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# PyTorch torch.expand_as Function * * PyTorch torch Reference Manual](#) `torch.expand_as` is a PyTorch function used to expand a tensor to the same size as another tensor. It is a convenient version of `torch.expand`, automatically using the reference tensor's size for expansion. ### Function Definition torch.expand_as(other) **Parameters**: * `other` (Tensor): the reference tensor; the current tensor will be expanded to the same size as this tensor. **Return Value**: * `torch.Tensor`: returns a view of the expanded tensor. * * * ## Usage Examples ## Example import torch # Create a vector x = torch.tensor([1,2,3,4]) # Create a target matrix other = torch.randn(3,4) # Expand x to the same shape as other y = x.expand_as(other) print("Original vector shape:", x.shape) print("Reference tensor shape:", other.shape) print("Expanded shape:", y.shape) print("nExpanded tensor:") print(y) Output: Original vector shape: torch.Size()Reference tensor shape: torch.Size([3, 4])Expanded shape: torch.Size([3, 4])Expanded tensor: tensor([[1, 2, 3, 4], [1, 2, 3, 4], [1, 2, 3, 4]]) ## Example import torch # Create a column vector x = torch.tensor([,,]) # Create a target 3D tensor other = torch.randn(3,4,5) # Expand x to the same shape as other y = x.expand_as(other) print("Original column vector shape:", x.shape) print("Reference tensor shape:", other.shape) print("Expanded shape:", y.shape) Output: Original column vector shape: torch.Size([3, 1])Reference tensor shape: torch.Size([3, 4, 5])Expanded shape: torch.Size([3, 4, 5]) ## Example import torch # Application example in neural networks # Suppose we have a bias vector needing broadcasting to feature maps bias = torch.tensor([0.1,0.2,0.3])# 3-channel bias # Simulate convolution output feature map (batch, channel, height, width) feature_map = torch.randn(8,3,32,32) # Expand bias to the same shape as feature map bias_expanded = bias.expand_as(feature_map) print("Bias shape:", bias.shape) print("Feature map shape:", feature_map.shape) print("Expanded bias shape:", bias_expanded.shape) # Add bias output = feature_map + bias_expanded print("nOutput shape after adding bias:", output.shape) Output: Bias shape: torch.Size()Feature map shape: torch.Size([8, 3, 32, 32])Expanded bias shape: torch.Size([8, 3, 32, 32])Output shape after adding bias: torch.Size([8, 3