Better test script for transformers t5

examples/t5/test_t5.py

 from transformers import T5Model, T5ForConditionalGeneration, T5Tokenizer
+device = 'cuda:1'
 tokenizer = T5Tokenizer.from_pretrained("t5-large")
-model = T5Model.from_pretrained("/dataset/fd5061f6/yanan/huggingface_models/t5-large")
-model = model.to('cuda')
+model = T5ForConditionalGeneration.from_pretrained("/dataset/fd5061f6/yanan/huggingface_models/t5-xl-lm-adapt")
+model = model.to(device)
 model.eval()
-input_ids = tokenizer('The <extra_id_0> walks in <extra_id_1> park', return_tensors='pt').input_ids.to('cuda')
-decoder_input_ids = tokenizer('<extra_id_0> cute dog <extra_id_1> the <extra_id_2>', return_tensors='pt').input_ids.to('cuda')
+input_ids = tokenizer('The <extra_id_0> walks in <extra_id_1> park', return_tensors='pt').input_ids.to(device)
+decoder_input_ids = tokenizer('<extra_id_0> cute dog <extra_id_1> the <extra_id_2>', return_tensors='pt').input_ids.to(device)
+breakpoint()
 output = model(input_ids=input_ids, labels=decoder_input_ids)
 output.loss.backward()
-breakpoint()
+a = 1
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