add print tensor function to debug
This commit is contained in:
jianyuzh
Meng, Hengyu
parent
3645f25d74
commit
bd38129aeb
3 changed files with 71 additions and 18 deletions
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@ -428,15 +428,17 @@ static void bad_arch(const sycl::stream &stream_ct1) {
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(void) bad_arch; // suppress unused function warning
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}
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//todo: debug for crash in some case
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void print_ggml_tensor(const char*name, struct ggml_tensor *src){
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void log_ggml_var_device(const char*name, float *src, size_t total_elements, bool src_on_device){
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if(!g_ggml_sycl_debug) return;
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if(!src){
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printf("GGML Tensor:%s skip to save for NULL pointer\n", name);
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return;
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}
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char filename[1024];
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sprintf(filename, "%s.txt", name);
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printf("GGML Tensor:%s save to %s:\n", name, filename);
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printf("GGML Tensor:%s save to %s\n", name, filename);
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size_t total_size = ggml_nbytes(src);
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const bool src_on_device = src->backend == GGML_BACKEND_GPU || src->backend == GGML_BACKEND_GPU_SPLIT;
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size_t total_size = total_elements*sizeof(float);
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float *local_buf = NULL;
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// printf("total_size %d2, src_on_device %d\n", total_size, src_on_device);
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if(src_on_device) {
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@ -445,17 +447,16 @@ void print_ggml_tensor(const char*name, struct ggml_tensor *src){
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ggml_sycl_set_device(g_main_device);
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dpct::queue_ptr main_stream = g_syclStreams[g_main_device_index][0];
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ggml_tensor_extra_gpu * src_extra = (ggml_tensor_extra_gpu *) src->extra;
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// printf("zjy before memcpy local_buf=%p, src->data=%p\n", local_buf, src->data);
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main_stream->memcpy(local_buf, src_extra->data_device[g_main_device_index], total_size);
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printf("zjy log dst_ddf=%p main_stream=%p g_main_device_index=%d\n", src,
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main_stream, g_main_device_index);
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main_stream->memcpy(local_buf, src, total_size);
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}
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else {
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local_buf = (float *)src->data;
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local_buf = (float *)src;
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// printf("local buf from src-> data %p\n", local_buf);
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}
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size_t total_elements = ggml_nelements(src);
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std::ofstream logfile;
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logfile.open(filename);
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// printf("local buf element %d\n", total_elements);
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@ -466,9 +467,44 @@ void print_ggml_tensor(const char*name, struct ggml_tensor *src){
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logfile <<std::endl;
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logfile.close();
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// printf("before free %p\n", local_buf);
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if(src_on_device) ggml_sycl_host_free(local_buf);
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// printf("free done\n");
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}
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//todo: debug for crash in some case
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void print_ggml_tensor(const char*name, struct ggml_tensor *src){
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if(!g_ggml_sycl_debug) return;
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if(!src){
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printf("GGML Tensor:%s skip to save for NULL pointer\n", name);
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return;
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}
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size_t total_elements = ggml_nelements(src);
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const bool src_on_device = src->backend == GGML_BACKEND_GPU || src->backend == GGML_BACKEND_GPU_SPLIT;
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float *src_data =NULL;
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if(src_on_device) {
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ggml_tensor_extra_gpu * src_extra = (ggml_tensor_extra_gpu *) src->extra;
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src_data = (float*)src_extra->data_device[g_main_device_index];
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}
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else {
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src_data = (float *)src->data;
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}
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log_ggml_var_device(name, src_data, total_elements, src_on_device);
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}
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static int log_file_name_idx=0;
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void log_tensor_with_cnt(const char* name, struct ggml_tensor * src, int stop_cnt) {
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stop_cnt = 4;
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if(log_file_name_idx>=stop_cnt) return;
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char filename[1280];
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sprintf(filename, "%s_%07d", name, log_file_name_idx);
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log_file_name_idx++;
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print_ggml_tensor(filename, src);
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// print_ggml_tensor("ggml_sycl_rms_norm_src0", (ggml_tensor *)src0);
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// print_ggml_tensor("ggml_sycl_rms_norm_src1", (ggml_tensor *)src1);
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// int *ptr = NULL;
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// *ptr = 0;
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}
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static __dpct_inline__ float warp_reduce_sum(float x,
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@ -8588,7 +8624,7 @@ static dpct::err0 ggml_sycl_cpy_tensor_2d(void *dst,
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if (src->backend == GGML_BACKEND_CPU) {
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kind = dpct::host_to_device;
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src_ptr = (char *) src->data;
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GGML_SYCL_DEBUG("ggml_sycl_cpy_tensor_2d GGML_BACKEND_CPU src_ptr %p\n", src_ptr);
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// GGML_SYCL_DEBUG("ggml_sycl_cpy_tensor_2d GGML_BACKEND_CPU src_ptr %p\n", src_ptr);
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} else if (src->backend == GGML_BACKEND_GPU || src->backend == GGML_BACKEND_GPU_SPLIT) {
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GGML_ASSERT(src->backend != GGML_BACKEND_GPU_SPLIT || (i1_low == 0 && i1_high == src->ne[1]));
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kind = dpct::device_to_device;
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@ -8596,10 +8632,10 @@ static dpct::err0 ggml_sycl_cpy_tensor_2d(void *dst,
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int id;
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SYCL_CHECK(CHECK_TRY_ERROR(
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id = get_current_device_index()));
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GGML_SYCL_DEBUG("current device index %d\n", id);
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// GGML_SYCL_DEBUG("current device index %d\n", id);
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src_ptr = (char *) extra->data_device[id];
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} else {
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GGML_SYCL_DEBUG("GGML_ASSERT(false)\n");
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// GGML_SYCL_DEBUG("GGML_ASSERT(false)\n");
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GGML_ASSERT(false);
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}
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char * dst_ptr = (char *) dst;
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@ -8616,7 +8652,7 @@ static dpct::err0 ggml_sycl_cpy_tensor_2d(void *dst,
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const char * x = src_ptr + i1_low*nb1 + i2*nb2 + i3*nb3;
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if (nb0 == ts && nb1 == ts*ne0/bs) {
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GGML_SYCL_DEBUG("stream->memcpy: dst_ptr=%p, x=%p, size=%lu\n", dst_ptr, x, i1_diff * nb1);
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// GGML_SYCL_DEBUG("stream->memcpy: dst_ptr=%p, x=%p, size=%lu\n", dst_ptr, x, i1_diff * nb1);
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// return CHECK_TRY_ERROR(stream->memcpy(dst_ptr, x, i1_diff * nb1));
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return CHECK_TRY_ERROR(dpct::async_dpct_memcpy(dst_ptr, x, i1_diff * nb1,
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kind, *stream));
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@ -9681,6 +9717,7 @@ static void ggml_sycl_op_flatten(const ggml_tensor *src0,
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}
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if (dst_on_device) {
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dst_ddf = (float *) dst_extra->data_device[g_main_device_index];
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// printf("zjy dst_ddf=%p main_stream=%p g_main_device_index=%d\n", dst_ddf, main_stream, g_main_device_index);
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} else {
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dst_ddf = dst_f.alloc(ggml_nelements(dst));
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}
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@ -10120,6 +10157,9 @@ static void ggml_sycl_get_rows(const ggml_tensor * src0, const ggml_tensor * src
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static void ggml_sycl_add(const ggml_tensor * src0, const ggml_tensor * src1, ggml_tensor * dst) {
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GGML_SYCL_DEBUG("call %s\n", __func__);
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ggml_sycl_op_flatten(src0, src1, dst, ggml_sycl_op_add);
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// log_tensor_with_cnt("log_ggml_sycl_add_src0", (struct ggml_tensor *) src0, 6);
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// log_tensor_with_cnt("log_ggml_sycl_add_src1", (struct ggml_tensor *)src1, 6);
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// log_tensor_with_cnt("log_ggml_sycl_add_dst", dst, 6);
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}
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static void ggml_sycl_acc(const ggml_tensor * src0, const ggml_tensor * src1, ggml_tensor * dst) {
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@ -10130,6 +10170,10 @@ static void ggml_sycl_acc(const ggml_tensor * src0, const ggml_tensor * src1, gg
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static void ggml_sycl_mul(const ggml_tensor * src0, const ggml_tensor * src1, ggml_tensor * dst) {
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GGML_SYCL_DEBUG("call %s\n", __func__);
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ggml_sycl_op_flatten(src0, src1, dst, ggml_sycl_op_mul);
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// log_tensor_with_cnt("log_ggml_sycl_mul_src0", (struct ggml_tensor *)src0, 6);
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// log_tensor_with_cnt("log_ggml_sycl_mul_src1", (struct ggml_tensor *)src1, 6);
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// log_tensor_with_cnt("log_ggml_sycl_mul_dst", dst, 6);
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}
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static void ggml_sycl_div(const ggml_tensor * src0, const ggml_tensor * src1, ggml_tensor * dst) {
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@ -10197,9 +10241,16 @@ static void ggml_sycl_pad(const ggml_tensor * src0, const ggml_tensor * src1, gg
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ggml_sycl_op_flatten(src0, src1, dst, ggml_sycl_op_pad);
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}
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static void ggml_sycl_rms_norm(const ggml_tensor * src0, const ggml_tensor * src1, ggml_tensor * dst) {
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GGML_SYCL_DEBUG("call %s\n", __func__);
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ggml_sycl_op_flatten(src0, src1, dst, ggml_sycl_op_rms_norm);
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log_tensor_with_cnt("log_ggml_sycl_rms_norm_src0", (struct ggml_tensor *)src0, 6);
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log_tensor_with_cnt("log_ggml_sycl_rms_norm_src1", (struct ggml_tensor *)src1, 6);
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log_tensor_with_cnt("log_ggml_sycl_rms_norm_dst", dst, 6);
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// int *ptr = NULL;
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// *ptr = 0;
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}
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bool ggml_sycl_can_mul_mat(const struct ggml_tensor * src0, const struct ggml_tensor * src1, struct ggml_tensor * dst) {
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@ -50,6 +50,7 @@ GGML_API ggml_backend_buffer_type_t ggml_backend_sycl_host_buffer_type(void);
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int get_main_device();
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void print_ggml_tensor(const char*name, struct ggml_tensor *src);
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void log_tensor_with_cnt(const char* name, struct ggml_tensor * src, int stop_cnt);
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#ifdef __cplusplus
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}
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5
run.sh
5
run.sh
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@ -11,8 +11,9 @@ else
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export GGML_SYCL_DEVICE=0
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fi
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echo GGML_SYCL_DEVICE=$GGML_SYCL_DEVICE
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#export GGML_SYCL_DEBUG=1
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export GGML_SYCL_DEBUG=1
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#export GGML_SYCL_LIST_DEVICE=1
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#./build/bin/main -m models/llama-2-7b.Q4_0.gguf -p "${INPUT1}" -e -n 400 -ngl 33 -c 2048
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./build/bin/main -m models/llama-2-7b.Q4_0.gguf -p "${INPUT2}" -n 400 -e -ngl 33
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#./build/bin/main -m models/llama-2-7b.Q4_0.gguf -p "${INPUT2}" -n 400 -e -ngl 33
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./build/bin/main -m models/llama-2-7b.Q4_0.gguf -p "${INPUT2}" -n 5 -e -ngl 33 -t 1 -s 0
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