[WebGPU] Implement SparseAttentionIndexer operator

docs/contrib_ops/cuda/sparse_attention_indexer.md

@@ -115,9 +115,10 @@ follow from `Lb`, `S` and `r` alone (see [§5](#5-policy-csa)).
 | `I` | `tensor(int64)` |
 | `M` | `tensor(int32)` |
 
-Only the CUDA execution provider registers a kernel. There is no CPU kernel; the header under
-`contrib_ops/cpu/sparse/` only holds the CUDA-free constants that the schema, the kernel and the
-tests must agree on.
+CUDA registers all three `T` types. WebGPU registers `float` and `float16`; see the
+[WebGPU implementation notes](../webgpu/sparse_attention_indexer.md). There is no CPU kernel; the
+header under `contrib_ops/cpu/sparse/` only holds the provider-neutral constants that the schema,
+kernels and tests must agree on.
 
 ### Output slot discipline
 

docs/contrib_ops/webgpu/sparse_attention_indexer.md

@@ -0,0 +1,49 @@
+# SparseAttentionIndexer on WebGPU
+
+The WebGPU execution provider implements version 1 of
+`com.microsoft.SparseAttentionIndexer` for the `qsa` and `csa` policies. It uses
+the provider-neutral schema and state ABI described in the
+[operator documentation](../cuda/sparse_attention_indexer.md).
+
+## Supported subset
+
+- batched inputs;
+- `qsa` and `csa` policy modes;
+- `float32` and `float16`;
+- explicit graph-visible key and packed projection-buffer state;
+- rank-2 INT64 QSA padding masks with internally derived causal visibility;
+- deterministic score-descending, index-ascending TopK ties.
+
+BF16, packed/variable-length inputs, and fixed-capacity caches using
+`past_sequence_length` are not supported by the WebGPU kernel. Unknown policies
+and policy-incompatible inputs or attributes are rejected.
+
+## Execution
+
+State concatenation, visible-token grouping, QSA pooling, CSA overlap
+compression, query/key RMS normalization, rotary embedding, scoring, selection, and
+output padding execute in WGSL. The implementation does not map GPU buffers,
+read selected values back to the host, or retain state in the kernel object.
+All reductions and softmax calculations accumulate in FP32, including for
+FP16 inputs.
+
+The rank-3 query projection is logically reshaped into heads inside the shader. Query and key
+projections therefore both connect directly to the operator; their consecutive norm-weight inputs
+are applied internally before rotary embedding.
+
+The initial implementation prioritizes correctness and uses one independently
+writable workgroup per query or completed CSA window. Candidate scoring during
+selection is recomputed rather than materialized, avoiding candidate-count
+limits and GPU-to-CPU synchronization at the cost of additional computation.
+
+## Follow-up work
+
+- packed/variable-length input;
+- fixed-capacity cache updates;
+- specialized large-candidate TopK;
+- subgroup-optimized reductions;
+- fused projection, pooling, and scoring;
+- reduced recomputation and temporary-buffer use;
+- selector/executor fusion;
+- WebGPU `DynamicSparseAttention` and `SparsePagedAttention`;
+- additional element types.