Revert configuration_grok1.py removal; rename "num_experts" to "num_local_experts"

configuration_grok1.py

@@ -0,0 +1,62 @@
+from transformers.configuration_utils import PretrainedConfig
+
+
+class Grok1Config(PretrainedConfig):
+    model_type = "grok-1"
+    keys_to_ignore_at_inference = ["past_key_values"]
+
+    def __init__(
+        self,
+        vocab_size=32000,
+        hidden_size=4096,
+        intermediate_size=32768,
+        num_hidden_layers=32,
+        num_attention_heads=32,
+        num_key_value_heads=32,
+        attn_output_multiplier=1.0,
+        max_attn_value=1.0,
+        max_position_embeddings=4096,
+        embedding_multiplier_scale: float = 1.0,
+        output_multiplier_scale: float = 1.0,
+        rms_norm_eps=1e-5,
+        use_cache=True,
+        pad_token_id=None,
+        bos_token_id=1,
+        eos_token_id=2,
+        tie_word_embeddings=True,
+        num_experts_per_tok=2,
+        num_local_experts=8,
+        output_router_logits=False,
+        router_aux_loss_coef=0.001,
+        **kwargs
+    ):
+        self.vocab_size = vocab_size
+        self.attn_output_multiplier = attn_output_multiplier
+        self.max_attn_value = max_attn_value
+        self.max_position_embeddings = max_position_embeddings
+        self.embedding_multiplier_scale = embedding_multiplier_scale
+        self.output_multiplier_scale = output_multiplier_scale
+        self.hidden_size = hidden_size
+        self.intermediate_size = intermediate_size
+        self.num_hidden_layers = num_hidden_layers
+        self.num_attention_heads = num_attention_heads
+
+        # for backward compatibility
+        if num_key_value_heads is None:
+            num_key_value_heads = num_attention_heads
+
+        self.num_key_value_heads = num_key_value_heads
+        self.rms_norm_eps = rms_norm_eps
+        self.use_cache = use_cache
+
+        self.num_experts_per_tok = num_experts_per_tok
+        self.num_local_experts = num_local_experts
+        self.output_router_logits = output_router_logits
+        self.router_aux_loss_coef = router_aux_loss_coef
+        super().__init__(
+            pad_token_id=pad_token_id,
+            bos_token_id=bos_token_id,
+            eos_token_id=eos_token_id,
+            tie_word_embeddings=tie_word_embeddings,
+            **kwargs,
+        )