chore: import upstream snapshot with attribution

2026-07-13 13:39:21 +08:00
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+#           🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨
+#               This file was automatically generated from <path_to_diff_file.py>.
+#         Do NOT edit this file manually as any edits will be overwritten by the generation of
+#         the file from the diff. If any change should be done, please apply the change to the
+#                                    diff.py file directly.
+#           🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨
+# coding=utf-8
+# Copyright 2024 Google Inc. HuggingFace Inc. team. 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.
+
+
+from transformers.models.gemma2.configuration_gemma2 import Gemma2Config
+
+class CostWiseGemmaConfig(Gemma2Config):
+    r"""
+    This is the configuration class to store the configuration of a [`GemmaModel`]. It is used to instantiate an Gemma
+    model according to the specified arguments, defining the model architecture. Instantiating a configuration with the
+    defaults will yield a similar configuration to that of the Gemma-7B.
+    e.g. [google/gemma-7b](https://huggingface.co/google/gemma-7b)
+    Configuration objects inherit from [`PretrainedConfig`] and can be used to control the model outputs. Read the
+    documentation from [`PretrainedConfig`] for more information.
+    Args:
+        start_layer (`int`, *optional*, defaults to 28):
+            The start layer to output score.
+        layer_sep (`int`, *optional*, defaults to 28):
+            The sep layer from the start layer to output score.
+        layer_wise (`bool`, *optional*, defaults to `False`):
+            Whether or not the model should be layerwise.
+    ```python
+    >>> from transformers import Gemma2Model, Gemma2Config
+    >>> # Initializing a Gemma2 gemma2-9b style configuration
+    >>> configuration = Gemma2Config()
+    >>> # Initializing a model from the gemma2-9b style configuration
+    >>> model = Gemma2Model(configuration)
+    >>> # Accessing the model configuration
+    >>> configuration = model.config
+    ```"""
+
+    model_type = "cost_wise_gemma"
+    keys_to_ignore_at_inference = ["past_key_values"]
+
+    def __init__(
+            self,
+            start_layer: int = 28,
+            layer_sep: int = 28,
+            layer_wise: bool = False,
+            **kwargs,
+    ):
+        self.start_layer = start_layer
+        self.layer_sep = layer_sep
+        self.layer_wise = layer_wise
+
+        super().__init__(
+            **kwargs,
+        )