mirror of
https://github.com/zama-ai/tfhe-rs.git
synced 2026-01-07 22:04:10 -05:00
chore: make typos version fixed
- add a script to properly install the correct version - correct new typos
This commit is contained in:
committed by
IceTDrinker
parent
67dc8583b1
commit
00ce0deec9
@@ -945,10 +945,10 @@ fn bench_swap_claim_throughput<FheType, F1, F2>(
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let bench_id =
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format!("{bench_name}::throughput::{fn_name}::{type_name}::{num_elems}_elems");
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group.bench_with_input(&bench_id, &num_elems, |b, &num_elems| {
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let pendings_0_in = (0..num_elems)
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let pending_0_in = (0..num_elems)
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.map(|_| FheType::encrypt(rng.gen::<u64>(), client_key))
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.collect::<Vec<_>>();
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let pendings_1_in = (0..num_elems)
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let pending_1_in = (0..num_elems)
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.map(|_| FheType::encrypt(rng.gen::<u64>(), client_key))
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.collect::<Vec<_>>();
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let total_tokens_0_in = (0..num_elems).map(|_| rng.gen::<u64>()).collect::<Vec<_>>();
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@@ -969,9 +969,9 @@ fn bench_swap_claim_throughput<FheType, F1, F2>(
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.collect::<Vec<_>>();
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b.iter(|| {
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let (amounts_0_out, amounts_1_out): (Vec<_>, Vec<_>) = pendings_0_in
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let (amounts_0_out, amounts_1_out): (Vec<_>, Vec<_>) = pending_0_in
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.par_iter()
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.zip(pendings_1_in.par_iter())
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.zip(pending_1_in.par_iter())
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.zip(total_tokens_0_in.par_iter())
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.zip(total_tokens_1_in.par_iter())
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.zip(total_tokens_0_out.par_iter())
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@@ -1084,10 +1084,10 @@ fn cuda_bench_swap_claim_throughput<FheType, F1, F2>(
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let bench_id =
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format!("{bench_name}::throughput::{fn_name}::{type_name}::{num_elems}_elems");
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group.bench_with_input(&bench_id, &num_elems, |b, &num_elems| {
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let pendings_0_in = (0..num_elems)
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let pending_0_in = (0..num_elems)
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.map(|_| FheType::encrypt(rng.gen::<u64>(), client_key))
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.collect::<Vec<_>>();
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let pendings_1_in = (0..num_elems)
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let pending_1_in = (0..num_elems)
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.map(|_| FheType::encrypt(rng.gen::<u64>(), client_key))
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.collect::<Vec<_>>();
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let total_tokens_0_in = (0..num_elems).map(|_| rng.gen::<u64>()).collect::<Vec<_>>();
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@@ -1116,9 +1116,9 @@ fn cuda_bench_swap_claim_throughput<FheType, F1, F2>(
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let num_streams_per_gpu = 2.min(num_elems / num_gpus);
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let chunk_size = (num_elems / num_gpus) as usize;
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b.iter(|| {
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pendings_0_in
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pending_0_in
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.par_chunks(chunk_size)
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.zip(pendings_1_in.par_chunks(chunk_size))
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.zip(pending_1_in.par_chunks(chunk_size))
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.zip(total_tokens_0_in.par_chunks(chunk_size))
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.zip(total_tokens_1_in.par_chunks(chunk_size))
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.zip(total_tokens_0_out.par_chunks(chunk_size))
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@@ -1131,7 +1131,7 @@ fn cuda_bench_swap_claim_throughput<FheType, F1, F2>(
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(
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(
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(
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(pendings_0_in_gpu_i, pendings_1_in_gpu_i),
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(pending_0_in_gpu_i, pending_1_in_gpu_i),
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total_tokens_0_in_gpu_i,
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),
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total_tokens_1_in_gpu_i,
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@@ -1142,10 +1142,10 @@ fn cuda_bench_swap_claim_throughput<FheType, F1, F2>(
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),
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)| {
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let stream_chunk_size =
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pendings_0_in_gpu_i.len() / num_streams_per_gpu as usize;
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pendings_0_in_gpu_i
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pending_0_in_gpu_i.len() / num_streams_per_gpu as usize;
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pending_0_in_gpu_i
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.par_chunks(stream_chunk_size)
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.zip(pendings_1_in_gpu_i.par_chunks(stream_chunk_size))
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.zip(pending_1_in_gpu_i.par_chunks(stream_chunk_size))
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.zip(total_tokens_0_in_gpu_i.par_chunks(stream_chunk_size))
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.zip(total_tokens_1_in_gpu_i.par_chunks(stream_chunk_size))
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.zip(total_tokens_0_out_gpu_i.par_chunks(stream_chunk_size))
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