[ExecuTorch][WebGPU] Add select_copy op (aten.select_copy.int)

backends/webgpu/CMakeLists.txt

@@ -43,6 +43,7 @@ set(WEBGPU_SRCS
     runtime/ops/rope/RotaryEmbedding.cpp
     runtime/ops/prepack/Prepack.cpp
     runtime/ops/view_copy/ViewCopy.cpp
+    runtime/ops/select/Select.cpp
 )
 
 add_library(webgpu_backend ${WEBGPU_SRCS})

backends/webgpu/runtime/ops/select/Select.cpp

@@ -0,0 +1,181 @@
+/*
+ * Copyright (c) Meta Platforms, Inc. and affiliates.
+ * All rights reserved.
+ *
+ * This source code is licensed under the BSD-style license found in the
+ * LICENSE file in the root directory of this source tree.
+ */
+
+#include <executorch/backends/webgpu/runtime/WebGPUGraph.h>
+#include <executorch/backends/webgpu/runtime/WebGPUUtils.h>
+#include <executorch/backends/webgpu/runtime/ops/OperatorRegistry.h>
+#include <executorch/backends/webgpu/runtime/ops/TensorMeta.h>
+#include <executorch/backends/webgpu/runtime/ops/select/select_wgsl.h>
+
+#include <webgpu/webgpu.h>
+
+#include <cstdint>
+#include <stdexcept>
+#include <string>
+#include <vector>
+
+namespace executorch::backends::webgpu {
+
+namespace {
+
+struct SelectParams {
+  uint32_t dim;
+  uint32_t index;
+  uint32_t _pad[2];
+};
+
+// dim/index are required Ints (SymInt throws); no Null default unlike slice.
+int64_t read_scalar(WebGPUGraph& graph, int id, const char* what) {
+  if (graph.get_value_type(id) == WebGPUGraph::ValueType::Int) {
+    return graph.get_int(id);
+  }
+  throw std::runtime_error(std::string("select: dynamic/unsupported ") + what);
+}
+
+void select_impl(WebGPUGraph& graph, const std::vector<int>& args) {
+  // args: [self, dim, index, out]; output rank = in rank - 1.
+  const int in_id = args.at(0);
+  const int out_id = args.at(3);
+
+  WGPUDevice device = graph.device();
+  const auto& in_tensor = graph.get_tensor(in_id);
+  const auto& out_tensor = graph.get_tensor(out_id);
+
+  const int in_ndim = static_cast<int>(in_tensor.dims.size());
+  int64_t dim = read_scalar(graph, args.at(1), "dim");
+  if (dim < 0) {
+    dim += in_ndim;
+  }
+  if (dim < 0 || dim >= in_ndim) {
+    throw std::runtime_error("select: dim out of range");
+  }
+  const int64_t in_size = in_tensor.dims[dim];
+  int64_t index = read_scalar(graph, args.at(2), "index");
+  if (index < 0) {
+    index += in_size;
+  }
+  if (index < 0 || index >= in_size) {
+    throw std::runtime_error("select: index out of range");
+  }
+
+  TensorMeta out_meta;
+  TensorMeta in_meta;
+  fill_tensor_meta(out_tensor, &out_meta);
+  fill_tensor_meta(in_tensor, &in_meta);
+  if (out_tensor.nbytes !=
+          static_cast<size_t>(out_meta.numel) * sizeof(float) ||
+      in_tensor.nbytes != static_cast<size_t>(in_meta.numel) * sizeof(float)) {
+    throw std::runtime_error("select: non-fp32 operand (nbytes != numel * 4)");
+  }
+
+  SelectParams params = {};
+  params.dim = static_cast<uint32_t>(dim);
+  params.index = static_cast<uint32_t>(index);
+
+  uint32_t wg_size = utils::clamp_workgroup_size(device, kSelectWorkgroupSizeX);
+  uint32_t workgroup_count = utils::compute_1d_workgroup_count(
+      device, out_meta.numel, wg_size, "select");
+
+  WGPUConstantEntry wg_size_constant = {};
+  wg_size_constant.key = {"wg_size", WGPU_STRLEN};
+  wg_size_constant.value = static_cast<double>(wg_size);
+
+  WGPUBuffer out_meta_buf =
+      utils::make_uniform(device, &out_meta, sizeof(TensorMeta));
+  WGPUBuffer in_meta_buf =
+      utils::make_uniform(device, &in_meta, sizeof(TensorMeta));
+  WGPUBuffer params_buf =
+      utils::make_uniform(device, &params, sizeof(SelectParams));
+  graph.add_uniform_buffer_bytes(2 * sizeof(TensorMeta) + sizeof(SelectParams));
+
+  WGPUShaderSourceWGSL wgsl_desc = {};
+  wgsl_desc.chain.sType = WGPUSType_ShaderSourceWGSL;
+  wgsl_desc.code = {kSelectWGSL, WGPU_STRLEN};
+  WGPUShaderModuleDescriptor shader_desc = {};
+  shader_desc.nextInChain = &wgsl_desc.chain;
+  WGPUShaderModule shader = wgpuDeviceCreateShaderModule(device, &shader_desc);
+
+  // Bind group: in, out (rw), out_meta, in_meta, params (3 uniforms).
+  WGPUBindGroupLayoutEntry entries[5] = {};
+  entries[0].binding = 0;
+  entries[0].visibility = WGPUShaderStage_Compute;
+  entries[0].buffer.type = WGPUBufferBindingType_ReadOnlyStorage;
+  entries[1].binding = 1;
+  entries[1].visibility = WGPUShaderStage_Compute;
+  entries[1].buffer.type = WGPUBufferBindingType_Storage;
+  entries[2].binding = 2;
+  entries[2].visibility = WGPUShaderStage_Compute;
+  entries[2].buffer.type = WGPUBufferBindingType_Uniform;
+  entries[3].binding = 3;
+  entries[3].visibility = WGPUShaderStage_Compute;
+  entries[3].buffer.type = WGPUBufferBindingType_Uniform;
+  entries[4].binding = 4;
+  entries[4].visibility = WGPUShaderStage_Compute;
+  entries[4].buffer.type = WGPUBufferBindingType_Uniform;
+
+  WGPUBindGroupLayoutDescriptor bgl_desc = {};
+  bgl_desc.entryCount = 5;
+  bgl_desc.entries = entries;
+  WGPUBindGroupLayout bgl = wgpuDeviceCreateBindGroupLayout(device, &bgl_desc);
+
+  WGPUPipelineLayoutDescriptor pl_desc = {};
+  pl_desc.bindGroupLayoutCount = 1;
+  pl_desc.bindGroupLayouts = &bgl;
+  WGPUPipelineLayout pipeline_layout =
+      wgpuDeviceCreatePipelineLayout(device, &pl_desc);
+
+  WGPUComputePipelineDescriptor pipeline_desc = {};
+  pipeline_desc.layout = pipeline_layout;
+  pipeline_desc.compute.module = shader;
+  pipeline_desc.compute.entryPoint = {"main", WGPU_STRLEN};
+  pipeline_desc.compute.constantCount = 1;
+  pipeline_desc.compute.constants = &wg_size_constant;
+  WGPUComputePipeline pipeline =
+      wgpuDeviceCreateComputePipeline(device, &pipeline_desc);
+
+  WGPUBindGroupEntry bg_entries[5] = {};
+  bg_entries[0].binding = 0;
+  bg_entries[0].buffer = in_tensor.buffer;
+  bg_entries[0].size = in_tensor.nbytes;
+  bg_entries[1].binding = 1;
+  bg_entries[1].buffer = out_tensor.buffer;
+  bg_entries[1].size = out_tensor.nbytes;
+  bg_entries[2].binding = 2;
+  bg_entries[2].buffer = out_meta_buf;
+  bg_entries[2].size = sizeof(TensorMeta);
+  bg_entries[3].binding = 3;
+  bg_entries[3].buffer = in_meta_buf;
+  bg_entries[3].size = sizeof(TensorMeta);
+  bg_entries[4].binding = 4;
+  bg_entries[4].buffer = params_buf;
+  bg_entries[4].size = sizeof(SelectParams);
+
+  WGPUBindGroupDescriptor bg_desc = {};
+  bg_desc.layout = bgl;
+  bg_desc.entryCount = 5;
+  bg_desc.entries = bg_entries;
+  WGPUBindGroup bind_group = wgpuDeviceCreateBindGroup(device, &bg_desc);
+
+  graph.add_dispatch({pipeline, bind_group, workgroup_count});
+
+  wgpuShaderModuleRelease(shader);
+  wgpuBindGroupLayoutRelease(bgl);
+  wgpuPipelineLayoutRelease(pipeline_layout);
+  // Drop our refs; the bind group keeps the uniforms alive until release.
+  wgpuBufferRelease(out_meta_buf);
+  wgpuBufferRelease(in_meta_buf);
+  wgpuBufferRelease(params_buf);
+}
+
+} // namespace
+
+WEBGPU_REGISTER_OPERATORS {
+  WEBGPU_REGISTER_OP(aten.select_copy.int, select_impl);
+}
+
+} // namespace executorch::backends::webgpu

backends/webgpu/runtime/ops/select/select.wgsl

@@ -0,0 +1,41 @@
+@group(0) @binding(0) var<storage, read> input: array<f32>;
+@group(0) @binding(1) var<storage, read_write> output: array<f32>;
+
+struct TensorMeta {
+  ndim: u32,
+  numel: u32,
+  sizes: vec4<u32>,
+  strides: vec4<u32>,
+}
+@group(0) @binding(2) var<uniform> out_meta: TensorMeta;
+@group(0) @binding(3) var<uniform> in_meta: TensorMeta;
+
+struct Params {
+  dim: u32,
+  index: u32,
+}
+@group(0) @binding(4) var<uniform> params: Params;
+
+override wg_size: u32 = 64u;
+
+@compute @workgroup_size(wg_size, 1, 1)
+fn main(@builtin(global_invocation_id) gid: vec3<u32>) {
+    let out_bufi = gid.x;
+    if (out_bufi >= out_meta.numel) {
+        return;
+    }
+
+    // Gather: out dim od -> in dim (od if od < dim else od+1); sel dim = index.
+    var rem = out_bufi;
+    var in_bufi: u32 = params.index * in_meta.strides[params.dim];
+    for (var od: u32 = 0u; od < out_meta.ndim; od = od + 1u) {
+        let coord = rem / out_meta.strides[od];
+        rem = rem % out_meta.strides[od];
+        var id = od;
+        if (od >= params.dim) {
+            id = od + 1u;
+        }
+        in_bufi = in_bufi + coord * in_meta.strides[id];
+    }
+    output[out_bufi] = input[in_bufi];
+}

backends/webgpu/runtime/ops/select/select_wgsl.h

@@ -0,0 +1,65 @@
+/*
+ * Copyright (c) Meta Platforms, Inc. and affiliates.
+ * All rights reserved.
+ *
+ * This source code is licensed under the BSD-style license found in the
+ * LICENSE file in the root directory of this source tree.
+ */
+
+#pragma once
+
+#include <cstdint>
+
+namespace executorch::backends::webgpu {
+
+// @generated from select.wgsl - DO NOT EDIT.
+// wgsl-sha256: 200cf5a8190045aa0562e782f01c1cfaf9681f30f679f5112ccc3d347a0ed8df
+inline constexpr const char* kSelectWGSL = R"(
+@group(0) @binding(0) var<storage, read> input: array<f32>;
+@group(0) @binding(1) var<storage, read_write> output: array<f32>;
+
+struct TensorMeta {
+  ndim: u32,
+  numel: u32,
+  sizes: vec4<u32>,
+  strides: vec4<u32>,
+}
+@group(0) @binding(2) var<uniform> out_meta: TensorMeta;
+@group(0) @binding(3) var<uniform> in_meta: TensorMeta;
+
+struct Params {
+  dim: u32,
+  index: u32,
+}
+@group(0) @binding(4) var<uniform> params: Params;
+
+override wg_size: u32 = 64u;
+
+@compute @workgroup_size(wg_size, 1, 1)
+fn main(@builtin(global_invocation_id) gid: vec3<u32>) {
+    let out_bufi = gid.x;
+    if (out_bufi >= out_meta.numel) {
+        return;
+    }
+
+    // Gather: out dim od -> in dim (od if od < dim else od+1); sel dim = index.
+    var rem = out_bufi;
+    var in_bufi: u32 = params.index * in_meta.strides[params.dim];
+    for (var od: u32 = 0u; od < out_meta.ndim; od = od + 1u) {
+        let coord = rem / out_meta.strides[od];
+        rem = rem % out_meta.strides[od];
+        var id = od;
+        if (od >= params.dim) {
+            id = od + 1u;
+        }
+        in_bufi = in_bufi + coord * in_meta.strides[id];
+    }
+    output[out_bufi] = input[in_bufi];
+}
+)";
+
+inline constexpr uint32_t kSelectWorkgroupSizeX = 64;
+inline constexpr uint32_t kSelectWorkgroupSizeY = 1;
+inline constexpr uint32_t kSelectWorkgroupSizeZ = 1;
+
+} // namespace executorch::backends::webgpu