fixed review item

Author: shewu-quic

backends/qualcomm/builders/op_custom_op.py

@@ -3,6 +3,7 @@
 #
 # This source code is licensed under the BSD-style license found in the
 # LICENSE file in the root directory of this source tree.
+import warnings
 from typing import Dict, Iterable
 
 import executorch.backends.qualcomm.python.PyQnnWrapperAdaptor as PyQnnWrapper
@@ -41,6 +42,12 @@ def define_node(
 
         custom_input_tensors = []
         custom_attr_keys = [arg.name for arg in node.target._schema.arguments]
+        if len(custom_attr_keys) != len(node.args):
+            warnings.warn(
+                f"Number of inputs ({len(node.args)}) mismatch the number of args ({len(custom_attr_keys)}) in schema for the custom node ({self.target}).",
+                stacklevel=1,
+            )
+            return
         for arg, arg_name in zip(node.args, custom_attr_keys):
             if arg is None:
                 continue

backends/qualcomm/runtime/backends/QnnBackendCommon.cpp

@@ -43,6 +43,9 @@ void QnnBackend::BackendRegisterOpPackage(
 #elif defined(__ANDROID__)
   current_platform = QnnExecuTorchOpPackagePlatform::AARCH64_ANDROID;
 #endif
+  if (current_platform == QnnExecuTorchOpPackagePlatform::UNKNOWN)
+    QNN_EXECUTORCH_LOG_ERROR(
+        "Failed to detect the platform. Only support x86_64 or android.");
   for (const auto op_package_info : *op_packages_infos) {
     if (current_platform != op_package_info->platform() ||
         op_package_manager_.Has(op_package_info->op_package_path()->c_str()))

examples/qualcomm/custom_op/README.md

@@ -94,71 +94,4 @@ For now, only support one output tensors.
 Consult the Qualcomm AI Engine Direct documentation for information on [generation op packages](https://docs.qualcomm.com/bundle/publicresource/topics/80-63442-50/op_def_schema.html).
 
 ## Registering Op Packages
-After an op package library has been generated, certain information needs to be passed to the `compile_spec` in order to properly delegate the nodes. The following code example shows how to construct the `QnnExecuTorchOpPackageOptions` and register op packages with the `compile spec`.
-```python
-def prepare_op_package(
-    workspace: str, op_package_dir: str, arch: HtpArch, build_op_package: bool
-):
-    if build_op_package:
-        _run(["rm", "-rf", "build"], cwd=op_package_dir)
-        _run(["make", "htp_x86", "htp_aarch64", f"htp_v{arch}"], cwd=op_package_dir)
-        _run(
-            [
-                "cp",
-                f"{op_package_dir}/build/hexagon-v{arch}/libQnnExampleOpPackage.so",
-                f"{op_package_dir}/build/hexagon-v{arch}/libQnnExampleOpPackage_HTP.so",
-            ]
-        )
-
-    op_package_paths = [
-        f"{op_package_dir}/build/hexagon-v{arch}/libQnnExampleOpPackage_HTP.so",
-        f"{op_package_dir}/build/aarch64-android/libQnnExampleOpPackage.so",
-    ]
-
-    op_package_infos_HTP = QnnExecuTorchOpPackageInfo()
-    op_package_infos_HTP.interface_provider = "ExampleOpPackageInterfaceProvider"
-    op_package_infos_HTP.op_package_name = "ExampleOpPackage"
-    op_package_infos_HTP.op_package_path = f"{workspace}/libQnnExampleOpPackage_HTP.so"
-    op_package_infos_HTP.target = QnnExecuTorchOpPackageTarget.HTP
-    op_package_infos_HTP.custom_op_name = "my_ops.mul3.default"
-    op_package_infos_HTP.qnn_op_type_name = "ExampleCustomOp"
-    op_package_infos_HTP.platform = QnnExecuTorchOpPackagePlatform.AARCH64_ANDROID
-    op_package_infos_aarch64_CPU = QnnExecuTorchOpPackageInfo()
-    op_package_infos_aarch64_CPU.interface_provider = (
-        "ExampleOpPackageInterfaceProvider"
-    )
-    op_package_infos_aarch64_CPU.op_package_name = "ExampleOpPackage"
-    op_package_infos_aarch64_CPU.op_package_path = (
-        f"{workspace}/libQnnExampleOpPackage.so"
-    )
-    op_package_infos_aarch64_CPU.target = QnnExecuTorchOpPackageTarget.CPU
-    op_package_infos_aarch64_CPU.custom_op_name = "my_ops.mul3.default"
-    op_package_infos_aarch64_CPU.qnn_op_type_name = "ExampleCustomOp"
-    op_package_infos_aarch64_CPU.platform = (
-        QnnExecuTorchOpPackagePlatform.AARCH64_ANDROID
-    )
-    op_package_infos_x86_CPU = QnnExecuTorchOpPackageInfo()
-    op_package_infos_x86_CPU.interface_provider = "ExampleOpPackageInterfaceProvider"
-    op_package_infos_x86_CPU.op_package_name = "ExampleOpPackage"
-    op_package_infos_x86_CPU.op_package_path = (
-        f"{op_package_dir}/build/x86_64-linux-clang/libQnnExampleOpPackage.so"
-    )
-    op_package_infos_x86_CPU.target = QnnExecuTorchOpPackageTarget.CPU
-    op_package_infos_x86_CPU.custom_op_name = "my_ops.mul3.default"
-    op_package_infos_x86_CPU.qnn_op_type_name = "ExampleCustomOp"
-    op_package_infos_x86_CPU.platform = QnnExecuTorchOpPackagePlatform.X86_64
-    op_package_options = QnnExecuTorchOpPackageOptions()
-    op_package_options.op_package_infos = [
-        op_package_infos_x86_CPU,
-        op_package_infos_aarch64_CPU,
-        op_package_infos_HTP,
-    ]
-
-    return op_package_options, op_package_paths
-...
-op_package_options, op_package_paths = prepare_op_package(...)
-compile_spec = generate_qnn_executorch_compiler_spec(
-    ...
-    op_package_options=op_package_options,
-),
-```
+After an op package library has been generated, certain information needs to be passed to the `compile_spec` in order to properly delegate the nodes. [The example script](custom_ops_1.py) shows how to construct the `QnnExecuTorchOpPackageOptions` and register op packages with the `compile spec`.