Patch huggingface-pytorch-inference:2.6.0-transformers4.51.3-gpu (#5331)

* ['dlc_developer_config.toml'] Update

* ['dlc_developer_config.toml'] Update build training

* toml update:

* test py package allowlist

* add cve to data folder

* fix json

* rebuild
:

* revert toml

Author: Jyothirmaikottu

data/ignore_ids_safety_scan.json

@@ -1446,7 +1446,8 @@
                 "77744": "urllib3 is a user-friendly HTTP client library for Python. Prior to 2.5.0, it is possible to disable redirects for all requests by instantiating a PoolManager and specifying retries in a way that disable redirects. By default, requests and botocore users are not affected. An application attempting to mitigate SSRF or open redirect vulnerabilities by disabling redirects at the PoolManager level will remain vulnerable. This issue has been patched in version 2.5.0.",
                 "79077": "Affected versions of the h2 package are vulnerable to HTTP Request Smuggling due to improper validation of illegal characters in HTTP headers. The package allows CRLF characters to be injected into header names and values without proper sanitisation, which can cause request boundary manipulation when HTTP/2 requests are downgraded to HTTP/1.1 by downstream servers.",
                 "79595": "Affected versions of the transformers package are vulnerable to Regular Expression Denial of Service (ReDoS) due to inefficient regular expressions in the EnglishNormalizer.normalize_numbers() method",
-                "79596": "Affected versions of the transformers package are vulnerable to Regular Expression Denial of Service (ReDoS) due to inefficient regular expressions in the MarianTokenizer.remove_language_code() method"
+                "79596": "Affected versions of the transformers package are vulnerable to Regular Expression Denial of Service (ReDoS) due to inefficient regular expressions in the MarianTokenizer.remove_language_code() method",
+                "79855": "Affected versions of the transformers package are vulnerable to Regular Expression Denial of Service (ReDoS) due to unbounded evaluation of user-supplied regular expressions in the AdamWeightDecay._do_use_weight_decay method. The TensorFlow optimizer’s _do_use_weight_decay iterates over include_in_weight_decay and exclude_from_weight_decay lists and calls re.search on each pattern against parameter names, enabling catastrophic backtracking on crafted inputs. An attacker who can control these lists can provide pathological patterns that saturate the CPU and cause processes using transformers to hang, resulting in a Denial of Service."
             }
         },
         "inference-neuron": {