modify the format of files 1126

This commit is contained in:
huanxiaoling 2022-11-26 10:38:34 +08:00
parent ddedbceeed
commit b30974c6d4
8 changed files with 12 additions and 12 deletions

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@ -78,7 +78,7 @@ mindspore.train
----------
.. mscnautosummary::
:toctree: mindspore
:toctree: train
mindspore.train.ConvertModelUtils
mindspore.train.ConvertNetUtils

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@ -55,4 +55,4 @@
- **ValueError** - 如果参数 `stride` 的取值范围不是 `[1, 255]`
- **ValueError** - 如果参数 `dilation` 的值小于1。
- **ValueError** - 如果参数 `pad_mode` 不是 `same``valid``SAME` 或者 `VALID`
- **ValueError** - 如果参数 `data_format` 不是字符串`NCHW`
- **ValueError** - 如果参数 `data_format` 不是字符串 `NCHW`

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@ -40,6 +40,6 @@ mindspore.ops.Lstsq
- **TypeError** - 若输入 `x``a` 不是Tensor。
- **TypeError** - 若 `x``a` 的数据类型不是以下之一float16、float32、float64。
- **TypeError** - 若 `x``a` 的数据类型不同。
- **TypeError** - 若 `x` 的维度不等于2。
- **ValueError** - 若 `x` 的维度不等于2。
- **ValueError** - 若 `a` 的维度不等于2或1。
- **ValueError** - 若 `x``a` shape的第0维不相等。

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@ -1,7 +1,7 @@
mindspore.ops.Nonzero
======================
.. py:class:: mindspore.nn.Nonzero
.. py:class:: mindspore.ops.Nonzero
计算输入Tensor中所有非零元素的下标。

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@ -82,7 +82,7 @@ Thor
---------------
.. autosummary::
:toctree: mindspore
:toctree: train
:nosignatures:
:template: classtemplate.rst

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@ -97,7 +97,7 @@ class Converter:
corresponding to `model_file` parameter; 'model.Caffemodel' is model weight value file, corresponding to
`weight_file` parameter. For example, "/home/user/model.caffemodel". Default: "".
config_file (str, optional): Set the path of the configuration file of Converter can be used to post-training,
offline split op to parallel, disable op fusion ability and set plugin so path. `config_file' uses the
offline split op to parallel, disable op fusion ability and set plugin so path. `config_file` uses the
`key = value` method to define the related parameters.
For the configuration parameters related to post training quantization, please refer to
`quantization <https://www.mindspore.cn/lite/docs/en/master/use/post_training_quantization.html>`_ .

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@ -5797,7 +5797,7 @@ class ComplexAbs(Primitive):
Outputs:
Tensor, has the same shape as x. If the type of x is complex64, the type of output is float32.
If the type of x is complex128, the type of output is float64.
If the type of x is complex128, the type of output is float64.
Raises:
TypeError: If the input is not a Tensor.
@ -7332,7 +7332,7 @@ class MatrixTriangularSolve(Primitive):
Raises:
TypeError: If `matrix` or `rhs` is not a Tensor.
TypeError: If `lower` or `adjoint` is not bool.
ValueError: If the batch sizes of `matrix`and `rhs` are not equal.
ValueError: If the batch sizes of `matrix` and `rhs` are not equal.
ValueError: If the inner-most 2 dimensions of `matrix` are not equal.
ValueError: If the second-last dimensions of `matrix` and `rhs` are not equal.

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@ -1405,9 +1405,9 @@ class DataFormatVecPermute(Primitive):
Permute input tensor from src_format to dst_format.
Args:
src_format (str): An optional value for source data format. The format can be 'NHWC' and 'NCHW'.
src_format (str, optional): An optional value for source data format. The format can be 'NHWC' and 'NCHW'.
Default: 'NHWC'.
dst_format (str): An optional value for destination data format. The format can be 'NHWC' and 'NCHW'.
dst_format (str, optional): An optional value for destination data format. The format can be 'NHWC' and 'NCHW'.
Default: 'NCHW'.
Inputs:
@ -10215,8 +10215,8 @@ class FractionalMaxPoolWithFixedKsize(Primitive):
TypeError: If data type of `random_samples` is not one of the following: float16, float32, float64.
ValueError: If `ksize` is not a number and `ksize` is not a tuple of length 2.
ValueError: If `output_shape` is not a number and `output_shape` is not a tuple of length 2.
ValueError: If the sum of `ksize`, `output_shape` and -1 is larger than the corresponding
dimension of `input_x`.
ValueError: If the sum of `ksize` , `output_shape` and
-1 is larger than the corresponding dimension of `input_x`.
ValueError: If the dimension of `random_samples` is not 3.
ValueError: If the first dimension size of `input_x` and `random_samples` is not equal.
ValueError: If the second dimension size of `input_x` and `random_samples` is not equal.