Add op: repeat_interleave.Tensor_out

Differential Revision: D67025538

Pull Request resolved: #7264

Author: manuelcandales

kernels/aten/functions.yaml

@@ -313,6 +313,8 @@
 
 - op: repeat.out
 
+- op: repeat_interleave.Tensor_out
+
 - op: reflection_pad1d.out
 
 - op: reflection_pad2d.out

kernels/portable/cpu/op_repeat_interleave.cpp

@@ -0,0 +1,111 @@
+/*
+ * 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/runtime/kernel/kernel_includes.h>
+
+namespace torch {
+namespace executor {
+namespace native {
+namespace {
+
+bool check_repeat_interleave_args(
+    const Tensor& repeats,
+    int64_t output_size_value,
+    int64_t repeats_sum,
+    Tensor& out) {
+  ET_LOG_MSG_AND_RETURN_IF_FALSE(
+      repeats.scalar_type() == ScalarType::Int ||
+          repeats.scalar_type() == ScalarType::Long,
+      "repeats must be int or long");
+  ET_LOG_MSG_AND_RETURN_IF_FALSE(repeats.dim() == 1, "repeats must be 1D");
+  ET_LOG_MSG_AND_RETURN_IF_FALSE(
+      output_size_value == repeats_sum,
+      "output_size, if provided, must be equal to repeats.sum()");
+  ET_LOG_AND_RETURN_IF_FALSE(tensors_have_same_dtype(repeats, out));
+
+  if (repeats.scalar_type() == ScalarType::Long) {
+    const int64_t* const repeats_data = repeats.const_data_ptr<int64_t>();
+    for (size_t i = 0; i < repeats.numel(); ++i) {
+      ET_LOG_MSG_AND_RETURN_IF_FALSE(
+          repeats_data[i] >= 0, "repeats cannot be negative");
+    }
+  } else {
+    const int32_t* const repeats_data = repeats.const_data_ptr<int32_t>();
+    for (size_t i = 0; i < repeats.numel(); ++i) {
+      ET_LOG_MSG_AND_RETURN_IF_FALSE(
+          repeats_data[i] >= 0, "repeats cannot be negative");
+    }
+  }
+
+  return true;
+}
+
+} // namespace
+
+using Tensor = exec_aten::Tensor;
+
+Tensor& repeat_interleave_Tensor_out(
+    KernelRuntimeContext& ctx,
+    const Tensor& repeats,
+    exec_aten::optional<int64_t> output_size,
+    Tensor& out) {
+  (void)ctx;
+
+  int64_t repeats_sum = 0;
+
+  constexpr auto name = "repeat_interleave.Tensor_out";
+
+  ET_SWITCH_TWO_TYPES(Int, Long, repeats.scalar_type(), ctx, name, CTYPE, [&] {
+    const CTYPE* repeats_data = repeats.const_data_ptr<CTYPE>();
+    for (size_t ix = 0; ix < repeats.numel(); ++ix) {
+      repeats_sum += static_cast<int64_t>(repeats_data[ix]);
+    }
+  });
+
+  int64_t output_size_value =
+      output_size.has_value() ? output_size.value() : repeats_sum;
+
+  ET_KERNEL_CHECK(
+      ctx,
+      check_repeat_interleave_args(
+          repeats, output_size_value, repeats_sum, out),
+      InvalidArgument,
+      out);
+
+  ET_KERNEL_CHECK(
+      ctx, tensors_have_same_dim_order(repeats, out), InvalidArgument, out);
+
+  ET_KERNEL_CHECK(
+      ctx, tensor_is_default_dim_order(repeats), InvalidArgument, out);
+
+  ET_KERNEL_CHECK_MSG(
+      ctx,
+      resize_tensor(
+          out, {static_cast<exec_aten::SizesType>(output_size_value)}) ==
+          Error::Ok,
+      InvalidArgument,
+      out,
+      "Failed to resize output tensor.");
+
+  ET_SWITCH_TWO_TYPES(Int, Long, repeats.scalar_type(), ctx, name, CTYPE, [&] {
+    const CTYPE* repeats_data = repeats.const_data_ptr<CTYPE>();
+    CTYPE* out_data = out.mutable_data_ptr<CTYPE>();
+    size_t out_ix = 0;
+    for (size_t ix = 0; ix < repeats.numel(); ix++) {
+      for (CTYPE i = 0; i < repeats_data[ix]; i++, out_ix++) {
+        out_data[out_ix] = static_cast<CTYPE>(ix);
+      }
+    }
+  });
+
+  return out;
+}
+
+} // namespace native
+} // namespace executor
+} // namespace torch

kernels/portable/functions.yaml

@@ -712,6 +712,11 @@
     - arg_meta: null
       kernel_name: torch::executor::repeat_out
 
+- op: repeat_interleave.Tensor_out
+  kernels:
+    - arg_meta: null
+      kernel_name: torch::executor::repeat_interleave_Tensor_out
+
 - op: reflection_pad1d.out
   kernels:
     - arg_meta: null

kernels/test/op_repeat_interleave_test.cpp

@@ -0,0 +1,43 @@
+/*
+ * 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/kernels/test/FunctionHeaderWrapper.h> // Declares the operator
+#include <executorch/kernels/test/TestUtil.h>
+#include <executorch/runtime/core/exec_aten/exec_aten.h>
+#include <executorch/runtime/core/exec_aten/testing_util/tensor_factory.h>
+#include <executorch/runtime/core/exec_aten/testing_util/tensor_util.h>
+
+using namespace ::testing;
+using exec_aten::optional;
+using exec_aten::ScalarType;
+using exec_aten::Tensor;
+using torch::executor::testing::TensorFactory;
+
+class OpRepeatInterleaveTensorOutTest : public OperatorTest {
+ protected:
+  Tensor& op_repeat_out(
+      const Tensor& repeats,
+      optional<int64_t> output_size,
+      Tensor& out) {
+    return torch::executor::aten::repeat_interleave_outf(
+        context_, repeats, output_size, out);
+  }
+};
+
+TEST_F(OpRepeatInterleaveTensorOutTest, SmokeTest) {
+  TensorFactory<ScalarType::Int> tf;
+
+  Tensor repeats = tf.make({3}, {2, 3, 1});
+
+  std::vector<int64_t> repeats_vec = {3, 4, 5, 6};
+  Tensor out = tf.zeros({6});
+  Tensor expected = tf.make({6}, {0, 0, 1, 1, 1, 2});
+  Tensor ret = op_repeat_out(repeats, 6, out);
+  EXPECT_TENSOR_EQ(ret, out);
+  EXPECT_TENSOR_EQ(ret, expected);
+}

kernels/test/targets.bzl

@@ -283,6 +283,7 @@ def define_common_targets():
     _common_op_test("op_relu_test", ["aten", "portable"])
     _common_op_test("op_remainder_test", ["aten", "portable"])
     _common_op_test("op_repeat_test", ["aten", "portable"])
+    _common_op_test("op_repeat_interleave_test", ["aten", "portable"])
     _common_op_test("op_reflection_pad1d_test", ["aten", "portable"])
     _common_op_test("op_reflection_pad2d_test", ["aten", "portable"])
     _common_op_test("op_reflection_pad3d_test", ["aten", "portable"])

shim/xplat/executorch/kernels/portable/op_registration_util.bzl

@@ -1001,6 +1001,9 @@ ATEN_OPS = (
             "//executorch/kernels/portable/cpu/util:repeat_util",
         ],
     ),
+    op_target(
+        name = "op_repeat_interleave",
+    ),
     op_target(
         name = "op_replication_pad1d",
         deps = [