remove duplication

Differential Revision: D65236267

Pull Request resolved: #7186

Author: skrtskrtfb

backends/cadence/aot/TARGETS

@@ -374,3 +374,37 @@ python_unittest(
         "//executorch/exir/dialects:lib",
     ],
 )
+
+
+python_library(
+    name = "memory_planning",
+    srcs = [
+        "memory_planning.py",
+    ],
+    deps = [
+        "fbsource//third-party/pypi/tabulate:tabulate",
+        ":memory_constraints",
+        ":pass_utils",
+        "//caffe2:torch",
+        "//executorch/exir:lib",
+        "//executorch/exir:memory_planning",
+        "//executorch/exir:tensor",
+        "//executorch/exir/passes:lib",
+    ],
+)
+
+
+python_library(
+    name = "memory_constraints",
+    srcs = [
+        "memory_constraints.py",
+    ],
+    deps = [
+        ":pass_utils",
+        ":utils",
+        "//caffe2:torch",
+        "//executorch/exir:memory",
+        "//executorch/exir:pass_manager",
+        "//executorch/exir:tensor",
+    ],
+)

backends/cadence/aot/memory_planning.py

@@ -4,6 +4,8 @@
 # This source code is licensed under the BSD-style license found in the
 # LICENSE file in the root directory of this source tree.
 
+# pyre-unsafe
+
 import collections
 import itertools
 import logging
@@ -331,14 +333,15 @@ def find_peak_memory_usage(
 # | Peak memory usage across all spaces | 2380032 bytes | Node 86 |
 # +-------------------------------------+---------------+---------+
 def print_memory_planning_info(
-    # pyre-fixme[11]: Annotation `ExecutorchProgramManager` is not defined as a type.
     executorch_prog: ExecutorchProgramManager,
     memory_config: MemoryConfig,
+    opt_level: int,
     alloc_graph_input: bool,
     alloc_graph_output: bool,
 ) -> None:
     # Get the peak memory usages per memory space
     mem_constraints = MemConstraints(
+        opt_level=opt_level,
         alloc_graph_input=alloc_graph_input,
         alloc_graph_output=alloc_graph_output,
     )
@@ -406,6 +409,7 @@ class CadenceMemoryPlanning:
     def __init__(
         self,
         memory_config: MemoryConfig,
+        opt_level: int,
         mem_algo: int,
         alloc_graph_input: bool = True,
         alloc_graph_output: bool = True,
@@ -421,6 +425,7 @@ def __init__(
         self._init_mem_algos()
 
         self.memory_config = memory_config
+        self.opt_level = opt_level
         self.mem_algo = mem_algo
         self.alloc_graph_input = alloc_graph_input
         self.alloc_graph_output = alloc_graph_output
@@ -434,6 +439,7 @@ def _init_mem_algos(self) -> None:
 
     def __call__(self, graph_module: torch.fx.GraphModule) -> PassResult:
         mem_constraints = MemConstraints(
+            opt_level=self.opt_level,
             alloc_graph_input=self.alloc_graph_input,
             alloc_graph_output=self.alloc_graph_output,
         )
@@ -448,7 +454,7 @@ def __call__(self, graph_module: torch.fx.GraphModule) -> PassResult:
         # True.
         mem_planning = MemoryPlanningPass(
             algo,
-            allow_lifetime_and_storage_overlap=False,
+            allow_lifetime_and_storage_overlap=(self.opt_level >= 2),
             alloc_graph_input=self.alloc_graph_input,
             alloc_graph_output=self.alloc_graph_output,
         )