# TypeError: Couldn't cast array of type int64 while mapping the dataset **URL:** \ **Category:** 🤗Datasets\ **Created:** [August 26, 2022, 2:26pm UTC](https://discuss.huggingface.co/t/typeerror-couldnt-cast-array-of-type-int64-while-mapping-the-dataset/22167 "2022-08-26T14:26:07Z")\ **Posts on this page:** 7\ **Page:** 1
**Author:** ![Laxmi9](https://avatars.discourse-cdn.com/v4/letter/l/0ea827/32.png) [@Laxmi9](https://discuss.huggingface.co/u/Laxmi9)\ **Post date:** [August 26, 2022, 2:26pm UTC](https://discuss.huggingface.co/t/typeerror-couldnt-cast-array-of-type-int64-while-mapping-the-dataset/22167/1 "2022-08-26T14:26:07Z")
Hai, I am trying to finetune LayoutLMV2 model for document image classification but in preprocessing stage I am getting error. Can some one please help me in fixing the error. ```auto dataset = Dataset.from_pandas(df_copy) dataset ``` ```auto Dataset({ features: ['Image_File_Path', 'Label'], num_rows: 12 }) ``` this is the code ```auto # we need to define custom features path = './Image FIle/' features = Features({ 'image': Array3D(dtype="int64", shape=(3, 224, 224)), 'input_ids': Sequence(feature=Value(dtype='int64')), 'attention_mask': Sequence(Value(dtype='int64')), 'token_type_ids': Sequence(Value(dtype='int64')), 'bbox': Array2D(dtype="int64", shape=(512, 4)), 'labels': Sequence(Value(dtype='int64')), }) def preprocess_data(examples): # take a batch of images images = [Image.open(os.path.join(path, file)).convert("RGB") for file in examples['Image_File_Path']] encoded_inputs = processor(images, padding="max_length", truncation=True) # add labels encoded_inputs["labels"] = [label2id[label] for label in examples["Label"]] return encoded_inputs encoded_dataset = dataset.map(preprocess_data, remove_columns=dataset.column_names, features=features, batched=True, batch_size=2) ``` this is the error ```auto **TypeError** Traceback (most recent call last) **d:\Working\Trans_LayoutLMV2_Doc_Classification.ipynb Cell 24** in **()** [18]encoded_inputs["labels"] = [label2id[label] for label in examples["Label"]] [19]return encoded_inputs **---> [21]encoded_dataset = dataset.map(preprocess_data, remove_columns=dataset.column_names, features=features, batched=True, batch_size=2) File **~\AppData\Roaming\Python\Python310\site-packages\datasets\arrow_dataset.py:2387** , in Dataset.map**(self, function, with_indices, with_rank, input_columns, batched, batch_size, drop_last_batch, remove_columns, keep_in_memory, load_from_cache_file, cache_file_name, writer_batch_size, features, disable_nullable, fn_kwargs, num_proc, suffix_template, new_fingerprint, desc)** 2384 disable_tqdm = not logging.is_progress_bar_enabled() 2386 if num_proc is None or num_proc == 1: **-> 2387** return self._map_single( 2388 function=function, 2389 with_indices=with_indices, 2390 with_rank=with_rank, 2391 input_columns=input_columns, 2392 batched=batched, 2393 batch_size=batch_size, 2394 drop_last_batch=drop_last_batch, 2395 remove_columns=remove_columns, 2396 keep_in_memory=keep_in_memory, 2397 load_from_cache_file=load_from_cache_file, 2398 cache_file_name=cache_file_name, 2399 writer_batch_size=writer_batch_size, 2400 features=features, 2401 disable_nullable=disable_nullable, 2402 fn_kwargs=fn_kwargs, 2403 new_fingerprint=new_fingerprint, 2404 disable_tqdm=disable_tqdm, 2405 desc=desc, 2406 ) 2407 else: 2409 def format_cache_file_name(cache_file_name, rank): File **~\AppData\Roaming\Python\Python310\site-packages\datasets\arrow_dataset.py:557** , in transmit_tasks..wrapper**(*args,**kwargs)** 555 self: "Dataset" = kwargs.pop("self") ... **TypeError** : Couldn't cast array of type int64 to Sequence(feature=Value(dtype='int64', id=None), length=-1, id=None) ``` ---
**Author:** ![mariosasko](https://sea2.discourse-cdn.com/hellohellohello/user_avatar/discuss.huggingface.co/mariosasko/32/31548_2.png) [@mariosasko](https://discuss.huggingface.co/u/mariosasko)\ **Post date:** [August 29, 2022, 10:38am UTC](https://discuss.huggingface.co/t/typeerror-couldnt-cast-array-of-type-int64-while-mapping-the-dataset/22167/2 "2022-08-29T10:38:32Z")
Hi! It seems like the cast fails on the `labels` column - `preprocess_data` returns a single label per example, so the correct feature type for it would be `Value("int64")`. ---
**Author:** ![Laxmi9](https://avatars.discourse-cdn.com/v4/letter/l/0ea827/32.png) [@Laxmi9](https://discuss.huggingface.co/u/Laxmi9)\ **Post date:** [August 31, 2022, 5:20am UTC](https://discuss.huggingface.co/t/typeerror-couldnt-cast-array-of-type-int64-while-mapping-the-dataset/22167/3 "2022-08-31T05:20:38Z")
Thanks for the guidance, I change the code as you guided but still getting the same error can you please help me. ![Annotation 2022-08-31 104835](https://us1.discourse-cdn.com/hellohellohello/original/2X/9/9137e48e584ae5c5671e96612aab0e2f9eeafd93.png) ![Annotation 2022-08-31 104933](https://us1.discourse-cdn.com/hellohellohello/original/2X/d/d37330419faf1cfff38c9b9da7e78e3aeb930d03.png) ---
**Author:** ![mariosasko](https://sea2.discourse-cdn.com/hellohellohello/user_avatar/discuss.huggingface.co/mariosasko/32/31548_2.png) [@mariosasko](https://discuss.huggingface.co/u/mariosasko)\ **Post date:** [August 31, 2022, 11:25am UTC](https://discuss.huggingface.co/t/typeerror-couldnt-cast-array-of-type-int64-while-mapping-the-dataset/22167/4 "2022-08-31T11:25:52Z")
This is not what I meant. What I meant is that the value of the `labels` key in the `features` dictionary should be `Value("int64")` (not the current `Sequence(Value("int64"))` ). ---
**Author:** ![Laxmi9](https://avatars.discourse-cdn.com/v4/letter/l/0ea827/32.png) [@Laxmi9](https://discuss.huggingface.co/u/Laxmi9)\ **Post date:** [August 31, 2022, 2:13pm UTC](https://discuss.huggingface.co/t/typeerror-couldnt-cast-array-of-type-int64-while-mapping-the-dataset/22167/5 "2022-08-31T14:13:47Z")
Thanks for the reply, This is what I did in the data frame it is int64 but when I load the data frame to huggingface dataset it is showing int. Can you please guide me what to do next. ![Annotation 2022-08-31 193917](https://us1.discourse-cdn.com/hellohellohello/original/2X/2/2a3193f87d6c6857a8a9613b51035a887bb88e1c.png) ---
**Author:** ![vijayakumar](https://avatars.discourse-cdn.com/v4/letter/v/b4bc9f/32.png) [@vijayakumar](https://discuss.huggingface.co/u/vijayakumar)\ **Post date:** [December 18, 2022, 5:13pm UTC](https://discuss.huggingface.co/t/typeerror-couldnt-cast-array-of-type-int64-while-mapping-the-dataset/22167/7 "2022-12-18T17:13:57Z")
![image](https://us1.discourse-cdn.com/hellohellohello/original/2X/7/7aecc7a15c7a154effcbf1f395eb38a31355b113.png) ---
**Author:** ![Mit1208](https://sea2.discourse-cdn.com/hellohellohello/user_avatar/discuss.huggingface.co/mit1208/32/32368_2.png) [@Mit1208](https://discuss.huggingface.co/u/Mit1208)\ **Post date:** [March 22, 2023, 8:31pm UTC](https://discuss.huggingface.co/t/typeerror-couldnt-cast-array-of-type-int64-while-mapping-the-dataset/22167/8 "2023-03-22T20:31:03Z")
I know this is very old question but still answering it. When I got same error I came here but not resolved error from this thread. After review few notebooks I resolved error. Try this: ```auto from datasets import Features, Sequence, ClassLabel, Value, Array2D, Array3D # we need to define custom features features = Features({ 'pixel_values': Array3D(dtype="float32", shape=(3, 224, 224)), 'input_ids': Sequence(feature=Value(dtype='int64')), 'attention_mask': Sequence(Value(dtype='int64')), 'bbox': Array2D(dtype="int64", shape=(512, 4)), # 'labels': ClassLabel(num_classes=len(labels), names=labels), 'labels':Sequence(ClassLabel(names=label_list)), }) def prepare_examples(examples): images = [Image.open(path).convert("RGB").resize(size=(224,224)) for path in examples['image_path']] words = examples[text_column_name] boxes = examples[boxes_column_name] word_labels = [[label2id[label]] for label in examples["label"]] encoding = processor(images, words, boxes=boxes,word_labels=word_labels, truncation=True, padding='max_length') ``` It worked for me. My labels were in string from the start so I used dict `label2id` to convert string to number and storing into list. As I am using dict I am mentioning `ClassLabel` in labels.