aten.index_select (#3744)

Summary:
Pull Request resolved: #3744

## The Operator
`nn.Module` invocations of [`torch.index_select`](https://pytorch.org/docs/stable/generated/torch.index_select.html) get compiled to `aten.index_select.default` in the Edge Dialect, which carries the following signature.
```
- func: index_select(Tensor self, int dim, Tensor index) -> Tensor
```

## Implementation
This is a C-packing-only implementation. It is very similar to `aten.slice`: #3171
```
- func: slice.Tensor(Tensor(a) self, int dim=0, SymInt? start=None, SymInt? end=None, SymInt step=1) -> Tensor(a)
```

It features a similar split between a shader for N,H,W and a shader for C, because copying from the C-dimension is more difficult due to C-packing.

Both `index_select` and `slice` copy specific indices across 1 dimension. The difference is in the way these indices are specified.
- `slice` uses `start=1`/`end=5`/`step=2` as three scalars for indices `1,3`.
- `index_select` lists the exact indices inside a tensor e.g. `index=torch.tensor([1,3])`.

Hence, `slice` uses a `offset=1` and `step=2` to compute input position. In `index_select`, we read the index tensor to compute input position.

Reviewed By: copyrightly

Differential Revision: D57745489

fbshipit-source-id: 4ef7f1a13d4bf74af20fe61149dbd5d461aaab0c

Author: jorgep31415

backends/vulkan/partitioner/supported_ops.py

@@ -99,6 +99,7 @@ def __contains__(self, op):
 ]
 
 INDEXING_OPS = [
+    exir_ops.edge.aten.index_select.default,
     exir_ops.edge.aten.select_copy.int,
     exir_ops.edge.aten.slice_copy.Tensor,
 ]

backends/vulkan/runtime/graph/ops/glsl/index_select.glsl

@@ -0,0 +1,44 @@
+/*
+ * 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.
+ */
+
+#version 450 core
+
+#define PRECISION ${PRECISION}
+
+#define VEC4_T ${texel_type(DTYPE)}
+
+layout(std430) buffer;
+
+#include "indexing_utils.h"
+
+${layout_declare_tensor(0, "w", "t_out", DTYPE, STORAGE)}
+${layout_declare_tensor(1, "r", "t_in", DTYPE, STORAGE)}
+${layout_declare_tensor(2, "r", "t_idx", "int", STORAGE)}
+${layout_declare_ubo(3, "ivec4", "sizes")}
+${layout_declare_ubo(4, "int", "gpu_dim", "int", "stride")}
+
+layout(local_size_x_id = 0, local_size_y_id = 1, local_size_z_id = 2) in;
+
+layout(constant_id = 3) const int packed_dim = C_DIM;
+
+void main() {
+  const ivec3 out_pos = ivec3(gl_GlobalInvocationID);
+
+  if (pos_out_of_bounds(out_pos, sizes, packed_dim)) {
+    return;
+  }
+
+  const int out_idx = out_pos[gpu_dim] / stride;
+  const int within_stride = out_pos[gpu_dim] % stride;
+  const int in_idx = texelFetch(t_idx, ivec3(out_idx, 0, 0), 0).x;
+
+  ivec3 in_pos = out_pos;
+  in_pos[gpu_dim] = in_idx * stride + within_stride;
+
+  imageStore(t_out, out_pos, texelFetch(t_in, in_pos, 0));
+}

backends/vulkan/runtime/graph/ops/glsl/index_select.yaml

@@ -0,0 +1,12 @@
+index_select:
+  parameter_names_with_default_values:
+    DTYPE: float
+    NDIM: 3
+    STORAGE: texture3d
+  generate_variant_forall:
+    DTYPE:
+      - VALUE: half
+      - VALUE: float
+      - VALUE: int
+  shader_variants:
+    - NAME: index_select

backends/vulkan/runtime/graph/ops/glsl/index_select_channel.glsl

@@ -0,0 +1,55 @@
+/*
+ * 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.
+ */
+
+#version 450 core
+
+#define PRECISION ${PRECISION}
+
+#define VEC4_T ${texel_type(DTYPE)}
+
+layout(std430) buffer;
+
+#include "indexing_utils.h"
+
+${layout_declare_tensor(0, "w", "t_out", DTYPE, STORAGE)}
+${layout_declare_tensor(1, "r", "t_in", DTYPE, STORAGE)}
+${layout_declare_tensor(2, "r", "t_idx", "int", STORAGE)}
+${layout_declare_ubo(3, "ivec4", "out_sizes")}
+${layout_declare_ubo(4, "ivec4", "in_sizes")}
+
+layout(local_size_x_id = 0, local_size_y_id = 1, local_size_z_id = 2) in;
+
+layout(constant_id = 3) const int packed_dim = C_DIM;
+
+void main() {
+  const ivec3 out_pos = ivec3(gl_GlobalInvocationID);
+
+  if (pos_out_of_bounds(out_pos, out_sizes, packed_dim)) {
+    return;
+  }
+
+  const ivec4 idx = to_tensor_idx(out_pos, out_sizes, packed_dim);
+  const ivec4 buffer_ixs = get_texel_nchw_buffer_ixs(idx, out_sizes, packed_dim);
+
+  VEC4_T out_texel;
+  for (int i = 0; i < 4; ++i) {
+      const ivec4 out_idx = from_nchw_buffer_i(buffer_ixs[i], out_sizes);
+      int out_channel = out_idx.z;
+      int in_channel = texelFetch(t_idx, ivec3(out_channel, 0, 0), 0).x;
+
+      ivec4 in_idx = out_idx;
+      in_idx.z = in_channel;
+
+      ivec4 in_elem_pos = to_texture_elem_pos(in_idx, in_sizes, packed_dim);
+
+      VEC4_T in_texel = texelFetch(t_in, in_elem_pos.xyz, 0);
+
+      out_texel[i] = in_texel[in_elem_pos.w];
+  }
+  imageStore(t_out, out_pos, out_texel);
+}

backends/vulkan/runtime/graph/ops/glsl/index_select_channel.yaml

@@ -0,0 +1,12 @@
+index_select_channel:
+  parameter_names_with_default_values:
+    DTYPE: float
+    NDIM: 3
+    STORAGE: texture3d
+  generate_variant_forall:
+    DTYPE:
+      - VALUE: half
+      - VALUE: float
+      - VALUE: int
+  shader_variants:
+    - NAME: index_select_channel

backends/vulkan/runtime/graph/ops/impl/IndexSelect.cpp

@@ -0,0 +1,134 @@
+/*
+ * 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/vulkan/runtime/graph/ops/OperatorRegistry.h>
+
+#include <executorch/backends/vulkan/runtime/graph/ops/impl/Staging.h>
+
+#include <executorch/backends/vulkan/runtime/graph/ops/impl/utils/DimUtils.h>
+#include <executorch/backends/vulkan/runtime/graph/ops/impl/utils/TensorUtils.h>
+
+#include <executorch/backends/vulkan/runtime/graph/ops/utils/ShaderNameUtils.h>
+
+namespace vkcompute {
+
+void check_index_select_args(
+    const vTensor& in,
+    const vTensor& idx,
+    const vTensor& out) {
+  VK_CHECK_COND(check_memory_layout_is(in, api::kChannelsPacked));
+  VK_CHECK_COND(check_memory_layout_is(idx, api::kChannelsPacked));
+  VK_CHECK_COND(check_memory_layout_is(out, api::kChannelsPacked));
+}
+
+void add_index_select_channel_node(
+    ComputeGraph& graph,
+    ValueRef in,
+    ValueRef idx,
+    ValueRef out) {
+  vTensorPtr t_in = graph.get_tensor(in);
+  vTensorPtr t_idx = graph.get_tensor(idx);
+  vTensorPtr t_out = graph.get_tensor(out);
+
+  check_index_select_args(*t_in, *t_idx, *t_out);
+
+  std::string kernel_name = "index_select_channel";
+  kernel_name.reserve(kShaderNameReserve);
+  add_dtype_suffix(kernel_name, *t_out);
+
+  api::utils::uvec3 global_size = t_out->image_extents();
+  api::utils::uvec3 local_size = adaptive_work_group_size(global_size);
+
+  graph.execute_nodes().emplace_back(new ExecuteNode(
+      graph,
+      VK_KERNEL_FROM_STR(kernel_name),
+      global_size,
+      local_size,
+      {{out, api::MemoryAccessType::WRITE},
+       {{in, idx}, api::MemoryAccessType::READ}},
+      {t_out->sizes_ubo(), t_in->sizes_ubo()}));
+}
+
+struct IndexSelectParams final {
+  int32_t gpu_dim;
+  int32_t stride;
+};
+
+IndexSelectParams create_index_select_params(
+    const int64_t dim_idx,
+    const vTensor& in) {
+  if (dim_idx == kWidth4D) {
+    return {0, 1};
+  } else if (dim_idx == kHeight4D) {
+    return {1, 1};
+  } else if (dim_idx == kBatch4D) {
+    int64_t n_channels = dim_at(in.sizes(), kChannel4D);
+    int64_t stride = api::utils::div_up_4(n_channels);
+    return {2, static_cast<int32_t>(stride)};
+  } else {
+    VK_THROW("Unexpected dim_idx!");
+  }
+}
+
+void add_index_select_node(
+    ComputeGraph& graph,
+    ValueRef in,
+    const int64_t dim_idx,
+    ValueRef idx,
+    ValueRef out) {
+  vTensorPtr t_in = graph.get_tensor(in);
+  vTensorPtr t_idx = graph.get_tensor(idx);
+  vTensorPtr t_out = graph.get_tensor(out);
+
+  check_index_select_args(*t_in, *t_idx, *t_out);
+
+  IndexSelectParams params = create_index_select_params(dim_idx, *t_in);
+
+  std::string kernel_name = "index_select";
+  kernel_name.reserve(kShaderNameReserve);
+  add_dtype_suffix(kernel_name, *t_out);
+
+  api::utils::uvec3 global_size = t_out->image_extents();
+  api::utils::uvec3 local_size = adaptive_work_group_size(global_size);
+
+  graph.execute_nodes().emplace_back(new ExecuteNode(
+      graph,
+      VK_KERNEL_FROM_STR(kernel_name),
+      global_size,
+      local_size,
+      {{out, api::MemoryAccessType::WRITE},
+       {{in, idx}, api::MemoryAccessType::READ}},
+      {t_out->sizes_ubo(), graph.create_params_buffer(params)}));
+}
+
+int64_t get_dim_idx(ComputeGraph& graph, ValueRef in, ValueRef dim_ref) {
+  vTensorPtr t_in = graph.get_tensor(in);
+  int64_t dim = graph.extract_scalar<int64_t>(dim_ref);
+  dim = normalize(dim, t_in->dim());
+  return normalize_to_dim_index(*t_in, dim);
+}
+
+void index_select(ComputeGraph& graph, const std::vector<ValueRef>& args) {
+  ValueRef in = prepack_if_tensor_ref(graph, args[0]);
+  ValueRef dim_ref = args[1];
+  ValueRef idx = prepack_if_tensor_ref(graph, args[2]);
+  ValueRef out = args[3];
+
+  const int64_t dim_idx = get_dim_idx(graph, in, dim_ref);
+  if (dim_idx == kChannel4D) {
+    add_index_select_channel_node(graph, in, idx, out);
+  } else {
+    add_index_select_node(graph, in, dim_idx, idx, out);
+  }
+}
+
+REGISTER_OPERATORS {
+  VK_REGISTER_OP(aten.index_select.default, index_select);
+}
+
+} // namespace vkcompute

backends/vulkan/test/op_tests/cases.py

@@ -416,13 +416,34 @@ def get_slice_inputs():
     test_suite = VkTestSuite([tuple(tc) for tc in test_cases])
 
     test_suite.dtypes = ["at::kFloat"]
-    test_suite.layouts = [
-        "api::kChannelsPacked",
-    ]
+    test_suite.layouts = ["api::kChannelsPacked"]
     test_suite.data_gen = "make_seq_tensor"
     return test_suite
 
 
+def get_index_select_inputs():
+    Test = namedtuple("VkIndexSelectTest", ["self", "dim", "index"])
+    Test.__new__.__defaults__ = (None, 0, None)
+
+    test_cases = []
+
+    for i in range(4):
+        test_cases += [
+            Test(self=[9, 9, 9, 9], dim=i, index=[0]),
+            Test(self=[9, 9, 9, 9], dim=i, index=[2]),
+            Test(self=[9, 9, 9, 9], dim=i, index=[0, 2]),
+            Test(self=[9, 9, 9, 9], dim=i, index=[3, 1]),
+            Test(self=[9, 9, 9, 9], dim=i, index=[5, 5]),
+            Test(self=[9, 9, 9, 9], dim=i, index=[2, 3, 4, 5, 7]),
+        ]
+
+    test_suite = VkTestSuite([tuple(tc) for tc in test_cases])
+
+    test_suite.dtypes = ["at::kFloat"]
+    test_suite.layouts = ["api::kChannelsPacked"]
+    return test_suite
+
+
 def get_unsqueeze_inputs():
     test_suite = VkTestSuite(
         [
@@ -816,6 +837,7 @@ def get_gelu_inputs():
     "aten.view_copy.default": get_view_inputs(),
     "aten.slice_copy.Tensor": get_slice_inputs(),
     "aten.slice.Tensor": get_slice_inputs(),
+    "aten.index_select.default": get_index_select_inputs(),
     "aten.unsqueeze_copy.default": get_unsqueeze_inputs(),
     "aten.clone.default": get_clone_inputs(),
     "aten.repeat.default": get_repeat_inputs(),

backends/vulkan/test/op_tests/utils/codegen_base.py

@@ -154,7 +154,12 @@ def create_input_data(self, arg: Argument, data: Any) -> str:  # noqa: C901
             ret_str = f"{cpp_type} {arg.name} = "
 
         if cpp_type == AT_TENSOR:
-            ret_str += f"{self.suite_def.data_gen}({init_list_str(data)}, test_dtype);"
+            if arg.name == "index":
+                ret_str += f"make_index_tensor({init_list_str(data)});"
+            else:
+                ret_str += (
+                    f"{self.suite_def.data_gen}({init_list_str(data)}, test_dtype);"
+                )
         elif cpp_type == OPT_AT_TENSOR:
             if str(data) == "None":
                 ret_str += "std::nullopt;"
@@ -267,7 +272,7 @@ def generate_suite_cpp(self) -> str:
 
 at::Tensor make_seq_tensor(
     std::vector<int64_t> sizes,
-      at::ScalarType dtype = at::kFloat) {{
+    at::ScalarType dtype = at::kFloat) {{
   int64_t n = 1;
   for (auto size: sizes) {{
     n *= size;
@@ -283,6 +288,16 @@ def generate_suite_cpp(self) -> str:
   return at::from_blob(values.data(), sizes, at::kFloat).toType(dtype).detach().clone();
 }}
 
+
+at::Tensor make_index_tensor(std::vector<int64_t> indices) {{
+  int64_t size = static_cast<int64_t>(indices.size());
+  at::ScalarType dtype = at::kInt;
+
+  // from_blob doesn't take ownership of data. Hence must create a copy as
+  // "values" will go out of scope.
+  return at::from_blob(indices.data(), {{size}}, dtype).detach().clone();
+}}
+
 {test_suites_cpp}
 """
 

backends/vulkan/test/test_vulkan_delegate.py

@@ -1272,3 +1272,39 @@ def forward(self, x):
             memory_layouts=[vk_graph_schema.VkMemoryLayout.TENSOR_CHANNELS_PACKED],
             custom_pass=[MeanToSumDiv()],
         )
+
+    def test_vulkan_backend_index_select_int(self):
+        class IndexSelectModule(torch.nn.Module):
+            def __init__(self, dim, indices):
+                super().__init__()
+                self.dim = dim
+                self.index = torch.tensor(indices, dtype=torch.int32)
+
+            def forward(self, x):
+                return torch.index_select(x, self.dim, self.index)
+
+        sample_inputs = (torch.arange(96).reshape(2, 8, 2, 3).int(),)
+
+        self.lower_module_and_test_output(
+            IndexSelectModule(dim=1, indices=[2, 3, 5, 6, 7]),
+            sample_inputs,
+            memory_layouts=[vk_graph_schema.VkMemoryLayout.TENSOR_CHANNELS_PACKED],
+        )
+
+    def test_vulkan_backend_index_select(self):
+        class IndexSelectModule(torch.nn.Module):
+            def __init__(self, dim, indices):
+                super().__init__()
+                self.dim = dim
+                self.index = torch.tensor(indices, dtype=torch.int32)
+
+            def forward(self, x):
+                return torch.index_select(x, self.dim, self.index)
+
+        sample_inputs = (torch.arange(144).reshape(12, 1, 3, 4).float(),)
+
+        self.lower_module_and_test_output(
+            IndexSelectModule(dim=0, indices=[1, 3, 5, 7, 8, 9, 10, 11, 2, 3]),
+            sample_inputs,
+            memory_layouts=[vk_graph_schema.VkMemoryLayout.TENSOR_CHANNELS_PACKED],
+        )