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@ -53,15 +53,15 @@ mindspore.rewrite
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异常：
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- **TypeError** - 参数 `network` 不是Cell类型对象。
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.. py:method:: mindspore.rewrite.SymbolTree.create_call_function(self, func, targets, args, kwargs)
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.. py:method:: mindspore.rewrite.SymbolTree.create_call_function(func, targets, args, kwargs)
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创建一个Node对象，并生成执行代码插入源码中。源码中以 `args` 和 `kwargs` 为参数调用 `func` 函数。
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参数：
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- **func** (FunctionType) - 要被调用的函数。
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- **targets** (list[str]) - 表示输出名称。在源代码中作为节点的输出。
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- **targets** (list[str]) - 表示输出名称。在源代码中作为节点的输出。
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- **args** (Union[MsDtypes, ParamTypes]) - 该节点的参数名称。用作源代码中代码语句的参数。默认为None表示 `cell` 没有参数输入。
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- **kwargs** ({str: Union[MsDtypes, ParamTypes]}) - 键的类型必须是str，值必须是MsDtypes或类型必须是ParamTypes。用来说明带有关键字的形参的输入参数名称。输入名称在源代码中作为语句表达式中的 `kwargs`。默认为None，表示没有 `kwargs` 输入。
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- **kwargs** (dict{str,Union[MsDtypes, ParamTypes]}) - 键的类型必须是str，值必须是MsDtypes或类型必须是ParamTypes。用来说明带有关键字的形参的输入参数名称。输入名称在源代码中作为语句表达式中的 `kwargs`。默认为None，表示没有 `kwargs` 输入。
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返回：
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一个Node实例。
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@ -3794,7 +3794,7 @@ class SBDataset(GeneratorDataset):
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- The tensor of column :py:obj:`image` is of the uint8 type.
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- The tensor of column :py:obj:`task` contains 20 images of the uint8 type if `task` is 'Boundaries' otherwise
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contains 1 image of the uint8 type.
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contains 1 image of the uint8 type.
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Args:
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dataset_dir (str): Path to the root directory that contains the dataset.
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@ -112,8 +112,8 @@ class MaxPool3d(Cell):
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Inputs:
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- **x** (Tensor) - Tensor of shape :math:`(N_{in}, C_{in}, D_{in}, H_{in}, W_{in})` or
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:math:`(C_{in}, D_{in}, H_{in}, W_{in})` with data type of int8, int16, int32,
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int64, uint8, uint16, uint32, uint64, float16, float32 or float64.
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:math:`(C_{in}, D_{in}, H_{in}, W_{in})` with data type of int8, int16, int32,
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int64, uint8, uint16, uint32, uint64, float16, float32 or float64.
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Outputs:
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If `return_indices` is False, output is a Tensor, with shape :math:`(N, C, D_{out}, H_{out}, W_{out})`, or
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@ -2263,7 +2263,7 @@ class GaussianNLLLoss(LossBase):
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full (bool): Include the constant term in the loss calculation. When :math:`full=True`, the constant term
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`const.` will be :math:`0.5 * log(2\pi)`. Default: False.
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eps (float): Used to improve the stability of log function. Default: 1e-6.
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reduction (string): Apply specific reduction method to the output: 'none', 'mean', or 'sum'. Default: 'mean'.
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reduction (str): Apply specific reduction method to the output: 'none', 'mean', or 'sum'. Default: 'mean'.
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Inputs:
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- **logits** (Tensor) - Tensor of shape :math:`(N, *)` or :math:`(*)` where :math:`*` means any number of
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@ -158,9 +158,9 @@ def reverse(x, axis):
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The value range of "axis" is [-dims, dims - 1]. "dims" is the dimension length of "input_x".
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Args:
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- **x** (Tensor) - The target tensor. The data type is Number except float64.
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The shape is :math:`(N,*)` where :math:`*` means, any number of additional dimensions.
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- **axis** (Union[tuple(int), list(int)]): The indices of the dimensions to reverse.
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x (Tensor): The target tensor. The data type is Number except float64.
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The shape is :math:`(N,*)` where :math:`*` means, any number of additional dimensions.
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axis (Union[tuple(int), list(int)]): The indices of the dimensions to reverse.
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Outputs:
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Tensor, has the same shape and type as `x`.
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@ -58,7 +58,7 @@ def _environment_check():
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class Profiler:
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"""
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r"""
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This class to enable the profiling of MindSpore neural networks.
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MindSpore users can import the mindspore.Profiler, initialize the Profiler object to start profiling,
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and use Profiler.analyse() to stop profiling and analyse the results.
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@ -85,7 +85,7 @@ class Profiler:
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- 2: Memory contains ub_read/write_bw, l1_read/write_bw, l2_read/write_bw, main_mem_read/write_bw etc.
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- 3: MemoryL0 contains l0a_read/write_bw, l0b_read/write_bw, l0c_read/write_bw etc.
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- 4: ResourceConflictRatio contains vec_bankgroup/bank/resc_cflt_ratio etc.
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- 5: MemoryUB contains ub_read/write_bw_mte, ub_read/write_bw_vector, ub_/write_bw_scalar etc.
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- 5: MemoryUB contains ub_read/write_bw_mte, ub_read/write_bw_vector, ub\_/write_bw_scalar etc.
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l2_cache (bool, optional): (Ascend only) Whether to collect l2 cache data, collect when True. Default: False.
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@ -75,17 +75,18 @@ class SymbolTree:
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raise TypeError(f"For call-function Node, got unsupported kwarg value: {v}, type: {type(v)}")
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def create_call_function(self, func, targets, *args, **kwargs):
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"""
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r"""
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Create a Node object and generate the execution code to insert into the source code.
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The source code calls the 'func' function with 'args' and' kwargs' as parameters.
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Args:
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func (FunctionType) - The function to be called.
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targets (list [str]) - indicates the output name. As the output of the node in the source code.
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args (Union[MsDtypes, ParamTypes]) - parameter name of the node. Used as a parameter to a code statement in
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func (FunctionType): The function to be called.
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targets (list[str]): indicates the output name. As the output of the node in the source code.
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args (Union[MsDtypes, ParamTypes]): parameter name of the node. Used as a parameter to a code statement in
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source code. The default value is None, which means there is no parameter input in the cell.
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kwargs ({str: Union[MsDtypes, ParamTypes]}) - The key type must be str, and the value must be value or type
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must be ParamTypes. The input parameter name used to describe the formal parameter with a keyword.
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kwargs (dict{str,Union[MsDtypes, ParamTypes]}): The key type must be str,
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and the value must be value or type must be ParamTypes.
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The input parameter name used to describe the formal parameter with a keyword.
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Enter the name in the source code as the 'kwargs' in the statement expression.The default value is
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None, which means there is no 'kwargs' input.
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