def __call__(self, x):
h = F.relu(self.conv1_1(x))
h = F.relu(self.conv1_2(h))
h = F.max_pooling_2d(h, 2, stride=2)
h = F.relu(self.conv2_1(h))
h = F.relu(self.conv2_2(h))
h = F.max_pooling_2d(h, 2, stride=2)
h = F.relu(self.conv3_1(h))
h = F.relu(self.conv3_2(h))
h = F.max_pooling_2d(h, 2, stride=2)
h = F.relu(self.conv4_1(h))
h = F.relu(self.conv4_2(h))
h = F.spatial_pyramid_pooling_2d(h, 3, F.MaxPooling2D)
h = F.tanh(self.fc4(h))
h = F.dropout(h, ratio=.5, train=self.train)
h = F.tanh(self.fc5(h))
h = F.dropout(h, ratio=.5, train=self.train)
h = self.fc6(h)
return h
python类spatial_pyramid_pooling_2d()的实例源码
spp_discriminator.py 文件源码
项目：Semantic-Segmentation-using-Adversarial-Networks
作者: oyam
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文件源码
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def __call__(self, x):
return functions.spatial_pyramid_pooling_2d(x, self.pyramid_height, self.pooling_class)
test_spatial_pyramid_pooling_2d.py 文件源码
项目：chainer-deconv
作者: germanRos
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def check_forward(self, x_data, use_cudnn=True):
x = chainer.Variable(x_data)
y = functions.spatial_pyramid_pooling_2d(
x, self.pyramid_height, self.pooling_class,
use_cudnn=use_cudnn)
self.assertEqual(y.data.dtype, self.dtype)
y_data = cuda.to_cpu(y.data)
self.assertEqual(self.gy.shape, y_data.shape)
test_spatial_pyramid_pooling_2d.py 文件源码
项目：chainer-deconv
作者: germanRos
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文件源码
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def check_forward_ones(self, x_data, use_cudnn=True):
x = chainer.Variable(x_data)
y = functions.spatial_pyramid_pooling_2d(
x, self.pyramid_height, self.pooling_class, use_cudnn=use_cudnn)
y_data = cuda.to_cpu(y.data)
self.assertEqual(y_data.shape, (self.n, self.output_dim, 1, 1))
self.assertEqual(y_data.dtype, self.dtype)
gradient_check.assert_allclose(y_data, numpy.ones_like(y_data))
test_spatial_pyramid_pooling_2d.py 文件源码
项目：chainer-deconv
作者: germanRos
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def check_invalid_dtype(self):
functions.spatial_pyramid_pooling_2d(
self.v, 3, functions.MaxPooling2D)
test_spatial_pyramid_pooling_2d.py 文件源码
项目：chainer-deconv
作者: germanRos
项目源码
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def forward(self):
x = chainer.Variable(self.x)
return functions.spatial_pyramid_pooling_2d(
x, 3, functions.MaxPooling2D,
use_cudnn=self.use_cudnn)
def __init__(self, pyramid_height, pooling_class, use_cudnn=True):
self._function = "spatial_pyramid_pooling_2d"
self.pyramid_height = pyramid_height
self.pooling_class = pooling_class
self.use_cudnn = use_cudnn
def __call__(self, x):
return F.spatial_pyramid_pooling_2d(x, self.pyramid_height, self.pooling_class, self.use_cudnn)
def __call__(self, x):
return functions.spatial_pyramid_pooling_2d(x, self.pyramid_height, self.pooling_class)
def __call__(self, x):
h = F.elu(self.conv1(x))
h = F.max_pooling_2d(h, 3, stride=2)
h = self.res2(h, self.train)
h = self.res3(h, self.train)
h = self.res4(h, self.train)
h = self.res5(h, self.train)
h = F.spatial_pyramid_pooling_2d(h, 3, F.MaxPooling2D)
h = F.elu(self.conv2(h))
h = F.dropout(h, ratio=0.5)
h = self.conv3(h)
h = F.reshape(h, (-1, self.num_class))
return h
def __init__(self, pyramid_height, pooling_class, use_cudnn=True):
self._function = "spatial_pyramid_pooling_2d"
self.pyramid_height = pyramid_height
self.pooling_class = pooling_class
self.use_cudnn = use_cudnn
def __call__(self, x):
return F.spatial_pyramid_pooling_2d(x, self.pyramid_height, self.pooling_class, self.use_cudnn)
def __init__(self, pyramid_height, pooling_class, use_cudnn=True):
self._function = "spatial_pyramid_pooling_2d"
self.pyramid_height = pyramid_height
self.pooling_class = pooling_class
self.use_cudnn = use_cudnn
def __call__(self, x):
return F.spatial_pyramid_pooling_2d(x, self.pyramid_height, self.pooling_class, self.use_cudnn)
def __init__(self, pyramid_height, pooling_class, use_cudnn=True):
self._function = "spatial_pyramid_pooling_2d"
self.pyramid_height = pyramid_height
self.pooling_class = pooling_class
self.use_cudnn = use_cudnn
def __call__(self, x):
return F.spatial_pyramid_pooling_2d(x, self.pyramid_height, self.pooling_class, self.use_cudnn)
def _spatial_pyramid_pooling_2d(x):
return F.spatial_pyramid_pooling_2d(x, 4, F.MaxPooling2D)
def _spatial_pyramid_pooling_2d(x):
return F.spatial_pyramid_pooling_2d(x, 4, F.MaxPooling2D)
