diff --git a/docs/api/api_python/mindspore.ops.primitive.rst b/docs/api/api_python/mindspore.ops.primitive.rst index ab158db3161..b187e5ece13 100644 --- a/docs/api/api_python/mindspore.ops.primitive.rst +++ b/docs/api/api_python/mindspore.ops.primitive.rst @@ -67,6 +67,7 @@ MindSpore中 `mindspore.ops` 接口与上一版本相比，新增、删除和支 mindspore.ops.FractionalMaxPool mindspore.ops.FractionalMaxPoolWithFixedKsize mindspore.ops.FractionalMaxPool3DWithFixedKsize + mindspore.ops.GridSampler2D mindspore.ops.GridSampler3D mindspore.ops.LayerNorm mindspore.ops.LRN @@ -196,7 +197,6 @@ MindSpore中 `mindspore.ops` 接口与上一版本相比，新增、删除和支 :template: classtemplate.rst mindspore.ops.ComputeAccidentalHits - mindspore.ops.GridSampler2D mindspore.ops.LogUniformCandidateSampler mindspore.ops.UniformCandidateSampler mindspore.ops.UpsampleNearest3D diff --git a/docs/api/api_python/mindspore/mindspore.load.rst b/docs/api/api_python/mindspore/mindspore.load.rst index 7cee74ad0c9..4a207bb8f8f 100644 --- a/docs/api/api_python/mindspore/mindspore.load.rst +++ b/docs/api/api_python/mindspore/mindspore.load.rst @@ -13,8 +13,10 @@ mindspore.load - **dec_key** (bytes) - 用于解密的字节类型密钥。有效长度为 16、24 或 32。 - **dec_mode** (Union[str, function]) - 指定解密模式，设置dec_key时生效。可选项：'AES-GCM' | 'SM4-CBC' | 'AES-CBC' ｜ 自定义解密函数。默认值："AES-GCM"。 + - 关于使用自定义解密加载的详情，请查看 `教程 `_。 - - **obf_func** (function) - 导入混淆模型所需要的函数，可以参考 `obfuscate_model() ` 了解详情。 + + - **obf_func** (function) - 导入混淆模型所需要的函数，可以参考 `obfuscate_model() `_ 了解详情。 返回： GraphCell，一个可以由 `GraphCell` 构成的可执行的编译图。 diff --git a/docs/api/api_python/mindspore/mindspore.load_distributed_checkpoint.rst b/docs/api/api_python/mindspore/mindspore.load_distributed_checkpoint.rst index f8bc7c7bb64..d6d9decd9be 100644 --- a/docs/api/api_python/mindspore/mindspore.load_distributed_checkpoint.rst +++ b/docs/api/api_python/mindspore/mindspore.load_distributed_checkpoint.rst @@ -3,7 +3,7 @@ mindspore.load_distributed_checkpoint .. py:function:: mindspore.load_distributed_checkpoint(network, checkpoint_filenames, predict_strategy=None, train_strategy_filename=None, strict_load=False, dec_key=None, dec_mode='AES-GCM') - 给分布式预测加载checkpoint文件到网络。用于分布式推理。关于分布式推理的细节，请参考：https://www.mindspore.cn/tutorials/experts/zh-CN/master/parallel/distributed_inference.html。 + 给分布式预测加载checkpoint文件到网络。用于分布式推理。关于分布式推理的细节，请参考： `分布式推理 `_ 。 参数： - **network** (Cell) - 分布式预测网络。 diff --git a/docs/api/api_python/mindspore/mindspore.reset_ps_context.rst b/docs/api/api_python/mindspore/mindspore.reset_ps_context.rst index a789f664d65..aed31742a8d 100644 --- a/docs/api/api_python/mindspore/mindspore.reset_ps_context.rst +++ b/docs/api/api_python/mindspore/mindspore.reset_ps_context.rst @@ -3,4 +3,4 @@ mindspore.reset_ps_context .. py:function:: mindspore.reset_ps_context() - 将参数服务器训练模式上下文中的属性重置为默认值。各字段的含义及其默认值见'set_ps_context'接口。 + 将参数服务器训练模式上下文中的属性重置为默认值。各字段的含义及其默认值见 :func:`mindspore.set_ps_context` 接口。 diff --git a/docs/api/api_python/nn/mindspore.nn.GetNextSingleOp.rst b/docs/api/api_python/nn/mindspore.nn.GetNextSingleOp.rst index 02151aed415..37769f6a9bf 100644 --- a/docs/api/api_python/nn/mindspore.nn.GetNextSingleOp.rst +++ b/docs/api/api_python/nn/mindspore.nn.GetNextSingleOp.rst @@ -3,7 +3,7 @@ mindspore.nn.GetNextSingleOp .. py:class:: mindspore.nn.GetNextSingleOp(dataset_types, dataset_shapes, queue_name) - 用于获取下一条数据的Cell。更详细的信息请参考 `mindspore.ops.GetNext` 。 + 用于获取下一条数据的Cell。更详细的信息请参考 :class:`mindspore.ops.GetNext` 。 参数： - **dataset_types** (list[:class:`mindspore.dtype`]) - 数据集类型。 diff --git a/docs/api/api_python/nn/mindspore.nn.GraphCell.rst b/docs/api/api_python/nn/mindspore.nn.GraphCell.rst index cb4c7a7f36c..de9676daff1 100644 --- a/docs/api/api_python/nn/mindspore.nn.GraphCell.rst +++ b/docs/api/api_python/nn/mindspore.nn.GraphCell.rst @@ -10,7 +10,7 @@ mindspore.nn.GraphCell 参数： - **graph** (FuncGraph) - 从MindIR加载的编译图。 - **params_init** (dict) - 需要在图中初始化的参数。key为参数名称，类型为字符串，value为 Tensor 或 Parameter。如果参数名在图中已经存在，则更新其值；如果不存在，则忽略。默认值：None。 - - **obf_password** (int) - 用于动态混淆保护的password。动态混淆是一种模型保护方法，可以参考 :func:`mindspore.train.serialization.obfuscate_model` 。如果导入的 `graph` 是一个经过混淆的模型，那么 `obf_password` 应该要提供。 `obf_password` 的取值范围是(0, 9223372036854775807]。默认值：None。 + - **obf_password** (int) - 用于动态混淆保护的password。动态混淆是一种模型保护方法，可以参考 :func:`mindspore.obfuscate_model` 。如果导入的 `graph` 是一个经过混淆的模型，那么 `obf_password` 应该要提供。 `obf_password` 的取值范围是(0, 9223372036854775807]。默认值：None。 异常： - **TypeError** - 如果图不是FuncGraph类型。 diff --git a/docs/api/api_python/nn/mindspore.nn.HingeEmbeddingLoss.rst b/docs/api/api_python/nn/mindspore.nn.HingeEmbeddingLoss.rst index ab1c4950f86..6a0bf1af8b5 100644 --- a/docs/api/api_python/nn/mindspore.nn.HingeEmbeddingLoss.rst +++ b/docs/api/api_python/nn/mindspore.nn.HingeEmbeddingLoss.rst @@ -28,7 +28,7 @@ mindspore.nn.HingeEmbeddingLoss - **reduction** (str) - 指定应用于输出结果的计算方式，'none'、'mean'、'sum'，默认值：'mean'。 输入： - - **logits** (Tensor) - 预测值，公式中表示为 :math:`x`，shape为:math:`(*)`。`*` 代表着任意数量的维度。 + - **logits** (Tensor) - 预测值，公式中表示为 :math:`x`，shape为 :math:`(*)`。`*` 代表着任意数量的维度。 - **labels** (Tensor) - 标签值，公式中表示为 :math:`y`，和 `logits` 具有相同shape，包含1或-1。 返回： diff --git a/docs/api/api_python/nn/mindspore.nn.ReflectionPad1d.rst b/docs/api/api_python/nn/mindspore.nn.ReflectionPad1d.rst index f15f0d08341..adf3fc8bc16 100644 --- a/docs/api/api_python/nn/mindspore.nn.ReflectionPad1d.rst +++ b/docs/api/api_python/nn/mindspore.nn.ReflectionPad1d.rst @@ -6,7 +6,7 @@ mindspore.nn.ReflectionPad1d 根据 `padding` 对输入 `x` 进行填充。 参数： - - **padding** (union[int, tuple]) - 填充大小，如果输入为int，则对所有边界进行相同大小的填充；如果是tuple，则为(pad_left, pad_right)。 + - **padding** (union[int, tuple]) - 填充大小，如果输入为int，则对所有边界进行相同大小的填充；如果是tuple，则为 :math:`(pad\_left, pad\_right)`。 输入： - **x** (Tensor) - 输入Tensor, 2D或3D。shape为 :math:`(C, W_{in})` 或 :math:`(N, C, W_{in})` 。 diff --git a/docs/api/api_python/nn/mindspore.nn.ReflectionPad2d.rst b/docs/api/api_python/nn/mindspore.nn.ReflectionPad2d.rst index 6d1d08f7a5b..7d09758cc8e 100644 --- a/docs/api/api_python/nn/mindspore.nn.ReflectionPad2d.rst +++ b/docs/api/api_python/nn/mindspore.nn.ReflectionPad2d.rst @@ -6,13 +6,13 @@ mindspore.nn.ReflectionPad2d 根据 `padding` 对输入 `x` 进行填充。 参数： - - **padding** (union[int, tuple]) - 填充大小，如果输入为int，则对所有边界进行相同大小的填充；如果是tuple，则顺序为 :math:`(pad_{left}, pad_{right}, pad_{up}, pad_{down})`。 + - **padding** (union[int, tuple]) - 填充大小，如果输入为int，则对所有边界进行相同大小的填充；如果是tuple，则顺序为 :math:`(pad\_left, pad\_right, pad\_up, pad\_down)`。 输入： - **x** (Tensor) - 输入Tensor, shape为 :math:`(C, H_{in}, W_{in})` 或 :math:`(N, C, H_{in}, W_{in})` 。 输出： - Tensor，填充后的Tensor, shape为 :math:`(C, H_{out}, W_{out})` 或 :math:`(N, C, H_{out}, W_{out})`。其中 :math:`H_{out} = H_{in} + pad_{up} + pad_{down}`, :math:`W_{out} = W_{in} + pad_{left} + pad_{right}` 。 + Tensor，填充后的Tensor, shape为 :math:`(C, H_{out}, W_{out})` 或 :math:`(N, C, H_{out}, W_{out})`。其中 :math:`H_{out} = H_{in} + pad\_up + pad\_down`, :math:`W_{out} = W_{in} + pad\_left + pad\_right` 。 异常： - **TypeError** - `padding` 不是tuple或int。 diff --git a/docs/api/api_python/nn/mindspore.nn.ReflectionPad3d.rst b/docs/api/api_python/nn/mindspore.nn.ReflectionPad3d.rst index 0444778cc1b..f9a313bf193 100644 --- a/docs/api/api_python/nn/mindspore.nn.ReflectionPad3d.rst +++ b/docs/api/api_python/nn/mindspore.nn.ReflectionPad3d.rst @@ -6,7 +6,7 @@ mindspore.nn.ReflectionPad3d 根据 `padding` 对输入 `x` 进行填充。 参数： - - **padding** (union[int, tuple]) - 填充大小，如果输入为int，则对所有边界进行相同大小的填充；如果是tuple，则顺序为 :math:`(pad_{left}, pad_{right}, pad_{up}, pad_{down}, pad_{front}, pad_{back})`。 + - **padding** (union[int, tuple]) - 填充大小，如果输入为int，则对所有边界进行相同大小的填充；如果是tuple，则顺序为 :math:`(pad\_left, pad\_right, pad\_up, pad\_down, pad\_front, pad\_back)`。 .. note:: ReflectionPad3d尚不支持5D Tensor输入。 @@ -15,7 +15,7 @@ mindspore.nn.ReflectionPad3d - **x** (Tensor) - 4D Tensor, shape为 :math:`(N, D_{in}, H_{in}, W_{in})` 。 输出： - Tensor，填充后的Tensor, shape为 :math:`(N, D_{out}, H_{out}, W_{out})`。其中 :math:`H_{out} = H_{in} + pad_{up} + pad_{down}`, :math:`W_{out} = W_{in} + pad_{left} + pad_{right}`, :math:`D_{out} = D_{in} + pad_{front} + pad_{back}` 。 + Tensor，填充后的Tensor, shape为 :math:`(N, D_{out}, H_{out}, W_{out})`。其中 :math:`H_{out} = H_{in} + pad\_up + pad\_down`, :math:`W_{out} = W_{in} + pad\_left + pad\_right`, :math:`D_{out} = D_{in} + pad\_front + pad\_back` 。 异常： - **TypeError** - `padding` 不是tuple或int。 diff --git a/docs/api/api_python/ops/mindspore.ops.GridSampler2D.rst b/docs/api/api_python/ops/mindspore.ops.GridSampler2D.rst index d61322e49fe..7b20bf46229 100644 --- a/docs/api/api_python/ops/mindspore.ops.GridSampler2D.rst +++ b/docs/api/api_python/ops/mindspore.ops.GridSampler2D.rst @@ -3,7 +3,7 @@ mindspore.ops.GridSampler2D .. py:class:: mindspore.ops.GridSampler2D(interpolation_mode='bilinear', padding_mode='zeros', align_corners=False) - 此操作使用基于流场网格的插值对 2D input_x进行采样，该插值通常由 `affine_grid` 生成。 + 此操作使用基于流场网格的插值对 2D input_x进行采样，该插值通常由 :func:`mindspore.ops.affine_grid` 生成。 参数： - **interpolation_mode** (str，可选) - 指定插值方法的可选字符串。可选值为："bilinear"、"nearest"，默认为："bilinear"。 diff --git a/docs/api/api_python/ops/mindspore.ops.Zeta.rst b/docs/api/api_python/ops/mindspore.ops.Zeta.rst index 2e008e97344..8018b73e878 100644 --- a/docs/api/api_python/ops/mindspore.ops.Zeta.rst +++ b/docs/api/api_python/ops/mindspore.ops.Zeta.rst @@ -10,7 +10,7 @@ mindspore.ops.Zeta .. math:: - \\zeta \\left ( x,q \\right )= \\textstyle \\sum_{n=0} ^ {\\infty} \\left ( q+n\\right )^{-x} + \zeta \left ( x,q \right )= \textstyle \sum_{n=0} ^ {\infty} \left ( q+n\right )^{-x} 输入： - **x** (Tensor) - Tensor，数据类型为：float32、float64。 diff --git a/docs/api/api_python/ops/mindspore.ops.func_arcsinh.rst b/docs/api/api_python/ops/mindspore.ops.func_arcsinh.rst index 764d22c39a4..abe9e92e712 100644 --- a/docs/api/api_python/ops/mindspore.ops.func_arcsinh.rst +++ b/docs/api/api_python/ops/mindspore.ops.func_arcsinh.rst @@ -1,6 +1,6 @@ mindspore.ops.arcsinh ====================== -.. py:function:: mindspore.ops.arcsinh() +.. py:function:: mindspore.ops.arcsinh(x) :func:`mindspore.ops.asinh` 的别名。 diff --git a/docs/api/api_python/ops/mindspore.ops.func_arctanh.rst b/docs/api/api_python/ops/mindspore.ops.func_arctanh.rst index d568f78fa67..9c958ff44a5 100644 --- a/docs/api/api_python/ops/mindspore.ops.func_arctanh.rst +++ b/docs/api/api_python/ops/mindspore.ops.func_arctanh.rst @@ -1,6 +1,6 @@ mindspore.ops.arctanh ====================== -.. py:function:: mindspore.ops.arctanh() +.. py:function:: mindspore.ops.arctanh(x) :func:`mindspore.ops.atanh` 的别名。 diff --git a/docs/api/api_python/ops/mindspore.ops.func_broadcast_to.rst b/docs/api/api_python/ops/mindspore.ops.func_broadcast_to.rst index 9033e05bfba..ec570c5d981 100644 --- a/docs/api/api_python/ops/mindspore.ops.func_broadcast_to.rst +++ b/docs/api/api_python/ops/mindspore.ops.func_broadcast_to.rst @@ -3,9 +3,9 @@ mindspore.ops.broadcast_to .. py:function:: mindspore.ops.broadcast_to(x, shape) - 将输入shape广播到目标shape。输入shape维度必须小于等于目标shape维度，设输入shape为 :math: `(x1, x2, ..., xm)`，目标shape为 :math:`(*, y_1, y_2, ..., y_m)`，其中 :math:`*` 为任意额外的维度。广播规则如下： + 将输入shape广播到目标shape。输入shape维度必须小于等于目标shape维度，设输入shape为 :math:`(x_1, x_2, ..., x_m)`，目标shape为 :math:`(*, y_1, y_2, ..., y_m)`，其中 :math:`*` 为任意额外的维度。广播规则如下： - 依次比较 `x_m` 与 `y_m` 、 `x_{m-1}` 与 `y_{m-1}` 、...、 `x_1` 与 `y_1` 的值确定是否可以广播以及广播后输出shape对应维的值。 + 依次比较 :math:`x_m` 与 :math:`y_m` 、 :math:`x_{m-1}` 与 :math:`y_{m-1}` 、...、 :math:`x_1` 与 :math:`y_1` 的值确定是否可以广播以及广播后输出shape对应维的值。 - 如果相等，则这个值即为目标shape该维的值。比如说输入shape为 :math:`(2, 3)` ，目标shape为 :math:`(2, 3)` ，则输出shape为 :math:`(2, 3)`。 diff --git a/docs/api/api_python/ops/mindspore.ops.func_clip_by_global_norm.rst b/docs/api/api_python/ops/mindspore.ops.func_clip_by_global_norm.rst index 396b4098241..5d85877cf82 100644 --- a/docs/api/api_python/ops/mindspore.ops.func_clip_by_global_norm.rst +++ b/docs/api/api_python/ops/mindspore.ops.func_clip_by_global_norm.rst @@ -6,10 +6,8 @@ 通过权重梯度总和的比率来裁剪多个Tensor的值。 .. note:: - 输入 `x` 应为Tensor的tuple或list。否则，将引发错误。 - - .. note:: - 在半自动并行模式或自动并行模式下，如果输入是梯度，那么将会自动汇聚所有设备上的梯度的平方和。 + - 输入 `x` 应为Tensor的tuple或list。否则，将引发错误。 + - 在半自动并行模式或自动并行模式下，如果输入是梯度，那么将会自动汇聚所有设备上的梯度的平方和。 参数： - **x** (Union(tuple[Tensor], list[Tensor])) - 由Tensor组成的tuple，其每个元素为任意维度的Tensor。 diff --git a/docs/api/api_python/ops/mindspore.ops.func_cummax.rst b/docs/api/api_python/ops/mindspore.ops.func_cummax.rst index 333abb98865..444829116a5 100644 --- a/docs/api/api_python/ops/mindspore.ops.func_cummax.rst +++ b/docs/api/api_python/ops/mindspore.ops.func_cummax.rst @@ -7,7 +7,7 @@ mindspore.ops.cummax .. math:: \begin{array}{ll} \\ - y{i} = max(x{1}, x{2}, ... , x{i}) + y_{i} = max(x_{1}, x_{2}, ... , x_{i}) \end{array} 参数： diff --git a/docs/api/api_python/ops/mindspore.ops.func_cummin.rst b/docs/api/api_python/ops/mindspore.ops.func_cummin.rst index feb8854fb12..64146df3b0d 100644 --- a/docs/api/api_python/ops/mindspore.ops.func_cummin.rst +++ b/docs/api/api_python/ops/mindspore.ops.func_cummin.rst @@ -7,7 +7,7 @@ mindspore.ops.cummin .. math:: \begin{array}{ll} \\ - y{i} = min(x{1}, x{2}, ... , x{i}) + y_{i} = min(x_{1}, x_{2}, ... , x_{i}) \end{array} 参数： diff --git a/docs/api/api_python/ops/mindspore.ops.func_floor.rst b/docs/api/api_python/ops/mindspore.ops.func_floor.rst index 31909567471..31e00c93c0f 100644 --- a/docs/api/api_python/ops/mindspore.ops.func_floor.rst +++ b/docs/api/api_python/ops/mindspore.ops.func_floor.rst @@ -9,7 +9,7 @@ mindspore.ops.floor out_i = \lfloor x_i \rfloor 参数： - - **x** (Tensor) - Floor的输入，任意维度的Tensor，秩应小于8。其数据类型必须为float16、float32。 + - **x** (Tensor) - floor的输入，任意维度的Tensor，秩应小于8。其数据类型必须为float16、float32。 返回： Tensor，shape与 `x` 相同。 diff --git a/docs/api/api_python/ops/mindspore.ops.func_l1_loss.rst b/docs/api/api_python/ops/mindspore.ops.func_l1_loss.rst index fd12b6c941b..42e0264eb59 100644 --- a/docs/api/api_python/ops/mindspore.ops.func_l1_loss.rst +++ b/docs/api/api_python/ops/mindspore.ops.func_l1_loss.rst @@ -1,7 +1,7 @@ mindspore.ops.l1_loss ===================== -.. py:function:: mindspore.ops.l1_loss(x, target, reduction='mean'): +.. py:function:: mindspore.ops.l1_loss(x, target, reduction='mean') l1_loss用于计算预测值和目标值之间的平均绝对误差。 diff --git a/docs/api/api_python/ops/mindspore.ops.func_max_unpool1d.rst b/docs/api/api_python/ops/mindspore.ops.func_max_unpool1d.rst index e97186e12a4..533899ab34b 100644 --- a/docs/api/api_python/ops/mindspore.ops.func_max_unpool1d.rst +++ b/docs/api/api_python/ops/mindspore.ops.func_max_unpool1d.rst @@ -3,8 +3,8 @@ mindspore.ops.max_unpool1d .. py:function:: mindspore.ops.max_unpool1d(x, indices, kernel_size, stride=None, padding=0, output_size=None) - `Maxpool1d` 的部分逆过程。 `Maxpool1d` 不是完全可逆的，因为非最大值丢失。 - `max_unpool1d` 以 `MaxPool1d` 的输出为输入，包括最大值的索引。在计算 `Maxpool1d` 部分逆的过程中，非最大值设置为零。 + `maxpool1d` 的部分逆过程。 `maxpool1d` 不是完全可逆的，因为非最大值丢失。 + `max_unpool1d` 以 `maxpool1d` 的输出为输入，包括最大值的索引。在计算 `maxpool1d` 部分逆的过程中，非最大值设置为零。 支持的输入数据格式为 :math:`(N, C, H_{in})` 或 :math:`(C, H_{in})` ，输出数据的格式为 :math:`(N, C, H_{out})` 或 :math:`(C, H_{out})` ，计算公式如下： diff --git a/docs/api/api_python/ops/mindspore.ops.func_sqrt.rst b/docs/api/api_python/ops/mindspore.ops.func_sqrt.rst index 81004bb51cc..a81cb7e1ff9 100644 --- a/docs/api/api_python/ops/mindspore.ops.func_sqrt.rst +++ b/docs/api/api_python/ops/mindspore.ops.func_sqrt.rst @@ -6,7 +6,7 @@ mindspore.ops.sqrt 逐元素返回当前Tensor的平方根。 .. math:: - out_{i} = \\sqrt{x_{i}} + out_{i} = \sqrt{x_{i}} 参数： - **x** (Tensor) - 输入Tensor，数据类型为number.Number，其rank需要在[0, 7]范围内. diff --git a/docs/api/api_python_en/mindspore.ops.primitive.rst b/docs/api/api_python_en/mindspore.ops.primitive.rst index 4a4b1f8c1ab..3091222b8a5 100644 --- a/docs/api/api_python_en/mindspore.ops.primitive.rst +++ b/docs/api/api_python_en/mindspore.ops.primitive.rst @@ -66,6 +66,7 @@ Neural Network mindspore.ops.FractionalMaxPool mindspore.ops.FractionalMaxPoolWithFixedKsize mindspore.ops.FractionalMaxPool3DWithFixedKsize + mindspore.ops.GridSampler2D mindspore.ops.GridSampler3D mindspore.ops.LayerNorm mindspore.ops.LRN @@ -196,7 +197,6 @@ Sampling Operator :template: classtemplate.rst mindspore.ops.ComputeAccidentalHits - mindspore.ops.GridSampler2D mindspore.ops.LogUniformCandidateSampler mindspore.ops.UniformCandidateSampler diff --git a/mindspore/python/mindspore/common/sparse_tensor.py b/mindspore/python/mindspore/common/sparse_tensor.py index d78e6eb541f..f1e45906784 100644 --- a/mindspore/python/mindspore/common/sparse_tensor.py +++ b/mindspore/python/mindspore/common/sparse_tensor.py @@ -507,7 +507,7 @@ class COOTensor(COOTensor_): TypeError: If (self/other)'s value's type is not matched with thresh's type Supported Platforms: - ``CPU`` ``GPU`` + ``GPU`` ``CPU`` Examples: >>> from mindspore import Tensor, COOTensor @@ -804,7 +804,7 @@ class CSRTensor(CSRTensor_): Tensor or CSRTensor. Supported Platforms: - ``CPU`` ``GPU`` + ``GPU`` ``CPU`` Examples: >>> from mindspore import Tensor, CSRTensor diff --git a/mindspore/python/mindspore/common/tensor.py b/mindspore/python/mindspore/common/tensor.py index 2abe8bcc5e7..1b27eb8a54b 100644 --- a/mindspore/python/mindspore/common/tensor.py +++ b/mindspore/python/mindspore/common/tensor.py @@ -4347,7 +4347,7 @@ class Tensor(Tensor_): ValueError: If all elements of input tensor are not greater than (p-1)/2. Supported Platforms: - ``CPU`` ``GPU`` + ``GPU`` ``CPU`` Examples: >>> x = Tensor(np.array([[3, 4, 5], [4, 2, 6]]), mindspore.float32) @@ -4384,7 +4384,7 @@ class Tensor(Tensor_): ValueError: If the shape of input tensor and `tensor2` could not broadcast together. Supported Platforms: - ``Ascend`` ``CPU`` ``GPU`` + ``Ascend`` ``GPU`` ``CPU`` Examples: >>> x = Tensor(np.arange(2*3*4).reshape(2, 3, 4), mindspore.float32) @@ -4439,7 +4439,7 @@ class Tensor(Tensor_): ValueError: If `input` and `other` are not the same shape. Supported Platforms: - ``Ascend`` ``CPU`` ``GPU`` + ``Ascend`` ``GPU`` ``CPU`` Examples: >>> x = Tensor(np.array([1.0, 5.0, 3.0]), mindspore.float32) @@ -4492,7 +4492,7 @@ class Tensor(Tensor_): ValueError: If input tensor and `value` are not the same shape. Supported Platforms: - ``Ascend`` ``CPU`` ``GPU`` + ``Ascend`` ``GPU`` ``CPU`` Examples: >>> x = Tensor(np.array([1.0, 2.0, 3.0]), mindspore.float32) @@ -4522,7 +4522,7 @@ class Tensor(Tensor_): Tensor, has the same shape and dtype as input. Supported Platforms: - ``Ascend`` ``CPU`` ``GPU`` + ``Ascend`` ``GPU`` ``CPU`` Examples: >>> x = Tensor(np.array([1, 2, -1, 2, 0, -3.5]), mindspore.float32) @@ -4557,7 +4557,7 @@ class Tensor(Tensor_): TypeError: If neither input tensor and `other` is a Tensor. Supported Platforms: - ``Ascend`` ``CPU`` ``GPU`` + ``Ascend`` ``GPU`` ``CPU`` Examples: >>> x = Tensor(np.array([1, 2, 3]), mindspore.float32) @@ -4593,7 +4593,7 @@ class Tensor(Tensor_): TypeError: If `size` is not an int, list or tuple of integers. Supported Platforms: - ``Ascend`` ``CPU`` ``GPU`` + ``Ascend`` ``GPU`` ``CPU`` Examples: >>> x = Tensor(np.array([1, 2, 3]), mindspore.float32) @@ -4627,7 +4627,7 @@ class Tensor(Tensor_): TypeError: If `size` is not an int, list or tuple of integers. Supported Platforms: - ``Ascend`` ``CPU`` ``GPU`` + ``Ascend`` ``GPU`` ``CPU`` Examples: >>> x = Tensor(np.array([1, 2, 3]), mindspore.float32) @@ -4690,7 +4690,7 @@ class Tensor(Tensor_): Tensor, has the same shape as input tensor. Supported Platforms: - ``Ascend`` ``CPU`` ``GPU`` + ``Ascend`` ``GPU`` ``CPU`` Examples: >>> x = Tensor(np.array([0.62, 0.28, 0.43, 0.62]), mindspore.float32) @@ -4721,7 +4721,7 @@ class Tensor(Tensor_): ValueError: If `dim` is not in range of [-len(x.shape), len(x.shape)). Supported Platforms: - ``Ascend`` ``CPU`` ``GPU`` + ``Ascend`` ``GPU`` ``CPU`` Examples: >>> x = Tensor(np.array([[8, 2, 1], [5, 9, 3], [4, 6, 7]]), mindspore.float16) @@ -4780,7 +4780,7 @@ class Tensor(Tensor_): Tensor, the shape is the same as the input tensor. Supported Platforms: - ``CPU`` ``GPU`` + ``GPU`` ``CPU`` Examples: >>> x = Tensor(np.asarray(np.complex(1.3 + 0.4j)), mindspore.complex64) diff --git a/mindspore/python/mindspore/context.py b/mindspore/python/mindspore/context.py index cec3e5fa58b..b2e2c742d1e 100644 --- a/mindspore/python/mindspore/context.py +++ b/mindspore/python/mindspore/context.py @@ -1154,6 +1154,8 @@ def reset_ps_context(): Reset parameter server training mode context attributes to the default values: - enable_ps: False. + + Meaning of each field and its default value refer to :func:`mindspore.set_ps_context`. """ _reset_ps_context() diff --git a/mindspore/python/mindspore/dataset/transforms/c_transforms.py b/mindspore/python/mindspore/dataset/transforms/c_transforms.py index 6a6c4c414db..3c9e8695a16 100644 --- a/mindspore/python/mindspore/dataset/transforms/c_transforms.py +++ b/mindspore/python/mindspore/dataset/transforms/c_transforms.py @@ -142,7 +142,7 @@ class TypeCast(TensorOperation): TypeError: If `data_type` is not of type bool, int, float or string. Supported Platforms: - ``CPU`` ``Ascend`` ``GPU`` + ``Ascend`` ``GPU`` ``CPU`` Examples: >>> import numpy as np diff --git a/mindspore/python/mindspore/dataset/transforms/transforms.py b/mindspore/python/mindspore/dataset/transforms/transforms.py index f0d53ad5743..96241d70b25 100644 --- a/mindspore/python/mindspore/dataset/transforms/transforms.py +++ b/mindspore/python/mindspore/dataset/transforms/transforms.py @@ -896,7 +896,7 @@ class TypeCast(TensorOperation): TypeError: If `data_type` is not of MindSpore data type bool, int, float, string or type :class:`numpy.dtype` . Supported Platforms: - ``CPU`` ``Ascend`` ``GPU`` + ``Ascend`` ``GPU`` ``CPU`` Examples: >>> import numpy as np diff --git a/mindspore/python/mindspore/dataset/vision/c_transforms.py b/mindspore/python/mindspore/dataset/vision/c_transforms.py index af8017d0354..7e4b4b6f86c 100644 --- a/mindspore/python/mindspore/dataset/vision/c_transforms.py +++ b/mindspore/python/mindspore/dataset/vision/c_transforms.py @@ -716,7 +716,7 @@ class HWC2CHW(ImageTensorOperation): RuntimeError: If given tensor shape is not or . Supported Platforms: - ``CPU`` ``Ascend`` ``GPU`` + ``Ascend`` ``GPU`` ``CPU`` Examples: >>> transforms_list = [c_vision.Decode(), @@ -822,7 +822,7 @@ class Normalize(ImageTensorOperation): RuntimeError: If given tensor shape is not or <...,H, W, C>. Supported Platforms: - ``CPU`` ``Ascend`` ``GPU`` + ``Ascend`` ``GPU`` ``CPU`` Examples: >>> decode_op = c_vision.Decode() @@ -1214,7 +1214,7 @@ class RandomColorAdjust(ImageTensorOperation): RuntimeError: If given tensor shape is not . Supported Platforms: - ``CPU`` ``Ascend`` ``GPU`` + ``Ascend`` ``GPU`` ``CPU`` Examples: >>> decode_op = c_vision.Decode() @@ -1561,7 +1561,7 @@ class RandomHorizontalFlip(ImageTensorOperation): RuntimeError: If given tensor shape is not or . Supported Platforms: - ``CPU`` ``Ascend`` ``GPU`` + ``Ascend`` ``GPU`` ``CPU`` Examples: >>> transforms_list = [c_vision.Decode(), c_vision.RandomHorizontalFlip(0.75)] @@ -2070,7 +2070,7 @@ class RandomSharpness(ImageTensorOperation): ValueError: If `degrees` is in (max, min) format instead of (min, max). Supported Platforms: - ``CPU`` ``Ascend`` ``GPU`` + ``Ascend`` ``GPU`` ``CPU`` Examples: >>> transforms_list = [c_vision.Decode(), c_vision.RandomSharpness(degrees=(0.2, 1.9))] @@ -2136,7 +2136,7 @@ class RandomVerticalFlip(ImageTensorOperation): RuntimeError: If given tensor shape is not or . Supported Platforms: - ``CPU`` ``Ascend`` ``GPU`` + ``Ascend`` ``GPU`` ``CPU`` Examples: >>> transforms_list = [c_vision.Decode(), c_vision.RandomVerticalFlip(0.25)] @@ -2200,7 +2200,7 @@ class Rescale(ImageTensorOperation): TypeError: If `shift` is not of type float. Supported Platforms: - ``CPU`` ``Ascend`` ``GPU`` + ``Ascend`` ``GPU`` ``CPU`` Examples: >>> transforms_list = [c_vision.Decode(), c_vision.Rescale(1.0 / 255.0, -1.0)] diff --git a/mindspore/python/mindspore/dataset/vision/transforms.py b/mindspore/python/mindspore/dataset/vision/transforms.py index 5474e1cf9a5..531d4164be1 100644 --- a/mindspore/python/mindspore/dataset/vision/transforms.py +++ b/mindspore/python/mindspore/dataset/vision/transforms.py @@ -3465,7 +3465,7 @@ class Rescale(ImageTensorOperation): TypeError: If `shift` is not of type float. Supported Platforms: - ``CPU`` ``Ascend`` ``GPU`` + ``Ascend`` ``GPU`` ``CPU`` Examples: >>> transforms_list = [vision.Decode(), vision.Rescale(1.0 / 255.0, -1.0)] @@ -4074,7 +4074,7 @@ class ToType(TypeCast): TypeError: If `data_type` is not of type :class:`mindspore.dtype` or :class:`numpy.dtype` . Supported Platforms: - ``CPU`` ``Ascend`` ``GPU`` + ``Ascend`` ``GPU`` ``CPU`` Examples: >>> import numpy as np diff --git a/mindspore/python/mindspore/nn/cell.py b/mindspore/python/mindspore/nn/cell.py index afe22c4b396..53ddc4ba9a4 100755 --- a/mindspore/python/mindspore/nn/cell.py +++ b/mindspore/python/mindspore/nn/cell.py @@ -2193,7 +2193,7 @@ class GraphCell(Cell): If the parameter exists in the graph according to the name, update it's value. If the parameter does not exist, ignore it. Default: None. obf_password (int): The password used for dynamic obfuscation. "dynamic obfuscation" is used for model - protection, which can refer to `mindspore.train.serialization.obfuscate_model()`. If the input 'graph' is a + protection, which can refer to :func:`mindspore.obfuscate_model`. If the input 'graph' is a func_graph loaded from a mindir file obfuscated in password mode, then obf_password should be provided. obf_password should be larger than zero and less or equal than int_64 (9223372036854775807). default: None. diff --git a/mindspore/python/mindspore/nn/layer/activation.py b/mindspore/python/mindspore/nn/layer/activation.py index 611066983b2..6deb8b91346 100644 --- a/mindspore/python/mindspore/nn/layer/activation.py +++ b/mindspore/python/mindspore/nn/layer/activation.py @@ -1322,7 +1322,7 @@ class SoftShrink(Cell): ValueError: If lambd is less than 0. Supported Platforms: - ``Ascend`` ``CPU`` ``GPU`` + ``Ascend`` ``GPU`` ``CPU`` Examples: >>> input_x = Tensor(np.array([[ 0.5297, 0.7871, 1.1754], [ 0.7836, 0.6218, -1.1542]]), mstype.float16) @@ -1370,7 +1370,7 @@ class HShrink(Cell): TypeError: If dtype of `input_x` is neither float16 nor float32. Supported Platforms: - ``Ascend`` ``CPU`` ``GPU`` + ``Ascend`` ``GPU`` ``CPU`` Examples: >>> import mindspore @@ -1419,7 +1419,7 @@ class Threshold(Cell): TypeError: If `value` is not a float or an int. Supported Platforms: - ``Ascend`` ``CPU`` ``GPU`` + ``Ascend`` ``GPU`` ``CPU`` Examples: >>> import mindspore diff --git a/mindspore/python/mindspore/nn/layer/basic.py b/mindspore/python/mindspore/nn/layer/basic.py index f4e6720235e..2d7b3c06017 100644 --- a/mindspore/python/mindspore/nn/layer/basic.py +++ b/mindspore/python/mindspore/nn/layer/basic.py @@ -644,7 +644,7 @@ class Identity(Cell): TypeError: If `x` is not a Tensor. Supported Platforms: - ``Ascend`` ``CPU`` ``GPU`` + ``Ascend`` ``GPU`` ``CPU`` Examples: >>> x = Tensor(np.array([1, 2, 3, 4]), mindspore.int64) @@ -1298,7 +1298,7 @@ class ResizeBilinear(Cell): ValueError: If `size` is a list or tuple whose length is not equal to 2. Supported Platforms: - ``Ascend`` ``CPU`` ``GPU`` + ``Ascend`` ``GPU`` ``CPU`` Examples: >>> x = Tensor([[[[1, 2, 3, 4], [5, 6, 7, 8]]]], mindspore.float32) diff --git a/mindspore/python/mindspore/nn/layer/padding.py b/mindspore/python/mindspore/nn/layer/padding.py index 87e61d441ab..1a73d87cf55 100644 --- a/mindspore/python/mindspore/nn/layer/padding.py +++ b/mindspore/python/mindspore/nn/layer/padding.py @@ -441,14 +441,14 @@ class ReflectionPad1d(_ReflectionPadNd): Args: padding (union[int, tuple]): The padding size to pad the last dimension of input tensor. If padding is an integer: all directions will be padded with the same size. - If padding is a tuple: uses :math:`(pad_{left}, pad_{right})` to pad. + If padding is a tuple: uses :math:`(pad\_left, pad\_right)` to pad. Inputs: - **x** (Tensor) - 2D or 3D, shape: :math:`(C, W_{in})` or :math:`(N, C, W_{in})`. Outputs: Tensor, after padding. Shape: :math:`(C, W_{out})` or :math:`(N, C, W_{out})`, - where :math:`W_{out} = W_{in} + pad_{left} + pad_{right}`. + where :math:`W_{out} = W_{in} + pad\_left + pad\_right`. Raises: TypeError: If 'padding' is not a tuple or int. @@ -490,14 +490,14 @@ class ReflectionPad2d(_ReflectionPadNd): Args: padding (union[int, tuple]): The padding size to pad the input tensor. If padding is an integer: all directions will be padded with the same size. - If padding is a tuple: uses :math:`(pad_{left}, pad_{right}, pad_{up}, pad_{down})` to pad. + If padding is a tuple: uses :math:`(pad\_left, pad\_right, pad\_up, pad\_down)` to pad. Inputs: - **x** (Tensor) - 3D or 4D, shape: :math:`(C, H_{in}, W_{out})` or :math:`(N, C, H_{out}, W_{out})`. Outputs: Tensor, after padding. Shape: :math:`(C, H_{out}, W_{out})` or :math:`(N, C, H_{out}, W_{out})`, - where :math:`H_{out} = H_{in} + pad_{up} + pad_{down}`, :math:`W_{out} = W_{in} + pad_{left} + pad_{right}`. + where :math:`H_{out} = H_{in} + pad\_up + pad\_down`, :math:`W_{out} = W_{in} + pad\_left + pad\_right`. Raises: TypeError: If 'padding' is not a tuple or int. @@ -545,17 +545,17 @@ class ReflectionPad3d(_ReflectionPadNd): Args: padding (union[int, tuple]): The padding size to pad the input tensor. - If padding is an integer: all directions will be padded with the same size. - If padding is a tuple: uses :math:`(pad_{left}, pad_{right}, pad_{up}, pad_{down}, - pad_{front}, pad_{back})` to pad. + If padding is an integer: all directions will be padded with the same size. + If padding is a tuple: uses :math:`(pad\_left, pad\_right, pad\_up, pad\_down, + pad\_front, pad\_back)` to pad. Inputs: - **x** (Tensor) - 4D Tensor, shape: :math:`(N, D_{in}, H_{in}, W_{out})`. Outputs: Tensor, after padding. Shape: :math:`(N, D_{out}, H_{out}, W_{out})`, - where :math:`D_{out} = D_{in} + pad_{front} + pad_{back}`, :math:`H_{out} = H_{in} + pad_{up} + pad_{down}` - :math:`W_{out} = W_{in} + pad_{left} + pad_{right}`. + where :math:`D_{out} = D_{in} + pad\_front + pad\_back`, :math:`H_{out} = H_{in} + pad\_up + pad\_down` + :math:`W_{out} = W_{in} + pad\_left + pad\_right`. Raises: TypeError: If 'padding' is not a tuple or int. @@ -586,11 +586,9 @@ class ReflectionPad3d(_ReflectionPadNd): [[[[3. 2. 3. 2.] [1. 0. 1. 0.] [3. 2. 3. 2.]] - [[7. 6. 7. 6.] [5. 4. 5. 4.] [7. 6. 7. 6.]] - [[3. 2. 3. 2.] [1. 0. 1. 0.] [3. 2. 3. 2.]]]] diff --git a/mindspore/python/mindspore/nn/optim/ada_grad.py b/mindspore/python/mindspore/nn/optim/ada_grad.py index de7f5fcfa0b..f9cc76a3ea0 100644 --- a/mindspore/python/mindspore/nn/optim/ada_grad.py +++ b/mindspore/python/mindspore/nn/optim/ada_grad.py @@ -159,7 +159,7 @@ class Adagrad(Optimizer): ValueError: If `accum` or `weight_decay` is less than 0. Supported Platforms: - ``Ascend`` ``CPU`` ``GPU`` + ``Ascend`` ``GPU`` ``CPU`` Examples: >>> import mindspore as ms diff --git a/mindspore/python/mindspore/nn/wrap/cell_wrapper.py b/mindspore/python/mindspore/nn/wrap/cell_wrapper.py index fc1ef275a2a..381af57e5f7 100644 --- a/mindspore/python/mindspore/nn/wrap/cell_wrapper.py +++ b/mindspore/python/mindspore/nn/wrap/cell_wrapper.py @@ -395,7 +395,7 @@ class GetNextSingleOp(Cell): """ Cell to run for getting the next operation. - For detailed information, refer to `mindspore.ops.GetNext`. + For detailed information, refer to :class:`mindspore.ops.GetNext`. Args: dataset_types (list[:class:`mindspore.dtype`]): The types of dataset. diff --git a/mindspore/python/mindspore/ops/composite/clip_ops.py b/mindspore/python/mindspore/ops/composite/clip_ops.py index 27c9cb11b13..bc015966364 100644 --- a/mindspore/python/mindspore/ops/composite/clip_ops.py +++ b/mindspore/python/mindspore/ops/composite/clip_ops.py @@ -96,12 +96,10 @@ def clip_by_global_norm(x, clip_norm=1.0, use_norm=None): Clips tensor values by the ratio of the sum of their norms. Note: - Input `x` should be a tuple or list of tensors. Otherwise, it will raise an error. - - Note: - On the SEMI_AUTO_PARALLEL mode or AUTO_PARALLEL mode, if the input `x` is the gradient, - the gradient norm values on all devices will be automatically aggregated by allreduce inserted after the local - square sum of the gradients. + - Input `x` should be a tuple or list of tensors. Otherwise, it will raise an error. + - On the SEMI_AUTO_PARALLEL mode or AUTO_PARALLEL mode, if the input `x` is the gradient, + the gradient norm values on all devices will be automatically aggregated by allreduce inserted after + the local square sum of the gradients. Args: x (Union(tuple[Tensor], list[Tensor])): Input data to clip. diff --git a/mindspore/python/mindspore/ops/function/array_func.py b/mindspore/python/mindspore/ops/function/array_func.py index 7b9adf5ad9d..f313dcba2ba 100644 --- a/mindspore/python/mindspore/ops/function/array_func.py +++ b/mindspore/python/mindspore/ops/function/array_func.py @@ -2107,7 +2107,7 @@ def scatter_max(input_x, indices, updates): and `updates` is greater than 8 dimensions. Supported Platforms: - ``Ascend`` ``CPU`` ``GPU`` + ``Ascend`` ``GPU`` ``CPU`` Examples: >>> input_x = Parameter(Tensor(np.array([[1.0, 2.0, 3.0], [4.0, 5.0, 6.0]]), mindspore.float32), name="input_x") @@ -3841,7 +3841,7 @@ def meshgrid(inputs, indexing='xy'): ValueError: If `indexing` is neither 'xy' nor 'ij'. Supported Platforms: - ``Ascend`` ``CPU`` ``GPU`` + ``Ascend`` ``GPU`` ``CPU`` Examples: >>> import numpy as np @@ -3947,11 +3947,12 @@ def affine_grid(theta, output_size, align_corners=False): def broadcast_to(x, shape): """ Broadcasts input tensor to a given shape. The dim of input shape must be smaller - than or equal to that of target shape. Suppose input shape is :math:`(x1, x2, ..., xm)`, + than or equal to that of target shape. Suppose input shape is :math:`(x_1, x_2, ..., x_m)`, target shape is :math:`(*, y_1, y_2, ..., y_m)`, where :math:`*` means any additional dimension. The broadcast rules are as follows: - Compare the value of `x_m` and `y_m`, `x_{m-1}` and `y_{m-1}`, ..., `x_1` and `y_1` consecutively and + Compare the value of :math:`x_m` and :math:`y_m`, :math:`x_{m-1}` and :math:`y_{m-1}`, ..., + :math:`x_1` and :math:`y_1` consecutively and decide whether these shapes are broadcastable and what the broadcast result is. If the value pairs at a specific dim are equal, then that value goes right into that dim of output shape. @@ -5464,7 +5465,7 @@ def fold(input, output_size, kernel_size, dilation=1, padding=0, stride=1): ValueError: If `input.shape[3]` does not match the calculated number of sliding blocks. Supported Platforms: - ``CPU`` ``GPU`` + ``GPU`` ``CPU`` Examples: >>> x = Tensor(input_data=np.random.rand(16, 16, 4, 25), dtype=mstype.float32) @@ -5728,7 +5729,7 @@ def mvlgamma(input, p): ValueError: If not all elements of `input` are greater than :math:`(p - 1) / 2`. Supported Platforms: - ``CPU`` ``GPU`` + ``GPU`` ``CPU`` Examples: >>> x = Tensor(np.array([[3, 4, 5], [4, 2, 6]]), mindspore.float32) diff --git a/mindspore/python/mindspore/ops/function/math_func.py b/mindspore/python/mindspore/ops/function/math_func.py index c04df5a894b..ade34d43def 100644 --- a/mindspore/python/mindspore/ops/function/math_func.py +++ b/mindspore/python/mindspore/ops/function/math_func.py @@ -953,7 +953,7 @@ def div(input, other, rounding_mode=None): ValueError: If `rounding_mode` value is not None, "floor" or "trunc". Supported Platforms: - ``Ascend`` ``CPU`` ``GPU`` + ``Ascend`` ``GPU`` ``CPU`` Examples: >>> x = Tensor(np.array([1.0, 2.0, 3.0]), mindspore.float32) @@ -1978,7 +1978,7 @@ def tan(x): TypeError: If `x` is not a Tensor. Supported Platforms: - ``Ascend`` ``CPU`` ``GPU`` + ``Ascend`` ``GPU`` ``CPU`` Examples: >>> x = Tensor(np.array([-1.0, 0.0, 1.0]), mindspore.float32) @@ -2442,7 +2442,7 @@ def atan2(x, y): when data type conversion of Parameter is not supported. Supported Platforms: - ``Ascend`` ``CPU`` ``GPU`` + ``Ascend`` ``GPU`` ``CPU`` Examples: >>> x = Tensor(np.array([0, 1]), mindspore.float32) @@ -3297,7 +3297,7 @@ def truncate_div(x, y): TypeError: If `x` and `y` is not one of the following: Tensor, Number, bool. Supported Platforms: - ``Ascend`` ``CPU`` ``GPU`` + ``Ascend`` ``GPU`` ``CPU`` Examples: >>> x = Tensor(np.array([2, 4, -1]), mindspore.int32) @@ -3343,7 +3343,7 @@ def truncate_mod(x, y): ValueError: If the shape `x` and `y` cannot be broadcasted to each other. Supported Platforms: - ``Ascend`` ``CPU`` ``GPU`` + ``Ascend`` ``GPU`` ``CPU`` Examples: >>> x = Tensor(np.array([2, 4, -1]), mindspore.int32) @@ -5488,7 +5488,7 @@ def cummin(x, axis): .. math:: \begin{array}{ll} \\ - y{i} = min(x{1}, x{2}, ... , x{i}) + y_{i} = min(x_{1}, x_{2}, ... , x_{i}) \end{array} Args: @@ -5540,7 +5540,7 @@ def cummax(x, axis): .. math:: \begin{array}{ll} \\ - y{i} = max(x{1}, x{2}, ... , x{i}) + y_{i} = max(x_{1}, x_{2}, ... , x_{i}) \end{array} Args: @@ -7131,7 +7131,7 @@ def renorm(input_x, p, dim, maxnorm): ValueError: If the value of `p` less than 1. Supported Platforms: - ``Ascend`` ``CPU`` ``GPU`` + ``Ascend`` ``GPU`` ``CPU`` Examples: >>> x = Tensor(np.array([[1, 1, 1], [2, 2, 2], [3, 3, 3]]), mindspore.float32) @@ -8163,7 +8163,7 @@ def kron(x, y): TypeError: If `y` is not a Tensor. Supported Platforms: - ``Ascend`` ``CPU`` ``GPU`` + ``Ascend`` ``GPU`` ``CPU`` Examples: >>> import mindspore @@ -8894,7 +8894,7 @@ def erfinv(input): TypeError: If dtype of `input` is not float16, float32 or float64. Supported Platforms: - ``Ascend`` ``CPU`` ``GPU`` + ``Ascend`` ``GPU`` ``CPU`` Examples: >>> x = Tensor(np.array([0, 0.5, -0.9]), mindspore.float32) @@ -8976,7 +8976,7 @@ def cumprod(input, dim, dtype=None): ValueError: If `dim` is None. Supported Platforms: - ``Ascend`` ``CPU`` ``GPU`` + ``Ascend`` ``GPU`` ``CPU`` Examples: >>> x = Tensor(np.array([1, 2, 3], np.float32)) @@ -9008,7 +9008,7 @@ def greater(input, other): Tensor, the shape is the same as the one after broadcasting, and the data type is bool. Supported Platforms: - ``Ascend`` ``CPU`` ``GPU`` + ``Ascend`` ``GPU`` ``CPU`` Examples: >>> x = Tensor(np.array([1, 2, 3]), mindspore.int32) @@ -9038,7 +9038,7 @@ def greater_equal(input, other): Tensor, the shape is the same as the one after broadcasting, and the data type is bool. Supported Platforms: - ``Ascend`` ``CPU`` ``GPU`` + ``Ascend`` ``GPU`` ``CPU`` Examples: >>> x = Tensor(np.array([1, 2, 3]), mindspore.int32) @@ -9087,7 +9087,7 @@ def igamma(input, other): ValueError: If `input` could not be broadcast to a tensor with shape of `other`. Supported Platforms: - ``Ascend`` ``CPU`` ``GPU`` + ``Ascend`` ``GPU`` ``CPU`` Examples: >>> a = Tensor(np.array([2.0, 4.0, 6.0, 8.0]).astype(np.float32)) @@ -9136,7 +9136,7 @@ def igammac(input, other): ValueError: If `input` could not be broadcast to a tensor with shape of `other`. Supported Platforms: - ``Ascend`` ``CPU`` ``GPU`` + ``Ascend`` ``GPU`` ``CPU`` Examples: >>> a = Tensor(np.array([2.0, 4.0, 6.0, 8.0]).astype(np.float32)) @@ -9285,7 +9285,7 @@ def isinf(input): TypeError: If `input` is not a Tensor. Supported Platforms: - ``CPU`` ``GPU`` + ``GPU`` ``CPU`` Examples: >>> x = Tensor(np.array([np.log(-1), 1, np.log(0)]), mindspore.float32) @@ -9406,7 +9406,7 @@ def imag(input): TypeError: If `input` is not a Tensor. Supported Platforms: - ``CPU`` ``GPU`` + ``GPU`` ``CPU`` Examples: >>> x = Tensor(np.asarray(np.complex(1.3 + 0.4j)), mindspore.complex64) diff --git a/mindspore/python/mindspore/ops/function/nn_func.py b/mindspore/python/mindspore/ops/function/nn_func.py index ed7e0477770..af5cadb7dcf 100644 --- a/mindspore/python/mindspore/ops/function/nn_func.py +++ b/mindspore/python/mindspore/ops/function/nn_func.py @@ -686,11 +686,11 @@ def adaptive_max_pool3d(x, output_size, return_indices=False): def max_unpool1d(x, indices, kernel_size, stride=None, padding=0, output_size=None): r""" - Computes a partial inverse of MaxPool1d. + Computes a partial inverse of maxpool1d. - MaxPool1d is not fully invertible, since the non-maximal values are lost. + maxpool1d is not fully invertible, since the non-maximal values are lost. - max_unpool1d takes the output of MaxPool1d as input including the indices of the maximal values + max_unpool1d takes the output of maxpool1d as input including the indices of the maximal values and computes a partial inverse in which all non-maximal values are set to zero. Typically the input is of shape :math:`(N, C, H_{in})` or :math:`(C, H_{in})`, and the output is of shape :math:`(N, C, H_{out}` or :math:`(C, H_{out}`. The operation is as follows. @@ -1134,7 +1134,7 @@ def celu(x, alpha=1.0): ValueError: If `alpha` has the value of 0. Supported Platforms: - ``Ascend`` ``CPU`` ``GPU`` + ``Ascend`` ``GPU`` ``CPU`` Examples: >>> x = Tensor(np.array([-2.0, -1.0, 1.0, 2.0]), mindspore.float32) @@ -2014,7 +2014,7 @@ def interpolate(x, roi=None, scales=None, sizes=None, coordinate_transformation_ ValueError: If `mode` is not in the support list. Supported Platforms: - ``Ascend`` ``CPU`` ``GPU`` + ``Ascend`` ``GPU`` ``CPU`` Examples: >>> # case 1: linear mode @@ -2161,7 +2161,7 @@ def soft_shrink(x, lambd=0.5): ValueError: If lambd is less than 0. Supported Platforms: - ``Ascend`` ``CPU`` ``GPU`` + ``Ascend`` ``GPU`` ``CPU`` Examples: >>> from mindspore import Tensor @@ -4168,7 +4168,7 @@ def batch_norm(input_x, running_mean, running_var, weight, bias, training=False, TypeError: If dtype of `input_x`, `weight` is neither float16 nor float32. Supported Platforms: - ``Ascend`` ``CPU`` ``GPU`` + ``Ascend`` ``GPU`` ``CPU`` Examples: >>> input_x = Tensor(np.ones([2, 2]), mindspore.float32) @@ -4789,7 +4789,7 @@ def gelu(input_x, approximate='none'): ValueError: If `approximate` value is neither `none` or `tanh`. Supported Platforms: - ``Ascend`` ``CPU`` ``GPU`` + ``Ascend`` ``GPU`` ``CPU`` Examples: >>> x = Tensor([1.0, 2.0, 3.0], mindspore.float32) @@ -5040,7 +5040,7 @@ def mse_loss(input_x, target, reduction='mean'): ValueError: If `input_x` and `target` have different shapes and cannot be broadcasted. Supported Platforms: - ``Ascend`` ``CPU`` ``GPU`` + ``Ascend`` ``GPU`` ``CPU`` Examples: >>> logits = Tensor(np.array([1, 2, 3]), mindspore.float32) @@ -5097,7 +5097,7 @@ def msort(x): TypeError: If dtype of `x` is neither float16 nor float32. Supported Platforms: - ``Ascend`` ``CPU`` ``GPU`` + ``Ascend`` ``GPU`` ``CPU`` Examples: >>> import mindspore as ms diff --git a/mindspore/python/mindspore/ops/function/sparse_func.py b/mindspore/python/mindspore/ops/function/sparse_func.py index 6893bf7ab72..c5559fd8b12 100644 --- a/mindspore/python/mindspore/ops/function/sparse_func.py +++ b/mindspore/python/mindspore/ops/function/sparse_func.py @@ -676,7 +676,7 @@ def coo_add(x1: COOTensor, x2: COOTensor, thresh: Tensor) -> COOTensor: TypeError: If (x1/x2)'s value's type is not matched with thresh's type. Supported Platforms: - ``CPU`` ``GPU`` + ``GPU`` ``CPU`` Examples: >>> from mindspore import Tensor, COOTensor diff --git a/mindspore/python/mindspore/ops/function/sparse_unary_func.py b/mindspore/python/mindspore/ops/function/sparse_unary_func.py index 5e655b4fdbd..f5e7b75b9d0 100755 --- a/mindspore/python/mindspore/ops/function/sparse_unary_func.py +++ b/mindspore/python/mindspore/ops/function/sparse_unary_func.py @@ -115,7 +115,7 @@ def csr_tan(x: CSRTensor) -> CSRTensor: TypeError: If `x` is not a CSRTensor. Supported Platforms: - ``Ascend`` ``CPU`` ``GPU`` + ``Ascend`` ``GPU`` ``CPU`` Examples: >>> indptr = Tensor([0, 1, 2, 2], dtype=mstype.int32) @@ -150,7 +150,7 @@ def coo_tan(x: COOTensor) -> COOTensor: TypeError: If `x` is not a COOTensor. Supported Platforms: - ``Ascend`` ``CPU`` ``GPU`` + ``Ascend`` ``GPU`` ``CPU`` Examples: >>> indices = Tensor([[0, 1], [1, 2]], dtype=mstype.int64) @@ -1938,7 +1938,7 @@ def csr_isinf(x: CSRTensor) -> CSRTensor: TypeError: If `x` is not a CSRTensor. Supported Platforms: - ``CPU`` ``GPU`` + ``GPU`` ``CPU`` Examples: >>> indptr = Tensor([0, 1, 2, 2], dtype=mstype.int32) @@ -1978,7 +1978,7 @@ def coo_isinf(x: COOTensor) -> COOTensor: TypeError: If `x` is not a COOTensor. Supported Platforms: - ``CPU`` ``GPU`` + ``GPU`` ``CPU`` Examples: >>> indices = Tensor([[0, 1], [1, 2]], dtype=mstype.int64) diff --git a/mindspore/python/mindspore/ops/operations/_grad_ops.py b/mindspore/python/mindspore/ops/operations/_grad_ops.py index 22264b797db..00fe03671e9 100644 --- a/mindspore/python/mindspore/ops/operations/_grad_ops.py +++ b/mindspore/python/mindspore/ops/operations/_grad_ops.py @@ -1444,7 +1444,7 @@ class LayerNormGradGrad(Primitive): ValueError: If gamma, d_dg, d_db don't have the same shape. Supported Platforms: - ``Ascend`` ``CPU`` ``GPU`` + ``Ascend`` ``GPU`` ``CPU`` """ @prim_attr_register @@ -1936,7 +1936,7 @@ class UpsampleNearest3DGrad(Primitive): ValueError: If shape of `x` is not 5D. Supported Platforms: - ``GPU`` ``Ascend`` ``CPU`` + ``Ascend`` ``GPU`` ``CPU`` """ @prim_attr_register def __init__(self, input_size, output_size=None, scales=None): @@ -2541,7 +2541,7 @@ class PdistGrad(Primitive): ValueError: If dimension of `x` is not 2. Supported Platforms: - ``Ascend`` ``CPU`` ``GPU`` + ``Ascend`` ``GPU`` ``CPU`` """ @prim_attr_register @@ -2616,7 +2616,7 @@ class HShrinkGrad(Primitive): TypeError: If dtype of `gradients` or `features` is neither float16 nor float32. Supported Platforms: - ``Ascend`` ``CPU`` ``GPU`` + ``Ascend`` ``GPU`` ``CPU`` """ @prim_attr_register @@ -2990,7 +2990,7 @@ class UpsampleTrilinear3DGrad(Primitive): ValueError: If elements number of `input_size` is not 5. Supported Platforms: - ``Ascend`` ``CPU`` ``GPU`` + ``Ascend`` ``GPU`` ``CPU`` """ @prim_attr_register def __init__(self, input_size, output_size=None, scales=None, align_corners=False): @@ -3240,7 +3240,7 @@ class TraceGrad(Primitive): ValueError: If length of shape of `x_shape` is not equal to 2. Support Platforms: - ``Ascend`` ``CPU`` ``GPU`` + ``Ascend`` ``GPU`` ``CPU`` """ @prim_attr_register @@ -3553,7 +3553,7 @@ class ResizeBicubicGrad(Primitive): ValueError: If `size` dim is not 4. Supported Platforms: - ``Ascend`` ``CPU`` ``GPU`` + ``Ascend`` ``GPU`` ``CPU`` """ @prim_attr_register def __init__(self, align_corners=False, half_pixel_centers=False): diff --git a/mindspore/python/mindspore/ops/operations/_inner_ops.py b/mindspore/python/mindspore/ops/operations/_inner_ops.py index 4e41878ec36..c78df321f4b 100755 --- a/mindspore/python/mindspore/ops/operations/_inner_ops.py +++ b/mindspore/python/mindspore/ops/operations/_inner_ops.py @@ -78,19 +78,25 @@ class ExtractImagePatches(Primitive): Tensor, a 4-D tensor whose data type is same as 'input_x', and the shape is [out_batch, out_depth, out_row, out_col], Where the out_batch is the same as the in_batch and + .. math:: out_depth=ksize\_row * ksize\_col * in\_depth + and if 'padding' is "valid": + .. math:: out\_row=floor((in\_row - (ksize\_row + (ksize\_row - 1) * (rate\_row - 1))) / stride\_row) + 1 out\_col=floor((in\_col - (ksize\_col + (ksize\_col - 1) * (rate\_col - 1))) / stride\_col) + 1 + if 'padding' is "same": + .. math:: out\_row=floor((in\_row - 1) / stride\_row) + 1 out\_col=floor((in\_col - 1) / stride\_col) + 1 - Supported Platforms: - ``GPU`` ``Ascend`` + + Supported Platforms: + ``Ascend`` ``GPU`` """ @prim_attr_register @@ -194,12 +200,14 @@ class Lamb(PrimitiveWithInfer): Default: 0.0. - **global_step** (Tensor) - Tensor to record current global step. - **gradient** (Tensor) - Gradient, has the same shape and data type as `var`. + Outputs: Tensor, the updated parameters. + - **var** (Tensor) - The same shape and data type as `var`. Supported Platforms: - ``GPU`` ``Ascend`` + ``Ascend````GPU`` """ @prim_attr_register diff --git a/mindspore/python/mindspore/ops/operations/array_ops.py b/mindspore/python/mindspore/ops/operations/array_ops.py index ed337c42c1f..cbe3b3c7186 100755 --- a/mindspore/python/mindspore/ops/operations/array_ops.py +++ b/mindspore/python/mindspore/ops/operations/array_ops.py @@ -3595,7 +3595,7 @@ class Mvlgamma(Primitive): Refer to :func:`mindspore.ops.mvlgamma` for more details. Supported Platforms: - ``Ascend`` ``CPU`` ``GPU`` + ``Ascend`` ``GPU`` ``CPU`` Examples: >>> x = Tensor(np.array([[3, 4, 5], [4, 2, 6]]), mindspore.float32) @@ -4039,7 +4039,7 @@ class ScatterMax(_ScatterOpDynamic): and `updates` is greater than 8 dimensions. Supported Platforms: - ``Ascend`` ``CPU`` ``GPU`` + ``Ascend`` ``GPU`` ``CPU`` Examples: >>> input_x = Parameter(Tensor(np.array([[1.0, 2.0, 3.0], [4.0, 5.0, 6.0]]), mindspore.float32), @@ -4272,7 +4272,7 @@ class ScatterSub(Primitive): is required when data type conversion of Parameter is not supported. Supported Platforms: - ``Ascend`` ``CPU`` ``GPU`` + ``Ascend`` ``GPU`` ``CPU`` Examples: >>> input_x = Parameter(Tensor(np.array([[0.0, 0.0, 0.0], [1.0, 1.0, 1.0]]), mindspore.float32), name="x") @@ -5465,7 +5465,7 @@ class Meshgrid(PrimitiveWithInfer): Refer to :func:`mindspore.ops.meshgrid` for more details. Supported Platforms: - ``Ascend`` ``CPU`` ``GPU`` + ``Ascend`` ``GPU`` ``CPU`` Examples: >>> x = Tensor(np.array([1, 2, 3, 4]).astype(np.int32)) @@ -5808,7 +5808,7 @@ class EmbeddingLookup(PrimitiveWithCheck): ValueError: If length of shape of `input_params` is greater than 2. Supported Platforms: - ``Ascend`` ``CPU`` ``GPU`` + ``Ascend`` ``GPU`` ``CPU`` Examples: >>> input_params = Tensor(np.array([[8, 9], [10, 11], [12, 13], [14, 15]]), mindspore.float32) @@ -5883,7 +5883,7 @@ class Identity(Primitive): TypeError: If `x` is not a Tensor. Supported Platforms: - ``Ascend`` ``CPU`` ``GPU`` + ``Ascend`` ``GPU`` ``CPU`` Examples: >>> x = Tensor(np.array([1, 2, 3, 4]), mindspore.int64) @@ -6689,7 +6689,7 @@ class TensorScatterElements(Primitive): value of that position in the output will be nondeterministic. Supported Platforms: - ``Ascend`` ``CPU`` ``GPU`` + ``Ascend`` ``GPU`` ``CPU`` Examples: >>> op = ops.TensorScatterElements(0, "none") @@ -6964,7 +6964,7 @@ class LowerBound(Primitive): ValueError: If the first dimension of the shape of `sorted_x` is not equal to that of `values`. Supported Platforms: - ``CPU`` ``GPU`` + ``GPU`` ``CPU`` Examples: >>> import mindspore @@ -7017,7 +7017,7 @@ class UpperBound(Primitive): ValueError: If the number of rows of `sorted_x` is not consistent with that of `values`. Supported Platforms: - ``CPU`` ``GPU`` + ``GPU`` ``CPU`` Examples: >>> import mindspore @@ -7618,7 +7618,7 @@ class HammingWindow(Primitive): ValueError: If data of `length` is negative. Supported Platforms: - ``Ascend`` ``CPU`` ``GPU`` + ``Ascend`` ``GPU`` ``CPU`` Examples: >>> # case 1: periodic=True. diff --git a/mindspore/python/mindspore/ops/operations/image_ops.py b/mindspore/python/mindspore/ops/operations/image_ops.py index 64123ba4435..051e9b1900e 100644 --- a/mindspore/python/mindspore/ops/operations/image_ops.py +++ b/mindspore/python/mindspore/ops/operations/image_ops.py @@ -462,7 +462,7 @@ class NonMaxSuppressionWithOverlaps(Primitive): ValueError: If the shape of `scores` is not equal to the shape of the dim0 or dim1 of `overlaps`. Supported Platforms: - ``Ascend`` ``CPU`` ``GPU`` + ``Ascend`` ``GPU`` ``CPU`` Examples: >>> overlaps = Tensor(np.array([[0.6964692, 0.28613934, 0.22685145, 0.5513148], @@ -662,7 +662,7 @@ class ResizeLinear1D(Primitive): TypeError: If `coordinate_transformation_mode` is not in the support list. Supported Platforms: - ``CPU`` ``GPU`` + ``GPU`` ``CPU`` Examples: >>> input = Tensor([[[1, 2, 3], [4, 5, 6]]], mindspore.float32) @@ -718,7 +718,7 @@ class ResizeBilinearV2(Primitive): ValueError: If `size` contains other than 2 elements. Supported Platforms: - ``Ascend`` ``CPU`` ``GPU`` + ``Ascend`` ``GPU`` ``CPU`` Examples: >>> x = Tensor([[[[1, 2, 3, 4, 5], [1, 2, 3, 4, 5]]]], mindspore.float32) @@ -780,7 +780,7 @@ class ResizeBicubic(Primitive): Supported Platforms: - ``Ascend`` ``CPU`` ``GPU`` + ``Ascend`` ``GPU`` ``CPU`` Examples: >>> class NetResizeBicubic(nn.Cell): @@ -883,7 +883,7 @@ class ResizeArea(Primitive): ValueError: If any value of `size` is not positive. Supported Platforms: - ``Ascend`` ``CPU`` ``GPU`` + ``Ascend`` ``GPU`` ``CPU`` Examples: >>> images = Tensor([[[[2], [4], [6], [8]], [[10], [12], [14], [16]]]], mindspore.float16) diff --git a/mindspore/python/mindspore/ops/operations/math_ops.py b/mindspore/python/mindspore/ops/operations/math_ops.py index 5eab5f77014..071c6efb94f 100644 --- a/mindspore/python/mindspore/ops/operations/math_ops.py +++ b/mindspore/python/mindspore/ops/operations/math_ops.py @@ -3278,7 +3278,7 @@ class TruncateDiv(Primitive): TypeError: If `x` and `y` is not one of the following: Tensor, Number, bool. Supported Platforms: - ``Ascend`` ``CPU`` ``GPU`` + ``Ascend`` ``GPU`` ``CPU`` Examples: >>> x = Tensor(np.array([2, 4, -1]), mindspore.int32) @@ -3331,7 +3331,7 @@ class TruncateMod(Primitive): ValueError: If the shape `x` and `y` cannot be broadcasted to each other. Supported Platforms: - ``Ascend`` ``CPU`` ``GPU`` + ``Ascend`` ``GPU`` ``CPU`` Examples: >>> x = Tensor(np.array([2, 4, -1]), mindspore.int32) @@ -4698,7 +4698,7 @@ class Sign(Primitive): TypeError: If `x` is not a Tensor. Supported Platforms: - ``Ascend`` ``CPU`` ``GPU`` + ``Ascend`` ``GPU`` ``CPU`` Examples: >>> x = Tensor(np.array([[2.0, 0.0, -1.0]]), mindspore.float32) @@ -4743,7 +4743,7 @@ class Tan(Primitive): Refer to :func:`mindspore.ops.tan` for more details. Supported Platforms: - ``Ascend`` ``CPU`` ``GPU`` + ``Ascend`` ``GPU`` ``CPU`` Examples: >>> tan = ops.Tan() @@ -4815,7 +4815,7 @@ class Atan2(_MathBinaryOp): Refer to :func:`mindspore.ops.atan2` for more details. Supported Platforms: - ``Ascend`` ``CPU`` ``GPU`` + ``Ascend`` ``GPU`` ``CPU`` Examples: >>> x = Tensor(np.array([0, 1]), mindspore.float32) @@ -4888,7 +4888,7 @@ class BitwiseAnd(_BitwiseBinaryOp): Refer to :func:`mindspore.ops.bitwise_and` for more details. Supported Platforms: - ``Ascend`` ``CPU`` ``GPU`` + ``Ascend`` ``GPU`` ``CPU`` Examples: >>> x = Tensor(np.array([0, 0, 1, -1, 1, 1, 1]), mindspore.int16) @@ -4907,7 +4907,7 @@ class BitwiseOr(_BitwiseBinaryOp): Refer to :func:`mindspore.ops.bitwise_or` for more details. Supported Platforms: - ``Ascend`` ``CPU`` ``GPU`` + ``Ascend`` ``GPU`` ``CPU`` Examples: >>> x = Tensor(np.array([0, 0, 1, -1, 1, 1, 1]), mindspore.int16) @@ -4926,7 +4926,7 @@ class BitwiseXor(_BitwiseBinaryOp): Refer to :func:`mindspore.ops.bitwise_xor` for more details. Supported Platforms: - ``Ascend`` ``CPU`` ``GPU`` + ``Ascend`` ``GPU`` ``CPU`` Examples: >>> x = Tensor(np.array([0, 0, 1, -1, 1, 1, 1]), mindspore.int16) @@ -5795,7 +5795,7 @@ class ComplexAbs(Primitive): TypeError: If the input type is not complex64 or complex128. Supported Platforms: - ``Ascend`` ``CPU`` ``GPU`` + ``Ascend`` ``GPU`` ``CPU`` Examples: >>> x = Tensor(np.asarray(np.complex(3+4j)), mindspore.complex64) @@ -5858,7 +5858,7 @@ class Complex(Primitive): TypeError: If the dtypes of two inputs are not same. Supported Platforms: - ``Ascend`` ``CPU`` ``GPU`` + ``Ascend`` ``GPU`` ``CPU`` Examples: >>> real = Tensor(np.array([1]), mindspore.float32) @@ -6363,7 +6363,7 @@ class LuSolve(Primitive): ValueError: If `x` dimension less than 2, `lu_data` dimension less than 2 or `lu_pivots` dimension less than 1. Supported Platforms: - ``Ascend`` ``CPU`` ``GPU`` + ``Ascend`` ``GPU`` ``CPU`` Examples: >>> x = Tensor(np.array([[1], [3], [3]]), mindspore.float32) @@ -6853,7 +6853,7 @@ class Zeta(Primitive): ValueError: If shape of `x` is not same as the `q`. Supported Platforms: - ``Ascend`` ``CPU`` ``GPU`` + ``Ascend`` ``GPU`` ``CPU`` Examples: >>> x = Tensor(np.array([10.]), mindspore.float32) @@ -6960,7 +6960,7 @@ class Renorm(Primitive): Refer to :func:`mindspore.ops.renorm` for more details. Supported Platforms: - ``Ascend`` ``CPU`` ``GPU`` + ``Ascend`` ``GPU`` ``CPU`` Examples: >>> x = Tensor(np.array([[1, 1, 1], [2, 2, 2], [3, 3, 3]]), mindspore.float32) @@ -7298,7 +7298,7 @@ class NextAfter(Primitive): ValueError: If `x1`'s shape is not the same as `x2`. Supported Platforms: - ``Ascend`` ``CPU`` ``GPU`` + ``Ascend`` ``GPU`` ``CPU`` Examples: >>> nextafter = ops.NextAfter() diff --git a/mindspore/python/mindspore/ops/operations/nn_ops.py b/mindspore/python/mindspore/ops/operations/nn_ops.py index a14a3fb217c..f24cc356209 100644 --- a/mindspore/python/mindspore/ops/operations/nn_ops.py +++ b/mindspore/python/mindspore/ops/operations/nn_ops.py @@ -1273,7 +1273,7 @@ class BatchNorm(PrimitiveWithInfer): TypeError: If dtype of `input_x`, `scale` is neither float16 nor float32. Supported Platforms: - ``Ascend`` ``CPU`` ``GPU`` + ``Ascend`` ``GPU`` ``CPU`` Examples: >>> input_x = Tensor(np.ones([2, 2]), mindspore.float32) @@ -3664,7 +3664,7 @@ class ResizeBilinear(PrimitiveWithInfer): ValueError: If length of shape of `x` is not equal to 4. Supported Platforms: - ``Ascend`` ``CPU`` ``GPU`` + ``Ascend`` ``GPU`` ``CPU`` Examples: >>> x = Tensor([[[[1, 2, 3, 4, 5], [1, 2, 3, 4, 5]]]], mindspore.float32) @@ -3752,7 +3752,7 @@ class UpsampleTrilinear3D(Primitive): ValueError: If size of `output_size` is not equal 3 when `output_size` is specified. Supported Platforms: - ``Ascend`` ``CPU`` ``GPU`` + ``Ascend`` ``GPU`` ``CPU`` Examples: >>> ops = ops.UpsampleTrilinear3D(output_size=[4, 64, 48]) @@ -5689,7 +5689,7 @@ class ApplyAdadelta(Primitive): is not supported. Supported Platforms: - ``Ascend`` ``CPU`` ``GPU`` + ``Ascend`` ``GPU`` ``CPU`` Examples: >>> import numpy as np @@ -5784,7 +5784,7 @@ class ApplyAdagrad(Primitive): RuntimeError: If the data type of `var`, `accum` and `grad` conversion of Parameter is not supported. Supported Platforms: - ``Ascend`` ``CPU`` ``GPU`` + ``Ascend`` ``GPU`` ``CPU`` Examples: >>> class Net(nn.Cell): @@ -5980,7 +5980,7 @@ class SparseApplyAdagradV2(Primitive): RuntimeError: If the data type of `var`, `accum` and `grad` conversion of Parameter is not supported. Supported Platforms: - ``Ascend`` ``CPU`` ``GPU`` + ``Ascend`` ``GPU`` ``CPU`` Examples: >>> class Net(nn.Cell): @@ -8363,7 +8363,7 @@ class SoftShrink(Primitive): Refer to :func:`mindspore.ops.soft_shrink` for more details. Supported Platforms: - ``Ascend`` ``CPU`` ``GPU`` + ``Ascend`` ``GPU`` ``CPU`` Examples: >>> import mindspore @@ -8391,7 +8391,7 @@ class HShrink(Primitive): Refer to :func:`mindspore.ops.hardshrink` for more details. Supported Platforms: - ``Ascend`` ``CPU`` ``GPU`` + ``Ascend`` ``GPU`` ``CPU`` Examples: >>> import mindspore as ms @@ -8596,7 +8596,7 @@ class SparseApplyRMSProp(Primitive): RuntimeError: If the data type of `var`, `ms`, `mom` and `grad` conversion of Parameter is not supported. Supported Platforms: - ``Ascend`` ``CPU`` ``GPU`` + ``Ascend`` ``GPU`` ``CPU`` Examples: >>> class SparseApplyRMSPropNet(nn.Cell): @@ -8938,7 +8938,7 @@ class ApplyAdamWithAmsgrad(Primitive): ValueError: If the shape of `beta1_power`, `beta2_power`, `lr` is not 0. Supported Platforms: - ``Ascend`` ``CPU`` ``GPU`` + ``Ascend`` ``GPU`` ``CPU`` Examples: >>> class ApplyAdamWithAmsgradNet(nn.Cell): @@ -9480,7 +9480,7 @@ class TripletMarginLoss(Primitive): ValueError: If `reduction` is not one of 'none', 'mean', 'sum'. Supported Platforms: - ``Ascend`` ``CPU`` ``GPU`` + ``Ascend`` ``GPU`` ``CPU`` Examples: >>> loss = ops.TripletMarginLoss() @@ -9510,7 +9510,7 @@ class DeformableOffsets(Primitive): Refer to :func:`mindspore.ops.deformable_conv2d` for more details. Supported Platforms: - ``Ascend`` ``CPU`` ``GPU`` + ``Ascend`` ``GPU`` ``CPU`` """ @prim_attr_register @@ -9559,8 +9559,7 @@ class DeformableOffsets(Primitive): class GridSampler2D(Primitive): """ This operation samples 2d input_x by using interpolation based on flow field grid, - which is usually gennerated by - affine_grid. + which is usually gennerated by :func:`mindspore.ops.affine_grid`. Args: interpolation_mode (str, optional): An optional string specifying the interpolation method. @@ -9656,7 +9655,7 @@ class Pdist(Primitive): ValueError: If dimension of `x` is not 2. Supported Platforms: - ``Ascend`` ``CPU`` ``GPU`` + ``Ascend`` ``GPU`` ``CPU`` Examples: >>> from mindspore import Tensor diff --git a/mindspore/python/mindspore/ops/operations/sparse_ops.py b/mindspore/python/mindspore/ops/operations/sparse_ops.py index d1f0e991e89..3399f611c31 100644 --- a/mindspore/python/mindspore/ops/operations/sparse_ops.py +++ b/mindspore/python/mindspore/ops/operations/sparse_ops.py @@ -223,7 +223,7 @@ class SparseSlice(Primitive): ValueError: If the shape of `shape` is not corresponding to `size`. Supported Platforms: - ``Ascend`` ``CPU`` ``GPU`` + ``Ascend`` ``GPU`` ``CPU`` Examples: >>> indices = Tensor(np.array([[0, 1], [1, 2], [1, 3], [2, 2]]).astype(np.int64)) @@ -1527,7 +1527,7 @@ class SparseAdd(Primitive): TypeError: If (x1_values/x2_values)'s type is not matched with thresh's type. Supported Platforms: - ``CPU`` ``GPU`` + ``GPU`` ``CPU`` Examples: >>> from mindspore import Tensor diff --git a/mindspore/python/mindspore/scipy/linalg.py b/mindspore/python/mindspore/scipy/linalg.py index b136f9b0025..f0149567b24 100755 --- a/mindspore/python/mindspore/scipy/linalg.py +++ b/mindspore/python/mindspore/scipy/linalg.py @@ -56,7 +56,7 @@ def block_diag(*arrs): ValueError: If there are Tensors with dimensions higher than 2 in all arguments. Supported Platforms: - ``CPU`` ``GPU`` + ``GPU`` ``CPU`` Examples: >>> import numpy as onp @@ -155,7 +155,7 @@ def solve_triangular(a, b, trans=0, lower=False, unit_diagonal=False, ValueError: If `a` is singular matrix. Supported Platforms: - ``CPU`` ``GPU`` + ``GPU`` ``CPU`` Examples: Solve the lower triangular system :math:`a x = b`, where:: @@ -224,7 +224,7 @@ def inv(a, overwrite_a=False, check_finite=True): ValueError: If :math:`a` is not square, or not 2D. Supported Platforms: - ``CPU`` ``GPU`` + ``GPU`` ``CPU`` Examples: >>> import numpy as onp @@ -289,7 +289,7 @@ def cho_factor(a, lower=False, overwrite_a=False, check_finite=True): ValueError: If input a tensor is not a square matrix or it's dims not equal to 2D. Supported Platforms: - ``CPU`` ``GPU`` + ``GPU`` ``CPU`` Examples: >>> import numpy as onp @@ -350,7 +350,7 @@ def cholesky(a, lower=False, overwrite_a=False, check_finite=True): ValueError: If input a tensor is not a square matrix or it's dims not equal to 2D. Supported Platforms: - ``CPU`` ``GPU`` + ``GPU`` ``CPU`` Examples: >>> import numpy as onp @@ -402,7 +402,7 @@ def cho_solve(c_and_lower, b, overwrite_b=False, check_finite=True): Tensor, the solution to the system a x = b Supported Platforms: - ``CPU`` ``GPU`` + ``GPU`` ``CPU`` Examples: >>> import numpy as onp @@ -512,7 +512,7 @@ def eigh(a, b=None, lower=True, eigvals_only=False, overwrite_a=False, ValueError: If `eigvals` is not None. Supported Platforms: - ``CPU`` ``GPU`` + ``GPU`` ``CPU`` Examples: >>> import numpy as onp @@ -603,7 +603,7 @@ def lu_factor(a, overwrite_a=False, check_finite=True): ValueError: If :math:`a` is not square. Supported Platforms: - ``CPU`` ``GPU`` + ``GPU`` ``CPU`` Examples: >>> import numpy as onp @@ -672,7 +672,7 @@ def lu(a, permute_l=False, overwrite_a=False, check_finite=True): - Tensor, :math:`(K, N)` upper triangular or trapezoidal matrix. Supported Platforms: - ``CPU`` ``GPU`` + ``GPU`` ``CPU`` Examples: >>> import numpy as onp @@ -750,7 +750,7 @@ def lu_solve(lu_and_piv, b, trans=0, overwrite_b=False, check_finite=True): Tensor, solution to the system Supported Platforms: - ``CPU`` ``GPU`` + ``GPU`` ``CPU`` Examples: >>> import numpy as onp diff --git a/mindspore/python/mindspore/scipy/optimize/line_search.py b/mindspore/python/mindspore/scipy/optimize/line_search.py index b87ab6a6949..675a0bbf159 100644 --- a/mindspore/python/mindspore/scipy/optimize/line_search.py +++ b/mindspore/python/mindspore/scipy/optimize/line_search.py @@ -327,7 +327,7 @@ def line_search(f, xk, pk, jac=None, gfk=None, old_fval=None, old_old_fval=None, LineSearchResults, results of line search results. Supported Platforms: - ``CPU`` ``GPU`` + ``GPU`` ``CPU`` Examples: >>> import numpy as onp diff --git a/mindspore/python/mindspore/scipy/optimize/minimize.py b/mindspore/python/mindspore/scipy/optimize/minimize.py index 82abfbec656..48cdc3b808d 100644 --- a/mindspore/python/mindspore/scipy/optimize/minimize.py +++ b/mindspore/python/mindspore/scipy/optimize/minimize.py @@ -96,7 +96,7 @@ def minimize(func, x0, args=(), method=None, jac=None, hess=None, hessp=None, bo OptimizeResults, object holding optimization results. Supported Platforms: - ``CPU`` ``GPU`` + ``GPU`` ``CPU`` Examples: >>> import numpy as onp diff --git a/mindspore/python/mindspore/scipy/sparse/linalg.py b/mindspore/python/mindspore/scipy/sparse/linalg.py index 7cc2a6e8a37..8406c012e83 100644 --- a/mindspore/python/mindspore/scipy/sparse/linalg.py +++ b/mindspore/python/mindspore/scipy/sparse/linalg.py @@ -318,7 +318,7 @@ def gmres(A, b, x0=None, *, tol=1e-5, restart=20, maxiter=None, >0 : convergence to tolerance not achieved, number of iterations. <0 : illegal input or breakdown. Supported Platforms: - ``CPU`` ``GPU`` + ``GPU`` ``CPU`` Examples: >>> import numpy as onp @@ -493,7 +493,7 @@ def cg(A, b, x0=None, *, tol=1e-5, atol=0.0, maxiter=None, M=None, callback=None TypeError: If `A` and `b` don't have the same data types. Supported Platforms: - ``CPU`` ``GPU`` + ``GPU`` ``CPU`` Examples: >>> import numpy as onp @@ -617,7 +617,7 @@ def bicgstab(A, b, x0=None, *, tol=1e-5, atol=0.0, maxiter=None, M=None): TypeError: If `A`, `x0` and `b` don't have the same float types(`mstype.float32` or `mstype.float64`). Supported Platforms: - ``CPU`` ``GPU`` + ``GPU`` ``CPU`` Examples: >>> import numpy as onp diff --git a/mindspore/python/mindspore/train/serialization.py b/mindspore/python/mindspore/train/serialization.py index bb631784d7e..4219ca7ff62 100644 --- a/mindspore/python/mindspore/train/serialization.py +++ b/mindspore/python/mindspore/train/serialization.py @@ -1884,7 +1884,8 @@ def load_distributed_checkpoint(network, checkpoint_filenames, predict_strategy= """ Load checkpoint into net for distributed predication. Used in the case of distributed inference. For details of distributed inference, please check: - ``_. + `Distributed Inference + `_ . Args: network (Cell): Network for distributed predication.