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fix pool APIs en doc, delete disable_static (#28679)

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* fix pool exclusive and delete disable_static, test=develop

* fix pool1d  exclusive, test=develop

* fix pool APIs en doc, test=document_fix
musl/fix_failed_unittests_in_musl
Double_V 4 years ago committed by GitHub
parent 03f46e3526
commit 960135285b
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GPG Key ID: 4AEE18F83AFDEB23
1 changed files with 4 additions and 12 deletions
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python/paddle/nn/layer/pooling.py
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@ -90,7 +90,6 @@ class AvgPool1D(layers.Layer):
import paddle
import paddle.nn as nn
paddle.disable_static()
data = paddle.to_tensor(np.random.uniform(-1, 1, [1, 3, 32]).astype(np.float32))
AvgPool1D = nn.AvgPool1D(kernel_size=2, stride=2, padding=0)
@ -181,7 +180,6 @@ class AvgPool2D(layers.Layer):
import paddle
import paddle.nn as nn
import numpy as np
paddle.disable_static()
# max pool2d
input = paddle.to_tensor(np.random.uniform(-1, 1, [1, 3, 32, 32]).astype(np.float32))
@ -273,7 +271,6 @@ class AvgPool3D(layers.Layer):
import paddle
import paddle.nn as nn
import numpy as np
paddle.disable_static()
# avg pool3d
input = paddle.to_tensor(np.random.uniform(-1, 1, [1, 2, 3, 32, 32]).astype(np.float32))
@ -370,7 +367,6 @@ class MaxPool1D(layers.Layer):
import paddle
import paddle.nn as nn
paddle.disable_static()
data = paddle.to_tensor(np.random.uniform(-1, 1, [1, 3, 32]).astype(np.float32))
MaxPool1D = nn.MaxPool1D(kernel_size=2, stride=2, padding=0)
@ -464,7 +460,6 @@ class MaxPool2D(layers.Layer):
import paddle
import paddle.nn as nn
import numpy as np
paddle.disable_static()
# max pool2d
input = paddle.to_tensor(np.random.uniform(-1, 1, [1, 3, 32, 32]).astype(np.float32))
@ -556,7 +551,6 @@ class MaxPool3D(layers.Layer):
import paddle
import paddle.nn as nn
import numpy as np
paddle.disable_static()
# max pool3d
input = paddle.to_tensor(np.random.uniform(-1, 1, [1, 2, 3, 32, 32]).astype(np.float32))
@ -652,7 +646,6 @@ class AdaptiveAvgPool1D(layers.Layer):
#
import paddle
import paddle.nn as nn
paddle.disable_static()
data = paddle.to_tensor(np.random.uniform(-1, 1, [1, 3, 32]).astype(np.float32))
AdaptiveAvgPool1D = nn.AdaptiveAvgPool1D(output_size=16)
@ -728,7 +721,7 @@ class AdaptiveAvgPool2D(layers.Layer):
#
import paddle
import numpy as np
paddle.disable_static()
input_data = np.random.rand(2, 3, 32, 32)
x = paddle.to_tensor(input_data)
# x.shape is [2, 3, 32, 32]
@ -816,7 +809,7 @@ class AdaptiveAvgPool3D(layers.Layer):
# avg(input[:, :, dstart:dend, hstart: hend, wstart: wend])
import paddle
import numpy as np
paddle.disable_static()
input_data = np.random.rand(2, 3, 8, 32, 32)
x = paddle.to_tensor(input_data)
# x.shape is [2, 3, 8, 32, 32]
@ -893,7 +886,6 @@ class AdaptiveMaxPool1D(layers.Layer):
#
import paddle
import paddle.nn as nn
paddle.disable_static()
data = paddle.to_tensor(np.random.uniform(-1, 1, [1, 3, 32]).astype(np.float32))
AdaptiveMaxPool1D = nn.AdaptiveMaxPool1D(output_size=16)
@ -964,7 +956,7 @@ class AdaptiveMaxPool2D(layers.Layer):
#
import paddle
import numpy as np
paddle.disable_static()
input_data = np.random.rand(2, 3, 32, 32)
x = paddle.to_tensor(input_data)
adaptive_max_pool = paddle.nn.AdaptiveMaxPool2D(output_size=3, return_mask=True)
@ -1036,7 +1028,7 @@ class AdaptiveMaxPool3D(layers.Layer):
# max(input[:, :, dstart:dend, hstart: hend, wstart: wend])
import paddle
import numpy as np
paddle.disable_static()
input_data = np.random.rand(2, 3, 8, 32, 32)
x = paddle.to_tensor(input_data)
pool = paddle.nn.AdaptiveMaxPool3D(output_size=4)

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