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Registering RESULT step
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ANSWER0=VQA(image=LEFT,question='How many prepared drinks are in serving cups?')
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ANSWER1=VQA(image=RIGHT,question='How many prepared drinks are in serving cups?')
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ANSWER2=EVAL(expr='{ANSWER0} == {ANSWER1}')
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FINAL_ANSWER=RESULT(var=ANSWER2)
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torch.Size([7, 3, 448, 448])
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Registering VQA_lavis step
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Registering EVAL step
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Registering RESULT step
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ANSWER0=VQA(image=LEFT,question='What shape are the pizzas?')
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ANSWER1=VQA(image=RIGHT,question='What shape are the pizzas?')
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ANSWER2=EVAL(expr='{ANSWER0} == "rectangle" and {ANSWER1} == "rectangle"')
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FINAL_ANSWER=RESULT(var=ANSWER2)
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torch.Size([7, 3, 448, 448])
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Registering VQA_lavis step
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Registering EVAL step
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Registering RESULT step
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question: ['How many prepared drinks are in serving cups?'], responses:['0']
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ANSWER0=VQA(image=RIGHT,question='Is the dog facing right in the image?')
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ANSWER1=VQA(image=LEFT,question='Is the dog facing left in the image?')
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ANSWER2=EVAL(expr='{ANSWER0} and {ANSWER1}')
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FINAL_ANSWER=RESULT(var=ANSWER2)
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[WARNING|tokenization_utils_base.py:2697] 2024-10-22 17:04:04,043 >> Asking to truncate to max_length but no maximum length is provided and the model has no predefined maximum length. Default to no truncation.
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Registering VQA_lavis step
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Registering EVAL step
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Registering RESULT step
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torch.Size([13, 3, 448, 448])
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ANSWER0=VQA(image=LEFT,question='How many boars are in the image?')
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ANSWER1=VQA(image=LEFT,question='Is the boar swimming in the water?')
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ANSWER2=EVAL(expr='{ANSWER0} == 1 and {ANSWER1}')
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FINAL_ANSWER=RESULT(var=ANSWER2)
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torch.Size([7, 3, 448, 448])
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[('0', 0.13077743594303964), ('circles', 0.12449813349255197), ('maroon', 0.12428926693968681), ('large', 0.1242263466991631), ('rooster', 0.12409315512763705), ('nuts', 0.12408018414184876), ('beige', 0.1240288472550799), ('bottle', 0.12400663040099273)]
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[['0', 'circles', 'maroon', 'large', 'rooster', 'nuts', 'beige', 'bottle']]
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Encountered ExecuteError: Unable to create tensor, you should probably activate truncation and/or padding with 'padding=True' 'truncation=True' to have batched tensors with the same length. Perhaps your features (`input_ids` in this case) have excessive nesting (inputs type `list` where type `int` is expected).
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Encountered TypeError: unsupported operand type(s) for +: 'NoneType' and 'str'
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ζεηζ¦ηεεΈδΈΊ: {True: 1e-09, False: 1e-09, 'Execute Error': 0.999999998}
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ANSWER0=VQA(image=LEFT,question='Is the shop door visible in the image?')
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ANSWER1=VQA(image=RIGHT,question='Is the shop door visible in the image?')
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ANSWER2=EVAL(expr='{ANSWER0} or {ANSWER1}')
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FINAL_ANSWER=RESULT(var=ANSWER2)
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torch.Size([1, 3, 448, 448])
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question: ['What shape are the pizzas?'], responses:['round']
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[WARNING|tokenization_utils_base.py:2697] 2024-10-22 17:04:04,749 >> Asking to truncate to max_length but no maximum length is provided and the model has no predefined maximum length. Default to no truncation.
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question: ['Is the shop door visible in the image?'], responses:['no']
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[('no', 0.1313955057270409), ('yes', 0.12592208734904367), ('no smoking', 0.12472972590078177), ('gone', 0.12376514658020793), ('man', 0.12367833016285167), ('meow', 0.1235796378467502), ('kia', 0.12347643720898455), ('no clock', 0.12345312922433942)]
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[['no', 'yes', 'no smoking', 'gone', 'man', 'meow', 'kia', 'no clock']]
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Encountered ExecuteError: Unable to create tensor, you should probably activate truncation and/or padding with 'padding=True' 'truncation=True' to have batched tensors with the same length. Perhaps your features (`input_ids` in this case) have excessive nesting (inputs type `list` where type `int` is expected).
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Encountered TypeError: unsupported operand type(s) for +: 'NoneType' and 'str'
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ζεηζ¦ηεεΈδΈΊ: {True: 1e-09, False: 1e-09, 'Execute Error': 0.999999998}
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question: ['How many boars are in the image?'], responses:['1']
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[('round', 0.12813543442466266), ('warning', 0.12464114900863767), ('exit', 0.12459056062387183), ('cut', 0.12456996524356728), ('cup', 0.12456900943720788), ('circle', 0.12452673539867194), ('tube', 0.12449066591861223), ('tile', 0.12447647994476846)]
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[['round', 'warning', 'exit', 'cut', 'cup', 'circle', 'tube', 'tile']]
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[WARNING|tokenization_utils_base.py:2697] 2024-10-22 17:04:05,231 >> Asking to truncate to max_length but no maximum length is provided and the model has no predefined maximum length. Default to no truncation.
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Encountered ExecuteError: Unable to create tensor, you should probably activate truncation and/or padding with 'padding=True' 'truncation=True' to have batched tensors with the same length. Perhaps your features (`input_ids` in this case) have excessive nesting (inputs type `list` where type `int` is expected).
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Encountered TypeError: unsupported operand type(s) for +: 'NoneType' and 'str'
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ζεηζ¦ηεεΈδΈΊ: {True: 1e-09, False: 1e-09, 'Execute Error': 0.999999998}
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ANSWER0=VQA(image=LEFT,question='How many live ibexes are standing in the grass and weeds?')
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ANSWER1=VQA(image=RIGHT,question='How many live ibexes are standing in the grass and weeds?')
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ANSWER2=EVAL(expr='{ANSWER0} >= 1 or {ANSWER1} >= 1')
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FINAL_ANSWER=RESULT(var=ANSWER2)
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torch.Size([3, 3, 448, 448])
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[('1', 0.12829009354978346), ('3', 0.12529928082343206), ('4', 0.12464806219229535), ('8', 0.12460015878893425), ('6', 0.12451220062887247), ('12', 0.124338487048427), ('2', 0.12420459433498025), ('47', 0.12410712263327517)]
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[['1', '3', '4', '8', '6', '12', '2', '47']]
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question: ['How many live ibexes are standing in the grass and weeds?'], responses:['1']
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[('1', 0.12829009354978346), ('3', 0.12529928082343206), ('4', 0.12464806219229535), ('8', 0.12460015878893425), ('6', 0.12451220062887247), ('12', 0.124338487048427), ('2', 0.12420459433498025), ('47', 0.12410712263327517)]
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[['1', '3', '4', '8', '6', '12', '2', '47']]
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question: ['Is the dog facing right in the image?'], responses:['yes']
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[WARNING|tokenization_utils_base.py:2697] 2024-10-22 17:04:05,827 >> Asking to truncate to max_length but no maximum length is provided and the model has no predefined maximum length. Default to no truncation.
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B: 8
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B: 8
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[('yes', 0.1298617250866936), ('congratulations', 0.12464161604141298), ('no', 0.12445222599225532), ('honey', 0.12437056445881921), ('solid', 0.12422595371654564), ('right', 0.12419889376311324), ('candle', 0.12414264780165109), ('chocolate', 0.12410637313950891)]
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[['yes', 'congratulations', 'no', 'honey', 'solid', 'right', 'candle', 'chocolate']]
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Encountered ExecuteError: Unable to create tensor, you should probably activate truncation and/or padding with 'padding=True' 'truncation=True' to have batched tensors with the same length. Perhaps your features (`input_ids` in this case) have excessive nesting (inputs type `list` where type `int` is expected).
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Encountered TypeError: unsupported operand type(s) for +: 'NoneType' and 'str'
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Encountered ExecuteError: shape '[8, 842]' is invalid for input of size 1
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Encountered TypeError: unsupported operand type(s) for +: 'NoneType' and 'str'
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ζεηζ¦ηεεΈδΈΊ: {True: 1e-09, False: 1e-09, 'Execute Error': 0.999999998}
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ANSWER0=VQA(image=LEFT,question='Does at least one dog have its mouth open?')
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ANSWER1=VQA(image=RIGHT,question='Does at least one dog have its mouth open?')
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ANSWER2=EVAL(expr='{ANSWER0} or {ANSWER1}')
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FINAL_ANSWER=RESULT(var=ANSWER2)
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torch.Size([1, 3, 448, 448])
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ζεηζ¦ηεεΈδΈΊ: {True: 1e-09, False: 1e-09, 'Execute Error': 0.999999998}
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question: ['Does at least one dog have its mouth open?'], responses:['yes']
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[('yes', 0.1298617250866936), ('congratulations', 0.12464161604141298), ('no', 0.12445222599225532), ('honey', 0.12437056445881921), ('solid', 0.12422595371654564), ('right', 0.12419889376311324), ('candle', 0.12414264780165109), ('chocolate', 0.12410637313950891)]
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[['yes', 'congratulations', 'no', 'honey', 'solid', 'right', 'candle', 'chocolate']]
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Encountered ExecuteError: Unable to create tensor, you should probably activate truncation and/or padding with 'padding=True' 'truncation=True' to have batched tensors with the same length. Perhaps your features (`input_ids` in this case) have excessive nesting (inputs type `list` where type `int` is expected).
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Encountered TypeError: unsupported operand type(s) for +: 'NoneType' and 'str'
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ζεηζ¦ηεεΈδΈΊ: {True: 1e-09, False: 1e-09, 'Execute Error': 0.999999998}
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Encountered ExecuteError: shape '[8, 1860]' is invalid for input of size 1
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Encountered TypeError: unsupported operand type(s) for +: 'NoneType' and 'str'
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ζεηζ¦ηεεΈδΈΊ: {True: 1e-09, False: 1e-09, 'Execute Error': 0.999999998}
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ANSWER0=VQA(image=LEFT,question='Is there a sofa/chair near the tall window?')
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ANSWER1=VQA(image=RIGHT,question='Is there a sofa/chair near the tall window?')
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ANSWER2=EVAL(expr='{ANSWER0}')
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FINAL_ANSWER=RESULT(var=ANSWER2)
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torch.Size([13, 3, 448, 448])
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question: ['Is there a sofa/chair near the tall window?'], responses:['yes']
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[('yes', 0.1298617250866936), ('congratulations', 0.12464161604141298), ('no', 0.12445222599225532), ('honey', 0.12437056445881921), ('solid', 0.12422595371654564), ('right', 0.12419889376311324), ('candle', 0.12414264780165109), ('chocolate', 0.12410637313950891)]
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