[executorch][serialization] Data serialization interface

Pull Request resolved: #7194

Introduce data serialization interface.
ghstack-source-id: 259211150
@exported-using-ghexport

Differential Revision: [D65947145](https://our.internmc.facebook.com/intern/diff/D65947145/)

Author: lucylq

exir/_serialize/data_serializer.py

@@ -0,0 +1,94 @@
+from abc import ABC, abstractmethod
+from dataclasses import dataclass
+from typing import Dict, List, Sequence
+
+from executorch.exir._serialize._cord import Cord
+
+from executorch.exir.schema import ScalarType
+
+
+@dataclass
+class TensorLayout:
+    """Tensor layout information for externally-serialized tensors.
+
+    Attributes:
+        scalar_type: type of the elements in the tensor.
+        sizes: size of each dim in the tensor.
+        dim_order: specifies the order the dimensions are laid out in memory,
+            from outer to inner.
+    """
+
+    scalar_type: ScalarType
+    sizes: List[int]
+    dim_order: List[int]
+
+
+@dataclass
+class TensorEntry:
+    """Represents a single tensor in `DataPayload`, specifying its location
+    and metadata.
+
+    Attributes:
+       buffer_index: The index inside `DataPayload.buffers` that this
+            TensorEntry refers to.
+       layout: Metadata about the tensor.
+    """
+
+    buffer_index: int
+    layout: TensorLayout
+
+
+@dataclass
+class DataPayload:
+    """Contains the data and metadata required for serialization. Having an
+    index-based arrangement instead of Dict[str, bytes] allows the caller to
+    deduplicate buffers and point multiple fully qualified names (FQNs) to the
+    same entry.
+
+    Attributes:
+        buffers: a sequence of tensor buffers.
+        fqn_to_buffer: a map from buffer name (fully qualified name) to TensorEntry.
+    """
+
+    buffers: Sequence[bytes]
+    fqn_to_data: Dict[str, TensorEntry]
+
+
+class DataSerializer(ABC):
+    """Serializes and deserializes FQN-tagged tensor data.
+
+    This base class enables serialization into different formats. See
+    executorch/extension/flat_tensor/ for an example.
+    """
+
+    @abstractmethod
+    def serialize(
+        self,
+        data: DataPayload,
+    ) -> Cord:
+        """
+        Serializes a list of tensors emitted by ExecuTorch into a binary blob.
+
+        Args:
+            serialization_info: the tensor buffers and tensor layout
+            information required for serialization.
+
+        Returns:
+            A binary blob that contains the serialized data.
+        """
+        raise NotImplementedError("serialize_data")
+
+    @abstractmethod
+    def deserialize(self, blob: Cord) -> DataPayload:
+        """
+        Deserializes a blob into a list of tensors. Reverses the effect of
+        serialize.
+
+        Args:
+            blob: A binary blob that contains the serialized data.
+
+        Returns:
+            DataPayload: tensor buffers and tensor layout information
+            deserialized from `blob`.
+        """
+        raise NotImplementedError("deserialize_data")