I haven’t had a great physique all my life – I have been up and down. A lot of my clients are very anxious about going to the gym so when they see what I have gone through, it helps them.” The 37-year-old started a cleaning company about 14 years ago but says he was “so miserable”

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Discrete ( 2 ) # {0, 1} >>> Discrete ( 3 , start =- 1 ) # {-1, 0, 1} class __init__ ( * args, ** kwargs ) # The awards, organised by Script Events and leading industry publication Workout, with support from headline sponsor ServiceSport, are now in their 12th year and recognise excellence and achievement in all corners of the industry.discrete = Discrete ( 5 ) >>> flatten_space ( discrete ) Box(5,) >>> flatten ( box , box . sample ()) in flatten_space ( box ) True Convert a batch of samples from this space to a JSONable data type. gym.spaces.Space. from_jsonable ( self, sample_n : list ) → List [ T_cov ] #

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A sampled value from the Box Dict # class gym.spaces. Dict ( spaces : Dict [ str , Space ] | Sequence [ Tuple [ str , Space ] ] | None = None, seed : dict | int | Generator | None = None, ** spaces_kwargs : Space ) # Three unique concept studios are home to our innovative fitness program. From Spin and HIIT to Holistic Meditation, we have a series of boutique training classes to keep you motivated and drive your performance.

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A space representing graph information as a series of nodes connected with edges according to an adjacency matrix represented as a series of edge_links. CitySpace Fitness features a large modern sports hall with spectator seating. It is the home to Team Sunderland, for training, fixtures and competition, as well as being available for casual bookings to play 5 a side, netball, table tennis, basketball, badminton and short tennis.

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Group membership includes full access to; City, Canary Wharf, Tower Bridge, Soho, Marylebone, Moorgate and Islington, but does not include Mayfair. n – This will fix the shape of elements of the space. It can either be an integer (if the space is flat) 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 mask – An optional mask for multi-discrete, expects tuples with a np.ndarray mask in the position of each

np.ndarray of integers, in which case the length of the sampled sequence is randomly drawn from this array. space = Dict ({ "position" : Discrete ( 2 ), "velocity" : Box ( 0 , 1 , shape = ( 2 , 2 ))}) >>> flatten_space ( space ) Box(6,) >>> flatten ( space , space . sample ()) in flatten_space ( space ) True