[ExecuTorch][WebGPU] Add select/boolean ops (where, scalar compares, logical_not) to the WebGPU backend

backends/vulkan/op_registry.py

@@ -1746,6 +1746,34 @@ def register_rms_norm():
     )
 
 
+@update_features(
+    [
+        exir_ops.edge.aten.ne.Scalar,
+        exir_ops.edge.aten.lt.Scalar,
+        exir_ops.edge.aten.le.Scalar,
+        exir_ops.edge.aten.ge.Scalar,
+    ]
+)
+def register_compare_scalar_ops():
+    return OpFeatures(
+        inputs_storage=utils.ANY_STORAGE,
+        inputs_dtypes=utils.FP_INT_T,
+        outputs_dtypes=utils.BOOL_T,
+        supports_resize=True,
+        supports_highdim=True,
+    )
+
+
+@update_features(exir_ops.edge.aten.logical_not.default)
+def register_logical_not():
+    return OpFeatures(
+        inputs_storage=utils.ANY_STORAGE,
+        inputs_dtypes=utils.BOOL_T,
+        supports_resize=True,
+        supports_highdim=True,
+    )
+
+
 #######################
 ## Utility functions ##
 #######################

backends/webgpu/CMakeLists.txt

@@ -59,7 +59,10 @@ set(WEBGPU_SRCS
     runtime/ops/reduce/Reduce.cpp
     runtime/ops/div/BinaryOp.cpp
     runtime/ops/sub/BinaryOp.cpp
+    runtime/ops/where/Where.cpp
+    runtime/ops/compare/Compare.cpp
     runtime/ops/linear/Linear.cpp
+    runtime/ops/logical_not/LogicalNot.cpp
 )
 
 add_library(webgpu_backend ${WEBGPU_SRCS})

backends/webgpu/runtime/ops/compare/Compare.cpp

@@ -0,0 +1,192 @@
+/*
+ * 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/compare/compare_wgsl.h>
+
+#include <webgpu/webgpu.h>
+
+#include <cstdint>
+#include <stdexcept>
+#include <string>
+#include <vector>
+
+namespace executorch::backends::webgpu {
+
+namespace {
+
+struct CompareParams {
+  uint32_t num_elements;
+  uint32_t mode;
+  float scalar;
+  uint32_t _pad;
+};
+
+float read_scalar(WebGPUGraph& graph, int id, const char* op_name) {
+  if (graph.get_value_type(id) == WebGPUGraph::ValueType::Double) {
+    return static_cast<float>(graph.get_double(id));
+  }
+  if (graph.get_value_type(id) == WebGPUGraph::ValueType::Int) {
+    return static_cast<float>(graph.get_int(id));
+  }
+  throw std::runtime_error(std::string(op_name) + ": scalar is not int/double");
+}
+
+// cmp(self[i], scalar) -> byte-packed bool; one u32 word packs 4 elems.
+void compare_impl(
+    WebGPUGraph& graph,
+    const std::vector<int>& args,
+    uint32_t mode,
+    const char* op_name) {
+  const int self_id = args.at(0);
+  const int out_id = args.at(args.size() - 1);
+  const float scalar = read_scalar(graph, args.at(1), op_name);
+
+  WGPUDevice device = graph.device();
+  const auto& self_tensor = graph.get_tensor(self_id);
+  const auto& out_tensor = graph.get_tensor(out_id);
+
+  if (self_tensor.buffer == nullptr || out_tensor.buffer == nullptr) {
+    throw std::runtime_error(std::string(op_name) + ": null buffer binding");
+  }
+  if (self_tensor.nbytes % sizeof(float) != 0) {
+    throw std::runtime_error(std::string(op_name) + ": self is not fp32");
+  }
+  const uint32_t numel =
+      static_cast<uint32_t>(self_tensor.nbytes / sizeof(float));
+  if (out_tensor.nbytes != static_cast<size_t>(numel)) {
+    throw std::runtime_error(
+        std::string(op_name) + ": out is not a 1-byte (bool) tensor");
+  }
+
+  const size_t out_bind_size = (out_tensor.nbytes + 3) & ~size_t(3);
+  const uint32_t n_words = (numel + 3u) / 4u;
+
+  uint32_t wg_size =
+      utils::clamp_workgroup_size(device, kCompareWorkgroupSizeX);
+  uint32_t workgroup_count =
+      utils::compute_1d_workgroup_count(device, n_words, wg_size, op_name);
+
+  WGPUConstantEntry wg_size_constant = {};
+  wg_size_constant.key = {"wg_size", WGPU_STRLEN};
+  wg_size_constant.value = static_cast<double>(wg_size);
+
+  CompareParams params = {numel, mode, scalar, 0u};
+  WGPUBuffer params_buf =
+      utils::make_uniform(device, &params, sizeof(CompareParams));
+  graph.add_uniform_buffer_bytes(sizeof(CompareParams));
+
+  WGPUShaderSourceWGSL wgsl_desc = {};
+  wgsl_desc.chain.sType = WGPUSType_ShaderSourceWGSL;
+  wgsl_desc.code = {kCompareWGSL, WGPU_STRLEN};
+  WGPUShaderModuleDescriptor shader_desc = {};
+  shader_desc.nextInChain = &wgsl_desc.chain;
+  WGPUShaderModule shader = wgpuDeviceCreateShaderModule(device, &shader_desc);
+
+  WGPUBindGroupLayoutEntry entries[3] = {};
+  entries[0].buffer.type = WGPUBufferBindingType_ReadOnlyStorage;
+  entries[1].buffer.type = WGPUBufferBindingType_Storage;
+  entries[2].buffer.type = WGPUBufferBindingType_Uniform;
+  for (uint32_t i = 0; i < 3; i++) {
+    entries[i].binding = i;
+    entries[i].visibility = WGPUShaderStage_Compute;
+  }
+
+  WGPUBindGroupLayoutDescriptor bgl_desc = {};
+  bgl_desc.entryCount = 3;
+  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[3] = {};
+  bg_entries[0].binding = 0;
+  bg_entries[0].buffer = self_tensor.buffer;
+  bg_entries[0].size = self_tensor.nbytes;
+  bg_entries[1].binding = 1;
+  bg_entries[1].buffer = out_tensor.buffer;
+  bg_entries[1].size = out_bind_size;
+  bg_entries[2].binding = 2;
+  bg_entries[2].buffer = params_buf;
+  bg_entries[2].size = sizeof(CompareParams);
+
+  WGPUBindGroupDescriptor bg_desc = {};
+  bg_desc.layout = bgl;
+  bg_desc.entryCount = 3;
+  bg_desc.entries = bg_entries;
+  WGPUBindGroup bind_group = wgpuDeviceCreateBindGroup(device, &bg_desc);
+
+  const size_t dispatch_idx =
+      graph.add_dispatch({pipeline, bind_group, workgroup_count});
+
+  WGPUBuffer p_buf = params_buf;
+  auto cmp_resize =
+      [self_id, out_id, mode, scalar, wg_size, dispatch_idx, p_buf, op_name](
+          WebGPUGraph& g) {
+        const auto& d = g.cur_dims(self_id);
+        uint32_t n = 1u;
+        for (auto x : d) {
+          n *= static_cast<uint32_t>(x);
+        }
+        g.set_cur_dims(out_id, d);
+        CompareParams p = {n, mode, scalar, 0u};
+        wgpuQueueWriteBuffer(g.queue(), p_buf, 0, &p, sizeof(p));
+        const uint32_t nw = (n + 3u) / 4u;
+        g.dispatch_at(dispatch_idx).workgroup_count_x =
+            utils::compute_1d_workgroup_count(g.device(), nw, wg_size, op_name);
+      };
+  graph.add_tensor_resize_hook(self_id, cmp_resize);
+
+  wgpuShaderModuleRelease(shader);
+  wgpuBindGroupLayoutRelease(bgl);
+  wgpuPipelineLayoutRelease(pipeline_layout);
+  graph.own_uniform_buffer(params_buf);
+}
+
+void eq_scalar_impl(WebGPUGraph& graph, const std::vector<int>& args) {
+  compare_impl(graph, args, 0u, "eq.Scalar");
+}
+void ne_scalar_impl(WebGPUGraph& graph, const std::vector<int>& args) {
+  compare_impl(graph, args, 1u, "ne.Scalar");
+}
+void le_scalar_impl(WebGPUGraph& graph, const std::vector<int>& args) {
+  compare_impl(graph, args, 2u, "le.Scalar");
+}
+void ge_scalar_impl(WebGPUGraph& graph, const std::vector<int>& args) {
+  compare_impl(graph, args, 3u, "ge.Scalar");
+}
+void lt_scalar_impl(WebGPUGraph& graph, const std::vector<int>& args) {
+  compare_impl(graph, args, 4u, "lt.Scalar");
+}
+
+} // namespace
+
+WEBGPU_REGISTER_OPERATORS {
+  WEBGPU_REGISTER_OP(aten.eq.Scalar, eq_scalar_impl);
+  WEBGPU_REGISTER_OP(aten.ne.Scalar, ne_scalar_impl);
+  WEBGPU_REGISTER_OP(aten.le.Scalar, le_scalar_impl);
+  WEBGPU_REGISTER_OP(aten.ge.Scalar, ge_scalar_impl);
+  WEBGPU_REGISTER_OP(aten.lt.Scalar, lt_scalar_impl);
+}
+
+} // namespace executorch::backends::webgpu

backends/webgpu/runtime/ops/compare/compare.wgsl

@@ -0,0 +1,45 @@
+@group(0) @binding(0) var<storage, read> input: array<f32>;
+@group(0) @binding(1) var<storage, read_write> output: array<u32>;
+
+struct Params {
+  num_elements: u32,
+  mode: u32,
+  scalar: f32,
+  _pad: u32,
+}
+@group(0) @binding(2) var<uniform> params: Params;
+
+override wg_size: u32 = 64u;
+
+// One thread per output u32 word packs 4 bool bytes -> no inter-thread race.
+@compute @workgroup_size(wg_size, 1, 1)
+fn main(@builtin(global_invocation_id) gid: vec3<u32>) {
+    let word_idx = gid.x;
+    let n_words = (params.num_elements + 3u) / 4u;
+    if (word_idx >= n_words) {
+        return;
+    }
+    var packed: u32 = 0u;
+    for (var j: u32 = 0u; j < 4u; j = j + 1u) {
+        let i = word_idx * 4u + j;
+        if (i < params.num_elements) {
+            let v = input[i];
+            var r: bool;
+            if (params.mode == 0u) {
+                r = v == params.scalar;
+            } else if (params.mode == 1u) {
+                r = v != params.scalar;
+            } else if (params.mode == 2u) {
+                r = v <= params.scalar;
+            } else if (params.mode == 3u) {
+                r = v >= params.scalar;
+            } else {
+                r = v < params.scalar;
+            }
+            if (r) {
+                packed = packed | (1u << (j * 8u));
+            }
+        }
+    }
+    output[word_idx] = packed;
+}

backends/webgpu/runtime/ops/compare/compare_wgsl.h

@@ -0,0 +1,69 @@
+/*
+ * 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 compare.wgsl - DO NOT EDIT.
+// wgsl-sha256: f13da085195696aa6975cae62b4d0b2f5837fc02584d95b0a46fd06dc418c4a4
+inline constexpr const char* kCompareWGSL = R"(
+@group(0) @binding(0) var<storage, read> input: array<f32>;
+@group(0) @binding(1) var<storage, read_write> output: array<u32>;
+
+struct Params {
+  num_elements: u32,
+  mode: u32,
+  scalar: f32,
+  _pad: u32,
+}
+@group(0) @binding(2) var<uniform> params: Params;
+
+override wg_size: u32 = 64u;
+
+// One thread per output u32 word packs 4 bool bytes -> no inter-thread race.
+@compute @workgroup_size(wg_size, 1, 1)
+fn main(@builtin(global_invocation_id) gid: vec3<u32>) {
+    let word_idx = gid.x;
+    let n_words = (params.num_elements + 3u) / 4u;
+    if (word_idx >= n_words) {
+        return;
+    }
+    var packed: u32 = 0u;
+    for (var j: u32 = 0u; j < 4u; j = j + 1u) {
+        let i = word_idx * 4u + j;
+        if (i < params.num_elements) {
+            let v = input[i];
+            var r: bool;
+            if (params.mode == 0u) {
+                r = v == params.scalar;
+            } else if (params.mode == 1u) {
+                r = v != params.scalar;
+            } else if (params.mode == 2u) {
+                r = v <= params.scalar;
+            } else if (params.mode == 3u) {
+                r = v >= params.scalar;
+            } else {
+                r = v < params.scalar;
+            }
+            if (r) {
+                packed = packed | (1u << (j * 8u));
+            }
+        }
+    }
+    output[word_idx] = packed;
+}
+)";
+
+inline constexpr uint32_t kCompareWorkgroupSizeX = 64;
+inline constexpr uint32_t kCompareWorkgroupSizeY = 1;
+inline constexpr uint32_t kCompareWorkgroupSizeZ = 1;
+
+} // namespace executorch::backends::webgpu