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@ -1,4 +1,4 @@
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# copyright (c) 2021 PaddlePaddle Authors. All Rights Reserve.
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# copyright (c) 2022 PaddlePaddle Authors. All Rights Reserve.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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@ -20,11 +20,7 @@ from __future__ import absolute_import
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from __future__ import division
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from __future__ import print_function
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import paddle
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from paddle import ParamAttr
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import paddle.nn as nn
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import paddle.nn.functional as F
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import numpy as np
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__all__ = ["ResNet32"]
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@ -51,10 +47,10 @@ class ResNet32(nn.Layer):
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def forward(self, inputs):
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"""
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Args:
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inputs (torch.Tensor): input feature
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inputs: input feature
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Returns:
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torch.Tensor: output feature
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output feature
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"""
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return self.ConvNet(inputs)
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@ -92,7 +88,7 @@ class BasicBlock(nn.Layer):
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out_planes (int): channels of the middle feature
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stride (int): stride of the convolution
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Returns:
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nn.Module: Conv2D with kernel = 3
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nn.Layer: Conv2D with kernel = 3
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"""
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@ -102,14 +98,6 @@ class BasicBlock(nn.Layer):
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bias_attr=False)
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def forward(self, x):
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"""
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Args:
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x (torch.Tensor): input feature
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Returns:
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torch.Tensor: output feature of the BasicBlock
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"""
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residual = x
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out = self.conv1(x)
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@ -246,14 +234,6 @@ class ResNet(nn.Layer):
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return nn.Sequential(*layers)
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def forward(self, x):
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"""
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Args:
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x (torch.Tensor): input feature
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Returns:
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torch.Tensor: output feature of the Resnet
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"""
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x = self.conv0_1(x)
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x = self.bn0_1(x)
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x = self.relu(x)
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@ -19,7 +19,6 @@ from __future__ import print_function
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import paddle
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import paddle.nn as nn
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import paddle.nn.functional as F
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import numpy as np
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class SPINAttentionHead(nn.Layer):
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@ -21,7 +21,6 @@ import paddle
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from paddle import nn, ParamAttr
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from paddle.nn import functional as F
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import numpy as np
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import itertools
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import functools
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from .tps import GridGenerator
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