[ExpandDimsOp] Micro-optimizations for tf.expand_dims().

1. Avoid calling `ctx->allocate_output()` with a dummy value, and instead call `ctx->set_output()` on the reshaped tensor.
2. Compute the expanded shape by writing directly into an `InlinedVector` instead of copying the original shape to an `std::vector`, then using `emplace()` to insert the new value and shift the old ones along.
3. Avoid calling `OpKernelContext::input()` repeatedly.
4. Avoid using `Tensor::flat<Tdim>` to access the axis: instead use `DMAHelper::base` to avoid the shape calculations and CHECK statements.

PiperOrigin-RevId: 308634055
Change-Id: I3eb86940943324d98542764506c1e39dcf2b9fa3

tensorflow/core/kernels/BUILD

@@ -1281,7 +1281,7 @@ tf_kernel_library(
 tf_kernel_library(
     name = "shape_ops",
     prefix = "shape_ops",
-    deps = ARRAY_DEPS,
+    deps = ARRAY_DEPS + ["//tensorflow/core/common_runtime:dma_helper"],
 )
 
 tf_kernel_library(
@@ -2280,6 +2280,25 @@ tf_kernel_library(
     ],
 )
 
+tf_cc_test(
+    name = "shape_ops_test",
+    size = "small",
+    srcs = ["shape_ops_test.cc"],
+    deps = [
+        ":ops_testutil",
+        ":ops_util",
+        ":shape_ops",
+        "//tensorflow/core:core_cpu",
+        "//tensorflow/core:framework",
+        "//tensorflow/core:lib",
+        "//tensorflow/core:protos_all_cc",
+        "//tensorflow/core:test",
+        "//tensorflow/core:test_main",
+        "//tensorflow/core:testlib",
+        "//tensorflow/core/kernels/data:single_threaded_executor",
+    ],
+)
+
 tf_cc_test(
     name = "slice_op_test",
     size = "small",

tensorflow/core/kernels/shape_ops.h

@@ -20,6 +20,8 @@ limitations under the License.
 #include <unordered_set>
 #include <vector>
 
+#include "absl/container/inlined_vector.h"
+#include "tensorflow/core/common_runtime/dma_helper.h"
 #include "tensorflow/core/framework/bounds_check.h"
 #include "tensorflow/core/framework/op_kernel.h"
 #include "tensorflow/core/framework/tensor.h"
@@ -138,41 +140,43 @@ class ExpandDimsOp : public OpKernel {
   explicit ExpandDimsOp(OpKernelConstruction* ctx) : OpKernel(ctx) {}
 
   void Compute(OpKernelContext* ctx) override {
-    OP_REQUIRES(ctx, ctx->input(0).dtype() != DT_VARIANT,
+    const Tensor& input_t = ctx->input(0);
+    OP_REQUIRES(ctx, input_t.dtype() != DT_VARIANT,
                 errors::InvalidArgument("ExpandDims on Variant not supported"));
 
+    const Tensor& dim_t = ctx->input(1);
     OP_REQUIRES(
-        ctx, (ctx->input(1).NumElements() == 1),
+        ctx, (dim_t.NumElements() == 1),
         errors::InvalidArgument("'dim' must be a tensor with a single value"));
-    Tdim dim = ctx->input(1).flat<Tdim>()(0);
-    OP_REQUIRES(
-        ctx, (dim >= -1 - ctx->input(0).dims() && dim <= ctx->input(0).dims()),
-        errors::InvalidArgument("Tried to expand dim index ", dim,
-                                " for tensor with ", ctx->input(0).dims(),
-                                " dimensions."));
-
-    auto existing_dims = ctx->input(0).shape().dim_sizes();
-    // Safe - # elements in tensor dims bounded.
-    const int existing_dims_size = static_cast<int>(existing_dims.size());
-    std::vector<int64> new_shape(existing_dims_size);
-    for (size_t i = 0; i < new_shape.size(); ++i) {
-      new_shape[i] = existing_dims[i];
-    }
+    DCHECK_EQ(dim_t.dtype(), DataTypeToEnum<Tdim>::v());
+    Tdim dim = *static_cast<const Tdim*>(DMAHelper::base(&dim_t));
+    const TensorShape& input_shape = input_t.shape();
+    int input_dims = input_shape.dims();
+    OP_REQUIRES(ctx, dim >= -1 - input_dims && dim <= input_dims,
+                errors::InvalidArgument("Tried to expand dim index ", dim,
+                                        " for tensor with ", input_dims,
+                                        " dimensions."));
 
     // We emulate numpy's interpretation of the dim axis when
     // -input.dims() >= dim <= input.dims().
     if (dim < 0) {
-      dim += existing_dims.size() + 1;
+      // Clamp to the end if needed.
+      dim = std::min<Tdim>(dim + input_dims + 1, input_dims);
     }
 
-    // Clamp to the end if needed.
-    dim = std::min<Tdim>(dim, existing_dims_size);
-    new_shape.emplace(new_shape.begin() + dim, 1);
-    const TensorShape output_shape(new_shape);
+    // Compute new shape with an additional dimension.
+    absl::InlinedVector<int64, 8> output_shape_vec(input_dims + 1);
+    for (int64 i = 0; i < dim; ++i) {
+      output_shape_vec[i] = input_shape.dim_size(i);
+    }
+    output_shape_vec[dim] = 1;
+    for (int64 i = dim + 1; i < input_dims + 1; ++i) {
+      output_shape_vec[i] = input_shape.dim_size(i - 1);
+    }
+    TensorShape output_shape(output_shape_vec);
 
-    Tensor* output = nullptr;
-    OP_REQUIRES_OK(ctx, ctx->allocate_output(0, {0}, &output));
-    if (!output->CopyFrom(ctx->input(0), output_shape)) {
+    Tensor output_t;
+    if (!output_t.CopyFrom(input_t, output_shape)) {
       // This should never happen, since the sizes of the input and output
       // should always be the same (we only expand the dimension with 1).
       ctx->SetStatus(
@@ -180,6 +184,7 @@ class ExpandDimsOp : public OpKernel {
                            ctx->input(0).shape().DebugString(),
                            " and output shape ", output_shape.DebugString()));
     }
+    ctx->set_output(0, std::move(output_t));
   }
 
   bool IsExpensive() override { return false; }

tensorflow/core/kernels/shape_ops_test.cc

@@ -0,0 +1,67 @@
+/* Copyright 2020 The TensorFlow Authors. 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.
+==============================================================================*/
+
+#include <functional>
+#include <memory>
+
+#include "tensorflow/core/common_runtime/kernel_benchmark_testlib.h"
+#include "tensorflow/core/framework/allocator.h"
+#include "tensorflow/core/framework/op_kernel.h"
+#include "tensorflow/core/framework/tensor.h"
+#include "tensorflow/core/framework/types.h"
+#include "tensorflow/core/framework/types.pb.h"
+#include "tensorflow/core/graph/algorithm.h"
+#include "tensorflow/core/graph/node_builder.h"
+#include "tensorflow/core/graph/testlib.h"
+#include "tensorflow/core/kernels/ops_testutil.h"
+#include "tensorflow/core/kernels/ops_util.h"
+#include "tensorflow/core/lib/core/status_test_util.h"
+#include "tensorflow/core/platform/test.h"
+#include "tensorflow/core/platform/test_benchmark.h"
+
+namespace tensorflow {
+namespace {
+
+static void BM_ExpandDims(int iters) {
+  testing::StopTiming();
+  Graph* g = new Graph(OpRegistry::Global());
+
+  Tensor input(DT_INT32, TensorShape({1, 1, 1, 1}));
+  input.flat<int32>()(0) = 10;
+
+  Tensor axis(DT_INT32, TensorShape({}));
+  axis.flat<int32>()(0) = 2;
+
+  Node* node;
+  TF_CHECK_OK(NodeBuilder(g->NewName("n"), "ExpandDims")
+                  .Input(test::graph::Constant(g, input))
+                  .Input(test::graph::Constant(g, axis))
+                  .Attr("T", DT_INT32)
+                  .Attr("Tdim", DT_INT32)
+                  .Finalize(g, &node));
+  FixupSourceAndSinkEdges(g);
+
+  testing::StartTiming();
+  test::Benchmark("cpu", g, nullptr, nullptr, nullptr,
+                  "SINGLE_THREADED_EXECUTOR")
+      .Run(iters);
+
+  testing::UseRealTime();
+}
+
+BENCHMARK(BM_ExpandDims);
+
+}  // namespace
+}  // namespace tensorflow