integration works knock on wood pt.2
This commit is contained in:
Joshua E. Jodesty
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cef6e652b3
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a7b01c1d07
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text = r'''
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Complex Adaptive Dynamics
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o i e
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m d s
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p e i
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u d g
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t n
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e
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r
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'''
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block_letters = r'''
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__________ ____
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________ __ _____/ ____/ | / __ \
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/ ___/ __` / __ / / / /| | / / / /
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/ /__/ /_/ / /_/ / /___/ ___ |/ /_/ /
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\___/\__,_/\__,_/\____/_/ |_/_____/
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by BlockScience
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'''
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production = r'''
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__________ ____
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________ __ _____/ ____/ | / __ \
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/ ___/ __` / __ / / / /| | / / / /
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/ /__/ /_/ / /_/ / /___/ ___ |/ /_/ /
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\___/\__,_/\__,_/\____/_/ |_/_____/
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by BlockScience
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======================================
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Complex Adaptive Dynamics
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o i e
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m d s
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p e i
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u d g
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t n
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e
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r
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'''
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@ -1,15 +0,0 @@
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Complex Adaptive Dynamics
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o i e
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m d s
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p e i
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u d g
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t n
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e
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r
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__________ ____
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________ __ _____/ ____/ | / __ \
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/ ___/ __` / __ / / / /| | / / / /
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/ /__/ /_/ / /_/ / /___/ ___ |/ /_/ /
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\___/\__,_/\__,_/\____/_/ |_/_____/
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by BlockScience
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@ -1,11 +1,5 @@
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name = "cadCAD"
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configs = []
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print(r'''
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__________ ____
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________ __ _____/ ____/ | / __ \
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/ ___/ __` / __ / / / /| | / / / /
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/ /__/ /_/ / /_/ / /___/ ___ |/ /_/ /
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\___/\__,_/\__,_/\____/_/ |_/_____/
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by BlockScience
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''')
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from ascii_art import production
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print(production)
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@ -79,28 +79,13 @@ def distributed_simulations(
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runIDs: List[int],
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sc: SparkContext = None
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):
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# params = list(zip(simulation_execs, var_dict_list, states_lists, configs_structs, env_processes_list, Ts, Ns,
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# userIDs, sessionIDs, simulationIDs, runIDs))
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# lambda t: t[0](t[1], t[2], t[3], t[4], t[5], t[6], t[7], t[8], t[9], t[10])
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func_params = list(
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func_params_zipped = list(
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zip(userIDs, sessionIDs, simulationIDs, runIDs, simulation_execs, configs_structs, env_processes_list)
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)
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func_params_dict = [
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# ((t[0], t[1], t[2], t[3]), {'sim_exec': t[4], 'config': t[5], 'env_procs': t[6]}) for t in func_params
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((t[0], t[1], t[2], t[3]), (t[4], t[5], t[6])) for t in func_params
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]
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val_params = list(zip(userIDs, sessionIDs, simulationIDs, runIDs, var_dict_list, states_lists, Ts, Ns))
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val_params_list = [
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(
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{'user_id': t[0], 'session_id': t[1], 'sim_id': t[2], 'run_id': t[3]},
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{'var_dict': t[4], 'states_lists': t[5], 'Ts': t[6], 'Ns': t[7]}
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) for t in val_params
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]
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func_params_kv = [((t[0], t[1], t[2], t[3]), (t[4], t[5], t[6])) for t in func_params_zipped]
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def simulate(k, v):
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(sim_exec, config, env_procs) = [f[1] for f in func_params_dict if f[0] == k][0]
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(sim_exec, config, env_procs) = [f[1] for f in func_params_kv if f[0] == k][0]
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print(env_procs)
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results = sim_exec(
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v['var_dict'], v['states_lists'], config, env_procs, v['Ts'], v['Ns'],
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@ -109,60 +94,16 @@ def distributed_simulations(
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return results
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# tuple(x[0].values())
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# x[1]
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vals_rdd = sc.parallelize(val_params_list).map(lambda x: simulate(tuple(x[0].values()), x[1]))
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pprint(vals_rdd.take(3))
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val_params = list(zip(userIDs, sessionIDs, simulationIDs, runIDs, var_dict_list, states_lists, Ts, Ns))
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val_params_kv = [
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(
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(t[0], t[1], t[2], t[3]),
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{'var_dict': t[4], 'states_lists': t[5], 'Ts': t[6], 'Ns': t[7]}
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) for t in val_params
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]
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results_rdd = sc.parallelize(val_params_kv).map(lambda x: simulate(*x))
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exit()
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# Pickle send to worker
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# atom = params[0]
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# # pprint(atom)
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# sim_exec = atom[0]
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# configs_struct = atom[3]
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# env_processes = atom[4]
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# pickled_sim_exec = cloudpickle.dumps(sim_exec)
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# pickled_configs = cloudpickle.dumps(configs_struct)
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# pickled_env_procs = cloudpickle.dumps(env_processes)
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#
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# def cucumber(pickled):
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# unpickled = pickle.loads(pickled)
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# return unpickled
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#
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# sc.parallelize([pickled_sim_exec]).map(cucumber).collect()
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# configs_structs, simulation_execs, env_processes_list
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results = [t[0](t[1], t[2], t[3], t[4], t[5], t[6], t[7], t[8], t[9], t[10], sc) for t in params]
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# def pickle_magic(cucumber):
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# cucumber[]
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# cloudpickle.dump()
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# cucumber = pickle.loads(pickled)
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pickled_params = cloudpickle.dump(params)
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results = sc.parallelize(pickled_params).map(
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lambda t: t[0](t[1], t[2], t[3], t[4], t[5], t[6], t[7], t[8], t[9], t[10])
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).collect()
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# with PPool(len(configs_structs)) as p:
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# results = p.map(lambda t: t[0](t[1], t[2], t[3], t[4], t[5], t[6], t[7], t[8], t[9], t[10], sc), params)
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return results
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# _pickle.PicklingError: Can't pickle <function <lambda> at 0x1115149e0>: attribute lookup <lambda> on
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# simulations.regression_tests.config1 failed
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# simulation_execs, env_processes_list
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# Configuration Layer: configs_structs
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# AttributeError: Can't pickle local object 'Identity.state_identity.<locals>.<lambda>'
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# pprint(configs_structs)
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# sc.parallelize([configs_structs])
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# exit()
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# result = sc.parallelize(params) \
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# .map(lambda t: t[0](t[1], t[2], t[3], t[4], t[5], t[6], t[7], t[8], t[9], t[10])) \
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# .collect()
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return list(results_rdd.collect())
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class ExecutionContext:
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def __init__(self, context: str = ExecutionMode.multi_proc) -> None:
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