Create modeling_scgpt.py

modeling_scgpt.py

@@ -0,0 +1,30 @@
+from transformers import PreTrainedModel
+#from timm.models.resnet import BasicBlock, Bottleneck, ResNet
+from .configuration_scgpt import ScgptConfig
+
+
+#BLOCK_MAPPING = {"basic": BasicBlock, "bottleneck": Bottleneck}
+
+
+class ScgptModel(PreTrainedModel):
+    config_class = ScgptConfig
+
+    def __init__(self, config):
+        super().__init__(config)
+        #block_layer = BLOCK_MAPPING[config.block_type]
+        #self.model = ScgptModel(
+        #    block_layer,
+        #    config.layers,
+        #    num_classes=config.num_classes,
+        #    in_chans=config.input_channels,
+        #    cardinality=config.cardinality,
+        #    base_width=config.base_width,
+        #    stem_width=config.stem_width,
+        #    stem_type=config.stem_type,
+        #    avg_down=config.avg_down,
+        #)
+        self.model = None
+
+    def forward(self, tensor):
+        #return self.model.forward_features(tensor)
+        return None