Datasets:
TMarcus
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InternVL

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Encountered ExecuteError: 'InternVLChatModel' object has no attribute 'tokenizer'
Encountered TypeError: unsupported operand type(s) for +: 'NoneType' and 'str'
ζœ€εŽηš„ζ¦‚ηŽ‡εˆ†εΈƒδΈΊ: {True: 1e-09, False: 1e-09, 'Execute Error': 0.999999998}
torch.Size([7, 3, 448, 448])
Encountered ExecuteError: 'InternVLChatModel' object has no attribute 'tokenizer'
Encountered TypeError: unsupported operand type(s) for +: 'NoneType' and 'str'
ζœ€εŽηš„ζ¦‚ηŽ‡εˆ†εΈƒδΈΊ: {True: 1e-09, False: 1e-09, 'Execute Error': 0.999999998}
ANSWER0=VQA(image=LEFT,question='How many dogs are in the image?')
ANSWER1=VQA(image=RIGHT,question='How many dogs are in the image?')
ANSWER2=EVAL(expr='{ANSWER0} + {ANSWER1} > 2')
FINAL_ANSWER=RESULT(var=ANSWER2)
ANSWER0=VQA(image=LEFT,question='How many cheetahs are in the image?')
ANSWER1=VQA(image=RIGHT,question='How many cheetahs are in the image?')
ANSWER2=EVAL(expr='{ANSWER0} + {ANSWER1} <= 4')
FINAL_ANSWER=RESULT(var=ANSWER2)
torch.Size([13, 3, 448, 448])
Encountered ExecuteError: 'InternVLChatModel' object has no attribute 'tokenizer'
Encountered TypeError: unsupported operand type(s) for +: 'NoneType' and 'str'
ζœ€εŽηš„ζ¦‚ηŽ‡εˆ†εΈƒδΈΊ: {True: 1e-09, False: 1e-09, 'Execute Error': 0.999999998}
torch.Size([13, 3, 448, 448])
ANSWER0=VQA(image=LEFT,question='Are two golf balls in a box?')
ANSWER1=VQA(image=RIGHT,question='Are two golf balls in a box?')
ANSWER2=EVAL(expr='not ({ANSWER0} and {ANSWER1})')
FINAL_ANSWER=RESULT(var=ANSWER2)
Encountered ExecuteError: 'InternVLChatModel' object has no attribute 'tokenizer'
Encountered TypeError: unsupported operand type(s) for +: 'NoneType' and 'str'
torch.Size([7, 3, 448, 448])
torch.Size([7, 3, 448, 448])
ζœ€εŽηš„ζ¦‚ηŽ‡εˆ†εΈƒδΈΊ: {True: 1e-09, False: 1e-09, 'Execute Error': 0.999999998}
Encountered ExecuteError: 'InternVLChatModel' object has no attribute 'tokenizer'
Encountered TypeError: unsupported operand type(s) for +: 'NoneType' and 'str'
ζœ€εŽηš„ζ¦‚ηŽ‡εˆ†εΈƒδΈΊ: {True: 1e-09, False: 1e-09, 'Execute Error': 0.999999998}
Encountered ExecuteError: 'InternVLChatModel' object has no attribute 'tokenizer'
Encountered TypeError: unsupported operand type(s) for +: 'NoneType' and 'str'
ζœ€εŽηš„ζ¦‚ηŽ‡εˆ†εΈƒδΈΊ: {True: 1e-09, False: 1e-09, 'Execute Error': 0.999999998}
torch.Size([3, 3, 448, 448])
Encountered ExecuteError: 'InternVLChatModel' object has no attribute 'tokenizer'
Encountered TypeError: unsupported operand type(s) for +: 'NoneType' and 'str'
ζœ€εŽηš„ζ¦‚ηŽ‡εˆ†εΈƒδΈΊ: {True: 1e-09, False: 1e-09, 'Execute Error': 0.999999998}
ANSWER0=VQA(image=LEFT,question='Are all shoes laced with black shoestrings?')
ANSWER1=VQA(image=RIGHT,question='Are all shoes laced with black shoestrings?')
ANSWER2=EVAL(expr='{ANSWER0} and {ANSWER1}')
FINAL_ANSWER=RESULT(var=ANSWER2)
torch.Size([5, 3, 448, 448])
Encountered ExecuteError: 'InternVLChatModel' object has no attribute 'tokenizer'
Encountered TypeError: unsupported operand type(s) for +: 'NoneType' and 'str'
ζœ€εŽηš„ζ¦‚ηŽ‡εˆ†εΈƒδΈΊ: {True: 1e-09, False: 1e-09, 'Execute Error': 0.999999998}
[2024-10-22 17:08:11,580] [INFO] [logging.py:96:log_dist] [Rank 0] rank=0 time (ms) | optimizer_allgather: 1.69 | optimizer_gradients: 0.76 | optimizer_step: 0.31
[2024-10-22 17:08:11,580] [INFO] [logging.py:96:log_dist] [Rank 0] rank=0 time (ms) | forward_microstep: 99.68 | backward_microstep: 1.38 | backward_inner_microstep: 0.48 | backward_allreduce_microstep: 0.82 | step_microstep: 64.65
[2024-10-22 17:08:11,580] [INFO] [logging.py:96:log_dist] [Rank 0] rank=0 time (ms) | forward: 99.70 | backward: 1.38 | backward_inner: 0.49 | backward_allreduce: 0.83 | step: 64.65
0%| | 4/26352 [00:14<14:49:54, 2.03s/it]Registering VQA_lavis step
Registering EVAL step
Registering RESULT step
ANSWER0=VQA(image=LEFT,question='Is the container filled with dark liquid?')
ANSWER1=VQA(image=RIGHT,question='Is the container filled with dark liquid?')
ANSWER2=EVAL(expr='{ANSWER0} and {ANSWER1}')
FINAL_ANSWER=RESULT(var=ANSWER2)
Registering VQA_lavis step
Registering VQA_lavis step
Registering EVAL step
Registering RESULT step
Registering EVAL step
Registering RESULT step
ANSWER0=VQA(image=LEFT,question='How many dogs are in the image?')
ANSWER1=EVAL(expr='{ANSWER0} >= 2')
FINAL_ANSWER=RESULT(var=ANSWER1)
Registering VQA_lavis step
Registering EVAL step
Registering RESULT step
torch.Size([1, 3, 448, 448])
Encountered ExecuteError: 'InternVLChatModel' object has no attribute 'tokenizer'
Encountered TypeError: unsupported operand type(s) for +: 'NoneType' and 'str'
ζœ€εŽηš„ζ¦‚ηŽ‡εˆ†εΈƒδΈΊ: {True: 1e-09, False: 1e-09, 'Execute Error': 0.999999998}
ANSWER0=VQA(image=RIGHT,question='How many golf balls are in the image?')
ANSWER1=EVAL(expr='{ANSWER0} >= 3')
FINAL_ANSWER=RESULT(var=ANSWER1)
ANSWER0=VQA(image=LEFT,question='Is one of the primates smoking?')
ANSWER1=VQA(image=RIGHT,question='Is one of the primates smoking?')
ANSWER2=EVAL(expr='{ANSWER0} or {ANSWER1}')
FINAL_ANSWER=RESULT(var=ANSWER2)
torch.Size([1, 3, 448, 448])
Encountered ExecuteError: 'InternVLChatModel' object has no attribute 'tokenizer'
Encountered TypeError: unsupported operand type(s) for +: 'NoneType' and 'str'
ζœ€εŽηš„ζ¦‚ηŽ‡εˆ†εΈƒδΈΊ: {True: 1e-09, False: 1e-09, 'Execute Error': 0.999999998}
ANSWER0=VQA(image=LEFT,question='How many dogs are in the image?')
ANSWER1=VQA(image=RIGHT,question='How many dogs are in the image?')
ANSWER2=EVAL(expr='{ANSWER0} + {ANSWER1} == 3')
FINAL_ANSWER=RESULT(var=ANSWER2)
torch.Size([7, 3, 448, 448])
Encountered ExecuteError: 'InternVLChatModel' object has no attribute 'tokenizer'
Encountered TypeError: unsupported operand type(s) for +: 'NoneType' and 'str'
ANSWER0=VQA(image=LEFT,question='Is a dog's tongue hanging out of its mouth?')
ANSWER1=VQA(image=RIGHT,question='Is a dog's tongue hanging out of its mouth?')
ANSWER2=EVAL(expr='{ANSWER0} or {ANSWER1}')
FINAL_ANSWER=RESULT(var=ANSWER2)
ζœ€εŽηš„ζ¦‚ηŽ‡εˆ†εΈƒδΈΊ: {True: 1e-09, False: 1e-09, 'Execute Error': 0.999999998}
ANSWER0=VQA(image=LEFT,question='How many oxen are standing in the water?')
ANSWER1=VQA(image=RIGHT,question='How many oxen are standing in the water?')
ANSWER2=EVAL(expr='{ANSWER0} + {ANSWER1} >= 1')