shape values in uint32 slots."
       },
       "attrs": { "end": 10 },
       "inputs": { "data": { "dtype": "float32", "shape": [3, 4, 5] } },
       "name": "onnx_backend_shape_clip_start",
       "provenance": {
         "source": "cmake/external/onnx/onnx/backend/test/data/node/test_shape_clip_start",
+        "notes": "ONNX Shape and Size return int64 values; this package stores representable shape values in uint32 slots."
       },
       "attrs": { "start": -10 },
       "inputs": { "data": { "dtype": "float32", "shape": [3, 4, 5] } },
       "name": "onnx_backend_shape_end_1",
       "provenance": {
         "source": "cmake/external/onnx/onnx/backend/test/data/node/test_shape_end_1",
+        "notes": "ONNX Shape and Size return int64 values; this package stores representable shape values in uint32 slots."
       },
       "attrs": { "end": 1 },
       "inputs": { "data": { "dtype": "float32", "shape": [3, 4, 5] } },
       "name": "onnx_backend_shape_end_negative_1",
       "provenance": {
         "source": "cmake/external/onnx/onnx/backend/test/data/node/test_shape_end_negative_1",
+        "notes": "ONNX Shape and Size return int64 values; this package stores representable shape values in uint32 slots."
       },
       "attrs": { "end": -1 },
       "inputs": { "data": { "dtype": "float32", "shape": [3, 4, 5] } },
       "name": "onnx_backend_shape_example",
       "provenance": {
         "source": "cmake/external/onnx/onnx/backend/test/data/node/test_shape_example",
+        "notes": "ONNX Shape and Size return int64 values; this package stores representable shape values in uint32 slots."
       },
       "inputs": { "data": { "dtype": "float32", "shape": [2, 3] } },
       "outputs": { "shape": { "dtype": "uint32", "shape": [2], "tolerance": 0 } }
       "name": "onnx_backend_shape_start_1",
       "provenance": {
         "source": "cmake/external/onnx/onnx/backend/test/data/node/test_shape_start_1",
+        "notes": "ONNX Shape and Size return int64 values; this package stores representable shape values in uint32 slots."
       },
       "attrs": { "start": 1 },
       "inputs": { "data": { "dtype": "float32", "shape": [3, 4, 5] } },
       "name": "onnx_backend_shape_start_1_end_2",
       "provenance": {
         "source": "cmake/external/onnx/onnx/backend/test/data/node/test_shape_start_1_end_2",
+        "notes": "ONNX Shape and Size return int64 values; this package stores representable shape values in uint32 slots."
       },
       "attrs": { "end": 2, "start": 1 },
       "inputs": { "data": { "dtype": "float32", "shape": [3, 4, 5] } },
       "name": "onnx_backend_shape_start_1_end_negative_1",
       "provenance": {
         "source": "cmake/external/onnx/onnx/backend/test/data/node/test_shape_start_1_end_negative_1",
+        "notes": "ONNX Shape and Size return int64 values; this package stores representable shape values in uint32 slots."
       },
       "attrs": { "end": -1, "start": 1 },
       "inputs": { "data": { "dtype": "float32", "shape": [3, 4, 5] } },
       "name": "onnx_backend_shape_start_greater_than_end",
       "provenance": {
         "source": "cmake/external/onnx/onnx/backend/test/data/node/test_shape_start_greater_than_end",
+        "notes": "ONNX Shape and Size return int64 values; this package stores representable shape values in uint32 slots."
       },
       "attrs": { "end": 1, "start": 2 },
       "inputs": { "data": { "dtype": "float32", "shape": [3, 4, 5] } },
       "name": "onnx_backend_shape_start_negative_1",
       "provenance": {
         "source": "cmake/external/onnx/onnx/backend/test/data/node/test_shape_start_negative_1",
+        "notes": "ONNX Shape and Size return int64 values; this package stores representable shape values in uint32 slots."
       },
       "attrs": { "start": -1 },
       "inputs": { "data": { "dtype": "float32", "shape": [3, 4, 5] } },
       "name": "rank7_full_shape",
       "provenance": {
         "source": "onnx spec: Shape returns the input tensor dimensions",
+        "notes": "A rank-7 tensor returns [1,2,1,3,1,4,1], exercising rank-agnostic full-shape emission."
       },
       "inputs": { "data": { "dtype": "float32", "shape": [1, 2, 1, 3, 1, 4, 1] } },
       "outputs": {