Delete .ipynb_checkpoints

.ipynb_checkpoints/config-checkpoint.json

@@ -1,23 +0,0 @@
-{
-  "architectures": [
-    "CSDModel"
-  ],
-  "attention_dropout": 0.0,
-  "content_projection_dim": 768,
-  "dropout": 0.0,
-  "hidden_act": "quick_gelu",
-  "hidden_size": 1024,
-  "image_size": 224,
-  "initializer_factor": 1.0,
-  "initializer_range": 0.02,
-  "intermediate_size": 4096,
-  "layer_norm_eps": 1e-05,
-  "num_attention_heads": 16,
-  "num_channels": 3,
-  "num_hidden_layers": 24,
-  "patch_size": 14,
-  "projection_dim": 768,
-  "style_projection_dim": 768,
-  "torch_dtype": "float32",
-  "transformers_version": "4.48.0"
-}

.ipynb_checkpoints/config-checkpoint.py

@@ -1,42 +0,0 @@
-from transformers import PretrainedConfig
-
-class CSDConfig(PretrainedConfig):
-    model_type = "CSDModel"
-    
-    def __init__(
-        self,
-        attention_dropout:float=0.0,
-        dropout:float=0.0,
-        hidden_act:str= "quick_gelu",
-        hidden_size:int= 1024,
-        image_size:int= 224,
-        initializer_factor:float= 1.0,
-        initializer_range:float=0.02,
-        intermediate_size:int=4096,
-        layer_norm_eps:float=1e-05,
-        num_attention_heads:int=16,
-        num_channels:int=3,
-        num_hidden_layers:int=24,
-        patch_size:int= 14,
-        projection_dim:int=768,
-        style_projection_dim:int=768,
-        content_projection_dim:int=768,
-        **kwargs,
-    ):   
-        super().__init__(**kwargs)
-        self.attention_dropout=attention_dropout
-        self.dropout=dropout
-        self.hidden_act=hidden_act
-        self.hidden_size=hidden_size
-        self.image_size=image_size
-        self.initializer_factor=initializer_factor
-        self.initializer_range=initializer_range
-        self.intermediate_size=intermediate_size
-        self.layer_norm_eps=layer_norm_eps
-        self.num_attention_heads=num_attention_heads
-        self.num_channels=num_channels
-        self.num_hidden_layers=num_hidden_layers
-        self.patch_size=patch_size
-        self.projection_dim=projection_dim
-        self.style_projection_dim=style_projection_dim
-        self.content_projection_dim=content_projection_dim

.ipynb_checkpoints/model-checkpoint.py

@@ -1,16 +0,0 @@
-import torch.nn as nn
-from .config import CSDConfig
-from transformers import PreTrainedModel, CLIPVisionModel
-
-class CSDModel(PreTrainedModel):
-    config_class = CSDConfig
-    def __init__(self, config: CSDConfig):
-        super().__init__(config)
-        self.backbone = CLIPVisionModel(config)
-        self.out_style = nn.Linear(config.hidden_size, config.style_projection_dim, bias=False)
-        self.out_content = nn.Linear(config.hidden_size, config.content_projection_dim, bias=False)
-
-    def forward(self, pixel_values):
-        features = self.backbone(pixel_values)
-        style_embeds = self.out_style(features)
-        content_embeds = self.out_content(features)