From d8e6daf8b8870b2efdc7056e50010e421053d6bd Mon Sep 17 00:00:00 2001 From: Wenqi Li Date: Wed, 21 Jun 2023 22:40:25 +0100 Subject: [PATCH] fixes #6638 Signed-off-by: Wenqi Li --- monai/networks/nets/regressor.py | 2 +- monai/networks/nets/varautoencoder.py | 2 +- 2 files changed, 2 insertions(+), 2 deletions(-) diff --git a/monai/networks/nets/regressor.py b/monai/networks/nets/regressor.py index a54b926bd0..a14d8f9345 100644 --- a/monai/networks/nets/regressor.py +++ b/monai/networks/nets/regressor.py @@ -143,7 +143,7 @@ def _get_layer( return layer def _get_final_layer(self, in_shape: Sequence[int]): - linear = nn.Linear(int(np.product(in_shape)), int(np.product(self.out_shape))) + linear = nn.Linear(int(np.prod(in_shape)), int(np.prod(self.out_shape))) return nn.Sequential(nn.Flatten(), linear) def forward(self, x: torch.Tensor) -> torch.Tensor: diff --git a/monai/networks/nets/varautoencoder.py b/monai/networks/nets/varautoencoder.py index 6cb8d6e40b..0674094aa7 100644 --- a/monai/networks/nets/varautoencoder.py +++ b/monai/networks/nets/varautoencoder.py @@ -120,7 +120,7 @@ def __init__( for s in strides: self.final_size = calculate_out_shape(self.final_size, self.kernel_size, s, padding) # type: ignore - linear_size = int(np.product(self.final_size)) * self.encoded_channels + linear_size = int(np.prod(self.final_size)) * self.encoded_channels self.mu = nn.Linear(linear_size, self.latent_size) self.logvar = nn.Linear(linear_size, self.latent_size) self.decodeL = nn.Linear(self.latent_size, linear_size)