Write a python code that implements function approximation on Taxi$-$v$3$ environment at openai gym framework. Use only linear function for the value or policy functions. The task in this environment is to pick up the passenger at one location and drop him off in another, located at possible $4$ locations $($labeled by different letters$).$ You are expected to pick him up at Y and drop him at G$.$ You receive $+20$ points for a successful dropoff, and lose $1$ point for every timestep it takes. There is also a $10$ point penalty for illegal pick$-$up and drop$-$off actions. Note that the dynamics of the model are assumed to be unknown. You can access the environment information from environment variable.

env.env.nS $=$ number of states

env.env.nA $=$ number of possible actions