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fixed rwkv, standardized new ctx usage

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Concedo 2023-07-10 20:05:53 +08:00
parent 2827920044
commit 523fc3be52
8 changed files with 27 additions and 8 deletions
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2
.gitignore vendored
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@ -68,3 +68,5 @@ koboldcpp_openblas.dll
koboldcpp_openblas_noavx2.dll
koboldcpp_clblast.dll
koboldcpp_cublas.dll
cublas64_11.dll
cublasLt64_11.dll

2
otherarch/gpt2_v3.cpp
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@ -707,7 +707,7 @@ bool gpt2_eval(
// run the computation
ggml_build_forward_expand(&gf, inpL);
ggml_graph_compute_with_ctx(ctx0, &gf, n_threads);
kcpp_graph_compute_helper(&gf, n_threads);
//if (n_past%100 == 0) {
// ggml_graph_print (&gf);

2
otherarch/gptj_v3.cpp
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@ -619,7 +619,7 @@ bool gptj_eval(
// run the computation
ggml_build_forward_expand(&gf, inpL);
ggml_graph_compute_with_ctx(ctx0, &gf, n_threads);
kcpp_graph_compute_helper(&gf, n_threads);
//if (n_past%100 == 0) {
// ggml_graph_print (&gf);

2
otherarch/mpt_v3.cpp
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@ -542,7 +542,7 @@ bool mpt_eval(const mpt_model & model, const int n_threads, const int n_past,
// run the computation
ggml_build_forward_expand(&gf, inpL);
ggml_graph_compute_with_ctx(ctx0, &gf, n_threads);
kcpp_graph_compute_helper(&gf, n_threads);
// std::cout << "Qcur" << std::endl;
// print_tensor(Qcur);

2
otherarch/neox_v3.cpp
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@ -638,7 +638,7 @@ bool gpt_neox_eval(
// run the computation
ggml_build_forward_expand(&gf, inpL);
ggml_graph_compute_with_ctx(ctx0, &gf, n_threads);
kcpp_graph_compute_helper(&gf, n_threads);
//if (n_past%100 == 0) {
// ggml_graph_print (&gf);

7
otherarch/rwkv_v3.cpp
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@ -13,6 +13,8 @@
#include "ggml-opencl.h"
#endif
#include "utils.h"
#include <string>
#include <vector>
#include <cstring>
@ -729,6 +731,7 @@ struct rwkv_context {
float * logits_out = 0; //stores address of output logit buffer
size_t gpu_layers;
std::vector<uint8_t> work_buffer;
};
// https://stackoverflow.com/a/6458689
@ -1627,7 +1630,7 @@ bool rwkv_eval(struct rwkv_context * ctx, const int n_threads, const uint32_t to
ctx->serial_graph.cgraph->n_leafs = ctx->serial_graph.post_logits_leafs;
}
ggml_graph_compute_with_ctx(ctx->serial_graph.ctx.ctx, ctx->serial_graph.cgraph.get(),n_threads);
kcpp_graph_compute_helper(ctx->serial_graph.cgraph.get(),n_threads);
rwkv_get_outputs(ctx, state_out, logits_out);
return true;
@ -1715,7 +1718,7 @@ bool rwkv_eval_sequence(struct rwkv_context * ctx, const int n_threads, const ui
ctx->sequence_graph.cgraph->n_leafs = ctx->sequence_graph.post_logits_leafs;
}
ggml_graph_compute_with_ctx(ctx->sequence_graph.ctx.ctx, ctx->sequence_graph.cgraph.get(),n_threads);
kcpp_graph_compute_helper(ctx->sequence_graph.cgraph.get(),n_threads);
rwkv_get_outputs(ctx, state_out, logits_out);
}

12
otherarch/utils.cpp
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@ -222,3 +222,15 @@ bool should_transpose_layer(std::string name)
}
return false;
}
static std::vector<uint8_t> kcpp_compute_buf;
void kcpp_graph_compute_helper(ggml_cgraph *graph, int n_threads)
{
struct ggml_cplan plan = ggml_graph_plan(graph, n_threads);
if (plan.work_size > 0)
{
kcpp_compute_buf.resize(plan.work_size);
plan.work_data = kcpp_compute_buf.data();
}
ggml_graph_compute(graph, &plan);
}

2
otherarch/utils.h
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@ -55,3 +55,5 @@ std::vector<gpt_vocab::id> gpt_tokenize(const gpt_vocab & vocab, const std::stri
bool should_transpose_layer(std::string name);
void kcpp_graph_compute_helper(ggml_cgraph * graph, int n_threads);