forked from mindspore-Ecosystem/mindspore
!7723 fix bugs of op ArgMinWithValue, LRN and AvgPool1d
Merge pull request !7723 from lihongkang/v2_master
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2e6794fcec
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@ -334,7 +334,7 @@ class AvgPool1d(_PoolNd):
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Tensor of shape :math:`(N, C_{out}, L_{out})`.
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Examples:
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>>> pool = nn.AvgPool1d(kernel_size=6, strides=1)
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>>> pool = nn.AvgPool1d(kernel_size=6, stride=1)
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>>> x = Tensor(np.random.randint(0, 10, [1, 3, 6]), mindspore.float32)
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>>> output = pool(x)
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>>> output.shape
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@ -1376,8 +1376,9 @@ class ArgMinWithValue(PrimitiveWithInfer):
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- output_x (Tensor) - The minimum value of input tensor, with the same shape as index.
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Examples:
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>>> input_x = Tensor(np.random.rand(5))
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>>> input_x = Tensor(np.random.rand(5), mindspore.float32)
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>>> index, output = P.ArgMinWithValue()(input_x)
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0 0.0496291
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"""
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@prim_attr_register
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@ -5740,9 +5740,13 @@ class LRN(PrimitiveWithInfer):
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Tensor, with the same shape and data type as the input tensor.
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Examples:
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>>> x = Tensor(np.random.rand(1, 10, 4, 4)), mindspore.float32)
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>>> x = Tensor(np.random.rand(1, 2, 2, 2), mindspore.float32)
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>>> lrn = P.LRN()
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>>> lrn(x)
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[[[[0.18990143 0.59475636]
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[0.6291904 0.1371534 ]]
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[[0.6258911 0.4964315 ]
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[0.3141494 0.43636137]]]]
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"""
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@prim_attr_register
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def __init__(self, depth_radius=5, bias=1.0, alpha=1.0, beta=0.5, norm_region="ACROSS_CHANNELS"):
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