[CP] CP Lm head fp32 and temp_logprob to release/2.1 (#3766)

* [Feature] Add temp_scaled_logprobs and top_p_normalized_logprobs parameters for logits and logprobs post processing (#3552)

* [feature] Add temp_scaled_logprobs and top_p_normalized_logprobs parameters for logits and logprobs post processing

* infer engine support temp_scaled_logprobs and top_p_normalized_logprobs

* delete some code

* code check

* code check and add doc

* fix tokenizer.decoder(-1), return 'Invalid Token'

* add ci for temp_scaled and top_p logprobs

* check test

* check seq len time shape

* logprob clip inf

---------

Co-authored-by: sunlei1024 <sunlei5788@gmail.com>

* [Precision] Support lm_head layer running in float32 (#3597)

* support lm_head fp32 bf16 fp16

* support lm_head fp32 bf16 fp16

* add doc and check code

* lm_head_fp32 specify lm_head as fp32

* code check

* check doc

* code check

---------

Co-authored-by: sunlei1024 <sunlei5788@gmail.com>

fastdeploy/model_executor/models/utils.py

@@ -23,6 +23,7 @@ import os
 import random
 import re
 import struct
+from contextlib import contextmanager
 from functools import partial
 from typing import Any, NamedTuple, Optional, Union
 
@@ -533,3 +534,15 @@ def parser_quant_type(quant_type):
             quant_type_list.append(default_type)
 
         return quant_type_list[0], quant_type_list[1], quant_type_list[2]
+
+
+@contextmanager
+def temporary_dtype(dtype: str):
+    """Temporarily set Paddle default dtype"""
+    orig_dtype = paddle.get_default_dtype()
+    try:
+        if dtype is not None and dtype == "float32":
+            paddle.set_default_dtype(dtype)
+        yield
+    finally:
+        paddle.set_default_dtype(orig_dtype)