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metal : fix kernel_norm (fixes Falcon on Metal) (#3057)

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* metal : fix kernel_norm

ggml-ci

* metal : put warning in kernel_norm to not combine the loops

* metal : restore original F16 mat-vec multiplication

It works after the norm fixes

* common : don't do warm-up with more than n_batch tokens (close #3058)

ggml-ci

* metal : minor
This commit is contained in:
Georgi Gerganov 2023-09-07 15:49:09 +03:00 committed by GitHub
parent fec2fb19e4
commit c4f496648c
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2 changed files with 24 additions and 21 deletions
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2
common/common.cpp
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@ -773,7 +773,7 @@ std::tuple<struct llama_model *, struct llama_context *> llama_init_from_gpt_par
LOG("warming up the model with an empty run\n");
const std::vector<llama_token> tmp = { llama_token_bos(lctx), llama_token_eos(lctx), };
llama_eval(lctx, tmp.data(), tmp.size(), 0, params.n_threads);
llama_eval(lctx, tmp.data(), std::min(tmp.size(), (size_t) params.n_batch), 0, params.n_threads);
llama_reset_timings(lctx);
}

43
ggml-metal.metal
View File

@ -220,27 +220,32 @@ kernel void kernel_norm(
}
threadgroup_barrier(mem_flags::mem_threadgroup);
}
//// broadcast
//if (tpitg == 0) {
// sum[0] /= ne00;
//}
//threadgroup_barrier(mem_flags::mem_threadgroup);
// broadcast
if (tpitg == 0) {
sum[0] /= ne00;
}
threadgroup_barrier(mem_flags::mem_threadgroup);
const float mean = sum[0];
// recenter and VARIANCE
// recenter
device float * y = dst + tgpig*ne00;
sum[tpitg] = 0.0f;
for (int i00 = tpitg; i00 < ne00; i00 += ntg) {
y[i00] = x[i00] - mean;
}
// VARIANCE
// parallel sum
//
// WARNING: combining this loop with the one above will give you wrong results for nth == 256
// I have no idea why, so for now I am keeping them separate. But this behavior is very concerning.
// Tested with:
// ./perplexity -m ./falcon-7b/ggml-model-q4_0.gguf -f wiki.test.raw -ngl 1 -t 4
//
sum[tpitg] = 0.0f;
for (int i00 = tpitg; i00 < ne00; i00 += ntg) {
sum[tpitg] += y[i00] * y[i00];
}
//// VARIANCE
//// parallel sum
//sum[tpitg] = 0.0f;
//for (int i00 = tpitg; i00 < ne00; i00 += ntg) {
// sum[tpitg] += y[i00] * y[i00];
//}
// reduce
threadgroup_barrier(mem_flags::mem_threadgroup);
for (uint i = ntg/2; i > 0; i /= 2) {
@ -249,11 +254,11 @@ kernel void kernel_norm(
}
threadgroup_barrier(mem_flags::mem_threadgroup);
}
//// broadcast
//if (tpitg == 0) {
// sum[0] /= ne00;
//}
//threadgroup_barrier(mem_flags::mem_threadgroup);
// broadcast
if (tpitg == 0) {
sum[0] /= ne00;
}
threadgroup_barrier(mem_flags::mem_threadgroup);
const float variance = sum[0];
const float scale = 1.0f/sqrt(variance + eps);
@ -262,7 +267,6 @@ kernel void kernel_norm(
}
}
kernel void kernel_rms_norm(
device const void * src0,
device float * dst,
@ -630,7 +634,6 @@ kernel void kernel_mul_mat_f16_f32(
}
}
}
}
kernel void kernel_alibi_f32(