2024-02-05 13:49:23

totrans/doc22_057.yaml

@@ -3,11 +3,13 @@
   prefs:
   - PREF_H1
   type: TYPE_NORMAL
+  zh: torch.futures
 - en: 原文：[https://pytorch.org/docs/stable/futures.html](https://pytorch.org/docs/stable/futures.html)
   id: totrans-1
   prefs:
   - PREF_BQ
   type: TYPE_NORMAL
+  zh: 原文：[https://pytorch.org/docs/stable/futures.html](https://pytorch.org/docs/stable/futures.html)
 - en: This package provides a [`Future`](#torch.futures.Future "torch.futures.Future")
     type that encapsulates an asynchronous execution and a set of utility functions
     to simplify operations on [`Future`](#torch.futures.Future "torch.futures.Future")
@@ -16,6 +18,8 @@
   id: totrans-2
   prefs: []
   type: TYPE_NORMAL
+  zh: 此软件包提供了一个[`Future`](#torch.futures.Future "torch.futures.Future")类型，封装了异步执行和一组实用函数，以简化对[`Future`](#torch.futures.Future
+    "torch.futures.Future")对象的操作。目前，[`Future`](#torch.futures.Future "torch.futures.Future")类型主要由[分布式RPC框架](rpc.html#distributed-rpc-framework)使用。
 - en: '[PRE0]'
   id: totrans-3
   prefs: []
@@ -27,14 +31,18 @@
   id: totrans-4
   prefs: []
   type: TYPE_NORMAL
+  zh: 封装了对可调用对象的异步执行的`torch._C.Future`的包装器，例如[`rpc_async()`](rpc.html#torch.distributed.rpc.rpc_async
+    "torch.distributed.rpc.rpc_async")。它还公开了一组API来添加回调函数和设置结果。
 - en: Warning
   id: totrans-5
   prefs: []
   type: TYPE_NORMAL
+  zh: 警告
 - en: GPU support is a beta feature, subject to changes.
   id: totrans-6
   prefs: []
   type: TYPE_NORMAL
+  zh: GPU支持是一个测试功能，可能会发生变化。
 - en: '[PRE1]'
   id: totrans-7
   prefs: []
@@ -50,6 +58,8 @@
   id: totrans-8
   prefs: []
   type: TYPE_NORMAL
+  zh: 将给定的回调函数附加到此`Future`，当`Future`完成时将运行该回调。可以向同一个`Future`添加多个回调，但不能保证它们将以何种顺序执行。回调必须接受一个参数，即对此`Future`的引用。回调函数可以使用[`value()`](#torch.futures.Future.value
+    "torch.futures.Future.value")方法获取值。请注意，如果此`Future`已经完成，给定的回调将内联运行。
 - en: We recommend that you use the [`then()`](#torch.futures.Future.then "torch.futures.Future.then")
     method as it provides a way to synchronize after your callback has completed.
     `add_done_callback` can be cheaper if your callback does not return anything.
@@ -58,24 +68,30 @@
   id: totrans-9
   prefs: []
   type: TYPE_NORMAL
+  zh: 我们建议您使用[`then()`](#torch.futures.Future.then "torch.futures.Future.then")方法，因为它提供了在回调完成后同步的方法。如果您的回调不返回任何内容，`add_done_callback`可能更便宜。但是[`then()`](#torch.futures.Future.then
+    "torch.futures.Future.then")和`add_done_callback`在底层使用相同的回调注册API。
 - en: With respect to GPU tensors, this method behaves in the same way as [`then()`](#torch.futures.Future.then
     "torch.futures.Future.then").
   id: totrans-10
   prefs: []
   type: TYPE_NORMAL
+  zh: 就GPU张量而言，此方法的行为与[`then()`](#torch.futures.Future.then "torch.futures.Future.then")相同。
 - en: Parameters
   id: totrans-11
   prefs: []
   type: TYPE_NORMAL
+  zh: 参数
 - en: '**callback** (`Future`) – a `Callable` that takes in one argument, which is
     the reference to this `Future`.'
   id: totrans-12
   prefs: []
   type: TYPE_NORMAL
+  zh: '**callback** (`Future`) – 一个接受一个参数（即对此`Future`的引用）的`Callable`。'
 - en: Note
   id: totrans-13
   prefs: []
   type: TYPE_NORMAL
+  zh: 注意
 - en: Note that if the callback function throws, either through the original future
     being completed with an exception and calling `fut.wait()`, or through other code
     in the callback, error handling must be carefully taken care of. For example,
@@ -85,10 +101,12 @@
   id: totrans-14
   prefs: []
   type: TYPE_NORMAL
+  zh: 请注意，如果回调函数抛出异常，无论是通过原始未来完成异常并调用`fut.wait()`，还是通过回调中的其他代码，都必须小心处理错误处理。例如，如果此回调稍后完成其他未来，那些未来不会被标记为已完成并带有错误，用户需要独立处理完成/等待这些未来。
 - en: 'Example::'
   id: totrans-15
   prefs: []
   type: TYPE_NORMAL
+  zh: '示例::'
 - en: '[PRE2]'
   id: totrans-16
   prefs: []
@@ -104,6 +122,7 @@
   id: totrans-18
   prefs: []
   type: TYPE_NORMAL
+  zh: 如果此`Future`已完成，则返回`True`。如果`Future`有结果或异常，则已完成。
 - en: If the value contains tensors that reside on GPUs, `Future.done()` will return
     `True` even if the asynchronous kernels that are populating those tensors haven’t
     yet completed running on the device, because at such stage the result is already
@@ -112,14 +131,18 @@
   id: totrans-19
   prefs: []
   type: TYPE_NORMAL
+  zh: 如果值包含在GPU上的张量，即使异步内核尚未在设备上完成运行，`Future.done()`将返回`True`，因为在这个阶段结果已经可用，只要执行适当的同步（参见[`wait()`](#torch.futures.Future.wait
+    "torch.futures.Future.wait")）。
 - en: Return type
   id: totrans-20
   prefs: []
   type: TYPE_NORMAL
+  zh: 返回类型
 - en: '[bool](https://docs.python.org/3/library/functions.html#bool "(in Python v3.12)")'
   id: totrans-21
   prefs: []
   type: TYPE_NORMAL
+  zh: '[bool](https://docs.python.org/3/library/functions.html#bool "(in Python v3.12)")'
 - en: '[PRE4]'
   id: totrans-22
   prefs: []
@@ -131,19 +154,24 @@
   id: totrans-23
   prefs: []
   type: TYPE_NORMAL
+  zh: 为此`Future`设置异常，这将标记此`Future`为已完成并触发所有附加的回调。请注意，当在此`Future`上调用wait()/value()时，此处设置的异常将内联引发。
 - en: Parameters
   id: totrans-24
   prefs: []
   type: TYPE_NORMAL
+  zh: 参数
 - en: '**result** ([*BaseException*](https://docs.python.org/3/library/exceptions.html#BaseException
     "(in Python v3.12)")) – the exception for this `Future`.'
   id: totrans-25
   prefs: []
   type: TYPE_NORMAL
+  zh: '**result** ([*BaseException*](https://docs.python.org/3/library/exceptions.html#BaseException
+    "(in Python v3.12)")) – 此`Future`的异常。'
 - en: 'Example::'
   id: totrans-26
   prefs: []
   type: TYPE_NORMAL
+  zh: '示例::'
 - en: '[PRE5]'
   id: totrans-27
   prefs: []
@@ -160,6 +188,7 @@
   id: totrans-29
   prefs: []
   type: TYPE_NORMAL
+  zh: 设置此`Future`的结果，这将标记此`Future`为已完成并触发所有附加的回调。请注意，`Future`不能被标记为已完成两次。
 - en: If the result contains tensors that reside on GPUs, this method can be called
     even if the asynchronous kernels that are populating those tensors haven’t yet
     completed running on the device, provided that the streams on which those kernels

totrans/doc22_061.yaml

 - en: torch.linalg
+  id: totrans-0
   prefs:
   - PREF_H1
   type: TYPE_NORMAL
+  zh: torch.linalg
 - en: 原文：[https://pytorch.org/docs/stable/linalg.html](https://pytorch.org/docs/stable/linalg.html)
+  id: totrans-1
   prefs:
   - PREF_BQ
   type: TYPE_NORMAL
+  zh: 原文：[https://pytorch.org/docs/stable/linalg.html](https://pytorch.org/docs/stable/linalg.html)
 - en: Common linear algebra operations.
+  id: totrans-2
   prefs: []
   type: TYPE_NORMAL
+  zh: 常见线性代数操作。
 - en: See [Linear algebra (torch.linalg)](notes/numerical_accuracy.html#linear-algebra-stability)
     for some common numerical edge-cases.
+  id: totrans-3
   prefs: []
   type: TYPE_NORMAL
+  zh: 查看[线性代数（torch.linalg）](notes/numerical_accuracy.html#linear-algebra-stability)以获取一些常见的数值边界情况。
 - en: '## Matrix Properties'
+  id: totrans-4
   prefs: []
   type: TYPE_NORMAL
+  zh: '## 矩阵属性'
 - en: '| [`norm`](generated/torch.linalg.norm.html#torch.linalg.norm "torch.linalg.norm")
     | Computes a vector or matrix norm. |'
+  id: totrans-5
   prefs: []
   type: TYPE_TB
+  zh: '| [`norm`](generated/torch.linalg.norm.html#torch.linalg.norm "torch.linalg.norm")
+    | 计算向量或矩阵范数。 |'
 - en: '| [`vector_norm`](generated/torch.linalg.vector_norm.html#torch.linalg.vector_norm
     "torch.linalg.vector_norm") | Computes a vector norm. |'
+  id: totrans-6
   prefs: []
   type: TYPE_TB
+  zh: '| [`vector_norm`](generated/torch.linalg.vector_norm.html#torch.linalg.vector_norm
+    "torch.linalg.vector_norm") | 计算向量范数。 |'
 - en: '| [`matrix_norm`](generated/torch.linalg.matrix_norm.html#torch.linalg.matrix_norm
     "torch.linalg.matrix_norm") | Computes a matrix norm. |'
+  id: totrans-7
   prefs: []
   type: TYPE_TB
+  zh: '| [`matrix_norm`](generated/torch.linalg.matrix_norm.html#torch.linalg.matrix_norm
+    "torch.linalg.matrix_norm") | 计算矩阵范数。 |'
 - en: '| [`diagonal`](generated/torch.linalg.diagonal.html#torch.linalg.diagonal "torch.linalg.diagonal")
     | Alias for [`torch.diagonal()`](generated/torch.diagonal.html#torch.diagonal
     "torch.diagonal") with defaults `dim1`= -2, `dim2`= -1. |'
+  id: totrans-8
   prefs: []
   type: TYPE_TB
+  zh: '| [`diagonal`](generated/torch.linalg.diagonal.html#torch.linalg.diagonal "torch.linalg.diagonal")
+    | [`torch.diagonal()`](generated/torch.diagonal.html#torch.diagonal "torch.diagonal")的别名，默认参数
+    `dim1`= -2, `dim2`= -1。 |'
 - en: '| [`det`](generated/torch.linalg.det.html#torch.linalg.det "torch.linalg.det")
     | Computes the determinant of a square matrix. |'
+  id: totrans-9
   prefs: []
   type: TYPE_TB
+  zh: '| [`det`](generated/torch.linalg.det.html#torch.linalg.det "torch.linalg.det")
+    | 计算方阵的行列式。 |'
 - en: '| [`slogdet`](generated/torch.linalg.slogdet.html#torch.linalg.slogdet "torch.linalg.slogdet")
     | Computes the sign and natural logarithm of the absolute value of the determinant
     of a square matrix. |'
+  id: totrans-10
   prefs: []
   type: TYPE_TB
+  zh: '| [`slogdet`](generated/torch.linalg.slogdet.html#torch.linalg.slogdet "torch.linalg.slogdet")
+    | 计算方阵行列式的符号和自然对数的绝对值。 |'
 - en: '| [`cond`](generated/torch.linalg.cond.html#torch.linalg.cond "torch.linalg.cond")
     | Computes the condition number of a matrix with respect to a matrix norm. |'
+  id: totrans-11
   prefs: []
   type: TYPE_TB
+  zh: '| [`cond`](generated/torch.linalg.cond.html#torch.linalg.cond "torch.linalg.cond")
+    | 计算矩阵相对于矩阵范数的条件数。 |'
 - en: '| [`matrix_rank`](generated/torch.linalg.matrix_rank.html#torch.linalg.matrix_rank
     "torch.linalg.matrix_rank") | Computes the numerical rank of a matrix. |'
+  id: totrans-12
   prefs: []
   type: TYPE_TB
+  zh: '| [`matrix_rank`](generated/torch.linalg.matrix_rank.html#torch.linalg.matrix_rank
+    "torch.linalg.matrix_rank") | 计算矩阵的数值秩。 |'
 - en: Decompositions
+  id: totrans-13
   prefs:
   - PREF_H2
   type: TYPE_NORMAL
+  zh: 分解
 - en: '| [`cholesky`](generated/torch.linalg.cholesky.html#torch.linalg.cholesky "torch.linalg.cholesky")
     | Computes the Cholesky decomposition of a complex Hermitian or real symmetric
     positive-definite matrix. |'
+  id: totrans-14
   prefs: []
   type: TYPE_TB
+  zh: '| [`cholesky`](generated/torch.linalg.cholesky.html#torch.linalg.cholesky "torch.linalg.cholesky")
+    | 计算复共轭Hermitian或实对称正定矩阵的Cholesky分解。 |'
 - en: '| [`qr`](generated/torch.linalg.qr.html#torch.linalg.qr "torch.linalg.qr")
     | Computes the QR decomposition of a matrix. |'
+  id: totrans-15
   prefs: []
   type: TYPE_TB
+  zh: '| [`qr`](generated/torch.linalg.qr.html#torch.linalg.qr "torch.linalg.qr")
+    | 计算矩阵的QR分解。 |'
 - en: '| [`lu`](generated/torch.linalg.lu.html#torch.linalg.lu "torch.linalg.lu")
     | Computes the LU decomposition with partial pivoting of a matrix. |'
+  id: totrans-16
   prefs: []
   type: TYPE_TB
+  zh: '| [`lu`](generated/torch.linalg.lu.html#torch.linalg.lu "torch.linalg.lu")
+    | 计算具有部分主元的矩阵LU分解。 |'
 - en: '| [`lu_factor`](generated/torch.linalg.lu_factor.html#torch.linalg.lu_factor
     "torch.linalg.lu_factor") | Computes a compact representation of the LU factorization
     with partial pivoting of a matrix. |'
+  id: totrans-17
   prefs: []
   type: TYPE_TB
+  zh: '| [`lu_factor`](generated/torch.linalg.lu_factor.html#torch.linalg.lu_factor
+    "torch.linalg.lu_factor") | 计算具有部分主元的矩阵LU分解的紧凑表示。 |'
 - en: '| [`eig`](generated/torch.linalg.eig.html#torch.linalg.eig "torch.linalg.eig")
     | Computes the eigenvalue decomposition of a square matrix if it exists. |'
+  id: totrans-18
   prefs: []
   type: TYPE_TB
+  zh: '| [`eig`](generated/torch.linalg.eig.html#torch.linalg.eig "torch.linalg.eig")
+    | 计算方阵的特征值分解（如果存在）。 |'
 - en: '| [`eigvals`](generated/torch.linalg.eigvals.html#torch.linalg.eigvals "torch.linalg.eigvals")
     | Computes the eigenvalues of a square matrix. |'
+  id: totrans-19
   prefs: []
   type: TYPE_TB
+  zh: '| [`eigvals`](generated/torch.linalg.eigvals.html#torch.linalg.eigvals "torch.linalg.eigvals")
+    | 计算方阵的特征值。 |'
 - en: '| [`eigh`](generated/torch.linalg.eigh.html#torch.linalg.eigh "torch.linalg.eigh")
     | Computes the eigenvalue decomposition of a complex Hermitian or real symmetric
     matrix. |'
+  id: totrans-20
   prefs: []
   type: TYPE_TB
+  zh: '| [`eigh`](generated/torch.linalg.eigh.html#torch.linalg.eigh "torch.linalg.eigh")
+    | 计算复共轭Hermitian或实对称矩阵的特征值分解。 |'
 - en: '| [`eigvalsh`](generated/torch.linalg.eigvalsh.html#torch.linalg.eigvalsh "torch.linalg.eigvalsh")
     | Computes the eigenvalues of a complex Hermitian or real symmetric matrix. |'
+  id: totrans-21
   prefs: []
   type: TYPE_TB
+  zh: '| [`eigvalsh`](generated/torch.linalg.eigvalsh.html#torch.linalg.eigvalsh "torch.linalg.eigvalsh")
+    | 计算复共轭Hermitian或实对称矩阵的特征值。 |'
 - en: '| [`svd`](generated/torch.linalg.svd.html#torch.linalg.svd "torch.linalg.svd")
     | Computes the singular value decomposition (SVD) of a matrix. |'
+  id: totrans-22
   prefs: []
   type: TYPE_TB
+  zh: '| [`svd`](generated/torch.linalg.svd.html#torch.linalg.svd "torch.linalg.svd")
+    | 计算矩阵的奇异值分解（SVD）。 |'
 - en: '| [`svdvals`](generated/torch.linalg.svdvals.html#torch.linalg.svdvals "torch.linalg.svdvals")
     | Computes the singular values of a matrix. |'
+  id: totrans-23
   prefs: []
   type: TYPE_TB
+  zh: '| [`svdvals`](generated/torch.linalg.svdvals.html#torch.linalg.svdvals "torch.linalg.svdvals")
+    | 计算矩阵的奇异值。 |'
 - en: '## Solvers'
+  id: totrans-24
   prefs: []
   type: TYPE_NORMAL
+  zh: '## 求解器'
 - en: '| [`solve`](generated/torch.linalg.solve.html#torch.linalg.solve "torch.linalg.solve")
     | Computes the solution of a square system of linear equations with a unique solution.
     |'
+  id: totrans-25
   prefs: []
   type: TYPE_TB
+  zh: '| [`solve`](generated/torch.linalg.solve.html#torch.linalg.solve "torch.linalg.solve")
+    | 计算具有唯一解的方阵线性方程组的解。 |'
 - en: '| [`solve_triangular`](generated/torch.linalg.solve_triangular.html#torch.linalg.solve_triangular
     "torch.linalg.solve_triangular") | Computes the solution of a triangular system
     of linear equations with a unique solution. |'
+  id: totrans-26
   prefs: []
   type: TYPE_TB
+  zh: '| [`solve_triangular`](generated/torch.linalg.solve_triangular.html#torch.linalg.solve_triangular
+    "torch.linalg.solve_triangular") | 计算具有唯一解的三角线性方程组的解。 |'
 - en: '| [`lu_solve`](generated/torch.linalg.lu_solve.html#torch.linalg.lu_solve "torch.linalg.lu_solve")
     | Computes the solution of a square system of linear equations with a unique solution
     given an LU decomposition. |'
+  id: totrans-27
   prefs: []
   type: TYPE_TB
+  zh: '| [`lu_solve`](generated/torch.linalg.lu_solve.html#torch.linalg.lu_solve "torch.linalg.lu_solve")
+    | 在给定LU分解的情况下计算具有唯一解的方阵线性方程组的解。 |'
 - en: '| [`lstsq`](generated/torch.linalg.lstsq.html#torch.linalg.lstsq "torch.linalg.lstsq")
     | Computes a solution to the least squares problem of a system of linear equations.
     |  ## Inverses'
+  id: totrans-28
   prefs: []
   type: TYPE_NORMAL
+  zh: '| [`lstsq`](generated/torch.linalg.lstsq.html#torch.linalg.lstsq "torch.linalg.lstsq")
+    | 计算线性方程组的最小二乘解。 |  ## 逆运算'
 - en: '| [`inv`](generated/torch.linalg.inv.html#torch.linalg.inv "torch.linalg.inv")
     | Computes the inverse of a square matrix if it exists. |'
+  id: totrans-29
   prefs: []
   type: TYPE_TB
+  zh: '| [`inv`](generated/torch.linalg.inv.html#torch.linalg.inv "torch.linalg.inv")
+    | 计算方阵的逆矩阵（如果存在）。 |'
 - en: '| [`pinv`](generated/torch.linalg.pinv.html#torch.linalg.pinv "torch.linalg.pinv")
     | Computes the pseudoinverse (Moore-Penrose inverse) of a matrix. |'
+  id: totrans-30
   prefs: []
   type: TYPE_TB
+  zh: '| [`pinv`](generated/torch.linalg.pinv.html#torch.linalg.pinv "torch.linalg.pinv")
+    | 计算矩阵的伪逆（Moore-Penrose 逆）。 |'
 - en: Matrix Functions
+  id: totrans-31
   prefs:
   - PREF_H2
   type: TYPE_NORMAL
+  zh: 矩阵函数
 - en: '| [`matrix_exp`](generated/torch.linalg.matrix_exp.html#torch.linalg.matrix_exp
     "torch.linalg.matrix_exp") | Computes the matrix exponential of a square matrix.
     |'
+  id: totrans-32
   prefs: []
   type: TYPE_TB
+  zh: '| [`matrix_exp`](generated/torch.linalg.matrix_exp.html#torch.linalg.matrix_exp
+    "torch.linalg.matrix_exp") | 计算方阵的矩阵指数。 |'
 - en: '| [`matrix_power`](generated/torch.linalg.matrix_power.html#torch.linalg.matrix_power
     "torch.linalg.matrix_power") | Computes the n-th power of a square matrix for
     an integer n. |'
+  id: totrans-33
   prefs: []
   type: TYPE_TB
+  zh: '| [`matrix_power`](generated/torch.linalg.matrix_power.html#torch.linalg.matrix_power
+    "torch.linalg.matrix_power") | 计算整数 n 的方阵的 n 次幂。 |'
 - en: Matrix Products
+  id: totrans-34
   prefs:
   - PREF_H2
   type: TYPE_NORMAL
+  zh: 矩阵乘积
 - en: '| [`cross`](generated/torch.linalg.cross.html#torch.linalg.cross "torch.linalg.cross")
     | Computes the cross product of two 3-dimensional vectors. |'
+  id: totrans-35
   prefs: []
   type: TYPE_TB
+  zh: '| [`cross`](generated/torch.linalg.cross.html#torch.linalg.cross "torch.linalg.cross")
+    | 计算两个三维向量的叉积。 |'
 - en: '| [`matmul`](generated/torch.linalg.matmul.html#torch.linalg.matmul "torch.linalg.matmul")
     | Alias for [`torch.matmul()`](generated/torch.matmul.html#torch.matmul "torch.matmul")
     |'
+  id: totrans-36
   prefs: []
   type: TYPE_TB
+  zh: '| [`matmul`](generated/torch.linalg.matmul.html#torch.linalg.matmul "torch.linalg.matmul")
+    | [`torch.matmul()`](generated/torch.matmul.html#torch.matmul "torch.matmul")
+    的别名 |'
 - en: '| [`vecdot`](generated/torch.linalg.vecdot.html#torch.linalg.vecdot "torch.linalg.vecdot")
     | Computes the dot product of two batches of vectors along a dimension. |'
+  id: totrans-37
   prefs: []
   type: TYPE_TB
+  zh: '| [`vecdot`](generated/torch.linalg.vecdot.html#torch.linalg.vecdot "torch.linalg.vecdot")
+    | 计算沿着维度的两批向量的点积。 |'
 - en: '| [`multi_dot`](generated/torch.linalg.multi_dot.html#torch.linalg.multi_dot
     "torch.linalg.multi_dot") | Efficiently multiplies two or more matrices by reordering
     the multiplications so that the fewest arithmetic operations are performed. |'
+  id: totrans-38
   prefs: []
   type: TYPE_TB
+  zh: '| [`multi_dot`](generated/torch.linalg.multi_dot.html#torch.linalg.multi_dot
+    "torch.linalg.multi_dot") | 通过重新排列乘法，使得执行最少的算术运算，高效地将两个或多个矩阵相乘。 |'
 - en: '| [`householder_product`](generated/torch.linalg.householder_product.html#torch.linalg.householder_product
     "torch.linalg.householder_product") | Computes the first n columns of a product
     of Householder matrices. |'
+  id: totrans-39
   prefs: []
   type: TYPE_TB
+  zh: '| [`householder_product`](generated/torch.linalg.householder_product.html#torch.linalg.householder_product
+    "torch.linalg.householder_product") | 计算 Householder 矩阵的前 n 列的乘积。 |'
 - en: Tensor Operations
+  id: totrans-40
   prefs:
   - PREF_H2
   type: TYPE_NORMAL
+  zh: 张量操作
 - en: '| [`tensorinv`](generated/torch.linalg.tensorinv.html#torch.linalg.tensorinv
     "torch.linalg.tensorinv") | Computes the multiplicative inverse of [`torch.tensordot()`](generated/torch.tensordot.html#torch.tensordot
     "torch.tensordot"). |'
+  id: totrans-41
   prefs: []
   type: TYPE_TB
+  zh: '| [`tensorinv`](generated/torch.linalg.tensorinv.html#torch.linalg.tensorinv
+    "torch.linalg.tensorinv") | 计算 [`torch.tensordot()`](generated/torch.tensordot.html#torch.tensordot
+    "torch.tensordot") 的乘法逆。 |'
 - en: '| [`tensorsolve`](generated/torch.linalg.tensorsolve.html#torch.linalg.tensorsolve
     "torch.linalg.tensorsolve") | Computes the solution X to the system torch.tensordot(A,
     X) = B. |'
+  id: totrans-42
   prefs: []
   type: TYPE_TB
+  zh: '| [`tensorsolve`](generated/torch.linalg.tensorsolve.html#torch.linalg.tensorsolve
+    "torch.linalg.tensorsolve") | 计算系统 torch.tensordot(A, X) = B 的解 X。 |'
 - en: Misc
+  id: totrans-43
   prefs:
   - PREF_H2
   type: TYPE_NORMAL
+  zh: 其他
 - en: '| [`vander`](generated/torch.linalg.vander.html#torch.linalg.vander "torch.linalg.vander")
     | Generates a Vandermonde matrix. |'
+  id: totrans-44
   prefs: []
   type: TYPE_TB
+  zh: '| [`vander`](generated/torch.linalg.vander.html#torch.linalg.vander "torch.linalg.vander")
+    | 生成 Vandermonde 矩阵。 |'
 - en: Experimental Functions
+  id: totrans-45
   prefs:
   - PREF_H2
   type: TYPE_NORMAL
+  zh: 实验性功能
 - en: '| [`cholesky_ex`](generated/torch.linalg.cholesky_ex.html#torch.linalg.cholesky_ex
     "torch.linalg.cholesky_ex") | Computes the Cholesky decomposition of a complex
     Hermitian or real symmetric positive-definite matrix. |'
+  id: totrans-46
   prefs: []
   type: TYPE_TB
+  zh: '| [`cholesky_ex`](generated/torch.linalg.cholesky_ex.html#torch.linalg.cholesky_ex
+    "torch.linalg.cholesky_ex") | 计算复 Hermite 或实对称正定矩阵的 Cholesky 分解。 |'
 - en: '| [`inv_ex`](generated/torch.linalg.inv_ex.html#torch.linalg.inv_ex "torch.linalg.inv_ex")
     | Computes the inverse of a square matrix if it is invertible. |'
+  id: totrans-47
   prefs: []
   type: TYPE_TB
+  zh: '| [`inv_ex`](generated/torch.linalg.inv_ex.html#torch.linalg.inv_ex "torch.linalg.inv_ex")
+    | 计算方阵的逆矩阵（如果可逆）。 |'
 - en: '| [`solve_ex`](generated/torch.linalg.solve_ex.html#torch.linalg.solve_ex "torch.linalg.solve_ex")
     | A version of [`solve()`](generated/torch.linalg.solve.html#torch.linalg.solve
     "torch.linalg.solve") that does not perform error checks unless `check_errors`=
     True. |'
+  id: totrans-48
   prefs: []
   type: TYPE_TB
+  zh: '| [`solve_ex`](generated/torch.linalg.solve_ex.html#torch.linalg.solve_ex "torch.linalg.solve_ex")
+    | [`solve()`](generated/torch.linalg.solve.html#torch.linalg.solve "torch.linalg.solve")
+    的一个版本，除非 `check_errors`= True，否则不执行错误检查。 |'
 - en: '| [`lu_factor_ex`](generated/torch.linalg.lu_factor_ex.html#torch.linalg.lu_factor_ex
     "torch.linalg.lu_factor_ex") | This is a version of [`lu_factor()`](generated/torch.linalg.lu_factor.html#torch.linalg.lu_factor
     "torch.linalg.lu_factor") that does not perform error checks unless `check_errors`=
     True. |'
+  id: totrans-49
   prefs: []
   type: TYPE_TB
+  zh: '| [`lu_factor_ex`](generated/torch.linalg.lu_factor_ex.html#torch.linalg.lu_factor_ex
+    "torch.linalg.lu_factor_ex") | 这是 [`lu_factor()`](generated/torch.linalg.lu_factor.html#torch.linalg.lu_factor
+    "torch.linalg.lu_factor") 的一个版本，除非 `check_errors`= True，否则不执行错误检查。 |'
 - en: '| [`ldl_factor`](generated/torch.linalg.ldl_factor.html#torch.linalg.ldl_factor
     "torch.linalg.ldl_factor") | Computes a compact representation of the LDL factorization
     of a Hermitian or symmetric (possibly indefinite) matrix. |'
+  id: totrans-50
   prefs: []
   type: TYPE_TB
+  zh: '| [`ldl_factor`](generated/torch.linalg.ldl_factor.html#torch.linalg.ldl_factor
+    "torch.linalg.ldl_factor") | 计算 Hermite 或对称（可能不定）矩阵的 LDL 分解的紧凑表示。 |'
 - en: '| [`ldl_factor_ex`](generated/torch.linalg.ldl_factor_ex.html#torch.linalg.ldl_factor_ex
     "torch.linalg.ldl_factor_ex") | This is a version of [`ldl_factor()`](generated/torch.linalg.ldl_factor.html#torch.linalg.ldl_factor
     "torch.linalg.ldl_factor") that does not perform error checks unless `check_errors`=
     True. |'
+  id: totrans-51
   prefs: []
   type: TYPE_TB
+  zh: '| [`ldl_factor_ex`](generated/torch.linalg.ldl_factor_ex.html#torch.linalg.ldl_factor_ex
+    "torch.linalg.ldl_factor_ex") | 这是 [`ldl_factor()`](generated/torch.linalg.ldl_factor.html#torch.linalg.ldl_factor
+    "torch.linalg.ldl_factor") 的一个版本，除非 `check_errors`= True，否则不执行错误检查。 |'
 - en: '| [`ldl_solve`](generated/torch.linalg.ldl_solve.html#torch.linalg.ldl_solve
     "torch.linalg.ldl_solve") | Computes the solution of a system of linear equations
     using the LDL factorization. |'
+  id: totrans-52
   prefs: []
   type: TYPE_TB
+  zh: '| [`ldl_solve`](generated/torch.linalg.ldl_solve.html#torch.linalg.ldl_solve
+    "torch.linalg.ldl_solve") | 使用 LDL 分解计算线性方程组的解。 |'

totrans/doc22_062.yaml

 - en: torch.monitor
+  id: totrans-0
   prefs:
   - PREF_H1
   type: TYPE_NORMAL
+  zh: torch.monitor
 - en: 原文：[https://pytorch.org/docs/stable/monitor.html](https://pytorch.org/docs/stable/monitor.html)
+  id: totrans-1
   prefs:
   - PREF_BQ
   type: TYPE_NORMAL
+  zh: 原文：[https://pytorch.org/docs/stable/monitor.html](https://pytorch.org/docs/stable/monitor.html)
 - en: Warning
+  id: totrans-2
   prefs: []
   type: TYPE_NORMAL
+  zh: 警告
 - en: This module is a prototype release, and its interfaces and functionality may
     change without warning in future PyTorch releases.
+  id: totrans-3
   prefs: []
   type: TYPE_NORMAL
+  zh: 此模块是原型版本，其接口和功能可能在未来的PyTorch版本中发生变化而没有警告。
 - en: '`torch.monitor` provides an interface for logging events and counters from
     PyTorch.'
+  id: totrans-4
   prefs: []
   type: TYPE_NORMAL
+  zh: '`torch.monitor`提供了一个接口，用于从PyTorch记录事件和计数器。'
 - en: The stat interfaces are designed to be used for tracking high level metrics
     that are periodically logged out to be used for monitoring system performance.
     Since the stats aggregate with a specific window size you can log to them from
     critical loops with minimal performance impact.
+  id: totrans-5
   prefs: []
   type: TYPE_NORMAL
+  zh: 统计接口旨在用于跟踪定期记录的高级指标，以用于监视系统性能。由于统计数据与特定窗口大小聚合，因此可以从关键循环中记录它们，对性能影响最小。
 - en: For more infrequent events or values such as loss, accuracy, usage tracking
     the event interface can be directly used.
+  id: totrans-6
   prefs: []
   type: TYPE_NORMAL
+  zh: 对于更不频繁的事件或值，如损失、准确性、使用跟踪，可以直接使用事件接口。
 - en: Event handlers can be registered to handle the events and pass them to an external
     event sink.
+  id: totrans-7
   prefs: []
   type: TYPE_NORMAL
+  zh: 事件处理程序可以注册以处理事件并将其传递给外部事件接收器。
 - en: '## API Reference'
+  id: totrans-8
   prefs: []
   type: TYPE_NORMAL
+  zh: '## API参考'
 - en: '[PRE0]'
+  id: totrans-9
   prefs: []
   type: TYPE_PRE
+  zh: '[PRE0]'
 - en: These are types of aggregations that can be used to accumulate stats.
+  id: totrans-10
   prefs:
   - PREF_BQ
   type: TYPE_NORMAL
+  zh: 这些是可用于累积统计数据的聚合类型。
 - en: 'Members:'
+  id: totrans-11
   prefs: []
   type: TYPE_NORMAL
+  zh: 成员：
 - en: 'VALUE :'
+  id: totrans-12
   prefs:
   - PREF_BQ
   type: TYPE_NORMAL
+  zh: VALUE：
 - en: ''
+  id: totrans-13
   prefs:
   - PREF_BQ
   type: TYPE_NORMAL
 - en: VALUE returns the last value to be added.
+  id: totrans-14
   prefs:
   - PREF_BQ
   type: TYPE_NORMAL
+  zh: VALUE返回最后添加的值。
 - en: ''
+  id: totrans-15
   prefs:
   - PREF_BQ
   type: TYPE_NORMAL
 - en: 'MEAN :'
+  id: totrans-16
   prefs:
   - PREF_BQ
   type: TYPE_NORMAL
+  zh: MEAN：
 - en: ''
+  id: totrans-17
   prefs:
   - PREF_BQ
   type: TYPE_NORMAL
 - en: MEAN computes the arithmetic mean of all the added values.
+  id: totrans-18
   prefs:
   - PREF_BQ
   type: TYPE_NORMAL
+  zh: MEAN计算所有添加值的算术平均值。
 - en: ''
+  id: totrans-19
   prefs:
   - PREF_BQ
   type: TYPE_NORMAL
 - en: 'COUNT :'
+  id: totrans-20
   prefs:
   - PREF_BQ
   type: TYPE_NORMAL
+  zh: COUNT：
 - en: ''
+  id: totrans-21
   prefs:
   - PREF_BQ
   type: TYPE_NORMAL
 - en: COUNT returns the total number of added values.
+  id: totrans-22
   prefs:
   - PREF_BQ
   type: TYPE_NORMAL
+  zh: COUNT返回添加值的总数。
 - en: ''
+  id: totrans-23
   prefs:
   - PREF_BQ
   type: TYPE_NORMAL
 - en: 'SUM :'
+  id: totrans-24
   prefs:
   - PREF_BQ
   type: TYPE_NORMAL
+  zh: SUM：
 - en: ''
+  id: totrans-25
   prefs:
   - PREF_BQ
   type: TYPE_NORMAL
 - en: SUM returns the sum of the added values.
+  id: totrans-26
   prefs:
   - PREF_BQ
   type: TYPE_NORMAL
+  zh: SUM返回添加值的总和。
 - en: ''
+  id: totrans-27
   prefs:
   - PREF_BQ
   type: TYPE_NORMAL
 - en: 'MAX :'
+  id: totrans-28
   prefs:
   - PREF_BQ
   type: TYPE_NORMAL
+  zh: MAX：
 - en: ''
+  id: totrans-29
   prefs:
   - PREF_BQ
   type: TYPE_NORMAL
 - en: MAX returns the max of the added values.
+  id: totrans-30
   prefs:
   - PREF_BQ
   type: TYPE_NORMAL
+  zh: MAX返回添加值的最大值。
 - en: ''
+  id: totrans-31
   prefs:
   - PREF_BQ
   type: TYPE_NORMAL
 - en: 'MIN :'
+  id: totrans-32
   prefs:
   - PREF_BQ
   type: TYPE_NORMAL
+  zh: MIN：
 - en: ''
+  id: totrans-33
   prefs:
   - PREF_BQ
   type: TYPE_NORMAL
 - en: MIN returns the min of the added values.
+  id: totrans-34
   prefs:
   - PREF_BQ
   type: TYPE_NORMAL
+  zh: MIN返回添加值的最小值。
 - en: '[PRE1]'
+  id: totrans-35
   prefs: []
   type: TYPE_PRE
+  zh: '[PRE1]'
 - en: '[PRE2]'
+  id: totrans-36
   prefs: []
   type: TYPE_PRE
+  zh: '[PRE2]'
 - en: Stat is used to compute summary statistics in a performant way over fixed intervals.
     Stat logs the statistics as an Event once every `window_size` duration. When the
     window closes the stats are logged via the event handlers as a `torch.monitor.Stat`
     event.
+  id: totrans-37
   prefs: []
   type: TYPE_NORMAL
+  zh: Stat用于以高效的方式在固定间隔内计算摘要统计信息。Stat每隔`window_size`持续时间记录一次统计信息作为事件。当窗口关闭时，统计信息将通过事件处理程序作为`torch.monitor.Stat`事件记录。
 - en: '`window_size` should be set to something relatively high to avoid a huge number
     of events being logged. Ex: 60s. Stat uses millisecond precision.'
+  id: totrans-38
   prefs: []
   type: TYPE_NORMAL
+  zh: '`window_size`应设置为相对较高的值，以避免记录大量事件。例如：60秒。Stat使用毫秒精度。'
 - en: If `max_samples` is set, the stat will cap the number of samples per window
     by discarding add calls once `max_samples` adds have occurred. If it’s not set,
     all `add` calls during the window will be included. This is an optional field
     to make aggregations more directly comparable across windows when the number of
     samples might vary.
+  id: totrans-39
   prefs: []
   type: TYPE_NORMAL
+  zh: 如果设置了`max_samples`，则统计数据将通过在发生`max_samples`次添加后丢弃添加调用来限制每个窗口的样本数量。如果未设置，窗口期间的所有`add`调用都将被包括在内。当样本数量可能变化时，这是一个可选字段，使聚合更直接可比较。
 - en: When the Stat is destructed it will log any remaining data even if the window
     hasn’t elapsed.
+  id: totrans-40
   prefs: []
   type: TYPE_NORMAL
+  zh: 当Stat被销毁时，即使窗口尚未过去，也会记录任何剩余数据。
 - en: '[PRE3]'
+  id: totrans-41
   prefs: []
   type: TYPE_PRE
+  zh: '[PRE3]'
 - en: Constructs the `Stat`.
+  id: totrans-42
   prefs: []
   type: TYPE_NORMAL
+  zh: 构造`Stat`。
 - en: '[PRE4]'
+  id: totrans-43
   prefs: []
   type: TYPE_PRE
+  zh: '[PRE4]'
 - en: Adds a value to the stat to be aggregated according to the configured stat type
     and aggregations.
+  id: totrans-44
   prefs: []
   type: TYPE_NORMAL
+  zh: 将一个值添加到要根据配置的统计类型和聚合进行聚合的统计数据中。
 - en: '[PRE5]'
+  id: totrans-45
   prefs: []
   type: TYPE_PRE
+  zh: '[PRE5]'
 - en: Number of data points that have currently been collected. Resets once the event
     has been logged.
+  id: totrans-46
   prefs: []
   type: TYPE_NORMAL
+  zh: 当前已收集的数据点数量。一旦事件已记录，将重置。
 - en: '[PRE6]'
+  id: totrans-47
   prefs: []
   type: TYPE_PRE
+  zh: '[PRE6]'
 - en: Returns the current value of the stat, primarily for testing purposes. If the
     stat has logged and no additional values have been added this will be zero.
+  id: totrans-48
   prefs: []
   type: TYPE_NORMAL
+  zh: 返回统计数据的当前值，主要用于测试目的。如果统计数据已记录且未添加任何额外值，则该值将为零。
 - en: '[PRE7]'
+  id: totrans-49
   prefs: []
   type: TYPE_PRE
+  zh: '[PRE7]'
 - en: The name of the stat that was set during creation.
+  id: totrans-50
   prefs: []
   type: TYPE_NORMAL
+  zh: 在创建时设置的统计名称。
 - en: '[PRE8]'
+  id: totrans-51
   prefs: []
   type: TYPE_PRE
+  zh: '[PRE8]'
 - en: data_value_t is one of `str`, `float`, `int`, `bool`.
+  id: totrans-52
   prefs: []
   type: TYPE_NORMAL
+  zh: data_value_t是`str`、`float`、`int`、`bool`之一。
 - en: '[PRE9]'
+  id: totrans-53
   prefs: []
   type: TYPE_PRE
+  zh: '[PRE9]'
 - en: Event represents a specific typed event to be logged. This can represent high-level
     data points such as loss or accuracy per epoch or more low-level aggregations
     such as through the Stats provided through this library.
+  id: totrans-54
   prefs: []
   type: TYPE_NORMAL
+  zh: Event表示要记录的特定类型事件。这可以表示每个时代的损失或准确性等高级数据点，或者通过此库提供的统计数据进行更低级别的聚合。
 - en: All Events of the same type should have the same name so downstream handlers
     can correctly process them.
+  id: totrans-55
   prefs: []
   type: TYPE_NORMAL
+  zh: 所有相同类型的事件应具有相同的名称，以便下游处理程序可以正确处理它们。
 - en: '[PRE10]'
+  id: totrans-56
   prefs: []
   type: TYPE_PRE
+  zh: '[PRE10]'
 - en: Constructs the `Event`.
+  id: totrans-57
   prefs: []
   type: TYPE_NORMAL
+  zh: 构造`Event`。
 - en: '[PRE11]'
+  id: totrans-58
   prefs: []
   type: TYPE_PRE
+  zh: '[PRE11]'
 - en: The structured data contained within the `Event`.
+  id: totrans-59
   prefs: []
   type: TYPE_NORMAL
+  zh: 包含在`Event`中的结构化数据。
 - en: '[PRE12]'
+  id: totrans-60
   prefs: []
   type: TYPE_PRE
+  zh: '[PRE12]'
 - en: The name of the `Event`.
+  id: totrans-61
   prefs: []
   type: TYPE_NORMAL
+  zh: '`Event`的名称。'
 - en: '[PRE13]'
+  id: totrans-62
   prefs: []
   type: TYPE_PRE
+  zh: '[PRE13]'
 - en: The timestamp when the `Event` happened.
+  id: totrans-63
   prefs: []
   type: TYPE_NORMAL
+  zh: 事件发生时的时间戳。
 - en: '[PRE14]'
+  id: totrans-64
   prefs: []
   type: TYPE_PRE
+  zh: '[PRE14]'
 - en: EventHandlerHandle is a wrapper type returned by `register_event_handler` used
     to unregister the handler via `unregister_event_handler`. This cannot be directly
     initialized.
+  id: totrans-65
   prefs: []
   type: TYPE_NORMAL
+  zh: EventHandlerHandle是由`register_event_handler`返回的包装类型，用于通过`unregister_event_handler`取消注册处理程序。不能直接初始化。
 - en: '[PRE15]'
+  id: totrans-66
   prefs: []
   type: TYPE_PRE
+  zh: '[PRE15]'
 - en: log_event logs the specified event to all of the registered event handlers.
     It’s up to the event handlers to log the event out to the corresponding event
     sink.
+  id: totrans-67
   prefs: []
   type: TYPE_NORMAL
+  zh: log_event将指定的事件记录到所有已注册的事件处理程序中。由事件处理程序负责将事件记录到相应的事件接收器。
 - en: If there are no event handlers registered this method is a no-op.
+  id: totrans-68
   prefs: []
   type: TYPE_NORMAL
+  zh: 如果没有注册事件处理程序，则此方法不执行任何操作。
 - en: '[PRE16]'
+  id: totrans-69
   prefs: []
   type: TYPE_PRE
+  zh: '[PRE16]'
 - en: register_event_handler registers a callback to be called whenever an event is
     logged via `log_event`. These handlers should avoid blocking the main thread since
     that may interfere with training as they run during the `log_event` call.
+  id: totrans-70
   prefs: []
   type: TYPE_NORMAL
+  zh: register_event_handler注册一个回调，每当通过`log_event`记录事件时都会调用该回调。这些处理程序应避免阻塞主线程，因为这可能会干扰训练，因为它们在`log_event`调用期间运行。
 - en: '[PRE17]'
+  id: totrans-71
   prefs: []
   type: TYPE_PRE
+  zh: '[PRE17]'
 - en: unregister_event_handler unregisters the `EventHandlerHandle` returned after
     calling `register_event_handler`. After this returns the event handler will no
     longer receive events.
+  id: totrans-72
   prefs: []
   type: TYPE_NORMAL
+  zh: unregister_event_handler取消注册在调用`register_event_handler`后返回的`EventHandlerHandle`。完成后，事件处理程序将不再接收事件。
 - en: '[PRE18]'
+  id: totrans-73
   prefs: []
   type: TYPE_PRE
+  zh: '[PRE18]'
 - en: TensorboardEventHandler is an event handler that will write known events to
     the provided SummaryWriter.
+  id: totrans-74
   prefs: []
   type: TYPE_NORMAL
+  zh: TensorboardEventHandler是一个事件处理程序，将已知事件写入提供的SummaryWriter。
 - en: This currently only supports `torch.monitor.Stat` events which are logged as
     scalars.
+  id: totrans-75
   prefs: []
   type: TYPE_NORMAL
+  zh: 目前仅支持作为标量记录的`torch.monitor.Stat`事件。
 - en: Example
+  id: totrans-76
   prefs: []
   type: TYPE_NORMAL
+  zh: 示例
 - en: '[PRE19]'
+  id: totrans-77
   prefs: []
   type: TYPE_PRE
+  zh: '[PRE19]'
 - en: '[PRE20]'
+  id: totrans-78
   prefs: []
   type: TYPE_PRE
+  zh: '[PRE20]'
 - en: Constructs the `TensorboardEventHandler`.
+  id: totrans-79
   prefs: []
   type: TYPE_NORMAL
+  zh: 构造`TensorboardEventHandler`。