# SOME DESCRIPTIVE TITLE.
# Copyright (C) 2023, InternLM Team
# This file is distributed under the same license as the InternLM package.
# FIRST AUTHOR <EMAIL@ADDRESS>, 2023.
#
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#: ../../source/initialize.rst:2
msgid "训练构建"
msgstr "Training Setup"

#: ../../source/initialize.rst:4
msgid "InternLM 的训练流程可以归纳为两个步骤："
msgstr "The training process of InternLM can be summarized into two steps: "

#: ../../source/initialize.rst:6
msgid "初始化"
msgstr "Initialization"

#: ../../source/initialize.rst:8
msgid "初始化模型、优化器、数据加载器、Trainer，生成不同种类的进程组，为混合并行的迭代训练做准备。"
msgstr ""
"Initialize model, optimizer, dataloader, trainer, and create different "
"types of process groups to prepare for iterative steps of hybrid parallel training. "

#: ../../source/initialize.rst:9
msgid "初始化Logger、Checkpoint管理器、Monitor管理器、Profiler，对迭代训练的过程观察、预警、记录。"
msgstr ""
"Initialize logger, checkpoint manager, monitor manager, and profiler to "
"watch, alert, and record the iterative training steps. "

#: ../../source/initialize.rst:11
msgid "迭代训练"
msgstr "Iterative training steps"

#: ../../source/initialize.rst:13
msgid "根据配置文件定义的张量并行、流水线并行、数据并行的大小，加载训练引擎和调度器进行混合并行训练。"
msgstr ""
"Load the training engine and scheduler for hybrid parallel training "
"according to the configuration such as tensor parallel size, pipeline "
"parallel size, and data parallel size. "

#: ../../source/initialize.rst:14
msgid "在迭代训练中，调用 Trainer API 进行梯度置零，前向传播计算损失并反向传播，参数更新。"
msgstr ""
"In iterative training steps, the Trainer API is called to perform zero "
"gradients, forward-loss-backward, and parameter update."

#: ../../source/initialize.rst:20
msgid "InternLM训练流程图"
msgstr "InternLM training process"

#: ../../source/initialize.rst:25
msgid "命令行参数解析"
msgstr "Argument Parsing"

#: ../../source/initialize.rst:27
msgid ""
"InternLM 使用 `argparse <https://docs.python.org/3/library/argparse.html>`_"
" 库来向InternLM运行时提供命令行参数配置。"
msgstr ""
"InternLM uses the `argparse "
"<https://docs.python.org/3/library/argparse.html>`_ library to supply "
"commandline configuration to the InternLM runtime. "

#: ../../source/initialize.rst:29
msgid ""
"用户可使用 ``internlm.initialize.get_default_parser()`` 来获取 InternLM "
"的默认解析器，其中包含一些内置参数，用户可以向此解析器添加自定义参数。"
msgstr ""
"Use ``internlm.initialize.get_default_parser()`` to get InternLM's "
"default parser with some builtin arguments, users can add custom "
"parameters to this parser."

#: internlm.initialize.launch.get_default_parser:1 of
msgid ""
"Reads user command line and uses an argument parser to parse the input "
"arguments. Input arguments include configuration, host, port, world size,"
" local rank, backend for torch.distributed."
msgstr ""

#: internlm.initialize.initialize_trainer.initialize_trainer
#: internlm.initialize.launch.get_default_parser
#: internlm.train.training_internlm.get_train_data_loader
#: internlm.train.training_internlm.initialize_model
#: internlm.train.training_internlm.initialize_optimizer of
msgid "返回"
msgstr ""

#: internlm.initialize.launch.get_default_parser:4 of
msgid ""
"Returns the parser with the default arguments, the user may add "
"customized arguments into this parser."
msgstr ""

#: internlm.initialize.initialize_trainer.initialize_trainer
#: internlm.initialize.launch.get_default_parser
#: internlm.train.training_internlm.initialize_model of
msgid "返回类型"
msgstr ""

#: ../../source/initialize.rst:45
msgid "模型初始化"
msgstr "Model Initialization"

#: internlm.train.training_internlm.initialize_model:1 of
msgid "Initialize model with Automatic Mixed Precision."
msgstr ""

#: internlm.train.training_internlm.initialize_model:3 of
msgid "The neural network model to be trained or evaluated."
msgstr ""

#: ../../source/initialize.rst:49
msgid "InternLM 在配置文件中使用字段 ``model_type`` 和 ``model`` 来控制模型初始化过程。示例模型初始化配置定义如下："
msgstr ""
"InternLM uses the field ``model_type`` and ``model`` in the config file "
"to control model initialization process. An example model initialization "
"configuratio"

#: ../../source/initialize.rst:77
msgid "字段 ``model_type`` 指明了要初始化的模型类型"
msgstr ""
"The field ``model_type`` specifics the model type has been registered and"
" to be initialized."

#: ../../source/initialize.rst:78
msgid "字段 ``model`` 中的参数指定了在模型初始化过程中的参数设置"
msgstr ""
"The parameters in field ``model`` specific the configuration settings "
"during model initialization."

#: ../../source/initialize.rst:80
msgid ""
"值得注意的是，用户可以定义新的模型类型，并使用装饰器 ``@MODEL_INITIALIZER.register_module`` "
"注册模型的初始化函数，其中 ``MODEL_INITIALIZER`` 是类 "
"``internlm.util.registry.Registry`` 的一个实例化对象，示例如下所示："
msgstr ""
"It is worth noting that, users can define new model type, and register "
"model's initialization function by decorater "
"``@MODEL_INITIALIZER.register_module``, which ``MODEL_INITIALIZER`` is an"
" instantiated object of class ``internlm.util.registry.Registry``, the "
"example is shown as follows."

#: ../../source/initialize.rst:92
msgid "优化器初始化"
msgstr "Optimizer Initialization"

#: internlm.train.training_internlm.initialize_optimizer:1 of
msgid "Initialize optimizer."
msgstr ""

#: internlm.initialize.initialize_trainer.initialize_trainer
#: internlm.train.training_internlm.get_train_data_loader
#: internlm.train.training_internlm.initialize_optimizer of
msgid "参数"
msgstr ""

#: internlm.train.training_internlm.initialize_optimizer:3 of
msgid "Your model instance to be trained or evaluated."
msgstr ""

#: internlm.train.training_internlm.initialize_optimizer:6 of
msgid "A tuple of (optimizer, beta2_scheduler, lr_scheduler)."
msgstr ""

#: ../../source/initialize.rst:99
msgid "数据加载器初始化"
msgstr "Dataloader Initialization"

#: internlm.train.training_internlm.get_train_data_loader:1 of
msgid "Generate and return the training data loader."
msgstr ""

#: internlm.train.training_internlm.get_train_data_loader:3 of
msgid "number of subprocesses used for dataloader."
msgstr ""

#: internlm.train.training_internlm.get_train_data_loader:5 of
msgid "generate function for dataset."
msgstr ""

#: internlm.train.training_internlm.get_train_data_loader:7 of
msgid "dataset sampler for training dataloader."
msgstr ""

#: internlm.train.training_internlm.get_train_data_loader:9 of
msgid "collate function for training dataloader."
msgstr ""

#: internlm.train.training_internlm.get_train_data_loader:12 of
msgid "A tuple of (train_dl, dataset_types)."
msgstr ""

#: ../../source/initialize.rst:106
msgid "Trainer 初始化"
msgstr "Trainer Initialization"

#: internlm.initialize.initialize_trainer.initialize_trainer:1 of
msgid ""
"Core function to wrap the essential training components with our "
"functionality based on the config which is loaded into gpc.config."
msgstr ""

#: internlm.initialize.initialize_trainer.initialize_trainer:4 of
msgid "Your model instance or a function to build the model."
msgstr ""

#: internlm.initialize.initialize_trainer.initialize_trainer:6 of
msgid "Your optimizer for training."
msgstr ""

#: internlm.initialize.initialize_trainer.initialize_trainer:8 of
msgid "Your criterion instance."
msgstr ""

#: internlm.initialize.initialize_trainer.initialize_trainer:10 of
msgid "Dataloader for training."
msgstr ""

#: internlm.initialize.initialize_trainer.initialize_trainer:12 of
msgid "Dataloader for testing."
msgstr ""

#: internlm.initialize.initialize_trainer.initialize_trainer:14 of
msgid "Your lr scheduler instance, optional."
msgstr ""

#: internlm.initialize.initialize_trainer.initialize_trainer:17 of
msgid ""
"A tuple of ``(trainer, train_dataloader, test_dataloader, lr_scheduler)``"
" where only ``trainer`` could not be None."
msgstr ""

