vbatts/llama.cpp
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added/corrected control on tensor size for Q4 repacking.

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This commit is contained in:
Djip007 2024-12-06 20:14:31 +01:00
parent 0a2be72dca
commit b14b47132a
1 changed files with 32 additions and 18 deletions
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40
ggml/src/ggml-cpu/ggml-cpu-aarch64.cpp
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@ -3680,17 +3680,17 @@ static block_q4_0x8 make_block_q4_0x8(block_q4_0 * in, unsigned int blck_size_in
static int repack_q4_0_to_q4_0_4_bl(struct ggml_tensor * t, int interleave_block, const void * GGML_RESTRICT data, size_t data_size) { static int repack_q4_0_to_q4_0_4_bl(struct ggml_tensor * t, int interleave_block, const void * GGML_RESTRICT data, size_t data_size) {
GGML_ASSERT(t->type == GGML_TYPE_Q4_0); GGML_ASSERT(t->type == GGML_TYPE_Q4_0);
GGML_ASSERT(interleave_block == 4 || interleave_block == 8); GGML_ASSERT(interleave_block == 4 || interleave_block == 8);
constexpr int nrows_interleaved = 4;
block_q4_0x4 * dst = (block_q4_0x4 *)t->data; block_q4_0x4 * dst = (block_q4_0x4 *)t->data;
const block_q4_0 * src = (const block_q4_0 *)data; const block_q4_0 * src = (const block_q4_0 *)data;
block_q4_0 dst_tmp[4]; block_q4_0 dst_tmp[4];
int nrow = t->ne[1]*t->ne[2]*t->ne[3]; // Number of rows int nrow = ggml_nrows(t);
int nrows_interleaved = 4;
int nblocks = t->ne[0] / QK4_0; int nblocks = t->ne[0] / QK4_0;
GGML_ASSERT(data_size == nrow * nblocks * sizeof(block_q4_0)); GGML_ASSERT(data_size == nrow * nblocks * sizeof(block_q4_0));
if (nrow % nrows_interleaved != 0 || t->ne[0] % 8 != 0) { if (t->ne[1] % nrows_interleaved != 0 || t->ne[0] % 8 != 0) {
return -1; return -1;
} }
@ -3711,17 +3711,17 @@ static int repack_q4_0_to_q4_0_4_bl(struct ggml_tensor * t, int interleave_block
static int repack_q4_0_to_q4_0_8_bl(struct ggml_tensor *t, int interleave_block, const void * GGML_RESTRICT data, size_t data_size) { static int repack_q4_0_to_q4_0_8_bl(struct ggml_tensor *t, int interleave_block, const void * GGML_RESTRICT data, size_t data_size) {
GGML_ASSERT(t->type == GGML_TYPE_Q4_0); GGML_ASSERT(t->type == GGML_TYPE_Q4_0);
GGML_ASSERT(interleave_block == 8); GGML_ASSERT(interleave_block == 8);
constexpr int nrows_interleaved = 8;
block_q4_0x8 * dst = (block_q4_0x8*)t->data; block_q4_0x8 * dst = (block_q4_0x8*)t->data;
const block_q4_0 * src = (const block_q4_0*) data; const block_q4_0 * src = (const block_q4_0*) data;
block_q4_0 dst_tmp[8]; block_q4_0 dst_tmp[8];
int nrow = t->ne[1]*t->ne[2]*t->ne[3]; // Number of rows int nrow = ggml_nrows(t);
int nrows_interleaved = 8;
int nblocks = t->ne[0] / QK4_0; int nblocks = t->ne[0] / QK4_0;
GGML_ASSERT(data_size == nrow * nblocks * sizeof(block_q4_0)); GGML_ASSERT(data_size == nrow * nblocks * sizeof(block_q4_0));
if (nrow % nrows_interleaved != 0 || t->ne[0] % 8 != 0) { if (t->ne[1] % nrows_interleaved != 0 || t->ne[0] % 8 != 0) {
return -1; return -1;
} }
@ -3779,13 +3779,13 @@ static int repack_iq4_nl_to_iq4_nl_4_bl(struct ggml_tensor * t, int interleave_b
block_iq4_nlx4 * dst = (block_iq4_nlx4 *)t->data; block_iq4_nlx4 * dst = (block_iq4_nlx4 *)t->data;
const block_iq4_nl * src = (const block_iq4_nl *)data; const block_iq4_nl * src = (const block_iq4_nl *)data;
block_iq4_nl dst_tmp[4]; block_iq4_nl dst_tmp[4];
int nrow = t->ne[1]*t->ne[2]*t->ne[3]; // Number of rows int nrow = ggml_nrows(t);
int nrows_interleaved = 4; int nrows_interleaved = 4;
int nblocks = t->ne[0] / QK4_0; int nblocks = t->ne[0] / QK4_0;
GGML_ASSERT(data_size == nrow * nblocks * sizeof(block_iq4_nl)); GGML_ASSERT(data_size == nrow * nblocks * sizeof(block_iq4_nl));
if (nrow % nrows_interleaved != 0 || t->ne[0] % 8 != 0) { if (t->ne[1] % nrows_interleaved != 0 || t->ne[0] % 8 != 0) {
return -1; return -1;
} }
@ -4121,19 +4121,27 @@ static const tensor_traits<block_iq4_nl, 4, 4> iq4_nl_4x4_q8_0;
static const ggml::cpu::tensor_traits * ggml_aarch64_get_optimal_repack_type(const struct ggml_tensor * cur) { static const ggml::cpu::tensor_traits * ggml_aarch64_get_optimal_repack_type(const struct ggml_tensor * cur) {
if (cur->type == GGML_TYPE_Q4_0) { if (cur->type == GGML_TYPE_Q4_0) {
if (ggml_cpu_has_avx2() || (ggml_cpu_has_sve() && ggml_cpu_has_matmul_int8() && ggml_cpu_get_sve_cnt() == QK8_0)) { if (ggml_cpu_has_avx2() || (ggml_cpu_has_sve() && ggml_cpu_has_matmul_int8() && ggml_cpu_get_sve_cnt() == QK8_0)) {
if (cur->ne[1] % 8==0) {
return &ggml::cpu::aarch64::q4_0_8x8_q8_0; return &ggml::cpu::aarch64::q4_0_8x8_q8_0;
} }
}
if (ggml_cpu_has_neon() && ggml_cpu_has_matmul_int8()) { if (ggml_cpu_has_neon() && ggml_cpu_has_matmul_int8()) {
if (cur->ne[1] % 4 == 0) {
return &ggml::cpu::aarch64::q4_0_4x8_q8_0; return &ggml::cpu::aarch64::q4_0_4x8_q8_0;
} }
}
if (ggml_cpu_has_neon() && ggml_cpu_has_dotprod()) { if (ggml_cpu_has_neon() && ggml_cpu_has_dotprod()) {
if (cur->ne[1] % 4 == 0) {
return &ggml::cpu::aarch64::q4_0_4x4_q8_0; return &ggml::cpu::aarch64::q4_0_4x4_q8_0;
} }
}
} else if (cur->type == GGML_TYPE_IQ4_NL) { } else if (cur->type == GGML_TYPE_IQ4_NL) {
if (ggml_cpu_has_neon() && ggml_cpu_has_dotprod()) { if (ggml_cpu_has_neon() && ggml_cpu_has_dotprod()) {
if (cur->ne[1] % 4 == 0) {
return &ggml::cpu::aarch64::iq4_nl_4x4_q8_0; return &ggml::cpu::aarch64::iq4_nl_4x4_q8_0;
} }
} }
}
return nullptr; return nullptr;
} }
@ -4184,9 +4192,12 @@ static size_t ggml_backend_cpu_aarch64_buffer_type_get_alignment(ggml_backend_bu
namespace ggml::cpu::aarch64 { namespace ggml::cpu::aarch64 {
class extra_buffer_type : ggml::cpu::extra_buffer_type { class extra_buffer_type : ggml::cpu::extra_buffer_type {
bool supports_op(ggml_backend_dev_t, const struct ggml_tensor * op) override { bool supports_op(ggml_backend_dev_t, const struct ggml_tensor * op) override {
if (op->op == GGML_OP_MUL_MAT && op->src[0]->buffer && (ggml_n_dims(op->src[0]) == 2) && if ( op->op == GGML_OP_MUL_MAT &&
op->src[0]->buffer &&
(ggml_n_dims(op->src[0]) == 2) &&
op->src[0]->buffer->buft == ggml_backend_cpu_aarch64_buffer_type() && op->src[0]->buffer->buft == ggml_backend_cpu_aarch64_buffer_type() &&
ggml_aarch64_get_optimal_repack_type(op->src[0])) { ggml_aarch64_get_optimal_repack_type(op->src[0])
) {
if (op->src[1]->buffer && !ggml_backend_buft_is_host(op->src[1]->buffer->buft)) { if (op->src[1]->buffer && !ggml_backend_buft_is_host(op->src[1]->buffer->buft)) {
return false; return false;
} }
@ -4197,9 +4208,12 @@ class extra_buffer_type : ggml::cpu::extra_buffer_type {
// return true; // return true;
//} //}
// may be possible if Q8_0 packed... // may be possible if Q8_0 packed...
} else if (op->op == GGML_OP_MUL_MAT_ID && op->src[0]->buffer && (ggml_n_dims(op->src[0]) == 3) && } else if (op->op == GGML_OP_MUL_MAT_ID
op->src[0]->buffer->buft == ggml_backend_cpu_aarch64_buffer_type() && && op->src[0]->buffer
ggml_aarch64_get_optimal_repack_type(op->src[0])) { && (ggml_n_dims(op->src[0]) == 3)
&& op->src[0]->buffer->buft == ggml_backend_cpu_aarch64_buffer_type()
&& ggml_aarch64_get_optimal_repack_type(op->src[0])
) {
if (op->src[1]->buffer && !ggml_backend_buft_is_host(op->src[1]->buffer->buft)) { if (op->src[1]->buffer && !ggml_backend_buft_is_host(op->src[1]->buffer->buft)) {
return false; return false;
} }