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Add a conv1d benchmark based on the whisper sizes. (#377)

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* Add a conv1d benchmark based on the whisper sizes.

* Enforce the batch-dim in conv1d.
This commit is contained in:
Laurent Mazare
2023-08-09 21:27:03 +02:00
committed by GitHub
parent 653ec5abc1
commit fcfdcbd337
4 changed files with 29 additions and 19 deletions
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4
candle-core/src/cpu_backend.rs
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@ -1037,10 +1037,10 @@ impl<'a> Map2 for Conv1D<'a> {
let (inp_s0, inp_s1, inp_s2) = crate::shape::dims3(inp_l.stride())?;
let (k_s0, k_s1, k_s2) = crate::shape::dims3(k_l.stride())?;
let l_out = p.l_out();
let dst_elems = p.c_out * l_out * p.b_size.unwrap_or(1);
let dst_elems = p.c_out * l_out * p.b_size;
let mut dst = vec![T::zero(); dst_elems];
// The output shape is [b_size, c_out, l_out]
for b_idx in 0..p.b_size.unwrap_or(1) {
for b_idx in 0..p.b_size {
let inp_idx = b_idx * inp_s0;
let dst_idx = b_idx * p.c_out * l_out;
for dst_c_idx in 0..p.c_out {