将 'int' 转换为 pytorch 'Variable' 会出问题
Convert 'int' to pytorch 'Variable' makes problems
第一个使用 pytorch 的项目,我在尝试将 MNIST 标签 'int' 转换为火炬 'Variable' 时遇到了困难。调试器说它没有维度?!
# numpy mnist data
X_train, Y_train = read_data("training")
X_test , Y_test = read_data("testing")
arr = np.zeros(5)
for i in range(5):
# in your training loop:
costs_ = 0
for k in range(10000):
optimizer.zero_grad() # zero the gradient buffers
a = torch.from_numpy(np.expand_dims(X_train[k].flatten(), axis=0)).float()
b = torch.from_numpy(np.array(Y_train[k], dtype=np.float)).float()
input = Variable(a)
output = net(input)
target = Variable(b) # PROBLEM!!
loss = criterion(output, target)
loss.backward()
optimizer.step() # Does the update
costs_ += loss.data.numpy()
arr[i] = costs_
print(i)
抛出的错误是:"RuntimeError: input and target have different number of elements: input[1 x 1] has 1 elements, while target[] has 0 elements at /b/wheel/pytorch-src/torch/lib/THNN/generic/MSECriterion.c:12"
错误告诉您到底发生了什么。您的 target
变量为空。
编辑(在下方评论后):
如果Y_train[k] = 5
,则np.array(Y_train[k], dtype=np.float).shape = ()
,进而Variable(b)
成为无量纲的张量。
为了解决这个问题,您需要将列表传递给 np.array()
而不是整数或浮点数。
像这样:
b = torch.from_numpy(np.array([Y_train[k]], dtype=np.float)).float()
第一个使用 pytorch 的项目,我在尝试将 MNIST 标签 'int' 转换为火炬 'Variable' 时遇到了困难。调试器说它没有维度?!
# numpy mnist data
X_train, Y_train = read_data("training")
X_test , Y_test = read_data("testing")
arr = np.zeros(5)
for i in range(5):
# in your training loop:
costs_ = 0
for k in range(10000):
optimizer.zero_grad() # zero the gradient buffers
a = torch.from_numpy(np.expand_dims(X_train[k].flatten(), axis=0)).float()
b = torch.from_numpy(np.array(Y_train[k], dtype=np.float)).float()
input = Variable(a)
output = net(input)
target = Variable(b) # PROBLEM!!
loss = criterion(output, target)
loss.backward()
optimizer.step() # Does the update
costs_ += loss.data.numpy()
arr[i] = costs_
print(i)
抛出的错误是:"RuntimeError: input and target have different number of elements: input[1 x 1] has 1 elements, while target[] has 0 elements at /b/wheel/pytorch-src/torch/lib/THNN/generic/MSECriterion.c:12"
错误告诉您到底发生了什么。您的 target
变量为空。
编辑(在下方评论后):
如果Y_train[k] = 5
,则np.array(Y_train[k], dtype=np.float).shape = ()
,进而Variable(b)
成为无量纲的张量。
为了解决这个问题,您需要将列表传递给 np.array()
而不是整数或浮点数。
像这样:
b = torch.from_numpy(np.array([Y_train[k]], dtype=np.float)).float()