Python get_all_archs примеры использования

Пример #1

Файл: run_exp.py Проект: sciforce/pytorch-kaldi

# Splitting data into chunks (see out_folder/additional_files)
create_lists(config)

# Writing the config files
create_configs(config)

print("- Chunk creation......OK!\n")

# create res_file
res_file_path = out_folder + "/res.res"
res_file = open(res_file_path, "w")
res_file.close()


# Learning rates and architecture-specific optimization parameters
arch_lst = get_all_archs(config)
lr = {}
auto_lr_annealing = {}
improvement_threshold = {}
halving_factor = {}
pt_files = {}

for arch in arch_lst:
    lr[arch] = expand_str_ep(config[arch]["arch_lr"], "float", N_ep, "|", "*")
    if len(config[arch]["arch_lr"].split("|")) > 1:
        auto_lr_annealing[arch] = False
    else:
        auto_lr_annealing[arch] = True
    improvement_threshold[arch] = float(config[arch]["arch_improvement_threshold"])
    halving_factor[arch] = float(config[arch]["arch_halving_factor"])
    pt_files[arch] = config[arch]["arch_pretrain_file"]

Пример #2

# Splitting data into chunks (see out_folder/additional_files)
create_lists(config)

# Writing the config files
create_configs(config)

print("- Chunk creation......OK!\n")

# create res_file
res_file_path = out_folder + '/res.res'  # 文件res.res总结了各个时期的训练和评估表现。
res_file = open(res_file_path, "w")
res_file.close()

# Learning rates and architecture-specific optimization parameters
arch_lst = get_all_archs(config)  # 获得所有层模型的cfg数据
lr = {}
auto_lr_annealing = {}
improvement_threshold = {}
halving_factor = {}
pt_files = {}

for arch in arch_lst:
    lr[arch] = expand_str_ep(config[arch]['arch_lr'], 'float', N_ep, '|',
                             '*')  # 学习率
    if len(config[arch]['arch_lr'].split('|')) > 1:
        auto_lr_annealing[arch] = False
    else:
        auto_lr_annealing[arch] = True
    improvement_threshold[arch] = float(
        config[arch]['arch_improvement_threshold'])