data:image/png;base64,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

What is your weight in kilograms?0

BMIHere are your BMIs

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KBgAAH6CYJECBAgIAA+wECBAgQIBAICHCAbpIAAQIECByxcQFpoRMBzwAAAABJRU5ErkJggg==The inputs of the program are the number of BMI, the weight of the users, and the height of users.The outputs of the program is the users BMI.2.680211.8343195266272176.760000000000001