hg mv backend example to a different place

examples/README.md

@@ -7,14 +7,15 @@ It also includes a list of modules, from a simple `Add` to a full model like `Mo
 ## Directory structure
 ```bash
 examples
-|── backend         # Contains examples for exporting delegate models and running them using custom executor runners
-├── custom_ops      # Contains examples to register custom operators into PyTorch as well as register its kernels into Executorch runtime
-├── executor_runner # This is an example C++ wrapper around the ET runtime
-├── export          # Python helper scripts to illustrate export workflow
-├── ios_demo_apps   # Contains iOS demo apps
-├── models          # Contains a set of simple to PyTorch models
-├── quantization    # Contains examples of quantization workflow
-└── README.md       # This file
+|── backend                           # Contains examples for exporting delegate models and running them using custom executor runners
+├── custom_ops                        # Contains examples to register custom operators into PyTorch as well as register its kernels into Executorch runtime
+├── example_quantizer_and_delegate    # Contains examples to to fully lowered a MobileNetV2 model to the example backend with an example quantizer
+├── executor_runner                   # This is an example C++ wrapper around the ET runtime
+├── export                            # Python helper scripts to illustrate export workflow
+├── ios_demo_apps                     # Contains iOS demo apps
+├── models                            # Contains a set of simple to PyTorch models
+├── quantization                      # Contains examples of quantization workflow
+└── README.md                         # This file
 ```
 
 ## Using the examples

backends/example/TARGETS → examples/example_quantizer_and_delegate/TARGETS

@@ -8,7 +8,7 @@ python_library(
     ],
     deps = [
         "//caffe2:torch",
-        "//executorch/backends/example/example_operators:example_operators_lib",
+        "//executorch/examples/example_quantizer_and_delegate/example_operators:example_operators_lib",
     ],
 )
 
@@ -18,7 +18,7 @@ python_library(
         "example_backend.py",
     ],
     deps = [
-        "//executorch/backends/example/example_backend_delegate_passes:lib",
+        "//executorch/examples/example_quantizer_and_delegate/example_backend_delegate_passes:lib",
         "//executorch/exir/backend:backend_details",
         "//executorch/exir/backend:compile_spec_schema",
     ],
@@ -32,7 +32,7 @@ python_library(
     deps = [
         ":example_backend",
         "//caffe2:torch",
-        "//executorch/backends/example/example_operators:example_operators_lib",
+        "//executorch/examples/example_quantizer_and_delegate/example_operators:example_operators_lib",
         "//executorch/exir:graph_module",
         "//executorch/exir/backend:partitioner",
         "//executorch/exir/backend/canonical_partitioners:canonical_partitioner_lib",

backends/example/example_backend.py → examples/example_quantizer_and_delegate/example_backend.py

@@ -7,10 +7,10 @@
 import copy
 from typing import final, List
 
-from executorch.backends.example.example_backend_delegate_passes.merge_to_dim_pass import (
+from executorch.examples.example_quantizer_and_delegate.example_backend_delegate_passes.merge_to_dim_pass import (
     MergeToDimPass,
 )
-from executorch.backends.example.example_backend_delegate_passes.permute_memory_formats_pass import (
+from executorch.examples.example_quantizer_and_delegate.example_backend_delegate_passes.permute_memory_formats_pass import (
     PermuteMemoryFormatsPass,
 )
 

backends/example/example_backend_delegate_passes/TARGETS → examples/example_quantizer_and_delegate/example_backend_delegate_passes/TARGETS

@@ -8,7 +8,7 @@ python_library(
     ],
     deps = [
         "//caffe2:torch",
-        "//executorch/backends/example/example_operators:example_operators_lib",
+        "//executorch/examples/example_quantizer_and_delegate/example_operators:example_operators_lib",
         "//executorch/exir:dim_order_utils",
         "//executorch/exir:pass_base",
         "//executorch/exir/dialects:lib",

backends/example/example_backend_delegate_passes/permute_memory_formats_pass.py → examples/example_quantizer_and_delegate/example_backend_delegate_passes/permute_memory_formats_pass.py

@@ -7,7 +7,9 @@
 from itertools import chain
 
 import torch
-from executorch.backends.example.example_operators.ops import module_to_annotator
+from executorch.examples.example_quantizer_and_delegate.example_operators.ops import (
+    module_to_annotator,
+)
 from executorch.exir.dialects._ops import ops as exir_ops
 from executorch.exir.dim_order_utils import get_dim_order
 from executorch.exir.pass_base import ExportPass, PassResult

backends/example/example_operators/adaptive_avg_pool2d.py → examples/example_quantizer_and_delegate/example_operators/adaptive_avg_pool2d.py

@@ -7,8 +7,10 @@
 from dataclasses import dataclass
 
 import torch
-from executorch.backends.example.example_operators.op_base import OpBase
-from executorch.backends.example.example_operators.utils import (
+from executorch.examples.example_quantizer_and_delegate.example_operators.op_base import (
+    OpBase,
+)
+from executorch.examples.example_quantizer_and_delegate.example_operators.utils import (
     _annotate_nodes,
     _nodes_are_annotated,
 )

backends/example/example_operators/add.py → examples/example_quantizer_and_delegate/example_operators/add.py

@@ -7,8 +7,10 @@
 from dataclasses import dataclass
 
 import torch
-from executorch.backends.example.example_operators.op_base import OpBase
-from executorch.backends.example.example_operators.utils import (
+from executorch.examples.example_quantizer_and_delegate.example_operators.op_base import (
+    OpBase,
+)
+from executorch.examples.example_quantizer_and_delegate.example_operators.utils import (
     _annotate_nodes,
     _nodes_are_annotated,
 )

backends/example/example_operators/conv2d.py → examples/example_quantizer_and_delegate/example_operators/conv2d.py

@@ -7,8 +7,10 @@
 from dataclasses import dataclass
 
 import torch
-from executorch.backends.example.example_operators.op_base import OpBase
-from executorch.backends.example.example_operators.utils import (
+from executorch.examples.example_quantizer_and_delegate.example_operators.op_base import (
+    OpBase,
+)
+from executorch.examples.example_quantizer_and_delegate.example_operators.utils import (
     _annotate_nodes,
     _nodes_are_annotated,
 )

backends/example/example_operators/conv_relu.py → examples/example_quantizer_and_delegate/example_operators/conv_relu.py

@@ -7,8 +7,10 @@
 from dataclasses import dataclass
 
 import torch
-from executorch.backends.example.example_operators.op_base import OpBase
-from executorch.backends.example.example_operators.utils import (
+from executorch.examples.example_quantizer_and_delegate.example_operators.op_base import (
+    OpBase,
+)
+from executorch.examples.example_quantizer_and_delegate.example_operators.utils import (
     _annotate_nodes,
     _nodes_are_annotated,
 )

backends/example/example_operators/dropout.py → examples/example_quantizer_and_delegate/example_operators/dropout.py

@@ -7,8 +7,10 @@
 from dataclasses import dataclass
 
 import torch
-from executorch.backends.example.example_operators.op_base import OpBase
-from executorch.backends.example.example_operators.utils import (
+from executorch.examples.example_quantizer_and_delegate.example_operators.op_base import (
+    OpBase,
+)
+from executorch.examples.example_quantizer_and_delegate.example_operators.utils import (
     _annotate_nodes,
     _nodes_are_annotated,
 )

backends/example/example_operators/flatten.py → examples/example_quantizer_and_delegate/example_operators/flatten.py

@@ -7,8 +7,10 @@
 from dataclasses import dataclass
 
 import torch
-from executorch.backends.example.example_operators.op_base import OpBase
-from executorch.backends.example.example_operators.utils import (
+from executorch.examples.example_quantizer_and_delegate.example_operators.op_base import (
+    OpBase,
+)
+from executorch.examples.example_quantizer_and_delegate.example_operators.utils import (
     _annotate_nodes,
     _nodes_are_annotated,
 )

backends/example/example_operators/linear.py → examples/example_quantizer_and_delegate/example_operators/linear.py

@@ -7,8 +7,10 @@
 from dataclasses import dataclass
 
 import torch
-from executorch.backends.example.example_operators.op_base import OpBase
-from executorch.backends.example.example_operators.utils import (
+from executorch.examples.example_quantizer_and_delegate.example_operators.op_base import (
+    OpBase,
+)
+from executorch.examples.example_quantizer_and_delegate.example_operators.utils import (
     _annotate_nodes,
     _nodes_are_annotated,
 )

backends/example/example_operators/ops.py → examples/example_quantizer_and_delegate/example_operators/ops.py

@@ -6,16 +6,28 @@
 
 from collections import OrderedDict
 
-from executorch.backends.example.example_operators.adaptive_avg_pool2d import (
+from executorch.examples.example_quantizer_and_delegate.example_operators.adaptive_avg_pool2d import (
     AdaptiveAvgPool2dNode,
 )
 
-from executorch.backends.example.example_operators.add import AddNode
-from executorch.backends.example.example_operators.conv2d import Conv2DNode
-from executorch.backends.example.example_operators.conv_relu import ConvReluNode
-from executorch.backends.example.example_operators.dropout import DropOutNode
-from executorch.backends.example.example_operators.flatten import FlattenNode
-from executorch.backends.example.example_operators.linear import LinearNode
+from executorch.examples.example_quantizer_and_delegate.example_operators.add import (
+    AddNode,
+)
+from executorch.examples.example_quantizer_and_delegate.example_operators.conv2d import (
+    Conv2DNode,
+)
+from executorch.examples.example_quantizer_and_delegate.example_operators.conv_relu import (
+    ConvReluNode,
+)
+from executorch.examples.example_quantizer_and_delegate.example_operators.dropout import (
+    DropOutNode,
+)
+from executorch.examples.example_quantizer_and_delegate.example_operators.flatten import (
+    FlattenNode,
+)
+from executorch.examples.example_quantizer_and_delegate.example_operators.linear import (
+    LinearNode,
+)
 
 # The ordering of this is important as the quantizer will try to match the patterns in this order.
 # That's why we want to match the fused patterns first and then the non-fused ones.

backends/example/example_partitioner.py → examples/example_quantizer_and_delegate/example_partitioner.py

@@ -7,12 +7,20 @@
 from typing import Dict, final
 
 import torch
-from executorch.backends.example.example_backend import TosaBackend
-from executorch.backends.example.example_operators.ops import module_to_annotator
+from executorch.examples.example_quantizer_and_delegate.example_backend import (
+    TosaBackend,
+)
+from executorch.examples.example_quantizer_and_delegate.example_operators.ops import (
+    module_to_annotator,
+)
 from executorch.exir.backend.canonical_partitioners.pattern_op_partitioner import (
     generate_partitions_from_list_of_nodes,
 )
-from executorch.exir.backend.partitioner import DelegationSpec, Partitioner
+from executorch.exir.backend.partitioner import (
+    DelegationSpec,
+    Partitioner,
+    PartitionResult,
+)
 from executorch.exir.dialects._ops import ops as exir_ops
 from executorch.exir.graph_module import get_control_flow_submodules
 from torch.ao.quantization.pt2e.graph_utils import find_sequential_partitions
@@ -28,7 +36,6 @@ class ExamplePartitioner(Partitioner):
     def __init__(self) -> None:
         self.patterns = module_to_annotator.keys()
         self.delegation_spec = DelegationSpec(TosaBackend.__name__, [])
-        self.partition_tags: Dict[str, DelegationSpec] = {}
 
         class DequantQuantOperatorSupport(OperatorSupportBase):
             def is_node_supported(self, _submodules, node: torch.fx.Node) -> bool:
@@ -39,9 +46,8 @@ def is_node_supported(self, _submodules, node: torch.fx.Node) -> bool:
 
         self.dequant_quant_support = DequantQuantOperatorSupport()
 
-    def partition(
-        self, edge_graph_module: torch.fx.GraphModule
-    ) -> torch.fx.GraphModule:
+    def partition(self, edge_graph_module: torch.fx.GraphModule) -> PartitionResult:
+        partition_tags: Dict[str, DelegationSpec] = {}
         partition_nodes = []
         for pattern in self.patterns:
             fused_partitions = find_sequential_partitions(
@@ -68,9 +74,11 @@ def partition(
                             and arg_node.op == "get_attr"
                         ):
                             arg_node.meta["delegation_tag"] = delegation_tag
-                self.partition_tags[delegation_tag] = self.delegation_spec
+                partition_tags[delegation_tag] = self.delegation_spec
 
         for _, submodule, _ in get_control_flow_submodules(edge_graph_module):
             self.partition(submodule)
 
-        return edge_graph_module
+        return PartitionResult(
+            tagged_graph=edge_graph_module, partition_tags=partition_tags
+        )

backends/example/example_quantizer.py → examples/example_quantizer_and_delegate/example_quantizer.py

@@ -8,7 +8,9 @@
 from typing import List
 
 import torch
-from executorch.backends.example.example_operators.ops import module_to_annotator
+from executorch.examples.example_quantizer_and_delegate.example_operators.ops import (
+    module_to_annotator,
+)
 from torch import fx
 from torch.ao.quantization.observer import HistogramObserver, MinMaxObserver
 from torch.ao.quantization.pt2e.graph_utils import find_sequential_partitions

backends/example/test_example_delegate.py → examples/example_quantizer_and_delegate/test_example_delegate.py

@@ -10,8 +10,12 @@
 import torch
 import torch._export as export
 from executorch import exir
-from executorch.backends.example.example_partitioner import ExamplePartitioner
-from executorch.backends.example.example_quantizer import ExampleQuantizer
+from executorch.examples.example_quantizer_and_delegate.example_partitioner import (
+    ExamplePartitioner,
+)
+from executorch.examples.example_quantizer_and_delegate.example_quantizer import (
+    ExampleQuantizer,
+)
 from executorch.exir.backend.backend_api import to_backend
 
 from executorch.exir.backend.canonical_partitioners.duplicate_dequant_node_pass import (