p47068915
/
mindspore
forked from mindspore-Ecosystem/mindspore
1
0
Fork 0
Code Issues Pull Requests Projects Releases Wiki Activity

Fix the docs for its format problems

This commit is contained in:
dinglinhe 2021-09-03 11:11:09 +08:00
parent 54cd78d25c
commit f6f445a30a
3 changed files with 6 additions and 8 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

4
mindspore/nn/grad/cell_grad.py
View File

@ -62,7 +62,7 @@ class Jvp(Cell):
>>> from mindspore.nn.grad import Jvp >>> from mindspore.nn.grad import Jvp
>>> class Net(nn.Cell): >>> class Net(nn.Cell):
... def construct(self, x, y): ... def construct(self, x, y):
... return x**3 + y ... return x**3 + y
>>> x = Tensor(np.array([[1, 2], [3, 4]]).astype(np.float32)) >>> x = Tensor(np.array([[1, 2], [3, 4]]).astype(np.float32))
>>> y = Tensor(np.array([[1, 2], [3, 4]]).astype(np.float32)) >>> y = Tensor(np.array([[1, 2], [3, 4]]).astype(np.float32))
>>> v = Tensor(np.array([[1, 1], [1, 1]]).astype(np.float32)) >>> v = Tensor(np.array([[1, 1], [1, 1]]).astype(np.float32))
@ -126,7 +126,7 @@ class Vjp(Cell):
>>> from mindspore.nn.grad import Vjp >>> from mindspore.nn.grad import Vjp
>>> class Net(nn.Cell): >>> class Net(nn.Cell):
... def construct(self, x, y): ... def construct(self, x, y):
... return x**3 + y ... return x**3 + y
>>> x = Tensor(np.array([[1, 2], [3, 4]]).astype(np.float32)) >>> x = Tensor(np.array([[1, 2], [3, 4]]).astype(np.float32))
>>> y = Tensor(np.array([[1, 2], [3, 4]]).astype(np.float32)) >>> y = Tensor(np.array([[1, 2], [3, 4]]).astype(np.float32))
>>> v = Tensor(np.array([[1, 1], [1, 1]]).astype(np.float32)) >>> v = Tensor(np.array([[1, 1], [1, 1]]).astype(np.float32))

6
mindspore/nn/wrap/loss_scale.py
View File

@ -175,8 +175,7 @@ class FixedLossScaleUpdateCell(Cell):
Examples: Examples:
>>> import numpy as np >>> import numpy as np
>>> from mindspore import Tensor, Parameter, nn >>> from mindspore import Tensor, Parameter, nn, ops
>>> from mindspore.ops as ops
>>> >>>
>>> class Net(nn.Cell): >>> class Net(nn.Cell):
... def __init__(self, in_features, out_features): ... def __init__(self, in_features, out_features):
@ -248,8 +247,7 @@ class TrainOneStepWithLossScaleCell(TrainOneStepCell):
Examples: Examples:
>>> import numpy as np >>> import numpy as np
>>> from mindspore import Tensor, Parameter, nn >>> from mindspore import Tensor, Parameter, nn, ops
>>> from mindspore.ops as ops
>>> from mindspore import dtype as mstype >>> from mindspore import dtype as mstype
>>> >>>
>>> class Net(nn.Cell): >>> class Net(nn.Cell):

4
mindspore/ops/primitive.py
View File

@ -143,7 +143,7 @@ class Primitive(Primitive_):
Args: Args:
stage (int): The stage id for the current operation. stage (int): The stage id for the current operation.
Examples: Examples:
>>> from mindspore.ops as ops >>> from mindspore import ops
>>> add = ops.Add() >>> add = ops.Add()
>>> print(add.set_stage(0)) >>> print(add.set_stage(0))
Prim[Add]<stage=0> Prim[Add]<stage=0>
@ -162,7 +162,7 @@ class Primitive(Primitive_):
Args: Args:
strategy (tuple): Strategy describes the distributed parallel mode of the current primitive. strategy (tuple): Strategy describes the distributed parallel mode of the current primitive.
Examples: Examples:
>>> from mindspore.ops as ops >>> from mindspore import ops
>>> add = ops.Add() >>> add = ops.Add()
>>> print(add.shard(((1, 1), (1, 1)))) >>> print(add.shard(((1, 1), (1, 1))))
Prim[Add]<strategy=((1, 1), (1, 1))> Prim[Add]<strategy=((1, 1), (1, 1))>