Can you tell me if these two pytorch operations are equivalent: "torch.bmm(attention_slice, value)" and "einsum('b i j, b j d -> b i d', attention_slice, value)"
user
Yes, both operations are equivalent in terms of their result, but they are implemented differently.

"torch.bmm(attention_slice, value)" uses the torch.bmm function, which performs a batch matrix-matrix product of matrices in a batch. In this case, the attention_slice and value tensors are matrices, and the result is a batch of matrices.

"einsum('b i j, b j d -> b i d', attention_slice, value)" uses the einsum function from the numpy library, which allows for a more flexible and efficient way of defining and computing multi-dimensional arrays. In this case, the einsum function is used to perform a dot product of the attention_slice and value tensors, where the resulting tensor has dimensions "b i d".

So in summary, both operations perform the same dot product operation, but the einsum function provides a more flexible way to specify the operations and allows for more efficient computation.
assistant