Create modeling_simple_classifier

modeling_simple_classifier

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+# modeling_simple_classifier.py
+import torch
+import torch.nn as nn
+import torch.nn.functional as F
+from transformers import PreTrainedModel
+
+
+class SimpleClassifierConfig:
+    model_type = "simple_classifier"
+
+
+class SimpleClassifier(PreTrainedModel):
+    config_class = SimpleClassifierConfig
+
+    def __init__(self, config):
+        super().__init__(config)
+        self.linear1 = nn.Linear(config.input_dim, 256)
+        self.ln1 = nn.LayerNorm(256)
+        self.dropout = nn.Dropout(config.p_dropout)
+        self.linear2 = nn.Linear(256, 128)
+        self.ln2 = nn.LayerNorm(128)
+        self.linear_out = nn.Linear(128, config.num_classes)
+        self.post_init()
+
+    def forward(self, x):
+        x = F.gelu(self.ln1(self.linear1(x)))
+        x = self.dropout(x)
+        x = F.gelu(self.ln2(self.linear2(x)))
+        x = self.dropout(x)
+        return self.linear_out(x)