upload coco summary script

run_summarization_coco.py

@@ -37,6 +37,7 @@ import nltk  # Here to have a nice missing dependency error message early on
 import numpy as np
 from datasets import Dataset, load_dataset, load_metric
 from tqdm import tqdm
+from PIL import Image
 
 import jax
 import jax.numpy as jnp
@@ -418,19 +419,24 @@ def main():
 
     # Setting padding="max_length" as we need fixed length inputs for jitted functions
     def preprocess_function(examples):
-    
+
         _pixel_values = []
-        for y in examples[image_file_column]:
+        _captions = []
+        for y, z in zip(examples[image_file_column], examples[caption_column]):
             with Image.open(y) as image:
-                encoder_inputs = feature_extractor(images=image, return_tensors="np")
+                try:
+                    encoder_inputs = feature_extractor(images=image, return_tensors="np")
+                except:
+                    continue
                 x = encoder_inputs.pixel_values
                 _pixel_values.append(x)
+                _captions.append(z + ' ' + tokenizer.eos_token)
         pixel_values = np.concatenate(_pixel_values)
 
-        targets = examples[caption_column]
+        targets = _captions
 
         # Add eos_token!!
-        targets = [x.lower() + ' ' + tokenizer.eos_token for x in targets]
+        #targets = [x + ' ' + tokenizer.eos_token for x in targets]
 
         model_inputs = {}
         model_inputs['pixel_values'] = pixel_values