Is Einsum slow?

Is Einsum slow?

einsum is slower than manual matmul/transpositions. (#1966 works equally fast for me, but this example is consistently slower) on CPU and GPU.

Is Einsum fast?

Einsum seems to be at least twice as fast for np. inner , np. outer , np. kron , and np.

Is NP Einsum slow?

einsum is significantly slower in numpy 1.15 (when compared to numpy 1.14).

Is torch einsum slow?

torch. einsum is 400x slower than numpy. einsum on a simple contraction. This is making some Pyro models very slow.

What is Torch Einsum?

torch. einsum (equation, *operands) → Tensor[source] Sums the product of the elements of the input operands along dimensions specified using a notation based on the Einstein summation convention.

How do you use NP Einsum?

To use numpy. einsum() , all you have to do is to pass the so-called subscripts string as an argument, followed by your input arrays. Let’s say you have two 2D arrays, A and B , and you want to do matrix multiplication.

What is NP Matmul?

The numpy. matmul() function returns the matrix product of two arrays. While it returns a normal product for 2-D arrays, if dimensions of either argument is >2, it is treated as a stack of matrices residing in the last two indexes and is broadcast accordingly.

What does NP Einsum do?

einsum. Evaluates the Einstein summation convention on the operands. Using the Einstein summation convention, many common multi-dimensional, linear algebraic array operations can be represented in a simple fashion.

What is TF Einsum?

Einsum allows defining Tensors by defining their element-wise computation. This computation is defined by equation , a shorthand form based on Einstein summation. As an example, consider multiplying two matrices A and B to form a matrix C.

What is batched matrix multiply?

Essentially you are multiplying a tensor of shape B x S x h with a tensor of shape B x h x 1 and it will result in B x S x 1 which is the attention weight for each batch.