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fix the docs of operators like Pad, MatrixDiag, Cellist and DemseThor

This commit is contained in:
dinglinhe 2021-07-07 19:14:28 +08:00
parent f9c910e40a
commit 9dfd4047e6
3 changed files with 9 additions and 8 deletions
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4
mindspore/nn/layer/basic.py
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@ -712,7 +712,7 @@ class Pad(Cell):
... self.pad = nn.Pad(paddings=((1, 1), (2, 2)), mode="CONSTANT")
... def construct(self, x):
... return self.pad(x)
>>> x = Tensor(np.array([[1, 2, 3], [4, 5, 6]]), mindsprore.float32)
>>> x = Tensor(np.array([[1, 2, 3], [4, 5, 6]]), mindspore.float32)
>>> pad = Net()
>>> output = pad(x)
>>> print(output)
@ -1277,7 +1277,7 @@ class MatrixDiagPart(Cell):
>>> x = Tensor([[-1, 0, 0, 1],
... [-1, 0, 0, 1],
... [-1, 0, 0, 1],
... [-1, 0, 0, 1], mindspore.float32)
... [-1, 0, 0, 1]], mindspore.float32)
>>> matrix_diag_part = nn.MatrixDiagPart()
>>> output = matrix_diag_part(x)
>>> print(output)

2
mindspore/nn/layer/container.py
View File

@ -262,7 +262,7 @@ class CellList(_CellListBase, Cell):
>>> cell_ls
CellList<
(0): Conv2d<input_channels=100, output_channels=20, kernel_size=(3, 3),stride=(1, 1), pad_mode=same,
padding=0, dilation=(1, 1), group=1, has_bias=Falseweight_init=normal, bias_init=zeros, format=NCHW>
padding=0, dilation=(1, 1), group=1, has_bias=False, weight_init=normal, bias_init=zeros, format=NCHW>
(1): BatchNorm2d<num_features=20, eps=1e-05, momentum=0.09999999999999998, gamma=Parameter (name=1.gamma,
shape=(20,), dtype=Float32, requires_grad=True), beta=Parameter (name=1.beta, shape=(20,), dtype=Float32,
requires_grad=True), moving_mean=Parameter (name=1.moving_mean, shape=(20,), dtype=Float32,

11
mindspore/nn/layer/thor_layer.py
View File

@ -68,11 +68,12 @@ class DenseThor(Cell):
``Ascend`` ``GPU``
Examples:
>>> x = Tensor(np.random.randint(0, 255, [2, 3]), mindspore.float32)
>>> net = nn.DenseThor(3, 4)
>>> net(x)
[[ 2.5246444 2.2738023 0.5711005 -3.9399147 ]
[ 1.0739875 4.0155234 0.94188046 -5.459526 ]]
>>> x = Tensor(np.array([[1, 2, 3], [3, 4, 5]]), mindspore.float32)
>>> net = nn.DenseThor(3, 4, weight_init="ones")
>>> output = net(x)
>>> print(output)
[[ 6. 6. 6. 6.]
[ 12. 12. 12. 12. ]]
"""
def __init__(self,
in_channels,