我有一个ImageView,我想在上面放一个渐变色。
所以,我使用FrameLayout,在其中放置一个ImageView和一个View。
import torch
class Network(torch.nn.Module):
def __init__(self):
super(Network, self).__init__()
self.linear = torch.nn.Linear(10, 1)
def forward(self, x):
return self.linear(x)
loss = torch.nn.MSELoss()
for i in range(0, 1000):
torch.manual_seed(i)
X = torch.randn(100, 10)
y = torch.randn(100, 1)
model=Network()
model.train()
optimizer=torch.optim.SGD(model.parameters(),lr=1.)
optimizer.zero_grad()
output = loss(model(X), y)
output.backward()
torch_grads=[]
for p in model.parameters():
torch_grads.append(p.grad.detach().data)
#df/dW = (-2X.T*y+2*X.T*b+2*X.T*X*W)/nsamples
#df/db = (2*b-2*y+2*W.T*X.T).mean() (the mean comes from implicit broadcasting of b)
theory_grad_w = (-2 * torch.matmul(X.t(), y)
+2 * torch.matmul(torch.t(X), torch.ones((X.shape[0], 1)))* list(model.parameters())[1]
+2 * torch.matmul(torch.matmul(X.t(), X), list(model.parameters())[0].t())
) / float(X.shape[0])
theory_grad_w = theory_grad_w.t()
theory_grad_b = torch.mean(2 * list(model.parameters())[1]- 2 * y+ 2 * torch.matmul((list(model.parameters())[0]), torch.t(X)))
theory_grads = [theory_grad_w, theory_grad_b]
b=all([torch.allclose(u, d) for u, d in zip(torch_grads, theory_grads)])
if not(b):
print("i=%s, pass=%s"%(i, b))
这是我的渐变色:
<FrameLayout
android:layout_width="match_parent"
android:layout_height="match_parent"
app:layout_constraintBottom_toBottomOf="parent"
app:layout_constraintEnd_toEndOf="parent"
app:layout_constraintHorizontal_bias="0.0"
app:layout_constraintStart_toStartOf="parent"
app:layout_constraintTop_toTopOf="parent"
app:layout_constraintVertical_bias="0.0">
<android.support.v7.widget.AppCompatImageView
android:layout_width="match_parent"
android:layout_height="match_parent"
android:scaleType="fitXY"
android:src="@mipmap/bg_login" />
<View
android:layout_width="match_parent"
android:layout_height="match_parent"
android:background="@drawable/bg_login_gradient"/>
</FrameLayout>
请帮助;)
预先感谢
答案 0 :(得分:0)
将背景图像放入drawable-xxhdpi可以正常工作。