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t2i_dtm_xl/toy_dataset/dataset.tar.gz

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+version https://git-lfs.github.com/spec/v1
+oid sha256:4938a18061bc7161e7dfea3e93923d2cf54057e091a1749688b3f1d6a31591ef
+size 2562182182

t2i_dtm_xl/toy_dataset/get_sampler.py

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+import math
+import json
+
+
+with open('bucket_categorization.json', 'r') as fp:
+    bucket_data = json.load(fp)
+
+
+print(len(bucket_data))
+base_batch_size = 16
+base_context_length = 1024 * 1024
+
+all_data = 0
+sampler_meta = []
+for bucket, indices in bucket_data.items():
+    resolution = bucket.split('x')
+    height, width = int(resolution[0]), int(resolution[1])  
+    batch_size = round(base_batch_size*base_context_length/(height*width))
+    batch_size = min(batch_size, 128)
+    num_batch = round(len(indices) / batch_size)
+    for i in range(num_batch):
+        current_indices = indices[i*batch_size: (i+1)*batch_size]
+        if len(current_indices) == batch_size:
+            all_data += batch_size
+            sampler_meta.append(current_indices)
+    
+print(all_data)
+print(len(sampler_meta))
+with open('bucket_sampler.json', 'w') as fp:
+    json.dump(sampler_meta, fp, indent=4)
+

t2i_dtm_xl/toy_dataset/unzip.sh

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+tar -xzvf dataset.tar.gz