chore: fix const import

instill-ai · Nov 14, 2023 · 0faa5ab · 0faa5ab
1 parent 5127b2b
commit 0faa5ab
Show file tree

Hide file tree

Showing 3 changed files with 21 additions and 12 deletions.
diff --git a/instill/helpers/__init__.py b/instill/helpers/__init__.py
diff --git a/instill/helpers/const.py b/instill/helpers/const.py
@@ -1,5 +1,5 @@
 from enum import Enum
-from typing import Dict
+from typing import Any, Dict
 
 
 class DataType(Enum):
@@ -24,5 +24,5 @@ class TextGenerationInput:
     top_k = 1
     temperature = 0.8
     random_seed = 0
-    stop_words = ""
+    stop_words: Any = ""
     extra_params: Dict[str, str] = {}
diff --git a/instill/helpers/ray_io.py b/instill/helpers/ray_io.py
@@ -3,7 +3,8 @@
 from typing import List
 
 import numpy as np
-from const import TextGenerationInput
+
+from instill.helpers.const import TextGenerationInput
 
 
 def serialize_byte_tensor(input_tensor):
@@ -77,7 +78,7 @@ def deserialize_bytes_tensor(encoded_tensor):
     while offset < len(val_buf):
         l = struct.unpack_from("<I", val_buf, offset)[0]
         offset += 4
-        sb = struct.unpack_from("<{}s".format(l), val_buf, offset)[0]
+        sb = struct.unpack_from(f"<{l}s", val_buf, offset)[0]
         offset += l
         strs.append(sb)
     return np.array(strs, dtype=bytes)
@@ -95,29 +96,33 @@ def parse_task_text_generation_input(request) -> TextGenerationInput:
                 input_tensor = deserialize_bytes_tensor(b_input_tensor)
                 text_generation_input.prompt = str(input_tensor[0].decode("utf-8"))
                 print(
-                    f"[DEBUG] input `prompt` type({type(text_generation_input.prompt)}): {text_generation_input.prompt}"
+                    f"[DEBUG] input `prompt` type\
+                        ({type(text_generation_input.prompt)}): {text_generation_input.prompt}"
                 )
 
             if input_name == "max_new_tokens":
                 text_generation_inputmax_new_tokens = int.from_bytes(
                     b_input_tensor, "little"
                 )
                 print(
-                    f"[DEBUG] input `max_new_tokens` type({type(text_generation_inputmax_new_tokens)}): {text_generation_inputmax_new_tokens}"
+                    f"[DEBUG] input `max_new_tokens` type\
+                        ({type(text_generation_inputmax_new_tokens)}): {text_generation_inputmax_new_tokens}"
                 )
 
             if input_name == "top_k":
                 text_generation_input.top_k = int.from_bytes(b_input_tensor, "little")
                 print(
-                    f"[DEBUG] input `top_k` type({type(text_generation_input.top_k)}): {text_generation_input.top_k}"
+                    f"[DEBUG] input `top_k` type\
+                        ({type(text_generation_input.top_k)}): {text_generation_input.top_k}"
                 )
 
             if input_name == "temperature":
                 text_generation_input.temperature = struct.unpack("f", b_input_tensor)[
                     0
                 ]
                 print(
-                    f"[DEBUG] input `temperature` type({type(text_generation_input.temperature)}): {text_generation_input.temperature}"
+                    f"[DEBUG] input `temperature` type\
+                        ({type(text_generation_input.temperature)}): {text_generation_input.temperature}"
                 )
                 temperature: float = round(temperature, 2)
 
@@ -126,14 +131,16 @@ def parse_task_text_generation_input(request) -> TextGenerationInput:
                     b_input_tensor, "little"
                 )
                 print(
-                    f"[DEBUG] input `random_seed` type({type(text_generation_input.random_seed)}): {text_generation_input.random_seed}"
+                    f"[DEBUG] input `random_seed` type\
+                        ({type(text_generation_input.random_seed)}): {text_generation_input.random_seed}"
                 )
 
             if input_name == "stop_words":
                 input_tensor = deserialize_bytes_tensor(b_input_tensor)
                 text_generation_input.stop_words = input_tensor[0]
                 print(
-                    f"[DEBUG] input `stop_words` type({type(text_generation_input.stop_words)}): {text_generation_input.stop_words}"
+                    f"[DEBUG] input `stop_words` type\
+                        ({type(text_generation_input.stop_words)}): {text_generation_input.stop_words}"
                 )
                 if len(text_generation_input.stop_words) == 0:
                     text_generation_input.stop_words = None
@@ -147,14 +154,16 @@ def parse_task_text_generation_input(request) -> TextGenerationInput:
                         str(text_generation_input.stop_words[0])
                     ]
                 print(
-                    f"[DEBUG] parsed input `stop_words` type({type(text_generation_input.stop_words)}): {text_generation_input.stop_words}"
+                    f"[DEBUG] parsed input `stop_words` type\
+                        ({type(text_generation_input.stop_words)}): {text_generation_input.stop_words}"
                 )
 
             if input_name == "extra_params":
                 input_tensor = deserialize_bytes_tensor(b_input_tensor)
                 extra_params_str = str(input_tensor[0].decode("utf-8"))
                 print(
-                    f"[DEBUG] input `extra_params` type({type(extra_params_str)}): {extra_params_str}"
+                    f"[DEBUG] input `extra_params` type\
+                        ({type(extra_params_str)}): {extra_params_str}"
                 )
 
                 try: