[executorch][serialization] Serialize PTD files.

exir/_serialize/TARGETS

@@ -33,6 +33,7 @@ runtime.python_library(
         "_dataclass.py",
         "_flatbuffer.py",
         "_program.py",
+        "_serialize.py",
         "data_serializer.py",
         "padding.py",
     ],

exir/_serialize/_serialize.py

@@ -0,0 +1,91 @@
+# Copyright (c) Meta Platforms, Inc. and affiliates.
+# All rights reserved.
+#
+# This source code is licensed under the BSD-style license found in the
+# LICENSE file in the root directory of this source tree.
+
+# pyre-strict
+
+
+from typing import Dict, Tuple
+
+from executorch.exir._serialize import _serialize_pte_binary
+
+from executorch.exir._serialize._cord import Cord
+from executorch.exir._serialize.data_serializer import (
+    DataPayload,
+    DataSerializer,
+    TensorEntry,
+    TensorLayout,
+)
+
+from executorch.exir.capture._config import ExecutorchBackendConfig
+from executorch.exir.emit import EmitterOutput
+from executorch.exir.schema import Tensor, TensorDataLocation
+
+
+def serialize_for_executorch(
+    emitter_output: EmitterOutput,
+    config: ExecutorchBackendConfig,
+    data_serializer: DataSerializer,
+) -> Tuple[Cord, Dict[str, Cord]]:
+    """Serialize the output from Emitter into ExecuTorch artifacts; PTE and PTD files."""
+
+    # Serialize PTE file.
+    pte: Cord = _serialize_pte_binary(
+        program=emitter_output.program,
+        mutable_data=emitter_output.mutable_data,
+        extract_delegate_segments=config.extract_delegate_segments,
+        segment_alignment=config.segment_alignment,
+        constant_tensor_alignment=config.constant_tensor_alignment,
+        delegate_alignment=config.delegate_alignment,
+    )
+
+    # Serialize PTD files.
+    ptd_files: Dict[str, Cord] = {}
+
+    # Find all external tensors and organize into {fqn: TensorLayout}.
+    fqn_to_tensor_layout: Dict[str, TensorLayout] = {}
+    for plan in emitter_output.program.execution_plan:
+        for evalue in plan.values:
+            if isinstance(evalue.val, Tensor):
+                tensor = evalue.val
+                if (
+                    tensor.extra_tensor_info is not None
+                    and tensor.extra_tensor_info.fully_qualified_name is not None
+                    and tensor.extra_tensor_info.location is TensorDataLocation.EXTERNAL
+                ):
+                    fqn_to_tensor_layout[
+                        tensor.extra_tensor_info.fully_qualified_name
+                    ] = TensorLayout(tensor.scalar_type, tensor.sizes, tensor.dim_order)
+
+    if len(fqn_to_tensor_layout) > 0:
+        # emitter_output.external_constant_map contains the mapping from
+        # {file: {fqn: index into external_constant_buffer}}
+        # Contains the locations of the tensor buffers, and must be non-empty
+        # if there are external tensors to serialize.
+        assert emitter_output.external_constant_map is not None
+        for (
+            filename,
+            fqn_to_index,
+        ) in (
+            # pyre-ignore Undefined attribute [16]: Optional type has no attribute `items`.
+            emitter_output.external_constant_map.items()
+        ):
+            # Create a TensorEntry for each external tensor.
+            fqn_to_tensor_entry: Dict[str, TensorEntry] = {}
+            for fqn, index in fqn_to_index.items():
+                assert fqn in fqn_to_tensor_layout
+                fqn_to_tensor_entry[fqn] = TensorEntry(
+                    buffer_index=index,
+                    layout=fqn_to_tensor_layout[fqn],
+                )
+
+            ptd_files[filename] = data_serializer.serialize(
+                DataPayload(
+                    buffers=emitter_output.external_constant_buffer,
+                    fqn_to_tensor=fqn_to_tensor_entry,
+                )
+            )
+
+    return pte, ptd_files

exir/program/TARGETS

@@ -44,6 +44,7 @@ python_library(
         "//executorch/exir/passes:spec_prop_pass",
         "//executorch/exir/passes:weights_to_outputs_pass",
         "//executorch/exir/verification:verifier",
+        "//executorch/extension/flat_tensor/serialize:serialize",
     ] +  (["//executorch/exir/program/fb:logger"] if not runtime.is_oss else [])
 )
 

exir/program/_program.py

@@ -9,12 +9,14 @@
 import copy
 import io
 import logging
+import os
 from typing import Any, Dict, List, Optional, Sequence, Set, TextIO, Tuple, Union
 
 import torch
 import torch._export
-from executorch.exir._serialize import _serialize_pte_binary
 from executorch.exir._serialize._cord import Cord
+from executorch.exir._serialize._serialize import serialize_for_executorch
+from executorch.exir._serialize.data_serializer import DataSerializer
 from executorch.exir._warnings import experimental
 from executorch.exir.backend.backend_api import to_backend
 from executorch.exir.backend.partitioner import Partitioner
@@ -59,6 +61,7 @@
     EXIREdgeDialectVerifier,
     get_aten_verifier,
 )
+from executorch.extension.flat_tensor.serialize.serialize import FlatTensorSerializer
 from torch._export.passes import ReplaceViewOpsWithViewCopyOpsPass
 from torch.export import ExportedProgram
 from torch.export._remove_auto_functionalized_pass import (
@@ -497,23 +500,31 @@ def __init__(
             )
         self.exported_program = exir_exported_program.exported_program
         self._pte_data: Optional[Cord] = None
+        self._tensor_data: Optional[Dict[str, Cord]] = None
         self._buffer: Optional[bytes] = None
         self._emitter_output: Optional[EmitterOutput] = None
         self._emit_stacktrace: bool = emit_stacktrace
         self._extract_delegate_segments: bool = extract_delegate_segments
         self._segment_alignment: int = segment_alignment
         self._constant_tensor_alignment: Optional[int] = constant_tensor_alignment
         self._delegate_alignment: Optional[int] = delegate_alignment
+        self._data_serializer: DataSerializer = FlatTensorSerializer()
+
+    def _get_emitter_output(self) -> EmitterOutput:
+        if self._emitter_output is None:
+            self._emitter_output = emit_program(
+                self.exported_program, self._emit_stacktrace
+            )
+        return self._emitter_output
 
     def _get_pte_data(self) -> Cord:
         if self._pte_data is None:
-            self._pte_data = _serialize_pte_binary(
-                program=self.program,
-                extract_delegate_segments=self._extract_delegate_segments,
-                segment_alignment=self._segment_alignment,
-                constant_tensor_alignment=self._constant_tensor_alignment,
-                delegate_alignment=self._delegate_alignment,
+            self._pte_data, self._tensor_data = serialize_for_executorch(
+                self._get_emitter_output(),
+                ExecutorchBackendConfig(),
+                self._data_serializer,
             )
+        assert self._pte_data is not None
         return self._pte_data
 
     @property
@@ -532,11 +543,7 @@ def buffer(self) -> bytes:
 
     @property
     def program(self) -> Program:
-        if self._emitter_output is None:
-            self._emitter_output = emit_program(
-                self.exported_program, self._emit_stacktrace
-            )
-        return self._emitter_output.program
+        return self._get_emitter_output().program
 
     @property
     def debug_handle_map(self) -> Dict[int, Union[int, List[int]]]:
@@ -571,6 +578,17 @@ def write_to_file(self, open_file: io.BufferedIOBase) -> None:
         """
         self._get_pte_data().write_to_file(open_file)
 
+    def write_tensor_data_to_file(self, outdir) -> None:
+        """
+        Writes the serialized ExecuTorch data files to the directory at `outdir`.
+        """
+        assert self._tensor_data is not None
+        # pyre-ignore[16]: `Optional` has no attribute `items`.
+        for filename, cord in self._tensor_data.items():
+            with open(os.path.join(outdir, f"{filename}.ptd"), "wb") as f:
+                logging.info(f"Writing data file to {filename}.ptd")
+                cord.write_to_file(f)
+
 
 def _get_aten_to_edge_passes(config: EdgeCompileConfig):
     # TODO: the last two passes for aten_to_edge need to be eliminated_dead_code -> debug_handle_generator. After enable
@@ -1453,13 +1471,9 @@ def __init__(
         )
 
         # Serialize emitter output, ready to be written to a file.
-        self._pte_data: Cord = _serialize_pte_binary(
-            program=self._emitter_output.program,
-            mutable_data=self._emitter_output.mutable_data,
-            extract_delegate_segments=backend_config.extract_delegate_segments,
-            segment_alignment=backend_config.segment_alignment,
-            constant_tensor_alignment=backend_config.constant_tensor_alignment,
-            delegate_alignment=backend_config.delegate_alignment,
+        self._data_serializer = FlatTensorSerializer()
+        self._pte_data, self._tensor_data = serialize_for_executorch(
+            self._emitter_output, ExecutorchBackendConfig(), self._data_serializer
         )
         self._buffer: Optional[bytes] = None
 
@@ -1542,6 +1556,16 @@ def write_to_file(self, open_file: io.BufferedIOBase) -> None:
         """
         self._pte_data.write_to_file(open_file)
 
+    def write_tensor_data_to_file(self, outdir) -> None:
+        """
+        Writes the serialized ExecuTorch data files to the directory at `outdir`.
+        """
+        assert self._tensor_data is not None
+        for filename, cord in self._tensor_data.items():
+            with open(os.path.join(outdir, f"{filename}.ptd"), "wb") as f:
+                logging.info(f"Writing data file to {filename}")
+                cord.write_to_file(f)
+
     def save(self, path: str) -> None:
         """
         Saves the serialized ExecuTorch binary to the file at `path`.

extension/export_util/utils.py

@@ -135,9 +135,12 @@ def save_pte_program(
         filename = os.path.join(output_dir, f"{model_name}.pte")
 
     try:
+        # Write program to file.
         with open(filename, "wb") as file:
             prog.write_to_file(file)
             logging.info(f"Saved exported program to {filename}")
+        # Write data to file/s.
+        prog.write_tensor_data_to_file(outdir=output_dir)
     except Exception as e:
         logging.error(f"Error while saving to {filename}: {e}")