Update on "[ET-VK][Ops] aten.tan.default from scratch implementation"

Following the instructions here for creating a new operator from scratch for learning purposes:
https://www.internalfb.com/wiki/ExecuTorch_Vulkan_Backend/Development_0/Adding_a_New_Operator_Implementation/

Goal is to create a tan operator and its test case

Differential Revision: [D75100188](https://our.internmc.facebook.com/intern/diff/D75100188/)

[ghstack-poisoned]

Author: morelos

.github/workflows/build-presets.yml

@@ -20,7 +20,7 @@ jobs:
     strategy:
       fail-fast: false
       matrix:
-        preset: [macos-arm64, pybind, llm]
+        preset: [macos, ios, ios-simulator, pybind, llm]
     with:
       job-name: build
       ref: ${{ github.event_name == 'pull_request' && github.event.pull_request.head.sha || github.sha }}
@@ -39,7 +39,7 @@ jobs:
     strategy:
       fail-fast: false
       matrix:
-        preset: [pybind, llm]
+        preset: [linux, pybind, llm]
         runner: [linux.2xlarge, linux.arm64.2xlarge]
         docker-image: [executorch-ubuntu-22.04-clang12, executorch-ubuntu-22.04-gcc11-aarch64]
         # Excluding specific runner + docker image combinations that don't make sense:

.lintrunner.toml

@@ -390,7 +390,6 @@ exclude_patterns = [
     "backends/arm/test/ops/**",
     "backends/vulkan/quantizer/**",
     "backends/vulkan/test/**",
-    "backends/cadence/aot/quantizer/**",
     "backends/qualcomm/quantizer/**",
     "examples/qualcomm/**",
     "backends/xnnpack/quantizer/**",

CMakePresets.json

@@ -7,13 +7,13 @@
       "binaryDir": "${sourceDir}/cmake-out"
     },
     {
-      "name": "macos-arm64",
-      "displayName": "Build everything buildable on macOS arm64",
+      "name": "macos",
+      "displayName": "Build everything buildable on macOS",
       "inherits": ["common"],
       "generator": "Xcode",
       "cacheVariables": {
         "CMAKE_TOOLCHAIN_FILE": "${sourceDir}/third-party/ios-cmake/ios.toolchain.cmake",
-        "EXECUTORCH_BUILD_PRESET_FILE": "${sourceDir}/tools/cmake/preset/macos-arm64.cmake",
+        "EXECUTORCH_BUILD_PRESET_FILE": "${sourceDir}/tools/cmake/preset/macos.cmake",
         "PLATFORM": "MAC_ARM64",
         "DEPLOYMENT_TARGET": "10.15"
       },
@@ -23,6 +23,54 @@
         "rhs": "Darwin"
       }
     },
+    {
+      "name": "ios",
+      "displayName": "Build everything buildable on iOS",
+      "inherits": ["common"],
+      "generator": "Xcode",
+      "cacheVariables": {
+        "CMAKE_TOOLCHAIN_FILE": "${sourceDir}/third-party/ios-cmake/ios.toolchain.cmake",
+        "EXECUTORCH_BUILD_PRESET_FILE": "${sourceDir}/tools/cmake/preset/ios.cmake",
+        "PLATFORM": "OS64",
+        "DEPLOYMENT_TARGET": "17.0"
+      },
+      "condition": {
+        "lhs": "${hostSystemName}",
+        "type": "equals",
+        "rhs": "Darwin"
+      }
+    },
+    {
+      "name": "ios-simulator",
+      "displayName": "Build everything buildable on iOS simulator",
+      "inherits": ["common"],
+      "generator": "Xcode",
+      "cacheVariables": {
+        "CMAKE_TOOLCHAIN_FILE": "${sourceDir}/third-party/ios-cmake/ios.toolchain.cmake",
+        "EXECUTORCH_BUILD_PRESET_FILE": "${sourceDir}/tools/cmake/preset/ios.cmake",
+        "PLATFORM": "SIMULATORARM64",
+        "DEPLOYMENT_TARGET": "17.0"
+      },
+      "condition": {
+        "lhs": "${hostSystemName}",
+        "type": "equals",
+        "rhs": "Darwin"
+      }
+    },
+    {
+      "name": "linux",
+      "displayName": "Build everything buildable on Linux",
+      "inherits": ["common"],
+      "cacheVariables": {
+        "CMAKE_SYSTEM_NAME": "Linux",
+        "EXECUTORCH_BUILD_PRESET_FILE": "${sourceDir}/tools/cmake/preset/linux.cmake"
+      },
+      "condition": {
+        "lhs": "${hostSystemName}",
+        "type": "equals",
+        "rhs": "Linux"
+      }
+    },
     {
       "name": "pybind",
       "displayName": "Build pybindings exported in the wheel",

backends/cadence/aot/compiler.py

@@ -123,7 +123,7 @@ def prepare_and_convert_pt2(
     assert isinstance(model_gm, torch.fx.GraphModule)
 
     # Prepare
-    prepared_model = prepare_pt2e(model_gm, quantizer)  # pyre-ignore[6]
+    prepared_model = prepare_pt2e(model_gm, quantizer)
 
     # Calibrate
     # If no calibration data is provided, use the inputs

backends/cadence/aot/quantizer/TARGETS

@@ -9,6 +9,7 @@ python_library(
     ],
     deps = [
         "//caffe2:torch",
+        "//pytorch/ao:torchao",
     ],
 )
 
@@ -34,7 +35,6 @@ python_library(
         ":patterns",
         ":utils",
         "//caffe2:torch",
-        "//executorch/backends/xnnpack/quantizer:xnnpack_quantizer_utils",
     ],
 )
 

backends/cadence/aot/quantizer/patterns.py

@@ -15,7 +15,7 @@
 
 from torch import fx
 from torch._ops import OpOverload
-from torch.ao.quantization.quantizer import (
+from torchao.quantization.pt2e.quantizer import (
     DerivedQuantizationSpec,
     SharedQuantizationSpec,
 )

backends/cadence/aot/quantizer/quantizer.py

@@ -29,19 +29,20 @@
     is_annotated,
     no_outside_users,
 )
-from executorch.backends.xnnpack.quantizer.xnnpack_quantizer_utils import (
+
+from torch import fx
+
+from torchao.quantization.pt2e import HistogramObserver, MinMaxObserver
+from torchao.quantization.pt2e.quantizer import (
+    ComposableQuantizer,
+    DerivedQuantizationSpec,
     OperatorConfig,
     QuantizationAnnotation,
     QuantizationConfig,
     QuantizationSpec,
+    Quantizer,
 )
 
-from torch import fx
-
-from torch.ao.quantization.observer import HistogramObserver, MinMaxObserver
-from torch.ao.quantization.quantizer import DerivedQuantizationSpec, Quantizer
-from torch.ao.quantization.quantizer.composable_quantizer import ComposableQuantizer
-
 
 act_qspec_asym8s = QuantizationSpec(
     dtype=torch.int8,

backends/cadence/aot/quantizer/utils.py

@@ -14,13 +14,13 @@
 import torch
 from torch import fx
 from torch._ops import OpOverload
-from torch.ao.quantization import ObserverOrFakeQuantize
 
 from torch.fx import GraphModule
 from torch.fx.passes.utils.source_matcher_utils import (
     check_subgraphs_connected,
     SourcePartition,
 )
+from torchao.quantization.pt2e import ObserverOrFakeQuantize
 
 
 def quantize_tensor_multiplier(

backends/cadence/aot/remove_ops.py

@@ -235,10 +235,7 @@ def call_operator(
         kwargs: dict[str, Argument],
         meta: NodeMetadata,
     ) -> ProxyValue:
-        if op not in {
-            exir_ops.edge.aten.linalg_vector_norm.default,
-            exir_ops.edge.cadence.linalg_vector_norm.default,
-        }:
+        if op is not exir_ops.edge.aten.linalg_vector_norm.default:
             return super().call_operator(op, args, kwargs, meta)
 
         # If the op has three args or less, it can't be a nop

backends/cadence/aot/tests/test_remove_ops_passes.py

@@ -467,10 +467,7 @@ def forward(self, x: torch.Tensor):
 
         # Expect the linalg_vector_norm op to be removed by the pass
         self.assertEqual(
-            count_node(graph_module, exir_ops.edge.aten.linalg_vector_norm.default)
-            + count_node(
-                graph_module, exir_ops.edge.cadence.linalg_vector_norm.default
-            ),
+            count_node(graph_module, exir_ops.edge.aten.linalg_vector_norm.default),
             0,
         )