Seed the PRNG of this space and possibly the PRNGs of subspaces. gym.spaces.Space. to_jsonable ( self, sample_n : Sequence [ T_cov ] ) → list # observation_space = MultiBinary ( 5 ) >>> observation_space . sample () array([0, 1, 0, 1, 0], dtype=int8) >>> observation_space = MultiBinary ([ 3 , 2 ]) >>> observation_space . sample () array([[0, 0], [0, 1], [1, 1]], dtype=int8) __init__ ( n : ndarray | Sequence [ int ] | int, seed : int | Generator | None = None ) # ValueError – If no shape information is provided (shape is None, low is None and high is None) then a

np.ndarray of integers, in which case the length of the sampled sequence is randomly drawn from this array. d = MultiDiscrete ( np . array ([[ 1 , 2 ], [ 3 , 4 ]])) >> d . sample () array ([[ 0 , 0 ], [ 2 , 3 ]]) __init__ ( nvec: ~numpy.ndarray | list, dtype=, seed: int | ~numpy.random._generator.Generator | None = None ) # He says he is hoping his fitness journey will continue to inspire others to take the plunge and join the gym. In 2017, Mr Brenner went from 24 to 18 stone in just 12 months.Mr Brenner’s partner, Kayleigh Dawkins is the operational manager at Mind and Muscle Fitness and tells of how Steve changed his diet when on his weight loss journey. Return the data type of this space. gym.spaces.Space. seed ( self, seed : int | None = None ) → list # A dictionary with the same key and sampled values from :attr:`self.spaces` Discrete # class gym.spaces. Discrete ( n : int, seed : int | Generator | None = None, start : int = 0 ) # Sampled values from space MultiDiscrete # class gym.spaces. MultiDiscrete ( nvec: ~numpy.ndarray | list, dtype=, seed: int | ~numpy.random._generator.Generator | None = None ) # seed – Optionally, you can use this argument to seed the RNG that is used to sample from the space.

sample ( mask : Tuple [ ndarray | tuple | None , ndarray | tuple | None ] | None = None, num_nodes : int = 10, num_edges : int | None = None ) → GraphInstance # Tuple of the subspace’s samples Utility Functions # gym.spaces.utils. flatdim ( space : Space ) → int # gym.spaces.utils. flatdim ( space : Box | MultiBinary ) → int gym.spaces.utils. flatdim ( space : Box | MultiBinary ) → int gym.spaces.utils. flatdim ( space : Discrete ) → int gym.spaces.utils. flatdim ( space : MultiDiscrete ) → int gym.spaces.utils. flatdim ( space : Tuple ) → int gym.spaces.utils. flatdim ( space : Dict ) → int gym.spaces.utils. flatdim ( space : Graph ) gym.spaces.utils. flatdim ( space : Text ) → int seed – Optionally, you can use this argument to seed the RNGs of the spaces to ensure reproducible sampling.seed – Optionally, you can use this argument to seed the RNGs of the spaces that make up the Dict space. Eccentric Resistance Training using flywheel equipment is scientifically proven can achieve higher levels of muscle mass, strength and functional performance in a shorter time compared to gravity-based resistance machines. This is because a flywheel's isoinertial exercises working both the concentric and the eccentric motion of an exercise, giving increased efficiency and an optimum workout every time. Space Gym comes with a handy wall chart and demonstration videos for 24 isoinertial exercises you can follow, helping you to lose weight, increase your fitness, raise energy levels, build and tone muscle as well as improved stability and strength in just 10-minutes a day. Includes everything you need to see fast, amazing results! implemented to deal with Dict actions. __init__ ( spaces : Dict [ str , Space ] | Sequence [ Tuple [ str , Space ] ] | None = None, seed : dict | int | Generator | None = None, ** spaces_kwargs : Space ) #

NotImplementedError – if the space is not defined in gym.spaces. gym.spaces.utils. flatten ( space : Space [ T ], x : T ) → ndarray | Dict | tuple | GraphInstance # gym.spaces.utils. flatten ( space : MultiBinary, x ) → ndarray gym.spaces.utils. flatten ( space : Box, x ) → ndarray gym.spaces.utils. flatten ( space : Discrete, x ) → ndarray gym.spaces.utils. flatten ( space : MultiDiscrete, x ) → ndarray gym.spaces.utils. flatten ( space : Tuple, x ) → tuple | ndarray gym.spaces.utils. flatten ( space : Dict, x ) → dict | ndarray gym.spaces.utils. flatten ( space : Graph, x ) → GraphInstance gym.spaces.utils. flatten ( space : Text, x : str ) → ndarray gym.spaces.utils. flatten ( space : Sequence, x ) → tuplen – This will fix the shape of elements of the space. It can either be an integer (if the space is flat) 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” 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.