Merge pull request pytorch#18 from cavusmustafa/input_validate_fix

Fix for input path bug in validation

Author: cavusmustafa

CMakeLists.txt

@@ -204,7 +204,7 @@ option(EXECUTORCH_BUILD_MPS "Build the MPS backend" OFF)
 
 option(EXECUTORCH_BUILD_NEURON "Build the backends/mediatek directory" OFF)
 
-option(EXECUTORCH_BUILD_OPENVINO "Build the Openvino backend" ON)
+option(EXECUTORCH_BUILD_OPENVINO "Build the Openvino backend" OFF)
 
 option(EXECUTORCH_BUILD_PYBIND "Build the Python Bindings" OFF)
 

backends/openvino/README.md

@@ -47,15 +47,13 @@ executorch
 
 Before you begin, ensure you have openvino installed and configured on your system:
 
-## TODO: Update with the openvino commit/Release tag once the changes in OpenVINO are merged
 ## TODO: Add instructions for support with OpenVINO release package
 
 ```bash
-git clone -b executorch_ov_backend https://github.com/ynimmaga/openvino
-cd openvino
+git clone https://github.com/openvinotoolkit/openvino.git
+cd openvino && git checkout 20ad7cb
 git submodule update --init --recursive
-mkdir build
-cd build
+mkdir build && cd build
 cmake .. -DCMAKE_BUILD_TYPE=Release -DENABLE_PYTHON=ON
 make -j<N>
 

backends/openvino/partitioner.py

@@ -7,7 +7,6 @@
 from typing import Callable, final, List, Optional, Tuple
 
 import torch
-import torch.fx as fx
 from executorch.backends.openvino.preprocess import OpenvinoBackend
 from executorch.exir.backend.backend_details import CompileSpec
 from executorch.exir.backend.partitioner import (

backends/openvino/preprocess.py

@@ -4,12 +4,8 @@
 # except in compliance with the License. See the license file in the root
 # directory of this source tree for more details.
 
-import contextlib
-import struct
+from typing import final, List
 
-from typing import cast, final, List
-
-import torch
 from executorch.exir.backend.backend_details import (
     BackendDetails,
     ExportedProgram,
@@ -36,17 +32,12 @@ def preprocess(
         Returns:
             PreprocessResult: The result of preprocessing, including the compiled model bytes.
         """
-        name_to_node_mappings = {node.name: node for node in edge_program.graph.nodes}
         input_names = edge_program.graph_signature.user_inputs
-        output_names = edge_program.graph_signature.user_outputs
         args = []
         for node in edge_program.graph.nodes:
             if node.target in input_names:
                 args.append(node.meta["val"])
 
-        input_shapes = []
-        output_shapes = []
-
         compile_options = {}
         for spec in module_compile_spec:
             compile_options[spec.key] = spec.value.decode()

backends/openvino/tests/ops/base_openvino_op_test.py

@@ -9,7 +9,7 @@
 import torch
 from executorch.backends.openvino.partitioner import OpenvinoPartitioner
 from executorch.backends.openvino.preprocess import OpenvinoBackend
-from executorch.exir import EdgeProgramManager, to_edge
+from executorch.exir import EdgeProgramManager, to_edge_transform_and_lower
 from executorch.exir.backend.backend_details import CompileSpec
 from torch.export import export, ExportedProgram
 
@@ -33,13 +33,14 @@ def execute_layer_test(
         # Export to aten dialect using torch.export
         aten_dialect: ExportedProgram = export(module, sample_inputs)
 
-        # Convert to edge dialect
-        edge_program: EdgeProgramManager = to_edge(aten_dialect)
-        to_be_lowered_module = edge_program.exported_program()
-
-        # Lower the module to the backend with a custom partitioner
+        # Convert to edge dialect and lower the module to the backend with a custom partitioner
         compile_spec = [CompileSpec("device", self.device.encode())]
-        lowered_module = edge_program.to_backend(OpenvinoPartitioner(compile_spec))
+        lowered_module: EdgeProgramManager = to_edge_transform_and_lower(
+            aten_dialect,
+            partitioner=[
+                OpenvinoPartitioner(compile_spec),
+            ],
+        )
 
         # Apply backend-specific passes
         exec_prog = lowered_module.to_executorch(

backends/openvino/tests/ops/test_pooling.py

@@ -78,9 +78,6 @@ def forward(self, x):
     def test_pooling2d(self):
         for params in d2_params:
             with self.subTest(params=params):
-                bias_shape = None
-                if "bias_shape" in params:
-                    bias_shape = params["bias_shape"]
                 module = self.create_model(
                     op_type="MaxPool2D",
                     kernel_size=params["kernel_size"],

docs/source/build-run-openvino.md

@@ -68,15 +68,13 @@ executorch
 
 Before you begin, ensure you have openvino installed and configured on your system:
 
-#### TODO: Update with the openvino commit/Release tag once the changes in OpenVINO are merged
 #### TODO: Add instructions for support with OpenVINO release package
 
 ```bash
-git clone -b executorch_ov_backend https://github.com/ynimmaga/openvino
-cd openvino
+git clone https://github.com/openvinotoolkit/openvino.git
+cd openvino && git checkout 20ad7cb
 git submodule update --init --recursive
-mkdir build
-cd build
+mkdir build && cd build
 cmake .. -DCMAKE_BUILD_TYPE=Release -DENABLE_PYTHON=ON
 make -j<N>
 

examples/openvino/aot/aot_openvino_compiler.py

@@ -17,7 +17,6 @@
 import numpy as np
 import timm
 import torch
-import torchvision.datasets as datasets
 import torchvision.models as torchvision_models
 from executorch.backends.openvino import OpenVINOQuantizer
 from executorch.backends.openvino.partitioner import OpenvinoPartitioner
@@ -30,6 +29,7 @@
 from torch.ao.quantization.quantize_pt2e import convert_pt2e, prepare_pt2e
 from torch.export import export
 from torch.export.exported_program import ExportedProgram
+from torchvision import datasets
 from transformers import AutoModel
 
 
@@ -119,10 +119,11 @@ def dump_inputs(calibration_dataset, dest_path):
     for idx, data in enumerate(calibration_dataset):
         feature, target = data
         targets.extend(target)
-        file_name = f"{dest_path}/input_{idx}_0.raw"
+        file_name = f"input_{idx}_0.raw"
+        file_path = f"{dest_path}/{file_name}"
         if not isinstance(feature, torch.Tensor):
             feature = torch.tensor(feature)
-        feature.detach().numpy().tofile(file_name)
+        feature.detach().numpy().tofile(file_path)
         input_files.append(file_name)
 
     return input_files, targets

examples/openvino/openvino_build_example.sh

@@ -24,6 +24,7 @@ main() {
           -DEXECUTORCH_BUILD_EXTENSION_MODULE=ON \
           -DEXECUTORCH_BUILD_EXTENSION_RUNNER_UTIL=ON \
           -DEXECUTORCH_BUILD_EXTENSION_TENSOR=ON \
+          -DEXECUTORCH_ENABLE_LOGGING=ON \
           -B"${build_dir}"