feat(compression): add DECODE operator types and metadata (#3589)

Add decode module with DecodeType constants and DecodeCommonMetadata,
per the TFLM DECODE Operator Design document.

BUG=part of #3256

Author: rkuester

tensorflow/lite/micro/compression/BUILD

@@ -247,6 +247,20 @@ tflm_py_test(
     ],
 )
 
+tflm_py_library(
+    name = "decode",
+    srcs = ["decode.py"],
+)
+
+tflm_py_test(
+    name = "decode_test",
+    size = "small",
+    srcs = ["decode_test.py"],
+    deps = [
+        ":decode",
+    ],
+)
+
 tflm_py_binary(
     name = "view",
     srcs = [

tensorflow/lite/micro/compression/decode.py

@@ -0,0 +1,238 @@
+# Copyright 2026 The TensorFlow Authors. All Rights Reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+"""DECODE compression module."""
+
+# Implements the DECODE operator compression scheme described in the
+# "TFLM DECODE Operator Design" document, revised May 20, 2025.
+#
+# The DECODE operator transforms an encoded tensor, alongside a paired
+# ancillary data tensor, into a tensor ready for use as input to any
+# operator. For example, an encoded tensor might contain compressed
+# data, while the paired ancillary data tensor holds the information
+# necessary for decompression. The DECODE operator's output is a fully
+# decompressed tensor.
+#
+# DECODE operators are inserted into the TfLite model subgraph
+# immediately before each operation that uses a decodable tensor as
+# input.
+#
+# Ancillary Data Tensor
+#
+# The ancillary data tensor contains the information necessary for
+# decoding. It begins with a 16-byte DECODE Common Metadata (DCM)
+# header, followed by decode-type-specific ancillary data.
+#
+# DECODE Common Metadata (DCM)
+#
+# Byte 0: Decode type
+#   0-127:   TFLM-supported decode operations (see below)
+#   128-255: Custom operations requiring application-registered
+#            handlers
+#
+#   Supported decode types:
+#
+#   0: LUT decompression
+#      All TFLM tensor types supported in reference and optimized
+#      code.
+#
+#   1: Huffman decompression using Xtensa format decode tables
+#      INT8 and INT16 tensor types only, in reference and optimized
+#      code.
+#
+#   2: Pruning decompression
+#      All TFLM tensor types supported in reference and optimized
+#      code.
+#
+#   3-127: Reserved
+#
+#   128-255: Custom decode types
+#      Requires user-supplied encoding module and decoding ancillary
+#      data.
+#
+# Byte 1: DCM version (currently 1)
+#
+# Bytes 2-3: Reserved
+#
+# Bytes 4-15: User-defined
+#   Used by TFLM decode types to avoid requiring additional alignment
+#   of metadata or ancillary data.
+#
+# The 16-byte DCM size ensures that subsequent metadata and ancillary
+# data are 128-bit aligned, which is required for some optimized
+# decoding operations such as Xtensa LUT decompression.
+#
+# For TFLM decode types, ancillary data starts immediately after the
+# DCM. For custom decode types, the location is determined by
+# user-defined metadata.
+
+from dataclasses import dataclass
+from typing import Protocol
+
+
+class DecodeType:
+  """Decode operation type (0-255).
+
+  Use predefined constants for built-in types or DecodeType.custom()
+  for custom types:
+      DecodeType.LUT        # 0
+      DecodeType.HUFFMAN    # 1
+      DecodeType.PRUNING    # 2
+      DecodeType.custom(200)  # Custom type 128-255
+  """
+
+  # Built-in decode types (class variables set after class definition)
+  LUT: 'DecodeType'
+  HUFFMAN: 'DecodeType'
+  PRUNING: 'DecodeType'
+
+  def __init__(self, code: int, name: str = None):
+    """Initialize DecodeType.
+
+    Args:
+        code: Integer code 0-255
+        name: Optional name for the type. If not provided:
+              - Codes 0-127: Named "TYPE_{code}"
+              - Codes 128-255: Named "CUSTOM_{code}"
+    """
+    if not 0 <= code <= 255:
+      raise ValueError(f"Decode type must be 0-255, got {code}")
+    self.code = code
+
+    # Auto-generate name if not provided
+    if name is None:
+      self.name = f"CUSTOM_{code}" if code >= 128 else f"TYPE_{code}"
+    else:
+      self.name = name
+
+    self._is_custom = code >= 128
+
+  @property
+  def is_custom(self) -> bool:
+    """True if this is a custom decode type (128-255)."""
+    return self._is_custom
+
+  @classmethod
+  def custom(cls, code: int) -> 'DecodeType':
+    """Create custom decode type (128-255).
+
+    Args:
+        code: Integer code 128-255
+
+    Returns:
+        DecodeType with name CUSTOM_{code}
+    """
+    if not 128 <= code <= 255:
+      raise ValueError(f"Custom decode type must be 128-255, got {code}")
+    return cls(code)
+
+  def __int__(self):
+    """Convert to integer for serialization."""
+    return self.code
+
+  def __eq__(self, other):
+    if isinstance(other, DecodeType):
+      return self.code == other.code
+    return self.code == other
+
+  def __repr__(self):
+    return f"DecodeType.{self.name}({self.code})"
+
+
+# Define built-in decode type constants
+DecodeType.LUT = DecodeType(0, "LUT")
+DecodeType.HUFFMAN = DecodeType(1, "HUFFMAN")
+DecodeType.PRUNING = DecodeType(2, "PRUNING")
+
+
+@dataclass
+class DecodeCommonMetadata:
+  """16-byte DECODE Common Metadata (DCM) header.
+
+  Attributes:
+    decode_type: Decode operation type. Use DecodeType constants or
+                 DecodeType.custom(code) for custom types.
+    version: DCM version (currently 1).
+    user_data: 12 bytes of user-defined data (bytes 4-15 of DCM). Used by TFLM
+               decode types to avoid requiring additional alignment of metadata
+               or ancillary data.
+  """
+  decode_type: DecodeType
+  version: int = 1
+  user_data: bytes = b'\x00' * 12
+
+  def to_bytes(self) -> bytes:
+    """Serialize DCM to 16-byte sequence."""
+    decode_code = int(self.decode_type)
+    if len(self.user_data) < 12:
+      # Pad with zeros if user_data is too short
+      user_data = self.user_data + b'\x00' * (12 - len(self.user_data))
+    else:
+      user_data = self.user_data[:12]
+
+    result = bytearray(16)
+    result[0] = decode_code
+    result[1] = self.version
+    # bytes 2-3 remain zero (reserved)
+    result[4:16] = user_data
+    return bytes(result)
+
+
+class AncillaryDataSerializer(Protocol):
+  """Protocol for objects that can serialize ancillary data."""
+
+  def to_bytes(self) -> bytes:
+    ...
+
+
+@dataclass
+class AncillaryDataTensor:
+  """Complete Ancillary Data Tensor (ADT): DCM + decode-type-specific data.
+
+  The ADT is stored as a buffer in the TFLite model. It begins with a 16-byte
+  DCM header, followed by decode-type-specific ancillary data.
+
+  Attributes:
+    dcm: The DECODE Common Metadata header.
+    ancillary_data: The decode-type-specific ancillary data, either as raw bytes
+                    or as an object implementing the AncillaryDataSerializer
+                    protocol. May be None if only the DCM is needed.
+  """
+  dcm: DecodeCommonMetadata
+  ancillary_data: AncillaryDataSerializer | bytes | None = None
+
+  def with_ancillary_data(
+      self, data: AncillaryDataSerializer | bytes) -> 'AncillaryDataTensor':
+    """Create new ADT with ancillary data added.
+
+    Args:
+      data: Ancillary data to add, either as raw bytes or as an object
+            implementing AncillaryDataSerializer.
+
+    Returns:
+      New AncillaryDataTensor with the specified ancillary data.
+    """
+    return AncillaryDataTensor(self.dcm, data)
+
+  def to_bytes(self) -> bytes:
+    """Serialize entire ADT to bytes.
+
+    Returns:
+      Byte sequence containing DCM followed by ancillary data (if present).
+    """
+    dcm_bytes = self.dcm.to_bytes()
+    if self.ancillary_data is None:
+      return dcm_bytes
+    if isinstance(self.ancillary_data, bytes):
+      return dcm_bytes + self.ancillary_data
+    return dcm_bytes + self.ancillary_data.to_bytes()