ValueError:预期的2D或3D输入(获得1D输入)PyTorch [英] ValueError: expected 2D or 3D input (got 1D input) PyTorch
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问题描述
class VAE(torch.nn.Module):
def __init__(self, input_size, hidden_sizes, batch_size):
super(VAE, self).__init__()
self.input_size = input_size
self.hidden_sizes = hidden_sizes
self.batch_size = batch_size
self.fc = torch.nn.Linear(input_size, hidden_sizes[0])
self.BN = torch.nn.BatchNorm1d(hidden_sizes[0])
self.fc1 = torch.nn.Linear(hidden_sizes[0], hidden_sizes[1])
self.BN1 = torch.nn.BatchNorm1d(hidden_sizes[1])
self.fc2 = torch.nn.Linear(hidden_sizes[1], hidden_sizes[2])
self.BN2 = torch.nn.BatchNorm1d(hidden_sizes[2])
self.fc3_mu = torch.nn.Linear(hidden_sizes[2], hidden_sizes[3])
self.fc3_sig = torch.nn.Linear(hidden_sizes[2], hidden_sizes[3])
self.fc4 = torch.nn.Linear(hidden_sizes[3], hidden_sizes[2])
self.BN4 = torch.nn.BatchNorm1d(hidden_sizes[2])
self.fc5 = torch.nn.Linear(hidden_sizes[2], hidden_sizes[1])
self.BN5 = torch.nn.BatchNorm1d(hidden_sizes[1])
self.fc6 = torch.nn.Linear(hidden_sizes[1], hidden_sizes[0])
self.BN6 = torch.nn.BatchNorm1d(hidden_sizes[0])
self.fc7 = torch.nn.Linear(hidden_sizes[0], input_size)
def sample_z(self, x_size, mu, log_var):
eps = torch.randn(x_size, self.hidden_sizes[-1])
return(mu + torch.exp(log_var/2) * eps)
def forward(self, x):
###########
# Encoder #
###########
out1 = self.fc(x)
out1 = nn.relu(self.BN(out1))
out2 = self.fc1(out1)
out2 = nn.relu(self.BN1(out2))
out3 = self.fc2(out2)
out3 = nn.relu(self.BN2(out3))
mu = self.fc3_mu(out3)
sig = nn.softplus(self.fc3_sig(out3))
###########
# Decoder #
###########
# sample from the distro
sample = self.sample_z(x.size(0), mu, sig)
out4 = self.fc4(sample)
out4 = nn.relu(self.BN4(out4))
out5 = self.fc5(out4)
out5 = nn.relu(self.BN5(out5))
out6 = self.fc6(out5)
out6 = nn.relu(self.BN6(out6))
out7 = nn.sigmoid(self.fc7(out6))
return(out7, mu, sig)
vae = VAE(input_size, hidden_sizes, batch_size)
vae.eval()
x_sample, z_mu, z_var = vae(X)
错误是:
File "VAE_LongTensor.py", line 200, in <module>
x_sample, z_mu, z_var = vae(X)
ValueError: expected 2D or 3D input (got 1D input)
推荐答案
在pytorch中构建 nn.Module
时, pytorch处理1D信号时,实际上希望输入是2D:第一个维度是小批量维度。
因此,您需要在 X $中添加单例维度。 c $ c>:
When you build a nn.Module
in pytorch for processing 1D signals, pytorch actually expects the input to be 2D: first dimension is the "mini batch" dimension.
Thus you need to add a singleton dimesion to your X
:
x_sample, z_mu, z_var = vae(X[None, ...])
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