pytorch · meta-codesync · Mar 4, 2026 · Mar 4, 2026
@@ -104,6 +104,19 @@ runtime.python_library(
     ],
 )
 
+runtime.python_library(
+    name = "insert_dtype_promotion",
+    srcs = ["insert_dtype_promotion.py"],
+    visibility = [
+        "//executorch/backends/...",
+    ],
+    deps = [
+        "//caffe2:torch",
+        "//executorch/exir:pass_base",
+        "//executorch/exir/dialects:lib",
+    ],
+)
+
 runtime.python_library(
     name = "fuse_patterns",
     srcs = ["fuse_patterns.py"],
@@ -133,6 +146,7 @@ runtime.python_library(
         ":fold_qdq",
         ":fuse_patterns",
         ":fuse_quantized_ops",
+        ":insert_dtype_promotion",
         ":insert_prepack_nodes",
         ":remove_asserts",
         ":remove_redundant_ops",

@@ -11,6 +11,9 @@
 from executorch.backends.vulkan._passes.fuse_quantized_ops import (
     FuseQuantizedOpsTransform,
 )
+from executorch.backends.vulkan._passes.insert_dtype_promotion import (
+    InsertDtypePromotionPass,
+)
 from executorch.backends.vulkan._passes.insert_prepack_nodes import insert_prepack_nodes
 from executorch.backends.vulkan._passes.remove_asserts import (
     remove_asserts,
@@ -28,6 +31,7 @@
     "FoldQDQPass",
     "FusePatternsPass",
     "FuseQuantizedOpsTransform",
+    "InsertDtypePromotionPass",
     "insert_prepack_nodes",
     "remove_asserts",
     "RemoveAssertsTransform",

@@ -0,0 +1,102 @@
+# 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.
+
+# pyre-strict
+
+from typing import Set, Union
+
+import torch
+from executorch.exir.dialects._ops import ops as exir_ops
+from executorch.exir.dialects.edge._ops import EdgeOpOverload
+from executorch.exir.pass_base import ExportPass, PassResult
+from executorch.exir.passes import dead_code_elimination_pass
+
+OpType = Union[str, torch._ops.OpOverload, EdgeOpOverload]
+
+# Binary ops whose first two args are tensor inputs that may need promotion
+BINARY_OPS: Set[OpType] = {
+    exir_ops.edge.aten.add.Tensor,
+    exir_ops.edge.aten.sub.Tensor,
+    exir_ops.edge.aten.mul.Tensor,
+    exir_ops.edge.aten.div.Tensor,
+    exir_ops.edge.aten.div.Tensor_mode,
+    exir_ops.edge.aten.pow.Tensor_Tensor,
+    exir_ops.edge.aten.minimum.default,
+    exir_ops.edge.aten.eq.Tensor,
+    exir_ops.edge.aten.lt.Tensor,
+    exir_ops.edge.aten.le.Tensor,
+    exir_ops.edge.aten.gt.Tensor,
+    exir_ops.edge.aten.ge.Tensor,
+}
+
+
+def _promote_dtype(a: torch.dtype, b: torch.dtype) -> torch.dtype:
+    """Promote to common dtype following PyTorch type promotion rules."""
+    if a == b:
+        return a
+    # Any mix of different dtypes promotes to float32
+    return torch.float32
+
+
+class InsertDtypePromotionPass(ExportPass):
+    """
+    Insert _to_copy nodes before binary ops when the two tensor inputs have
+    different dtypes, promoting both to a common dtype.
+    """
+
+    def call(self, graph_module: torch.fx.GraphModule) -> PassResult:
+        dirty = False
+        for node in graph_module.graph.nodes:
+            if node.op != "call_function" or node.target not in BINARY_OPS:
+                continue
+
+            lhs = node.args[0]
+            rhs = node.args[1]
+
+            if not isinstance(lhs, torch.fx.Node) or not isinstance(rhs, torch.fx.Node):
+                continue
+
+            if "val" not in lhs.meta or "val" not in rhs.meta:
+                continue
+
+            lhs_dtype = lhs.meta["val"].dtype
+            rhs_dtype = rhs.meta["val"].dtype
+
+            if lhs_dtype == rhs_dtype:
+                continue
+
+            promoted = _promote_dtype(lhs_dtype, rhs_dtype)
+
+            if lhs_dtype != promoted:
+                with graph_module.graph.inserting_before(node):
+                    cast_lhs = graph_module.graph.create_node(
+                        "call_function",
+                        exir_ops.edge.aten._to_copy.default,
+                        (lhs,),
+                        {"dtype": promoted},
+                    )
+                    cast_lhs.meta["val"] = lhs.meta["val"].to(promoted)
+                node.replace_input_with(lhs, cast_lhs)
+                dirty = True
+
+            if rhs_dtype != promoted:
+                with graph_module.graph.inserting_before(node):
+                    cast_rhs = graph_module.graph.create_node(
+                        "call_function",
+                        exir_ops.edge.aten._to_copy.default,
+                        (rhs,),
+                        {"dtype": promoted},
+                    )
+                    cast_rhs.meta["val"] = rhs.meta["val"].to(promoted)
+                node.replace_input_with(rhs, cast_rhs)
+                dirty = True
+
+        if dirty:
+            graph_module.graph.eliminate_dead_code()
+            graph_module.recompile()
+            dead_code_elimination_pass(graph_module)
+
+        return PassResult(graph_module, dirty)
@@ -307,8 +307,8 @@ def check_to_copy_node(node: torch.fx.Node) -> bool:
 
     return OpFeatures(
         inputs_storage=utils.ANY_STORAGE,
-        inputs_dtypes=utils.FP_T,
-        outputs_dtypes=utils.FP_T,
+        inputs_dtypes=utils.FP_INT_T,
+        outputs_dtypes=utils.FP_INT_T,
         supports_resize=True,
         are_node_inputs_supported_fn=check_to_copy_node,
     )

@@ -46,7 +46,7 @@ binary_op:
           - VALUE: half
           - VALUE: float
     - NAME: binary_eq_texture3d
-      OPERATOR: all(lessThanEqual(abs(X - Y), VEC4_T(1e-5)))
+      OPERATOR: lessThanEqual(abs(X - Y), VEC4_T(1e-5))
       STORAGE: texture3d
       generate_variant_forall:
         DTYPE:
@@ -61,7 +61,7 @@ binary_op:
           - VALUE: float
           - VALUE: int32
     - NAME: binary_lt_texture3d
-      OPERATOR: all(lessThan(X, Y))
+      OPERATOR: lessThan(X, Y)
       STORAGE: texture3d
       generate_variant_forall:
         DTYPE:
@@ -77,7 +77,7 @@ binary_op:
           - VALUE: float
           - VALUE: int32
     - NAME: binary_le_texture3d
-      OPERATOR: all(lessThanEqual(X, Y))
+      OPERATOR: lessThanEqual(X, Y)
       STORAGE: texture3d
       generate_variant_forall:
         DTYPE:
@@ -93,7 +93,7 @@ binary_op:
           - VALUE: float
           - VALUE: int32
     - NAME: binary_gt_texture3d
-      OPERATOR: all(greaterThan(X, Y))
+      OPERATOR: greaterThan(X, Y)
       STORAGE: texture3d
       generate_variant_forall:
         DTYPE:
@@ -109,7 +109,7 @@ binary_op:
           - VALUE: float
           - VALUE: int32
     - NAME: binary_ge_texture3d
-      OPERATOR: all(greaterThanEqual(X, Y))
+      OPERATOR: greaterThanEqual(X, Y)
       STORAGE: texture3d
       generate_variant_forall:
         DTYPE:

@@ -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 IN_VEC4_T ${texel_type(IN_DTYPE)}
+#define OUT_VEC4_T ${texel_type(OUT_DTYPE)}
+
+${define_required_extensions("texture3d", IN_DTYPE)}
+${define_required_extensions("texture3d", OUT_DTYPE)}
+
+#include "indexing_utils.h"
+
+layout(std430) buffer;
+
+${layout_declare_tensor(B, "w", "t_out", OUT_DTYPE, "texture3d")}
+${layout_declare_tensor(B, "r", "t_in", IN_DTYPE, "texture3d")}
+
+layout(push_constant) uniform restrict Block {
+  ivec4 out_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 pos = ivec3(gl_GlobalInvocationID);
+  const ivec4 idx = to_tensor_idx(pos, out_sizes, packed_dim);
+
+  if (any(greaterThanEqual(idx, out_sizes))) {
+    return;
+  }
+
+  IN_VEC4_T in_texel = IN_VEC4_T(texelFetch(t_in, pos, 0));
+  imageStore(t_out, pos, OUT_VEC4_T(in_texel));
+}
@@ -0,0 +1,19 @@
+# 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.
+
+view_convert_texture:
+  parameter_names_with_default_values:
+    IN_DTYPE: float
+    OUT_DTYPE: float
+    STORAGE: texture3d
+  generate_variant_forall:
+    combination:
+      parameter_names: [IN_DTYPE, OUT_DTYPE]
+      combos:
+        - parameter_values: [int32, float]
+        - parameter_values: [float, int32]
+  shader_variants:
+    - NAME: view_convert_texture
@@ -9,8 +9,8 @@
 #include <executorch/backends/vulkan/runtime/graph/ops/BlitNode.h>
 #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/View.h>
 #include <executorch/backends/vulkan/runtime/graph/ops/utils/ShaderNameUtils.h>
-#include <set>
 
 namespace vkcompute {
 
@@ -25,19 +25,29 @@ void resize_to_copy_op_node(
   graph->virtual_resize(out, graph->sizes_of(self));
 }
 
+bool is_float_type(vkapi::ScalarType dtype) {
+  return dtype == vkapi::ScalarType::Float || dtype == vkapi::ScalarType::Half;
+}
+
 void add_to_copy_node(ComputeGraph& graph, ValueRef in, ValueRef out) {
-  static std::set<vkapi::ScalarType> supported_types = {
-      vkapi::ScalarType::Float, vkapi::ScalarType::Half};
-
-  VK_CHECK_COND(
-      supported_types.find(graph.dtype_of(in)) != supported_types.end() &&
-          supported_types.find(graph.dtype_of(out)) != supported_types.end(),
-      "Unsupported dtype for to_copy, only Float and Half are currently supported, recieved ",
-      vkapi::to_string(graph.dtype_of(in)),
-      " <-> ",
-      vkapi::to_string(graph.dtype_of(out)));
-
-  graph.execute_nodes().emplace_back(new BlitNode(graph, in, out));
+  vkapi::ScalarType in_dtype = graph.dtype_of(in);
+  vkapi::ScalarType out_dtype = graph.dtype_of(out);
+
+  // Same-dtype or float<->half conversions can use BlitNode
+  if (in_dtype == out_dtype ||
+      (is_float_type(in_dtype) && is_float_type(out_dtype))) {
+    graph.execute_nodes().emplace_back(new BlitNode(graph, in, out));
+    return;
+  }
+
+  // Other conversions (e.g. int<->float) use view_convert shaders
+  if (graph.is_buffer_storage(in)) {
+    add_view_copy_convert_buffer_node(
+        graph, in, out, {}, resize_to_copy_op_node);
+  } else {
+    add_view_copy_convert_texture_node(
+        graph, in, out, {}, resize_to_copy_op_node);
+  }
 }
 
 void to_copy(ComputeGraph& graph, const std::vector<ValueRef>& args) {

@@ -127,6 +127,35 @@ void add_view_copy_buffer_node(
       resize_fn));
 }
 
+void add_view_copy_convert_texture_node(
+    ComputeGraph& graph,
+    ValueRef in,
+    ValueRef out,
+    const std::vector<ValueRef>& resize_args,
+    const ExecuteNode::ResizeFunction& resize_fn) {
+  std::string kernel_name = "view_convert_texture";
+  add_dtype_suffix(kernel_name, graph.dtype_of(in));
+  add_dtype_suffix(kernel_name, graph.dtype_of(out));
+
+  graph.execute_nodes().emplace_back(new DynamicDispatchNode(
+      graph,
+      VK_KERNEL_FROM_STR(kernel_name),
+      default_pick_global_wg_size,
+      default_pick_local_wg_size,
+      // Inputs and Outputs
+      {{out, vkapi::kWrite}, {in, vkapi::kRead}},
+      // Parameter Buffers
+      {},
+      // Push Constants
+      {{graph.sizes_pc_of(out)}},
+      // Specialization Constants
+      {graph.packed_dim_of(out)},
+      // Resize Args
+      resize_args,
+      // Resizing Logic
+      resize_fn));
+}
+
 void add_view_copy_convert_buffer_node(
     ComputeGraph& graph,
     ValueRef in,

@@ -37,6 +37,18 @@ void add_view_copy_convert_buffer_node(
     const std::vector<ValueRef>& resize_args,
     const ExecuteNode::ResizeFunction& resize_fn);
 
+/*
+ * Dispatches the view_convert_texture compute shader. This can be used to
+ * convert between different data types for 3D texture tensors while
+ * preserving the texel positions.
+ */
+void add_view_copy_convert_texture_node(
+    ComputeGraph& graph,
+    ValueRef in,
+    ValueRef out,
+    const std::vector<ValueRef>& resize_args,
+    const ExecuteNode::ResizeFunction& resize_fn);
+
 void add_view_node(
     ComputeGraph& graph,
     ValueRef in,

@@ -21,6 +21,7 @@
     FoldQDQPass,
     FuseQuantizedOpsTransform,
     insert_prepack_nodes,
+    InsertDtypePromotionPass,
     RemoveRedundantOpsTransform,
     SqueezeUnsqueezeInputs,
     TagMemoryMetaPass,
@@ -165,6 +166,7 @@ def preprocess(  # noqa: C901
                 AddmmToLinearTransform(),
                 FuseBatchNormPass(program),
                 AddmmToLinearTransform(),
+                InsertDtypePromotionPass(),
                 FusePatternsPass(),
                 FuseClampPass(),
                 RemoveRedundantOpsTransform(),