[executorch][emitter] Emit FQNs

Pull Request resolved: #7192

Emit FQNs for external tensors. In the emitter, store external tensors as:
```
// list of unique tensors
external_constants_buffer: List[bytes]

// map of {constant_tag: {fqn: index into external_constant_buffer}}
// constant_tag: may want to save multiple external constant files; group them together via the tag.
// {fqn: index}; there may be multiple fqns pointing to the same data buffer. This is for deduplication.
external_constants_map: [Dict[str, Dict[str, int]]
```
ghstack-source-id: 257245125
@exported-using-ghexport

Differential Revision: [D66523226](https://our.internmc.facebook.com/intern/diff/D66523226/)

Co-authored-by: lucylq <[email protected]>

Author: pytorchbot

exir/emit/_emit_program.py

@@ -47,6 +47,13 @@ class EmitterOutput:
 
     mutable_data: Optional[List[Buffer]]
 
+    # Constants are optionally stored in external files.
+    # Aggregate unique external constants into one buffer.
+    external_constant_buffer: List[bytes]
+    # Each constant_tag groups a set of constants together.
+    # {constant_tag: {fqn: index into external_constant_buffer}}
+    external_constant_map: Optional[Dict[str, Dict[str, int]]]
+
 
 def _remove_non_user_outputs(exported_program: ExportedProgram) -> torch.fx.GraphModule:
     gm = exported_program.graph_module
@@ -199,4 +206,6 @@ def emit_program(
             if len(program_state.mutable_buffer) > 1
             else None
         ),
+        external_constant_buffer=program_state.external_constant_buffer,
+        external_constant_map=program_state.external_constant_map,
     )

exir/emit/_emitter.py

@@ -63,6 +63,7 @@
     DoubleList,
     EValue,
     ExecutionPlan,
+    ExtraTensorInfo,
     FreeCall,
     Instruction,
     Int,
@@ -76,6 +77,7 @@
     ScalarType,
     String,
     Tensor,
+    TensorDataLocation,
     TensorList,
     TensorShapeDynamism,
 )
@@ -121,6 +123,14 @@ class _ProgramState:
     # and should be copied to Program.backend_delegate_data.
     backend_delegate_data: List[BackendDelegateInlineData] = field(default_factory=list)
 
+    # Constants are optionally stored in external files.
+    # Aggregate unique external constants into one buffer.
+    external_constant_buffer: List[bytes] = field(default_factory=list)
+    external_constant_hash: Dict[str, int] = field(default_factory=dict)
+    # Each constant_tag groups a set of constants together.
+    # {constant_tag: {fqn: index into external_constant_buffer}}
+    external_constant_map: Dict[str, Dict[str, int]] = field(default_factory=dict)
+
 
 @dataclass
 class _EmitterState:
@@ -363,7 +373,8 @@ def _save_new_const_tensor(
         spec: TensorSpec,
         buffer_data: bytes,
         hashed: str,
-        allocation_info: Optional[AllocationDetails],
+        allocation_info: Optional[AllocationDetails] = None,
+        constant_tag: Optional[str] = None,
     ) -> int:
         """Saves a new constant tensor to the constant buffer and returns the buffer idx"""
 
@@ -372,17 +383,45 @@ def _save_new_const_tensor(
 
         # Update buffer_idx to point to the end of the list where we are adding the new buffer.
         buffer = Buffer(storage=buffer_data)
+
+        # Tensor is mutable with initial state.
         if allocation_info:
             buffer_idx = len(self.program_state.mutable_buffer)
             self.program_state.cached_spec_mutable_hash_values[hashed] = buffer_idx
             self.program_state.mutable_buffer.append(buffer)
+
+        # Tensor is constant.
         else:
-            buffer_idx = len(self.program_state.constant_buffer)
-            self.program_state.cached_spec_hash_values[hashed] = buffer_idx
-            self.program_state.constant_buffer.append(buffer)
+            # Tensor is stored outside of the PTE file.
+            if (
+                spec.extra_tensor_info is not None
+                and spec.extra_tensor_info.fully_qualified_name is not None
+                and spec.extra_tensor_info.location == TensorDataLocation.EXTERNAL
+            ):
+                assert (
+                    constant_tag is not None
+                ), "Constant tag is not set for external tensor"
+
+                buffer_idx = len(self.program_state.external_constant_buffer)
+                self.program_state.external_constant_hash[hashed] = buffer_idx
+                self.program_state.external_constant_buffer.append(buffer_data)
+                if constant_tag not in self.program_state.external_constant_map:
+                    self.program_state.external_constant_map[constant_tag] = {}
+                self.program_state.external_constant_map[constant_tag][
+                    spec.extra_tensor_info.fully_qualified_name  # pyre-ignore Undefined attribute [16]: `Optional` has no attribute `fully_qualified_name`.
+                ] = buffer_idx
+
+            # Tensor is stored in the PTE file.
+            else:
+                buffer_idx = len(self.program_state.constant_buffer)
+                self.program_state.cached_spec_hash_values[hashed] = buffer_idx
+                self.program_state.constant_buffer.append(buffer)
+
         return buffer_idx
 
-    def _tensor_spec_to_evalue(self, spec: TensorSpec) -> EValue:
+    def _tensor_spec_to_evalue(
+        self, spec: TensorSpec, constant_tag: Optional[str] = None
+    ) -> EValue:
         """Constructs an EValue from the given TensorSpec."""
 
         allocation_info = None
@@ -420,13 +459,18 @@ def _tensor_spec_to_evalue(self, spec: TensorSpec) -> EValue:
                 buffer_idx = self.program_state.cached_spec_mutable_hash_values.get(
                     hashed, -1
                 )
+            elif (
+                spec.extra_tensor_info is not None
+                and spec.extra_tensor_info.location == TensorDataLocation.EXTERNAL
+            ):
+                buffer_idx = self.program_state.external_constant_hash.get(hashed, -1)
             else:
                 buffer_idx = self.program_state.cached_spec_hash_values.get(hashed, -1)
 
             # Haven't seen this constant before.
             if buffer_idx == -1:
                 buffer_idx = self._save_new_const_tensor(
-                    spec, buffer_data, hashed, allocation_info
+                    spec, buffer_data, hashed, allocation_info, constant_tag
                 )
 
             if spec.const and spec.nbytes() != len(buffer_data):
@@ -1557,11 +1601,26 @@ def placeholder(
         https://pytorch.org/docs/stable/fx.html#torch.fx.Graph.placeholder
         """
         spec = self.node.meta["spec"]
+        constant_tag = self.node.meta.get("constant_tag", None)
         is_user_input = True
 
         if isinstance(target, str) and isinstance(spec, TensorSpec):
             fqn, is_mutable_buffer = self._find_fqn_for_placeholder(target, spec)
 
+            # If the placeholder has a constant_tag, it is external to the PTE file
+            # and requires a fqn and location=TensorDataLocation.EXTERNAL
+            if constant_tag is not None:
+                assert (
+                    fqn is not None
+                ), "constant tagged tensors require a fully qualified name"
+                if spec.extra_tensor_info is None:
+                    spec.extra_tensor_info = ExtraTensorInfo(
+                        fully_qualified_name=fqn, location=TensorDataLocation.EXTERNAL
+                    )
+                else:
+                    spec.extra_tensor_info.fully_qualified_name = fqn
+                    spec.extra_tensor_info.location = TensorDataLocation.EXTERNAL
+
             # From the fqn find the corresponding tensor
             real_tensor = None
             if fqn in self.exported_program.state_dict:
@@ -1599,7 +1658,7 @@ def placeholder(
             spec.const = not (is_user_input or is_mutable_buffer)
 
         evalue = (
-            self._tensor_spec_to_evalue(spec)
+            self._tensor_spec_to_evalue(spec, constant_tag)
             if isinstance(spec, TensorSpec)
             else self._constant_to_evalue(spec, None)
         )