add torchray example

examples/TorchRay_MMBT_example.py

+from mmxai.interpretability.classification.torchray.extremal_perturbation.multimodal_extremal_perturbation import multi_extremal_perturbation, image2tensor
+import torch
+from PIL import Image
+from mmf.models.mmbt import MMBT
+
+def main():
+    image_path = input("enter your image path : ")
+    text = input("enter your text : ")
+
+    model = MMBT.from_pretrained("mmbt.hateful_memes.images")
+    model.to(torch.device("cuda:0" if torch.cuda.is_available() else "cpu"))
+    image_tensor = image2tensor(image_path)
+    mask_, hist_, output_tensor, txt_summary, text_explaination = multi_extremal_perturbation(
+        model,
+        image_tensor,
+        image_path,
+        text,
+        0,  # 0 non hateful 1 hateful
+        max_iter=50,
+        areas=[0.12],
+    )
+    return output_tensor, txt_summary, text_explaination
+if __name__ == "__main__":
+    main()