[ET-VK] Add high dim support for permute

backends/vulkan/op_registry.py

@@ -490,7 +490,6 @@ def register_rotary_emb_op():
 @update_features(
     [
         exir_ops.edge.aten.permute.default,
-        exir_ops.edge.aten.permute_copy.default,
     ]
 )
 def register_view_ops():
@@ -506,6 +505,7 @@ def register_view_ops():
         exir_ops.edge.aten.squeeze_copy.dims,
         exir_ops.edge.aten.unsqueeze_copy.default,
         exir_ops.edge.aten.clone.default,
+        exir_ops.edge.aten.permute_copy.default,
     ]
 )
 def register_view_ops_with_buffer_meta():

backends/vulkan/runtime/graph/ops/glsl/indexing.glslh

@@ -98,6 +98,15 @@ uint idx_at(const TensorIndex tidx, const int dim) {
   return tidx.data[div_4(dim)][mod_4(dim)];
 }
 
+void permute(inout TensorIndex tidx, const ivec4 permute_order[DIMLIMIT_DIV4]) {
+  TensorIndex new_tidx = tidx;
+  for (int d = 0; d < DIMLIMIT; ++d) {
+    int src_dim = permute_order[div_4(d)][mod_4(d)];
+    new_tidx.data[div_4(d)][mod_4(d)] = idx_at(tidx, src_dim);
+  }
+  tidx = new_tidx;
+}
+
 //
 // Index Conversions
 //

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

@@ -18,55 +18,31 @@ ${define_required_extensions(DTYPE)}
 
 layout(std430) buffer;
 
-#include "indexing_utils.h"
+#include "indexing.glslh"
 
-${layout_declare_tensor(B, "w", "t_out", DTYPE, "buffer")}
-${layout_declare_tensor(B, "r", "t_in", DTYPE, "buffer")}
+${layout_declare_tensor(B, "w", "t_outp", DTYPE, "buffer")}
+${layout_declare_tensor(B, "r", "t_inp", DTYPE, "buffer")}
 
-${layout_declare_ubo(B, "ivec4", "in_sizes")}
-${layout_declare_ubo(B, "ivec4", "out_strides")}
-${layout_declare_ubo(B, "int", "out_numel")}
+${layout_declare_ubo(B, "BufferMetadata", "outp")}
+${layout_declare_ubo(B, "BufferMetadata", "inp")}
 
-layout(push_constant) uniform restrict Block {
-  ivec4 in_strides;
-  ivec4 permute_dims; // Permutation mapping: permute_dims[i] = j means output dim i comes from input dim j
-};
-
-${layout_declare_spec_const(C, "int", "out_layout", "DEFAULT_LAYOUT")}
-${layout_declare_spec_const(C, "int", "in_layout", "DEFAULT_LAYOUT")}
-
-const lowp ivec4 out_dim_order = unhash_dim_order(out_layout);
+${layout_declare_ubo(B, "ivec4[DIMLIMIT_DIV4]", "permute_order")}
 
 layout(local_size_x_id = 0, local_size_y_id = 1, local_size_z_id = 2) in;
 
-// Convert output tensor index to input tensor index based on permutation
-ivec4 out_tidx_to_in_tidx(const ivec4 out_tidx) {
-  ivec4 in_tidx;
-
-  // Apply the permutation mapping: in_tidx[permute_dims[i]] = out_tidx[i]
-  in_tidx[permute_dims.x] = out_tidx.x;
-  in_tidx[permute_dims.y] = out_tidx.y;
-  in_tidx[permute_dims.z] = out_tidx.z;
-  in_tidx[permute_dims.w] = out_tidx.w;
-
-  return in_tidx;
-}
-
 void main() {
-  const int out_bufi = ivec3(gl_GlobalInvocationID).x;
-  if (out_bufi >= out_numel) {
+  const uint inp_bufi = gl_GlobalInvocationID.x;
+  if (inp_bufi >= numel(inp)) {
     return;
   }
 
-  // Convert buffer index to tensor index for output
-  const ivec4 out_tidx = bufi_to_tidx(out_bufi, out_strides, out_dim_order);
-
-  // Convert output tensor index to input tensor index using permutation
-  const ivec4 in_tidx = out_tidx_to_in_tidx(out_tidx);
+  TensorIndex inp_tidx;
+  linear_idx_to_tensor_idx(inp, inp_bufi, inp_tidx);
 
-  // Convert input tensor index back to buffer index
-  const int in_bufi = tidx_to_bufi(in_tidx, in_strides);
+  TensorIndex outp_tidx = inp_tidx;
+  permute(outp_tidx, permute_order);
 
+  const uint outp_bufi = tensor_idx_to_linear_idx(outp, outp_tidx);
   // Copy data from input to output
-  t_out[out_bufi] = t_in[in_bufi];
+  t_outp[outp_bufi] = t_inp[inp_bufi];
 }

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

@@ -129,37 +129,22 @@ void add_permute_node(
   std::vector<PushConstantDataInfo> push_constants;
   vkapi::SpecVarList spec_vars;
 
-  if (graph.is_buffer_storage(out)) {
-    param_buffers.append(graph.sizes_ubo(in));
-    param_buffers.append(graph.strides_ubo(out));
-    param_buffers.append(graph.numel_ubo(out));
-
-    // Buffer storage - use permute_buffer shader
-    push_constants = {
-        graph.strides_pc_of(in),
-        PushConstantDataInfo(&whcn_permute_dims, sizeof(whcn_permute_dims)),
-    };
-
-    spec_vars = {graph.hashed_layout_of(out), graph.hashed_layout_of(in)};
-  } else {
-    // Texture storage - use permute_texture shader
-    const int32_t out_channels = dim_at<kChannel4D>(graph.sizes_of(out));
-    const int32_t in_channels = dim_at<kChannel4D>(graph.sizes_of(in));
-
-    const int32_t packed_dim = graph.packed_dim_of(in);
-    ivec2 channel_info = {out_channels, in_channels};
-    if (packed_dim == WHCN::kChannelsDim) {
-      channel_info[0] = utils::align_up_4(channel_info[0]);
-      channel_info[1] = utils::align_up_4(channel_info[1]);
-    }
+  const int32_t out_channels = dim_at<kChannel4D>(graph.sizes_of(out));
+  const int32_t in_channels = dim_at<kChannel4D>(graph.sizes_of(in));
+
+  const int32_t packed_dim = graph.packed_dim_of(in);
+  ivec2 channel_info = {out_channels, in_channels};
+  if (packed_dim == WHCN::kChannelsDim) {
+    channel_info[0] = utils::align_up_4(channel_info[0]);
+    channel_info[1] = utils::align_up_4(channel_info[1]);
+  }
 
-    push_constants = {
-        graph.sizes_pc_of(out),
-        graph.sizes_pc_of(in),
-        PushConstantDataInfo(&whcn_permute_dims, sizeof(whcn_permute_dims))};
+  push_constants = {
+      graph.sizes_pc_of(out),
+      graph.sizes_pc_of(in),
+      PushConstantDataInfo(&whcn_permute_dims, sizeof(whcn_permute_dims))};
 
-    spec_vars = {graph.hashed_layout_of(out), graph.hashed_layout_of(in)};
-  }
+  spec_vars = {graph.hashed_layout_of(out), graph.hashed_layout_of(in)};
 
   graph.execute_nodes().emplace_back(new DynamicDispatchNode(
       graph,
@@ -179,8 +164,83 @@ void add_permute_node(
       resize_permute_node));
 }
 
+struct WHCNPermuteDims {
+  int32_t whcn_permute_dims[api::kTensorDimLimit];
+
+  void initialize(const std::vector<int64_t>& permute_dims) {
+    const int32_t permute_ndim = permute_dims.size();
+    for (int32_t whcn_i = 0; whcn_i < permute_ndim; whcn_i++) {
+      const int32_t nchw_i = permute_ndim - 1 - whcn_i;
+      int64_t index_val = permute_dims.at(nchw_i);
+      if (index_val < 0) {
+        index_val += permute_ndim;
+      }
+      const int32_t permute_dim_whcn = permute_ndim - 1 - index_val;
+      whcn_permute_dims[whcn_i] = permute_dim_whcn;
+    }
+    for (int32_t whcn_i = permute_ndim; whcn_i < api::kTensorDimLimit;
+         whcn_i++) {
+      whcn_permute_dims[whcn_i] = whcn_i;
+    }
+  }
+};
+
+void add_permute_buffer_node(
+    ComputeGraph& graph,
+    const ValueRef in,
+    const ValueRef permute_dims,
+    const ValueRef out) {
+  check_args(graph, in, permute_dims, out);
+
+  WHCNPermuteDims whcn_permute_dims;
+  // Convert the permute dims to WHCN dimension order, which is the standard in
+  // our compute shaders. The following transformations are applied.
+  // 1. Change dimension index values from NCHW order valueto WHCN order value
+  // 2. Extend the permute array to kTensorDimLimit
+  {
+    IntListPtr permute_dims_ptr = graph.get_int_list(permute_dims);
+    whcn_permute_dims.initialize(*permute_dims_ptr);
+  }
+
+  std::string kernel_name = "permute";
+  kernel_name.reserve(kShaderNameReserve);
+  add_storage_type_suffix(kernel_name, graph.storage_type_of(out));
+  add_dtype_suffix(kernel_name, graph.dtype_of(out));
+
+  vkapi::ParamsBindList param_buffers = {
+      graph.buffer_meta_ubo(out),
+      graph.buffer_meta_ubo(in),
+      graph.create_params_buffer(whcn_permute_dims),
+  };
+
+  graph.execute_nodes().emplace_back(new DynamicDispatchNode(
+      graph,
+      VK_KERNEL_FROM_STR(kernel_name),
+      default_pick_global_wg_size,
+      default_pick_local_wg_size,
+      {{out, vkapi::kWrite}, {in, vkapi::kRead}},
+      // Parameter buffers
+      param_buffers,
+      // Push Constants
+      {},
+      // Specialization Constants
+      {},
+      // Resize Args
+      {permute_dims},
+      // Resizing Logic
+      resize_permute_node));
+}
+
 void permute(ComputeGraph& graph, const std::vector<ValueRef>& args) {
-  return add_permute_node(graph, args[0], args[1], args[2]);
+  int idx = 0;
+  const ValueRef in = args.at(idx++);
+  const ValueRef permute_dims = args.at(idx++);
+  const ValueRef out = args.at(idx++);
+
+  if (graph.is_buffer_storage(args[2])) {
+    return add_permute_buffer_node(graph, in, permute_dims, out);
+  }
+  return add_permute_node(graph, in, permute_dims, out);
 }
 
 REGISTER_OPERATORS {