import gradio as gr
import os
from torch import nn
import torchvision

def create_EffNetB2_model(num_classes:int=3, 
                                  seed:int = 42):
    """

    """

    weights = torchvision.models.EfficientNet_B2_Weights.DEFAULT
    transform = weights.transforms()

    model = torchvision.models.efficientnet_b2(weights=weights)

    for parm in model.parameters():
        parm.requires_grad = False
    
    # set_seeds(seed)

    model.classifier = nn.Sequential(nn.Dropout(p=0.2, inplace=True), 
                                    nn.Linear(in_features=1408, 
                                            out_features=num_classes, 
                                            bias=True
                                            ))

    return model, transform