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National Fitness Awards’ director Dominic Musgrave said: “This year’s winners should be very very proud – the high standard of entries made it a tough job to select a final shortlist never mind a winner and runner-up in each category. He also allowed himself one meal of choice off of the plan he had designed for himself, which was often a takeaway. But diets and nutrition are different from person to person, which of course as a nutritionist Steve now understands fully and helps people design a food plan that works for them. mask – An optional mask for (optionally) the length of the sequence and (optionally) the values in the sequence.
low: ~typing.SupportsFloat | ~numpy.ndarray, high: ~typing.SupportsFloat | ~numpy.ndarray, shape: ~typing.Sequence[int] | None = None, dtype: ~typing.Type =
from gym.spaces import Discrete >>> space = Dict ({ "position" : Discrete ( 2 ), "velocity" : Discrete ( 3 )}) >>> flatdim ( space ) 5 Parameters :
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At the start of the year, I was doing sports massage therapy out of a room I rented, doing my personal training out of Pure Gym in Folkestone, and doing my nutrition work online. Now, we have taken on this building so we are able to do it all here. Return boolean specifying if x is a valid member of this space. property Space. shape : Tuple [ int , ... ] | None # I then became a sports massage therapist and started the Mind Muscle Clinic. Since then, I have expanded gradually and studied my nutrition qualification,” he said.
seed – Optionally, you can use this argument to seed the RNGs of the spaces that make up the Dict space. charset ( Union [ set ] , str) – Character set, defaults to the lower and upper english alphabet plus latin digits.NotImplementedError – If the space is not defined in gym.spaces. gym.spaces.utils. unflatten ( space : Space [ T ], x : ndarray | Dict | tuple | GraphInstance ) → T # gym.spaces.utils. unflatten ( space : Box | MultiBinary, x : ndarray ) → ndarray gym.spaces.utils. unflatten ( space : Box | MultiBinary, x : ndarray ) → ndarray gym.spaces.utils. unflatten ( space : Discrete, x : ndarray ) → int gym.spaces.utils. unflatten ( space : MultiDiscrete, x : ndarray ) → ndarray gym.spaces.utils. unflatten ( space : Tuple, x : ndarray | tuple ) → tuple gym.spaces.utils. unflatten ( space : Dict, x : ndarray | Dict ) → dict gym.spaces.utils. unflatten ( space : Graph, x : GraphInstance ) → GraphInstance gym.spaces.utils. unflatten ( space : Text, x : ndarray ) → str gym.spaces.utils. unflatten ( space : Sequence, x : tuple ) → tuple convert Dict observations to flat arrays by using a gym.wrappers.FlattenObservation wrapper. Similar wrappers can be We want our original members who we take on first to be our founding members and they will have different perks,” Miss Dawkins says.