Update on "Support export program in intermediate numeric discrepancy detector"

This diff enables intermediate numeric discrepancy detector to leverage export program as label.

More specific, if user creates etrecord with exported program, and the exported program is one of the exported programs in the export flow, then our numeric discrepancy detector will use it as label. Otherwise, we will continue use edge dialect graph as label.

Differential Revision: [D78298935](https://our.internmc.facebook.com/intern/diff/D78298935/)

[ghstack-poisoned]

Author: Gasoonjia

.ci/docker/ci_commit_pins/pytorch.txt

@@ -1 +1 @@
-2dccff7dcf56b0d168ebfd7ca08bdeca37273c56
+ab43fe4bdf5ccd82897f0e982c451a0127bd175e

.github/workflows/trunk.yml

@@ -269,7 +269,7 @@ jobs:
         if [[ ${{ matrix.os}} == "bare_metal" ]]; then
           bash test/build_size_test.sh "-DCMAKE_TOOLCHAIN_FILE=${toolchain_cmake} -DEXECUTORCH_BUILD_ARM_BAREMETAL=ON"
         elif [[ ${{ matrix.os}} == "zephyr-preset" ]]; then
-          CXXFLAGS=${cxx_flags} cmake --preset zephyr -DCMAKE_BUILD_TYPE=Release -DEXECUTORCH_OPTIMIZE_SIZE=ON -DCMAKE_INSTALL_PREFIX=cmake-out -Bcmake-out .
+          CXXFLAGS=${cxx_flags} cmake --preset zephyr -DCMAKE_BUILD_TYPE=Release -DEXECUTORCH_OPTIMIZE_SIZE=ON -DEXECUTORCH_BUILD_EXTENSION_DATA_LOADER=ON -DCMAKE_INSTALL_PREFIX=cmake-out -Bcmake-out .
           cmake --build cmake-out -j9 --target install --config Release
           CXXFLAGS=${cxx_flags}  cmake -DCMAKE_TOOLCHAIN_FILE=${toolchain_cmake} -DCMAKE_BUILD_TYPE=Release -DCMAKE_INSTALL_PREFIX=cmake-out -Bcmake-out/test test
           cmake --build cmake-out/test -j9 --config Release

backends/qualcomm/_passes/layout_transform.py

@@ -103,8 +103,8 @@ class LayoutTransform(ExportPass):
         exir_ops.edge.aten.pow.Tensor_Scalar,
         exir_ops.edge.aten.prelu.default,
         exir_ops.edge.aten.repeat.default,
-        exir_ops.edge.aten.round.default,
         exir_ops.edge.aten.relu.default,
+        exir_ops.edge.aten.round.default,
         exir_ops.edge.aten.sigmoid.default,
         exir_ops.edge.aten.split_with_sizes.default,
         exir_ops.edge.aten.split_with_sizes_copy.default,

backends/qualcomm/quantizer/annotators.py

@@ -278,7 +278,9 @@ def annotate_masked_fill(node: Node, quantization_config: QuantizationConfig) ->
     )
 
 
-@register_annotator([torch.ops.aten.mul, torch.ops.aten.mul.Tensor])
+@register_annotator(
+    [torch.ops.aten.mul, torch.ops.aten.mul.Tensor, torch.ops.aten.mul_.Tensor]
+)
 def annotate_mul(node: Node, quantization_config: QuantizationConfig) -> None:
     annotate_binary(node, quantization_config)
 
@@ -1311,7 +1313,7 @@ def annotate_where(node: Node, quantization_config: QuantizationConfig) -> None:
     )
 
 
-@register_annotator([torch.ops.aten.zeros.default])
+@register_annotator([torch.ops.aten.zeros.default, torch.ops.aten.zeros_like.default])
 def annotate_zeros(node: Node, quantization_config: QuantizationConfig) -> None:
     if _is_annotated([node]) or not _is_float_tensor(node):
         return

backends/qualcomm/quantizer/custom_annotation.py

@@ -153,7 +153,9 @@ def annotate_prefill_kv_output(gm: torch.fx.GraphModule, kv_quant_attrs: dict):
                 )
 
 
-def annotate_matmul_16a8w(gm: torch.fx.GraphModule) -> None:  # noqa: C901
+def annotate_matmul_16a8w(  # noqa: C901
+    gm: torch.fx.GraphModule, annotate_conv=True
+) -> None:
     """
     This function is specific for matmul op 16a8w.
     For k, we will tag such as the below, and
@@ -317,9 +319,10 @@ def annotate_matmul_input1(node: Node):
                 # The arguments of cat op: (the past kv cache, the new kv cache)
                 node = node.args[0][1]
             elif node.target == torch.ops.aten.conv2d.default:
-                annotate_conv2d(
-                    node, quantization_config=quantization_config_8a4w_per_channel
-                )
+                if annotate_conv:
+                    annotate_conv2d(
+                        node, quantization_config=quantization_config_8a4w_per_channel
+                    )
                 break
             elif node.target in [torch.ops.aten.add.Tensor, torch.ops.aten.sub.Tensor]:
                 break

backends/qualcomm/scripts/build.sh

@@ -85,6 +85,7 @@ if [ "$BUILD_AARCH64" = true ]; then
         -DEXECUTORCH_BUILD_EXTENSION_FLAT_TENSOR=ON \
         -DEXECUTORCH_BUILD_EXTENSION_TENSOR=ON \
         -DEXECUTORCH_ENABLE_EVENT_TRACER=ON \
+        -DEXECUTORCH_ENABLE_LOGGING=ON \
         -DQNN_SDK_ROOT=$QNN_SDK_ROOT \
         -DCMAKE_TOOLCHAIN_FILE=$ANDROID_NDK_ROOT/build/cmake/android.toolchain.cmake \
         -DANDROID_ABI='arm64-v8a' \
@@ -104,6 +105,9 @@ if [ "$BUILD_AARCH64" = true ]; then
         -DANDROID_ABI='arm64-v8a' \
         -DANDROID_PLATFORM=android-30 \
         -DCMAKE_PREFIX_PATH=$CMAKE_PREFIX_PATH \
+        -DSUPPORT_REGEX_LOOKAHEAD=ON \
+        -DBUILD_TESTING=OFF \
+        -DEXECUTORCH_ENABLE_LOGGING=ON \
         -DEXECUTORCH_BUILD_KERNELS_QUANTIZED=ON \
         -DCMAKE_FIND_ROOT_PATH_MODE_PACKAGE=BOTH \
         -DPYTHON_EXECUTABLE=$PYTHON_EXECUTABLE \
@@ -134,6 +138,7 @@ if [ "$BUILD_X86_64" = true ]; then
         -DEXECUTORCH_BUILD_KERNELS_QUANTIZED=ON \
         -DEXECUTORCH_BUILD_EXTENSION_TENSOR=ON \
         -DEXECUTORCH_ENABLE_EVENT_TRACER=ON \
+        -DEXECUTORCH_ENABLE_LOGGING=ON \
         -DPYTHON_EXECUTABLE=$PYTHON_EXECUTABLE \
         -S $PRJ_ROOT \
         -B $BUILD_ROOT \
@@ -157,6 +162,9 @@ if [ "$BUILD_X86_64" = true ]; then
        -DCMAKE_PREFIX_PATH=$CMAKE_PREFIX_PATH \
        -DCMAKE_FIND_ROOT_PATH_MODE_PACKAGE=BOTH \
        -DPYTHON_EXECUTABLE=$PYTHON_EXECUTABLE \
+       -DSUPPORT_REGEX_LOOKAHEAD=ON \
+       -DBUILD_TESTING=OFF \
+       -DEXECUTORCH_ENABLE_LOGGING=ON \
        -B$EXAMPLE_ROOT
 
    cmake --build $EXAMPLE_ROOT -j$BUILD_JOB_NUMBER

backends/qualcomm/tests/test_qnn_delegate.py

@@ -4049,7 +4049,7 @@ def test_llama3_2_1b(self):
             "16a4w",
             "--temperature",
             "0",
-            "--llama_model",
+            "--decoder_model",
             "llama3_2",
             "--model_mode",
             "hybrid",
@@ -4129,7 +4129,7 @@ def test_llama_stories_110m(self):
             "16a4w",
             "--temperature",
             "0",
-            "--llama_model",
+            "--decoder_model",
             "stories110m",
             "--model_mode",
             "hybrid",
@@ -4171,6 +4171,65 @@ def test_llama_stories_110m(self):
                 if not self.compile_only and not self.enable_x86_64:
                     self.assertGreaterEqual(msg["inference_speed"], 220)  # Lanai
 
+    def test_qwen2_5(self):
+        if not self.required_envs():
+            self.skipTest("missing required envs")
+
+        prompt = "My favourite condiment is "
+        cmds = [
+            "python",
+            f"{self.executorch_root}/examples/qualcomm/oss_scripts/llama/llama.py",
+            "--artifact",
+            self.artifact_dir,
+            "--build_folder",
+            self.build_folder,
+            "--model",
+            self.model,
+            "--ip",
+            self.ip,
+            "--port",
+            str(self.port),
+            "--prompt",
+            f"{prompt}",
+            "--ptq",
+            "16a8w",
+            "--decoder_model",
+            "qwen2_5",
+            "--model_mode",
+            "hybrid",
+            "--prefill_ar_len",
+            "32",
+            "--max_seq_len",
+            "128",
+        ]
+        if self.compile_only:
+            cmds.extend(["--compile_only"])
+        elif self.device:
+            cmds.extend(["--device", self.device])
+        if self.host:
+            cmds.extend(["--host", self.host])
+        elif self.enable_x86_64:
+            cmds.extend(["--enable_x86_64"])
+        if self.pre_gen_pte:
+            cmds.extend(["--pre_gen_pte", self.pre_gen_pte])
+
+        # Accuracy is bad for now. Just check user's prompt is returned.
+        golden_start_with = "My favourite condiment is "
+        p = subprocess.Popen(cmds, stdout=subprocess.DEVNULL)
+        with Listener((self.ip, self.port)) as listener:
+            conn = listener.accept()
+            p.communicate()
+            msg = json.loads(conn.recv())
+            if "Error" in msg:
+                self.fail(msg["Error"])
+            else:
+                model_out = msg["result"][0]
+                self.assertTrue(
+                    model_out.startswith(golden_start_with),
+                    f"Expected Output: {golden_start_with}. Actual Output: {model_out}",
+                )
+                self.assertGreaterEqual(msg["inference_speed"], 95)  # Lanai
+
 
 class TestExampleOssScript(TestQNN):
     def test_albert(self):

backends/test/suite/flow.py

@@ -62,4 +62,13 @@ def all_flows() -> dict[str, TestFlow]:
     except Exception as e:
         logger.info(f"Skipping Core ML flow registration: {e}")
 
+    try:
+        from executorch.backends.test.suite.flows.vulkan import VULKAN_TEST_FLOW
+
+        flows += [
+            VULKAN_TEST_FLOW,
+        ]
+    except Exception as e:
+        logger.info(f"Skipping Vulkan flow registration: {e}")
+
     return {f.name: f for f in flows if f is not None}

backends/test/suite/flows/vulkan.py

@@ -0,0 +1,17 @@
+from executorch.backends.test.suite.flow import TestFlow
+from executorch.backends.vulkan.test.tester import VulkanTester
+
+
+def _create_vulkan_flow(
+    name: str,
+    quantize: bool = False,
+) -> TestFlow:
+    return TestFlow(
+        name,
+        backend="vulkan",
+        tester_factory=VulkanTester,
+        quantize=quantize,
+    )
+
+
+VULKAN_TEST_FLOW = _create_vulkan_flow("vulkan")

backends/vulkan/test/TARGETS

@@ -1,4 +1,5 @@
 load("@fbcode_macros//build_defs:python_unittest.bzl", "python_unittest")
+load("@fbsource//xplat/executorch/build:runtime_wrapper.bzl", "runtime")
 
 oncall("executorch")
 
@@ -57,3 +58,12 @@ python_unittest(
         "//executorch/backends/vulkan:vulkan_preprocess",
     ],
 )
+
+runtime.python_library(
+    name = "tester",
+    srcs = ["tester.py"],
+    deps = [
+        "//executorch/backends/vulkan/partitioner:vulkan_partitioner",
+        "//executorch/backends/vulkan:vulkan_preprocess",
+    ]
+)