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build : fix and ignore MSVC warnings (#1889)

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This commit is contained in:
Borislav Stanimirov
2023-06-16 21:23:53 +03:00
committed by GitHub
parent 3d01122610
commit 9cbf50c041
16 changed files with 88 additions and 37 deletions
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18
examples/train-text-from-scratch/train-text-from-scratch.cpp
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@ -12,6 +12,9 @@
#include <algorithm>
#include <string>
#if defined(_MSC_VER)
#pragma warning(disable: 4244 4267) // possible loss of data
#endif
struct random_normal_distribution {
std::mt19937 gen;
@ -20,7 +23,6 @@ struct random_normal_distribution {
float max;
};
struct random_uniform_distribution {
std::mt19937 gen;
std::uniform_real_distribution<float> rd;
@ -2366,7 +2368,7 @@ void write_tensor(struct llama_file * file, struct ggml_tensor * tensor) {
file->write_u32(0);
file->write_u32(0);
file->write_u32(GGML_TYPE_F32);
file->seek(-file->tell() & 31, SEEK_CUR);
file->seek(0-file->tell() & 31, SEEK_CUR);
return;
}
const char * name = ggml_get_name(tensor);
@ -2381,7 +2383,7 @@ void write_tensor(struct llama_file * file, struct ggml_tensor * tensor) {
file->write_u32(tensor->type);
file->write_raw(ne, sizeof(ne[0]) * nd);
file->write_raw(name, name_len);
file->seek(-file->tell() & 31, SEEK_CUR);
file->seek(0-file->tell() & 31, SEEK_CUR);
file->write_raw(tensor->data, ggml_nbytes(tensor));
}
@ -2402,7 +2404,7 @@ void read_tensor(struct llama_file * file, struct ggml_tensor * tensor) {
std::string name = file->read_string(name_len);
GGML_ASSERT(strncmp(ggml_get_name(tensor), name.c_str(), sizeof(tensor->name)-1) == 0);
file->seek(-file->tell() & 31, SEEK_CUR);
file->seek(0-file->tell() & 31, SEEK_CUR);
file->read_raw(tensor->data, ggml_nbytes(tensor));
}
@ -2756,8 +2758,8 @@ struct train_params get_default_train_params() {
params.lbfgs_n_iter = 16;
params.adam_n_iter = 16;
params.adam_alpha = 1e-3;
params.adam_decay = 1e-3;
params.adam_alpha = 1e-3f;
params.adam_decay = 1e-3f;
params.mem_model_gb = 2;
params.mem_compute_gb = 24;
@ -3331,8 +3333,8 @@ int main(int argc, char ** argv) {
int n_gen = params.n_predict;
int sample_ctx = n_tokens - n_tokens/8;
sampler.params.temp = 0.2;
sampler.params.repeat_penalty = 1.1;
sampler.params.temp = 0.2f;
sampler.params.repeat_penalty = 1.1f;
sampler.params.mirostat = 2;
init_sampler(&sampler, lctx);