[WASM] Add Addn used by MobileNet (#2408)

FEATURE

Add `Addn` used by MobileNet

tfjs-backend-wasm/src/cc/BUILD

@@ -78,6 +78,7 @@ tfjs_cc_library(
   deps = [
     ":Abs",
     ":Add",
+    ":AddN",
     ":BatchMatMul",
     ":MaxPool",
     ":ClipByValue",
@@ -154,6 +155,15 @@ tfjs_cc_library(
   ],
 )
 
+tfjs_cc_library(
+  name = "AddN",
+  srcs = ["kernels/AddN.cc"],
+  deps = [
+    ":backend",
+    ":util",
+  ],
+)
+
 tfjs_cc_library(
   name = "BatchMatMul",
   srcs = ["kernels/BatchMatMul.cc"],

tfjs-backend-wasm/src/cc/kernels/AddN.cc

@@ -0,0 +1,78 @@
+/* Copyright 2019 Google Inc. All Rights Reserved.
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ * ===========================================================================*/
+
+#ifdef __EMSCRIPTEN__
+#include <emscripten.h>
+#endif
+
+#include <vector>
+
+#include "src/cc/backend.h"
+#include "src/cc/util.h"
+
+namespace {
+
+template <typename T>
+void addn(const std::vector<const T*>& inputs_buf, const int size, T* out_buf) {
+  // Initialize the output to 0.
+  memset(out_buf, 0, size * sizeof(T));
+
+  for (size_t in_idx = 0; in_idx < inputs_buf.size(); ++in_idx) {
+    const T* input = inputs_buf[in_idx];
+    for (size_t i = 0; i < size; ++i) {
+      out_buf[i] += input[i];
+    }
+  }
+}
+
+}  // namespace
+
+namespace tfjs {
+namespace wasm {
+// We use C-style API to interface with Javascript.
+extern "C" {
+
+#ifdef __EMSCRIPTEN__
+EMSCRIPTEN_KEEPALIVE
+#endif
+void AddN(const int* input_ids_ptr, const int input_ids_len, const DType dtype,
+          const int out_id) {
+  std::vector<int> inputs(input_ids_ptr, input_ids_ptr + input_ids_len);
+  auto& out_info = backend::get_tensor_info_out(out_id);
+  std::vector<void*> inputs_buf;
+  std::transform(
+      inputs.begin(), inputs.end(), std::back_inserter(inputs_buf),
+      [](int id) { return backend::get_tensor_info(id).memory_offset; });
+
+  switch (dtype) {
+    case DType::float32:
+      addn<float>(reinterpret_cast<std::vector<const float*>&>(inputs_buf),
+                  out_info.size, out_info.f32_write());
+      break;
+    case DType::int32:
+      addn<int>(reinterpret_cast<std::vector<const int*>&>(inputs_buf),
+                out_info.size, out_info.i32_write());
+      break;
+    case DType::boolean:
+      addn<bool>(reinterpret_cast<std::vector<const bool*>&>(inputs_buf),
+                 out_info.size, out_info.b_write());
+      break;
+    default:
+      util::warn("AddN failed. Unknown dtype %d", dtype);
+  }
+}
+
+}  // extern "C"
+}  // namespace wasm
+}  // namespace tfjs

tfjs-backend-wasm/src/kernels/AddN.ts

@@ -0,0 +1,58 @@
+/**
+ * @license
+ * Copyright 2019 Google Inc. All Rights Reserved.
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ * =============================================================================
+ */
+
+import {KernelFunc, registerKernel, TensorInfo, util} from '@tensorflow/tfjs-core';
+
+import {BackendWasm} from '../backend_wasm';
+import {CppDType} from './types';
+
+let wasmFunc:
+    (inputIds: Uint8Array, inputIdsLen: number, dtype: number, outId: number) =>
+        void;
+
+function setupFunc(backend: BackendWasm): void {
+  wasmFunc = backend.wasm.cwrap('AddN', null /* void */, [
+    'array',   // input_ids
+    'number',  // input_ids.length
+    'number',  // dtype
+    'number',  // out_id
+  ]);
+}
+
+function addn(args: {inputs: TensorInfo[], backend: BackendWasm}) {
+  const {inputs, backend} = args;
+  const out = backend.makeOutput(inputs[0].shape, inputs[0].dtype);
+
+  // Short-circuit zero-sized tensors.
+  if (util.sizeFromShape(out.shape) === 0) {
+    return out;
+  }
+
+  const inputIds = inputs.map(x => backend.dataIdMap.get(x.dataId).id);
+  const inputIdsBytes = new Uint8Array(new Int32Array(inputIds).buffer);
+  const outId = backend.dataIdMap.get(out.dataId).id;
+  wasmFunc(inputIdsBytes, inputIds.length, CppDType[out.dtype], outId);
+
+  return out;
+}
+
+registerKernel({
+  kernelName: 'AddN',
+  backendName: 'wasm',
+  setupFunc,
+  kernelFunc: addn as {} as KernelFunc,
+});

tfjs-backend-wasm/src/kernels/all_kernels.ts

@@ -20,6 +20,7 @@
 // the contents of this file and import only the kernels that are needed.
 import './Abs';
 import './Add';
+import './AddN';
 import './BatchMatMul';
 import './Cast';
 import './ClipByValue';

tfjs-backend-wasm/src/setup_test.ts

@@ -183,6 +183,7 @@ const TEST_FILTERS: TestFilter[] = [
   },
   {include: 'pad ', excludes: ['complex', 'zerosLike']},
   {include: 'clip', excludes: ['gradient']},
+  {include: 'addN'},
 ];
 
 const customInclude = (testName: string) => {

tfjs-core/src/ops/binary_ops.ts

@@ -128,7 +128,8 @@ function addN_<T extends Tensor>(tensors: Array<T|TensorLike>): T {
     return ders;
   };
   const inputs: NamedTensorMap = $tensors as {} as NamedTensorMap;
-  return ENGINE.runKernelFunc(backend => backend.addN($tensors), inputs, der);
+  return ENGINE.runKernelFunc(
+      backend => backend.addN($tensors), inputs, der, 'AddN');
 }
 
 /**