diff --git a/docs/api/api_python/ops/mindspore.ops.func_coo_concat.rst b/docs/api/api_python/ops/mindspore.ops.func_coo_concat.rst index 6938e10df9d..205ee559329 100644 --- a/docs/api/api_python/ops/mindspore.ops.func_coo_concat.rst +++ b/docs/api/api_python/ops/mindspore.ops.func_coo_concat.rst @@ -10,14 +10,13 @@ mindspore.ops.coo_concat 参数： - **sp_input** (Union[list(COOTensor), tuple(COOTensor)]) - 输入的需要concat合并的稀疏张量。 - - **concat_dim** (标量) - 指定需要合并的轴序号, 它的取值必须是在[-rank, rank)之内， - 其中rank为sp_input中COOTensor的shape的维度值。缺省值为0。 + - **concat_dim** (scalar) - 指定需要合并的轴序号, 它的取值必须是在[-rank, rank)之内， + 其中rank为sp_input中COOTensor的shape的维度值。缺省值为0。 返回： COOTensor，按concat_dim轴合并后的COOTensor。这个COOTensor的稠密shape值为： - 非concat_dim轴shape与输入一致，concat_dim轴shape是所有输入对应轴shape的累加。 + 非concat_dim轴shape与输入一致，concat_dim轴shape是所有输入对应轴shape的累加。 异常： - **ValueError** - 如果只有一个COOTensor输入，报错。 - - **ValueError** - 如果输入的COOTensor的shape纬度大于3。COOTensor的构造会报错， - 目前COOTensor的shape维度只能为2。 + - **ValueError** - 如果输入的COOTensor的shape纬度大于3。COOTensor的构造会报错，目前COOTensor的shape维度只能为2。 diff --git a/docs/api/api_python/ops/mindspore.ops.func_max_unpool3d.rst b/docs/api/api_python/ops/mindspore.ops.func_max_unpool3d.rst index 469256a6691..9d8c3dd3055 100644 --- a/docs/api/api_python/ops/mindspore.ops.func_max_unpool3d.rst +++ b/docs/api/api_python/ops/mindspore.ops.func_max_unpool3d.rst @@ -33,7 +33,7 @@ mindspore.ops.max_unpool3d 取值范围需满足： :math:`[(N, C, D_{out} - stride[0], H_{out} - stride[1], W_{out} - stride[2]), (N, C, D_{out} + stride[0], H_{out} + stride[1], W_{out} + stride[2])]` 。 - 输出： + 返回： shape为 :math:`(N, C, D_{out}, H_{out}, W_{out})` 或 :math:`(C, D_{out}, H_{out}, W_{out})` 的Tensor， 数据类型与输入 `x` 相同。 diff --git a/docs/api/api_python/ops/mindspore.ops.func_split.rst b/docs/api/api_python/ops/mindspore.ops.func_split.rst index dbac73659dd..2b39fe28401 100644 --- a/docs/api/api_python/ops/mindspore.ops.func_split.rst +++ b/docs/api/api_python/ops/mindspore.ops.func_split.rst @@ -8,8 +8,8 @@ mindspore.ops.split 参数： - **x** (Tensor) - Tensor的shape为 :math:`(x_1, x_2, ..., x_R)` 。 - **split_size_or_sections** (Union[int, tuple(int), list(int)]) - 如果 `split_size_or_sections` 是int类型， - `x` 将被均匀的切分成块，每块的大小为 `split_size_or_sections` ，若 `x.shape[axis]` 不能被 `split_size_or_sections` 整除，最后一块大小将小于 `split_size_or_sections` 。 - 如果 `split_size_or_sections` 是个list类型，`x` 将沿 `axis` 轴被切分成 `len(split_size_or_sections)` 块，大小为 `split_size_or_sections` 。 + `x` 将被均匀的切分成块，每块的大小为 `split_size_or_sections` ，若 `x.shape[axis]` 不能被 `split_size_or_sections` 整除，最后一块大小将小于 `split_size_or_sections` 。 + 如果 `split_size_or_sections` 是个list类型，`x` 将沿 `axis` 轴被切分成 `len(split_size_or_sections)` 块，大小为 `split_size_or_sections` 。 - **axis** (int) - 指定分割轴。默认值：0。 返回： diff --git a/docs/api/api_python/ops/mindspore.ops.func_unique_consecutive.rst b/docs/api/api_python/ops/mindspore.ops.func_unique_consecutive.rst index c09d60cadfb..899910ab305 100644 --- a/docs/api/api_python/ops/mindspore.ops.func_unique_consecutive.rst +++ b/docs/api/api_python/ops/mindspore.ops.func_unique_consecutive.rst @@ -20,7 +20,7 @@ mindspore.ops.unique_consecutive 异常： - **TypeError** - `x` 不是Tensor。 - - **TypeError** - `x`的数据类型不支持。 + - **TypeError** - `x` 的数据类型不支持。 - **TypeError** - `return_idx` 不是bool。 - **TypeError** - `return_counts` 不是bool。 - **TypeError** - `axis` 不是int。 diff --git a/mindspore/python/mindspore/dataset/core/config.py b/mindspore/python/mindspore/dataset/core/config.py index 8c3d96fc29f..198f519cfce 100644 --- a/mindspore/python/mindspore/dataset/core/config.py +++ b/mindspore/python/mindspore/dataset/core/config.py @@ -947,9 +947,9 @@ def get_error_samples_mode(): Returns: ErrorSamplesMode, The method in which erroneous samples should be processed in a dataset pipeline. - - ErrorSamplesMode.RETURN: means erroneous sample results in error raised and returned. - - ErrorSamplesMode.REPLACE: means erroneous sample is replaced with an internally determined sample. - - ErrorSamplesMode.SKIP: means erroneous sample is skipped. + - ErrorSamplesMode.RETURN: means erroneous sample results in error raised and returned. + - ErrorSamplesMode.REPLACE: means erroneous sample is replaced with an internally determined sample. + - ErrorSamplesMode.SKIP: means erroneous sample is skipped. Examples: >>> error_samples_mode = ds.config.get_error_samples_mode() diff --git a/mindspore/python/mindspore/ops/function/array_func.py b/mindspore/python/mindspore/ops/function/array_func.py index 9ac1356be69..a580168f731 100644 --- a/mindspore/python/mindspore/ops/function/array_func.py +++ b/mindspore/python/mindspore/ops/function/array_func.py @@ -1010,7 +1010,7 @@ def unique_consecutive(x, return_idx=False, return_counts=False, axis=None): Args: x (Tensor): The input tensor. return_idx (bool, optional): Whether to return the index of where the element in the original input - maps to the position in the output. Default: False. + maps to the position in the output. Default: False. return_counts (bool, optional): Whether to return the counts of each unique element. Default: False. axis (int, optional): The dimension to apply unique. If None, the unique of the flattened input is returned. If specified, it must be int32 or int64. Default: None. diff --git a/mindspore/python/mindspore/ops/function/math_func.py b/mindspore/python/mindspore/ops/function/math_func.py index fdc9592299e..823022e8b13 100644 --- a/mindspore/python/mindspore/ops/function/math_func.py +++ b/mindspore/python/mindspore/ops/function/math_func.py @@ -3687,7 +3687,7 @@ def is_complex(x): Return True if the data type of the tensor is complex, otherwise return False. Args: - x (Tensor) - The input tensor. + x (Tensor): The input tensor. Returns: Bool, return whether the data type of the tensor is complex.