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llama.cpp
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working on ops function and pipeline

This commit is contained in:
Ilia Ilmer 2025-12-16 22:00:30 -05:00
parent d9b5b17411
commit fc11fd3ff4
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2 changed files with 51 additions and 2 deletions
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21
ggml/src/ggml-metal/ggml-metal-device.cpp
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@ -384,6 +384,27 @@ ggml_metal_pipeline_with_params ggml_metal_library_get_pipeline_soft_max(ggml_me
return res;
}
ggml_metal_pipeline_with_params ggml_metal_library_get_pipeline_cross_entropy(ggml_metal_library_t lib, const ggml_tensor * op) {
GGML_ASSERT(!op->src[0] || op->src[0]->type == GGML_TYPE_F32);
char base[256];
char name[256];
const ggml_type tsrc1 = GGML_TYPE_F32;
snprintf(base, 256, "kernel_cross_entropy_loss_%s", ggml_type_name(tsrc1));
snprintf(name, 256, "%s", base);
ggml_metal_pipeline_with_params res = ggml_metal_library_get_pipeline(lib, name);
if (!res.pipeline) {
res = ggml_metal_library_compile_pipeline(lib, base, name, nullptr);
}
res.smem = 32*sizeof(float);
return res;
}
ggml_metal_pipeline_with_params ggml_metal_library_get_pipeline_ssm_conv(ggml_metal_library_t lib, const ggml_tensor * op) {
GGML_ASSERT(op->src[0]->type == GGML_TYPE_F32);
GGML_ASSERT(op->src[1]->type == GGML_TYPE_F32);

32
ggml/src/ggml-metal/ggml-metal-ops.cpp
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@ -1334,14 +1334,42 @@ int ggml_metal_op_soft_max(ggml_metal_op_t ctx, int idx) {
}
int ggml_metal_op_cross_entropy_loss(ggml_metal_op_t ctx, int idx){
const ggml_tensor * src0 = ctx->node(idx)->src[0]; // NOTE: logits
const ggml_tensor * src1 = ctx->node(idx)->src[1]; // NOTE: labels
ggml_tensor * op = ctx->node(idx);
ggml_metal_library_t lib = ctx->lib;
ggml_metal_encoder_t enc = ctx->enc;
const ggml_tensor * src0 = op->src[0]; // NOTE: logits
const ggml_tensor * src1 = op->src[1]; // NOTE: labels
GGML_ASSERT(src0->type == GGML_TYPE_F32);
GGML_ASSERT(src1->type == GGML_TYPE_F32);
GGML_ASSERT(ggml_is_contiguous(src0));
GGML_ASSERT(ggml_is_contiguous(src1));
const int32_t ne00 = src0->ne[0];
const int32_t nrows = ggml_nrows(src1);
ggml_metal_kargs_cross_entropy_loss args = {
/*int32_t*/ ne00,
/*int32_t*/ nrows,
/*int32_t*/ nrows,
};
int nth = 32;
auto pipeline = ggml_metal_library_get_pipeline_cross_entropy(lib, op);
const size_t smem = pipeline.smem;
ggml_metal_encoder_set_bytes(enc, &args, sizeof(args), 0);
ggml_metal_encoder_set_buffer(enc, ggml_metal_get_buffer_id(op->src[0]), 1);
if (op->src[1]) {
ggml_metal_encoder_set_buffer(enc, ggml_metal_get_buffer_id(op->src[1]), 2);
} else {
ggml_metal_encoder_set_buffer(enc, ggml_metal_get_buffer_id(op->src[0]), 2);
}
ggml_metal_encoder_set_buffer(enc, ggml_metal_get_buffer_id(op), 4);
ggml_metal_encoder_set_threadgroup_memory_size(enc, smem, 0);
ggml_metal_encoder_dispatch_threadgroups(enc, ne00, nrows, nrows, nth, 1, 1);
return 1;
}