Merge branch 'main' into refactor/samsung_backend_schema

Author: onuralpszr

.github/workflows/add-unanswered-to-project.yml

@@ -12,6 +12,7 @@ jobs:
       - name: Add open issues and open, non-draft PRs to org project (excluding certain authors)
         uses: actions/github-script@v7
         with:
+          github-token: ${{ secrets.ET_EXT_CONTRIB }}
           script: |
             const projectId = "PVT_kwDOAUB9vs4A_PUL"; // PyTorch org project 136
             const owner = 'pytorch';

backends/arm/_passes/__init__.py

@@ -91,6 +91,7 @@
     ReplaceScalarWithTensorArgPassTOSABI,
     ReplaceScalarWithTensorArgPassTOSAMI,
 )
+from .rewrite_upsample import RewriteUpsamplePass  # noqa
 from .scalars_to_attribute_pass import ScalarsToAttributePass  # noqa
 from .size_adjust_input_pass import SizeAdjustInputPass  # noqa
 from .to_tosa_memory_format_pass import ToTosaMemoryFormatPass  # noqa

backends/arm/_passes/annotate_decomposed_matmul.py

@@ -11,6 +11,9 @@
 
 import torch
 from executorch.backends.arm._passes.arm_pass_utils import create_node
+from executorch.backends.arm._passes.fold_qdq_with_annotated_qparams_pass import (
+    FoldAndAnnotateQParamsPass,
+)
 
 from executorch.backends.arm.constants import DQ_OPS, Q_OPS
 from executorch.exir.dialects._ops import ops as exir_ops
@@ -29,7 +32,7 @@ class AnnotateDecomposedMatmulPass(ExportPass):
     matmul-op (can be mm or bmm).
     """
 
-    _passes_required_after: Set[Type[ExportPass]] = set()
+    _passes_required_after: Set[Type[ExportPass]] = {FoldAndAnnotateQParamsPass}
 
     def _match_partition_to_node(
         self, node: torch.fx.Node, partitioned_inputs: List[torch.fx.Node]

backends/arm/_passes/arm_pass_manager.py

@@ -91,6 +91,7 @@
     ReplaceScalarWithTensorArgPassTOSABI,
     ReplaceScalarWithTensorArgPassTOSAMI,
     RetraceFoldedDtypesPass,
+    RewriteUpsamplePass,
     ScalarsToAttributePass,
     SizeAdjustInputPass,
     ToTosaMemoryFormatPass,
@@ -206,6 +207,7 @@ def _tosa_INT_pipeline(self, exported_program: ExportedProgram) -> GraphModule:
         # needs to happen before AddBiasPass, but after the table ops are inserted
         # to be able to validate that conv2d has right dtype arguments.
         self.add_pass(DecomposeConv2dWithInt16ActivationPass())
+        self.add_pass(RewriteUpsamplePass(exported_program))
         self.add_pass(AddBiasPass(exported_program))
 
         self.add_pass(FuseEqualPlaceholdersPass(exported_program))
@@ -290,6 +292,7 @@ def _tosa_FP_pipeline(self, exported_program: ExportedProgram) -> GraphModule:
         self.add_pass(FuseViewCopyTransform())
         self.add_pass(FuseConstantArgsPass(exported_program))
         self.add_pass(CastInt64BuffersToInt32Pass(exported_program))
+        self.add_pass(RewriteUpsamplePass(exported_program))
         self.add_pass(AddBiasPass(exported_program))
         self.add_pass(InsertTableOpsPass(exported_program))
         self.add_pass(FuseEqualPlaceholdersPass(exported_program))

backends/arm/_passes/conv1d_unsqueeze_pass.py

@@ -8,6 +8,9 @@
 
 from typing import Set, Type
 
+from executorch.backends.arm._passes.add_bias_pass import AddBiasPass
+from executorch.backends.arm._passes.size_adjust_input_pass import SizeAdjustInputPass
+
 from executorch.exir.dialects._ops import ops as exir_ops
 from executorch.exir.pass_base import ExportPass
 
@@ -23,7 +26,7 @@ class Conv1dUnsqueezePass(ExportPass):
     3) squeeze the output back down to 3d.
     """
 
-    _passes_required_after: Set[Type[ExportPass]] = set()
+    _passes_required_after: Set[Type[ExportPass]] = {AddBiasPass, SizeAdjustInputPass}
 
     def call_operator(self, op, args, kwargs, meta):
         if op != exir_ops.edge.aten.convolution.default:

backends/arm/_passes/convert_any_default_dim_dims_pass.py

@@ -6,6 +6,9 @@
 from typing import Set, Type
 
 import torch
+from executorch.backends.arm._passes.convert_squeezes_to_view import (
+    ConvertSqueezesToViewPass,
+)
 from executorch.exir.dialects._ops import (  # type: ignore[import-not-found]
     ops as exir_ops,
 )
@@ -46,7 +49,7 @@ class ConvertAnyDefaultDimDimsPass(ExportPass):
         squeeze(dim = [dim1, dim2])
     """
 
-    _passes_required_after: Set[Type[ExportPass]] = set()
+    _passes_required_after: Set[Type[ExportPass]] = {ConvertSqueezesToViewPass}
 
     def call(self, graph_module: torch.fx.GraphModule):
         modified = False

backends/arm/_passes/convert_expand_copy_to_repeat.py

@@ -10,6 +10,9 @@
 
 import torch
 
+from executorch.backends.arm._passes.unsqueeze_before_repeat_pass import (
+    UnsqueezeBeforeRepeatPass,
+)
 from executorch.exir.dialects._ops import ops as exir_ops
 from executorch.exir.pass_base import ExportPass
 
@@ -50,7 +53,7 @@ class ConvertExpandCopyToRepeatPass(ExportPass):
     Replace expand copy with repeat since it is a repeat that can only repeat singleton dimensions.
     """
 
-    _passes_required_after: Set[Type[ExportPass]] = set()
+    _passes_required_after: Set[Type[ExportPass]] = {UnsqueezeBeforeRepeatPass}
 
     expand_copy = exir_ops.edge.aten.expand_copy.default
     repeat = exir_ops.edge.aten.repeat.default

backends/arm/_passes/convert_full_like_to_full_pass.py

@@ -5,11 +5,14 @@
 
 from typing import Set, Type
 
+from executorch.backends.arm._passes.arm_pass import ArmPass
+from executorch.backends.arm._passes.fuse_constant_ops_pass import ComputeConstantOpsAOT
+
 from executorch.exir.dialects._ops import ops as exir_ops
 from executorch.exir.pass_base import ExportPass
 
 
-class ConvertFullLikeToFullPass(ExportPass):
+class ConvertFullLikeToFullPass(ArmPass):
     """As per the full_like pytorch documentation,
     `torch.full_like(input, fill_value)` is equivalent to
     `torch.full(input.size(),
@@ -21,7 +24,7 @@ class ConvertFullLikeToFullPass(ExportPass):
     Skip layout and device since it's not relevant for our backend.
     """
 
-    _passes_required_after: Set[Type[ExportPass]] = set()
+    _passes_required_after: Set[Type[ExportPass]] = {ComputeConstantOpsAOT}
 
     def call_operator(self, op, args, kwargs, meta):
         if op not in [

backends/arm/_passes/convert_int64_const_ops_to_int32.py

@@ -31,7 +31,7 @@ class ConvertInt64ConstOpsToInt32Pass(ExportPass):
       5. `torch.tensor`
     """
 
-    _passes_required_after: Set[Type[ExportPass]] = set()
+    _passes_required_after: Set[Type[ExportPass]] = {ComputeConstantOpsAOT}
 
     torch_ops = [
         torch.ops.aten.full.default,

backends/arm/_passes/convert_minmax_pass.py

@@ -6,6 +6,9 @@
 from typing import Set, Type
 
 import torch
+from executorch.backends.arm._passes.convert_squeezes_to_view import (
+    ConvertSqueezesToViewPass,
+)
 from executorch.exir.dialects._ops import ops as exir_ops
 from executorch.exir.pass_base import ExportPass, PassResult
 
@@ -31,7 +34,7 @@ class ConvertMinMaxPass(ExportPass):
         squeeze(dim = [dim1, dim2])
     """
 
-    _passes_required_after: Set[Type[ExportPass]] = set()
+    _passes_required_after: Set[Type[ExportPass]] = {ConvertSqueezesToViewPass}
 
     def check_argmax(self, node):
         """