RuntimeError: Expected 3D (unbatched) or 4D (batched) input to conv2d, but got input of size: [1, 1, 374, 402, 3]

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I am getting error in this line. I can’t understand why I am getting this.

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Had to add in the comment section as new users can’t upload more than one media.

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nn.Conv2d expects an input in the shape [batch_size, channels, height, width] while you are passing a 5-dimensional input as given in the error message.
Remove the unnecessary dimension and permute the input to have the aforementioned channels-first memory layout.

PS: you can post code snippets by wrapping them into three backticks ```.

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@jrTanvirHasan27
is your problem solved or not?
i am facing the same error?

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You can either reduce the dimension as @ptrblck says, or if available for your use case use the conv3d instead of the 2d counterpart.

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You can use the .reshape() method to flatten the data. Specifically, if you have a tensor with dimensions [batch_size, num_frames, channels, height, width], you can use .reshape() to turn it into a tensor with dimensions [batch_size * num_frames, channels, height, width]. This means all batch and frame sizes will be stacked together to form a single large batch. Result should be : ([1, 374, 402, 3])