From 6a9eef2c2c1a7f8ed97bebb522454336f9c9a7c5 Mon Sep 17 00:00:00 2001
From: yzhangcs <yzhang.cs@outlook.com>
Date: Wed, 17 May 2023 22:01:56 +0800
Subject: [PATCH] Support back and forth conversion of sents/bytes

---
 supar/utils/transform.py | 34 ++++++++++++++++++++++++++++++----
 1 file changed, 30 insertions(+), 4 deletions(-)

diff --git a/supar/utils/transform.py b/supar/utils/transform.py
index 7d2b92e8..1db865ff 100644
--- a/supar/utils/transform.py
+++ b/supar/utils/transform.py
@@ -2,12 +2,15 @@
 
 from __future__ import annotations
 
-from typing import Any, Iterable, Optional, Tuple
+import os
+import pickle
+import struct
+from io import BytesIO
+from typing import Any, Iterable, Optional
 
 import torch
 from torch.distributions.utils import lazy_property
 
-from supar.utils.fn import debinarize
 from supar.utils.logging import get_logger, progress_bar
 
 logger = get_logger(__name__)
@@ -212,6 +215,29 @@ def numericalize(self, fields):
         self.pad_index = fields[0].pad_index
         return self
 
+    def tobytes(self) -> bytes:
+        bufs, fields = [], {}
+        for name, value in self.fields.items():
+            if isinstance(value, torch.Tensor):
+                fields[name] = value
+                buf, dtype = value.numpy().tobytes(), value.dtype
+                self.fields[name] = (len(buf), dtype)
+                bufs.append(buf)
+        buf, sentence = b''.join(bufs), pickle.dumps(self)
+        for name, value in fields.items():
+            self.fields[name] = value
+        return buf + sentence + struct.pack('LL', len(buf), len(sentence))
+
     @classmethod
-    def from_cache(cls, fbin: str, pos: Tuple[int, int]) -> Sentence:
-        return debinarize(fbin, pos)
+    def frombuffer(cls, buf: bytes) -> Sentence:
+        mm = BytesIO(buf)
+        mm.seek(-len(struct.pack('LL', 0, 0)), os.SEEK_END)
+        offset, length = struct.unpack('LL', mm.read())
+        mm.seek(offset)
+        sentence = pickle.loads(mm.read(length))
+        mm.seek(0)
+        for name, value in sentence.fields.items():
+            if isinstance(value, tuple) and isinstance(value[1], torch.dtype):
+                length, dtype = value
+                sentence.fields[name] = torch.frombuffer(bytearray(mm.read(length)), dtype=dtype)
+        return sentence