rename ExecutorTorch with ExecuTorch

backends/aoti/README.md

@@ -1,6 +1,6 @@
 # AOTI Common Library
 
-This directory contains **common library components** for AOTI (Ahead-of-Time Inference) driven backends in ExecutorTorch, **not a standalone backend**.
+This directory contains **common library components** for AOTI (Ahead-of-Time Inference) driven backends in ExecuTorch, **not a standalone backend**.
 
 ## Purpose
 

backends/apple/metal/CMakeLists.txt

@@ -49,7 +49,7 @@ add_library(metal_backend STATIC ${_aoti_metal_sources})
 target_include_directories(
   metal_backend
   PUBLIC $<BUILD_INTERFACE:${EXECUTORCH_ROOT}> $<INSTALL_INTERFACE:include>
-         # PyTorch AOTI headers from ExecutorTorch's torch detection
+         # PyTorch AOTI headers from ExecuTorch's torch detection
          ${TORCH_INCLUDE_DIRS}
 )
 

backends/apple/metal/runtime/metal_backend.cpp

@@ -418,7 +418,7 @@ class ET_EXPERIMENTAL MetalBackend final
 
     int32_t mps_device_type = aoti_torch_device_type_mps(); // Returns 13
 
-    // NOTE: ExecutorTorch tensors are always on CPU/host memory
+    // NOTE: ExecuTorch tensors are always on CPU/host memory
     // We need to create GPU copies for Metal kernel execution
     std::vector<AOTITensorHandle> gpu_inputs(
         n_inputs); // GPU copies for kernel execution
@@ -427,14 +427,14 @@ class ET_EXPERIMENTAL MetalBackend final
 
     ET_LOG(Debug, "MetalBackend input/output vectors generated");
 
-    // Process input tensors: ExecutorTorch provides CPU tensors, create GPU
+    // Process input tensors: ExecuTorch provides CPU tensors, create GPU
     // copies
     for (int i = 0; i < n_inputs; i++) {
       ET_LOG(Debug, "Processing input %d from args to inputs vector", i);
       ET_LOG(
           Debug, "is %d input a tensor input? %d", i, int(args[i]->isTensor()));
 
-      // Get tensor dimensions and properties from ExecutorTorch CPU tensor
+      // Get tensor dimensions and properties from ExecuTorch CPU tensor
       auto cpu_tensor = &(args[i]->toTensor());
       auto sizes = cpu_tensor->sizes();
       auto scalar_type = cpu_tensor->scalar_type();
@@ -509,10 +509,10 @@ class ET_EXPERIMENTAL MetalBackend final
 
     ET_LOG(Debug, "MetalBackend GPU inputs generated");
 
-    // Process output tensors: create GPU counterparts for ExecutorTorch CPU
+    // Process output tensors: create GPU counterparts for ExecuTorch CPU
     // tensors
     for (int i = 0; i < n_outputs; i++) {
-      // Get output tensor dimensions from ExecutorTorch CPU tensor
+      // Get output tensor dimensions from ExecuTorch CPU tensor
       auto cpu_output_tensor = &(args[i + n_inputs]->toTensor());
       auto sizes = cpu_output_tensor->sizes();
       auto scalar_type = cpu_output_tensor->scalar_type();
@@ -618,7 +618,7 @@ class ET_EXPERIMENTAL MetalBackend final
       ET_LOG(Debug, "Copied GPU output %d back to CPU", i);
     }
 
-    // Clean up GPU tensors that we created (ExecutorTorch tensors are always
+    // Clean up GPU tensors that we created (ExecuTorch tensors are always
     // CPU, so all GPU tensors are our copies)
     for (int i = 0; i < n_inputs; i++) {
       // All GPU input tensors were created by us, delete them

backends/apple/metal/runtime/shims/et_metal_ops.h

@@ -19,7 +19,7 @@ extern "C" {
 #endif
 
 /**
- * ExecutorTorch implementation of aoti_torch_mps_mm_out.
+ * ExecuTorch implementation of aoti_torch_mps_mm_out.
  * Performs simple matrix multiplication: out = self @ mat2
  */
 AOTITorchError aoti_torch_mps_mm_out(
@@ -28,7 +28,7 @@ AOTITorchError aoti_torch_mps_mm_out(
     AOTITensorHandle mat2);
 
 /**
- * ExecutorTorch implementation of aoti_torch_mps_bmm_out.
+ * ExecuTorch implementation of aoti_torch_mps_bmm_out.
  * Performs batched matrix multiplication: out = self @ mat2
  * All tensors must be 3-D with matching batch dimensions.
  */
@@ -38,7 +38,7 @@ AOTITorchError aoti_torch_mps_bmm_out(
     AOTITensorHandle mat2);
 
 /**
- * ExecutorTorch implementation of aoti_torch_mps_convolution.
+ * ExecuTorch implementation of aoti_torch_mps_convolution.
  * Performs 2D convolution operation - matches PyTorch AOTI signature
  */
 AOTITorchError aoti_torch_mps_convolution(
@@ -58,7 +58,7 @@ AOTITorchError aoti_torch_mps_convolution(
     AOTITensorHandle* ret0);
 
 /**
- * ExecutorTorch implementation of
+ * ExecuTorch implementation of
  * aoti_torch_mps__scaled_dot_product_attention_math_for_mps. Performs scaled
  * dot product attention calculation - matches PyTorch AOTI signature
  */

backends/apple/metal/runtime/shims/et_metal_ops.mm

@@ -366,7 +366,7 @@ AOTITorchError aoti_torch_mps_mm_out(
 
   @autoreleasepool {
     try {
-      // Convert AOTITensorHandle to ExecutorTorch tensors
+      // Convert AOTITensorHandle to ExecuTorch tensors
       auto out_tensor = reinterpret_cast<Tensor*>(out);
       auto self_tensor = reinterpret_cast<Tensor*>(self);
       auto mat2_tensor = reinterpret_cast<Tensor*>(mat2);
@@ -639,7 +639,7 @@ AOTITorchError aoti_torch_mps_bmm_out(
 
   @autoreleasepool {
     try {
-      // Convert AOTITensorHandle to ExecutorTorch tensors
+      // Convert AOTITensorHandle to ExecuTorch tensors
       auto out_tensor = reinterpret_cast<Tensor*>(out);
       auto self_tensor = reinterpret_cast<Tensor*>(self);
       auto mat2_tensor = reinterpret_cast<Tensor*>(mat2);
@@ -942,7 +942,7 @@ AOTITorchError aoti_torch_mps_convolution(
 
   @autoreleasepool {
     try {
-      // Convert AOTITensorHandle to ExecutorTorch tensors
+      // Convert AOTITensorHandle to ExecuTorch tensors
       auto input_tensor = reinterpret_cast<Tensor*>(input);
       auto weight_tensor = reinterpret_cast<Tensor*>(weight);
 
@@ -1479,7 +1479,7 @@ AOTITorchError aoti_torch_mps__scaled_dot_product_attention_math_for_mps(
 
   try {
     @autoreleasepool {
-      // Convert AOTITensorHandle to ExecutorTorch tensors
+      // Convert AOTITensorHandle to ExecuTorch tensors
       auto* query_tensor = reinterpret_cast<Tensor*>(query);
       auto* key_tensor = reinterpret_cast<Tensor*>(key);
       auto* value_tensor = reinterpret_cast<Tensor*>(value);

backends/apple/metal/runtime/shims/types.h

@@ -16,14 +16,14 @@ namespace executorch {
 namespace backends {
 namespace metal {
 
-// Common using declarations for ExecutorTorch types
+// Common using declarations for ExecuTorch types
 using executorch::runtime::Error;
 using executorch::runtime::etensor::Tensor;
 
 extern "C" {
 
 // Common AOTI type aliases
-// Note: AOTITensorHandle is aliased to Tensor* for ExecutorTorch compatibility
+// Note: AOTITensorHandle is aliased to Tensor* for ExecuTorch compatibility
 using AOTITensorHandle = Tensor*;
 using AOTIRuntimeError = Error;
 using AOTITorchError = Error;

backends/cadence/generic/operators/cadence_type_util.h

@@ -25,7 +25,7 @@
  *
  * Where MACRO is defined as: #define MACRO(ctype, name) ...
  * - ctype: C++ type (uint8_t or int8_t)
- * - name: ExecutorTorch ScalarType name suffix (Byte or Char)
+ * - name: ExecuTorch ScalarType name suffix (Byte or Char)
  *
  * Example:
  *   #define HANDLE_TYPE(ctype, name) \
@@ -52,7 +52,7 @@
  *
  * Where MACRO is defined as: #define MACRO(ctype, name) ...
  * - ctype: C++ type (uint8_t, int8_t, or int16_t)
- * - name: ExecutorTorch ScalarType name suffix (Byte, Char, or Short)
+ * - name: ExecuTorch ScalarType name suffix (Byte, Char, or Short)
  *
  * This macro includes int16_t support for operators that can handle 16-bit
  * quantized values (e.g., quantized_linear, quantized_fully_connected).

backends/cuda/CMakeLists.txt

@@ -33,7 +33,7 @@ set(CUDA_USE_STATIC_CUDA_RUNTIME OFF)
 
 find_package(CUDAToolkit REQUIRED)
 
-# Use ExecutorTorch's standard way to find PyTorch libraries for AOTI
+# Use ExecuTorch's standard way to find PyTorch libraries for AOTI
 include(${EXECUTORCH_ROOT}/tools/cmake/Utils.cmake)
 find_package_torch()
 

backends/cuda/runtime/shims/tensor_attribute.h

@@ -15,7 +15,7 @@
 
 namespace executorch::backends::cuda {
 
-// Common using declarations for ExecutorTorch types
+// Common using declarations for ExecuTorch types
 using executorch::runtime::Error;
 using executorch::runtime::etensor::Tensor;
 

examples/arm/zephyr/CMakeLists.txt

@@ -117,7 +117,7 @@ if(NOT DEFINED EXECUTORCH_DIR)
   else()
     message(
       FATAL_ERROR
-        "ExecutorTorch module not found. Ensure it's properly configured in your Zephyr workspace."
+        "ExecuTorch module not found. Ensure it's properly configured in your Zephyr workspace."
     )
   endif()
 else()

examples/openvino/stable_diffusion/export_lcm.py

@@ -62,7 +62,7 @@ def export_text_encoder(self, output_path: str, device: str = "CPU") -> bool:
                 exported_program, partitioner=[partitioner]
             )
 
-            # Convert to ExecutorTorch program
+            # Convert to ExecuTorch program
             executorch_program = edge_manager.to_executorch(
                 config=ExecutorchBackendConfig()
             )
@@ -102,7 +102,7 @@ def export_unet(self, output_path: str, device: str = "CPU") -> bool:
                 exported_program, partitioner=[partitioner]
             )
 
-            # Convert to ExecutorTorch program
+            # Convert to ExecuTorch program
             executorch_program = edge_manager.to_executorch(
                 config=ExecutorchBackendConfig()
             )
@@ -142,7 +142,7 @@ def export_vae_decoder(self, output_path: str, device: str = "CPU") -> bool:
                 exported_program, partitioner=[partitioner]
             )
 
-            # Convert to ExecutorTorch program
+            # Convert to ExecuTorch program
             executorch_program = edge_manager.to_executorch(
                 config=ExecutorchBackendConfig()
             )