mirror of https://github.com/InternLM/InternLM
162 lines
5.0 KiB
Plaintext
162 lines
5.0 KiB
Plaintext
# 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.
|
||
#
|
||
msgid ""
|
||
msgstr ""
|
||
"Project-Id-Version: InternLM \n"
|
||
"Report-Msgid-Bugs-To: \n"
|
||
"POT-Creation-Date: 2023-09-14 12:23+0800\n"
|
||
"PO-Revision-Date: YEAR-MO-DA HO:MI+ZONE\n"
|
||
"Last-Translator: FULL NAME <EMAIL@ADDRESS>\n"
|
||
"Language: en\n"
|
||
"Language-Team: en <LL@li.org>\n"
|
||
"Plural-Forms: nplurals=2; plural=(n != 1);\n"
|
||
"MIME-Version: 1.0\n"
|
||
"Content-Type: text/plain; charset=utf-8\n"
|
||
"Content-Transfer-Encoding: 8bit\n"
|
||
"Generated-By: Babel 2.12.1\n"
|
||
|
||
#: ../../source/training.rst:2
|
||
msgid "训练 API"
|
||
msgstr "Training API"
|
||
|
||
#: ../../source/training.rst:4
|
||
msgid ""
|
||
"InternLM 的训练 API 由 ``internlm.core.trainer.Trainer`` "
|
||
"管理。在定义了训练引擎和调度器之后，我们可以调用 Trainer API 来执行模型训练、评估、梯度清零和参数更新等。"
|
||
msgstr ""
|
||
"InternLM training API is managed in ``internlm.core.trainer.Trainer``. "
|
||
"After defining the training engine and runtime scheduler, we can call "
|
||
"training API to perform training, evaluation, zero gradients and "
|
||
"parameter update steps."
|
||
|
||
#: ../../source/training.rst:6
|
||
msgid "有关详细用法，请参阅 Trainer API 文档和示例。"
|
||
msgstr ""
|
||
"For detailed usage, please refer to Trainer API documentation and "
|
||
"examples."
|
||
|
||
#: internlm.core.trainer.Trainer:1 of
|
||
msgid ""
|
||
"This is a class tending for easy deployments of users' training and "
|
||
"evaluation instead of writing their own scripts."
|
||
msgstr ""
|
||
|
||
#: internlm.core.trainer.Trainer internlm.core.trainer.Trainer.execute_schedule
|
||
#: of
|
||
msgid "参数"
|
||
msgstr ""
|
||
|
||
#: internlm.core.trainer.Trainer:4 of
|
||
msgid "Engine responsible for the process function."
|
||
msgstr ""
|
||
|
||
#: internlm.core.trainer.Trainer:6 of
|
||
msgid "Runtime schedule. Defaults to None."
|
||
msgstr ""
|
||
|
||
#: internlm.core.trainer.Trainer.engine:1 of
|
||
msgid ""
|
||
"Returns the engine that responsible for managing the training and "
|
||
"evaluation process."
|
||
msgstr ""
|
||
|
||
#: internlm.core.trainer.Trainer.schedule:1 of
|
||
msgid "Returns the runtime scheduler."
|
||
msgstr ""
|
||
|
||
#: internlm.core.trainer.Trainer.uses_pipeline:1 of
|
||
msgid "Returns whether the pipeline parallel is used or not."
|
||
msgstr ""
|
||
|
||
#: internlm.core.trainer.Trainer.train:1 of
|
||
msgid "Sets the model to training mode."
|
||
msgstr ""
|
||
|
||
#: internlm.core.trainer.Trainer.eval:1 of
|
||
msgid "Sets the model to evaluation mode."
|
||
msgstr ""
|
||
|
||
#: internlm.core.trainer.Trainer.zero_grad:1 of
|
||
msgid "Sets the gradient of all parameters in the model to zero."
|
||
msgstr ""
|
||
|
||
#: internlm.core.trainer.Trainer.step:1 of
|
||
msgid "Executes the parameter update step."
|
||
msgstr ""
|
||
|
||
#: internlm.core.trainer.Trainer.execute_schedule:1 of
|
||
msgid ""
|
||
"Runs the forward, loss computation, and backward for the model. Returns a"
|
||
" tuple of (output, label, loss)."
|
||
msgstr ""
|
||
|
||
#: internlm.core.trainer.Trainer.execute_schedule:4 of
|
||
msgid "The data iterator."
|
||
msgstr ""
|
||
|
||
#: internlm.core.trainer.Trainer.execute_schedule:6 of
|
||
msgid "Additional keyword arguments."
|
||
msgstr ""
|
||
|
||
#: internlm.core.trainer.Trainer.execute_schedule of
|
||
msgid "返回"
|
||
msgstr ""
|
||
|
||
#: internlm.core.trainer.Trainer.execute_schedule:8 of
|
||
msgid "A tuple of (output, label, loss)."
|
||
msgstr ""
|
||
|
||
#: internlm.core.trainer.Trainer.execute_schedule of
|
||
msgid "返回类型"
|
||
msgstr ""
|
||
|
||
#: internlm.core.trainer.Trainer.execute_schedule:9 of
|
||
msgid "Tuple[:class:`torch.Tensor`]"
|
||
msgstr ""
|
||
|
||
#~ 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: "
|
||
|
||
#~ msgid "初始化"
|
||
#~ msgstr "Initialization"
|
||
|
||
#~ 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. "
|
||
|
||
#~ 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. "
|
||
|
||
#~ msgid "迭代训练"
|
||
#~ msgstr "Iterative training steps"
|
||
|
||
#~ 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. "
|
||
|
||
#~ 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."
|
||
|
||
#~ msgid "InternLM训练流程图"
|
||
#~ msgstr "InternLM training process"
|
||
|