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configuration_pangu_moe.py

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+# coding=utf-8
+# Copyright (c) Huawei Technologies Co., Ltd. 2025. All rights reserved.
+# Copyright 2024 The Qwen team, Alibaba Group and the 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.
+""" PanguProMoE model configuration"""
+
+
+from transformers.configuration_utils import PretrainedConfig
+from transformers.utils import logging
+
+
+logger = logging.get_logger(__name__)
+
+
+class PanguProMoEConfig(PretrainedConfig):
+   
+    model_type = "PanguProMoE"
+    _auto_class = "AutoConfig"
+
+    def __init__(
+        self,
+        vocab_size=153376,
+        hidden_size=4608,
+        intermediate_size=10240,
+        num_hidden_layers=50,
+        num_attention_heads=64,
+        num_key_value_heads=4,
+        mlp_only_layers=[0,1,2,3],
+        hidden_act="silu",
+        max_position_embeddings=8192,
+        initializer_range=0.02,
+        rms_norm_eps=1e-5,
+        use_cache=True,
+        tie_word_embeddings=False,
+        rope_theta=100000,
+        moe_intermediate_size=1280,
+        shared_expert_intermediate_size=2560,
+        num_experts_per_tok=8,
+        num_experts=80,
+        norm_topk_prob=True,
+        router_enable_expert_bias=True,
+        output_router_logits=False,
+        routed_scaling_factor=2.5,
+        qk_nope_dim = 128,
+        qk_rope_dim = 64,
+        v_channels = 128,
+        sandwich_norm=True,
+        param_sink_number = 128,
+        param_sink_with_value=True,
+        **kwargs,
+    ):
+        self.vocab_size = vocab_size
+        self.max_position_embeddings = max_position_embeddings
+        self.hidden_size = hidden_size
+        self.num_hidden_layers = num_hidden_layers
+        self.num_attention_heads = num_attention_heads
+        self.num_key_value_heads = num_key_value_heads
+        self.hidden_act = hidden_act
+        self.initializer_range = initializer_range
+        self.rms_norm_eps = rms_norm_eps
+        self.use_cache = use_cache
+        self.rope_theta = rope_theta
+        self.mlp_only_layers = mlp_only_layers
+        self.intermediate_size = intermediate_size
+
+        # MoE arguments
+        self.moe_intermediate_size = moe_intermediate_size
+        self.shared_expert_intermediate_size = shared_expert_intermediate_size
+        self.num_experts_per_tok = num_experts_per_tok
+        self.num_experts = num_experts
+        self.norm_topk_prob = norm_topk_prob
+        self.output_router_logits = output_router_logits
+        self.router_enable_expert_bias = router_enable_expert_bias
+        self.routed_scaling_factor = routed_scaling_factor
+        self.qk_nope_dim = qk_nope_dim
+        self.qk_rope_dim = qk_rope_dim
+        self.v_channels = v_channels
+        self.sandwich_norm = sandwich_norm
+        self.param_sink_number = param_sink_number
+        self.param_sink_with_value = param_sink_with_value
+
+        super().__init__(
+            tie_word_embeddings=tie_word_embeddings,
+            **kwargs,
+        )