Spaces:
Sleeping
Sleeping
| # distutils:language=c++ | |
| # cython:language_level=3 | |
| from libcpp.vector cimport vector | |
| cdef class MinMaxStatsList: | |
| cdef CMinMaxStatsList *cmin_max_stats_lst | |
| def __cinit__(self, int num): | |
| self.cmin_max_stats_lst = new CMinMaxStatsList(num) | |
| def set_delta(self, float value_delta_max): | |
| self.cmin_max_stats_lst[0].set_delta(value_delta_max) | |
| def __dealloc__(self): | |
| del self.cmin_max_stats_lst | |
| cdef class ResultsWrapper: | |
| cdef CSearchResults cresults | |
| def __cinit__(self, int num): | |
| self.cresults = CSearchResults(num) | |
| def get_search_len(self): | |
| return self.cresults.search_lens | |
| cdef class Action: | |
| cdef int is_root_action | |
| cdef vector[float] value | |
| cdef CAction action | |
| def __cinit__(self): | |
| pass | |
| def __cinit__(self, vector[float] value, int is_root_action): | |
| self.is_root_action = is_root_action | |
| self.value = value | |
| cdef class Roots: | |
| cdef int root_num | |
| cdef int action_space_size | |
| cdef int num_of_sampled_actions | |
| cdef CRoots *roots | |
| cdef bool continuous_action_space | |
| def __cinit__(self): | |
| pass | |
| def __cinit__(self, int root_num, list legal_actions_list, int action_space_size, int num_of_sampled_actions, | |
| bool continuous_action_space): | |
| #def __cinit__(self, int root_num, list legal_actions_list, int action_space_size, int num_of_sampled_actions): | |
| self.root_num = root_num | |
| self.action_space_size = action_space_size | |
| self.num_of_sampled_actions = num_of_sampled_actions | |
| self.roots = new CRoots(root_num, legal_actions_list, action_space_size, num_of_sampled_actions, | |
| continuous_action_space) | |
| def prepare(self, float root_noise_weight, list noises, list value_prefix_pool, list policy_logits_pool, | |
| vector[int] & to_play_batch): | |
| self.roots[0].prepare(root_noise_weight, noises, value_prefix_pool, policy_logits_pool, to_play_batch) | |
| def prepare_no_noise(self, list value_prefix_pool, list policy_logits_pool, vector[int] & to_play_batch): | |
| self.roots[0].prepare_no_noise(value_prefix_pool, policy_logits_pool, to_play_batch) | |
| def get_trajectories(self): | |
| return self.roots[0].get_trajectories() | |
| def get_distributions(self): | |
| return self.roots[0].get_distributions() | |
| def get_sampled_actions(self): | |
| return self.roots[0].get_sampled_actions() | |
| def get_values(self): | |
| return self.roots[0].get_values() | |
| def clear(self): | |
| self.roots[0].clear() | |
| def __dealloc__(self): | |
| del self.roots | |
| def num(self): | |
| return self.root_num | |
| cdef class Node: | |
| cdef CNode cnode | |
| cdef bool continuous_action_space | |
| def __cinit__(self): | |
| pass | |
| #def __cinit__(self, float prior, vector[int] &legal_actions, int action_space_size, int num_of_sampled_actions): | |
| def __cinit__(self, float prior, vector[int] & legal_actions, int action_space_size, int num_of_sampled_actions, | |
| bool continuous_action_space): | |
| pass | |
| def expand(self, int to_play, int current_latent_state_index, int batch_index, float value_prefix, | |
| list policy_logits): | |
| cdef vector[float] cpolicy = policy_logits | |
| self.cnode.expand(to_play, current_latent_state_index, batch_index, value_prefix, cpolicy) | |
| def batch_backpropagate(int current_latent_state_index, float discount_factor, list value_prefixs, list values, list policies, | |
| MinMaxStatsList min_max_stats_lst, ResultsWrapper results, list is_reset_list, | |
| list to_play_batch): | |
| cdef int i | |
| cdef vector[float] cvalue_prefixs = value_prefixs | |
| cdef vector[float] cvalues = values | |
| cdef vector[vector[float]] cpolicies = policies | |
| cbatch_backpropagate(current_latent_state_index, discount_factor, cvalue_prefixs, cvalues, cpolicies, | |
| min_max_stats_lst.cmin_max_stats_lst, results.cresults, is_reset_list, to_play_batch) | |
| def batch_traverse(Roots roots, int pb_c_base, float pb_c_init, float discount_factor, MinMaxStatsList min_max_stats_lst, | |
| ResultsWrapper results, list virtual_to_play_batch, bool continuous_action_space): | |
| cbatch_traverse(roots.roots, pb_c_base, pb_c_init, discount_factor, min_max_stats_lst.cmin_max_stats_lst, results.cresults, | |
| virtual_to_play_batch, continuous_action_space) | |
| return results.cresults.latent_state_index_in_search_path, results.cresults.latent_state_index_in_batch, results.cresults.last_actions, results.cresults.virtual_to_play_batchs | |