Reduce compiler warnings step 2
This commit is contained in:
Akarshan Biswas
parent
3930184d14
commit
a708dfc587
9 changed files with 70 additions and 43 deletions
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@ -11,6 +11,7 @@
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//
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#include "common.hpp"
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#include "ggml-impl.h"
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int get_current_device_id() {
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return dpct::dev_mgr::instance().current_device_id();
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@ -28,11 +29,7 @@ void* ggml_sycl_host_malloc(size_t size) try {
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if (err != 0) {
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// clear the error
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fprintf(
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stderr,
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"WARNING: failed to allocate %.2f MB of pinned memory: %s\n",
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size / 1024.0 / 1024.0,
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"syclGetErrorString is not supported");
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GGML_LOG_ERROR("WARNING: failed to allocate %.2f MB of pinned memory: %s\n", size / 1024.0 / 1024.0, "syclGetErrorString is not supported");
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return nullptr;
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}
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@ -66,17 +63,21 @@ int64_t downsample_sycl_global_range(int64_t accumulate_block_num, int64_t block
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void ggml_sycl_op_flatten(ggml_backend_sycl_context & ctx, const ggml_tensor *src0,
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const ggml_tensor *src1, ggml_tensor *dst,
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const ggml_sycl_op_flatten_t op) try {
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const int64_t nrows0 = ggml_nrows(src0);
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// TODO: What's the use of these?
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// const int64_t nrows0 = ggml_nrows(src0);
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// const int64_t nrows1 = use_src1 ? ggml_nrows(src1) : 1;
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const bool use_src1 = src1 != nullptr;
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const int64_t nrows1 = use_src1 ? ggml_nrows(src1) : 1;
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GGML_ASSERT(!use_src1 || src1->backend != GGML_BACKEND_TYPE_GPU_SPLIT);
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GGML_ASSERT( dst->backend != GGML_BACKEND_TYPE_GPU_SPLIT);
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ggml_tensor_extra_gpu * src0_extra = (ggml_tensor_extra_gpu *) src0->extra;
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ggml_tensor_extra_gpu * src1_extra = use_src1 ? (ggml_tensor_extra_gpu *) src1->extra : nullptr;
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ggml_tensor_extra_gpu * dst_extra = (ggml_tensor_extra_gpu *) dst->extra;
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// TODO: What are these uses of these?
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// ggml_tensor_extra_gpu * src0_extra = (ggml_tensor_extra_gpu *) src0->extra;
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// ggml_tensor_extra_gpu * src1_extra = use_src1 ? (ggml_tensor_extra_gpu *) src1->extra : nullptr;
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// ggml_tensor_extra_gpu * dst_extra = (ggml_tensor_extra_gpu *) dst->extra;
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// dd = data device
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float * src0_ddf = (float *) src0->data;
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@ -424,7 +424,7 @@ static void convert_unary(const void * __restrict__ vx, dst_t * __restrict__ y,
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const int64_t global_id = item_ct1.get_local_id(2) + work_group_size * item_ct1.get_group(2);
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// make each work-item deal with more elements since sycl global range can not exceed max int
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const src_t * x = (src_t *) vx;
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const src_t * x = (const src_t *) vx;
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for (int64_t i = global_id; i < k; i += work_group_size * item_ct1.get_group_range(2)) {
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y[i] = x[i];
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}
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@ -237,7 +237,7 @@ void upscale_f32(const float *x, float *dst, const int nb00, const int nb01,
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int i02 = i12 / sf2;
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int i03 = i13 / sf3;
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dst[index] = *(float *)((const char *)x + i03 * nb03 + i02 * nb02 + i01 * nb01 + i00 * nb00);
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dst[index] = *(const float *)((const char *)x + i03 * nb03 + i02 * nb02 + i01 * nb01 + i00 * nb00);
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}
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void pad_f32(const float *x, float *dst, const int ne0, const int ne00, const int ne01, const int ne02,
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@ -251,8 +251,7 @@ void pad_f32(const float *x, float *dst, const int ne0, const int ne00, const i
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// operation
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int offset_dst = nidx + item_ct1.get_group(1) * ne0 +
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item_ct1.get_group(0) * ne0 * item_ct1.get_group_range(1);
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if (nidx < ne00 && item_ct1.get_group(1) < ne01 &&
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item_ct1.get_group(0) < ne02) {
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if (nidx < ne00 && item_ct1.get_group(1) < (size_t) ne01 && item_ct1.get_group(0) < (size_t) ne02) {
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int offset_src = nidx + item_ct1.get_group(1) * ne00 +
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item_ct1.get_group(0) * ne00 * ne01;
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dst[offset_dst] = x[offset_src];
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@ -23,6 +23,10 @@
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#include "dnnl.hpp"
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#include "dnnl_sycl.hpp"
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// TODO: Remove this when needed
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# pragma clang diagnostic push
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# pragma clang diagnostic ignored "-Wcast-qual"
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class DnnlGemmWrapper {
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public:
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using dt = dnnl::memory::data_type;
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@ -96,6 +100,7 @@ public:
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}
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};
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# pragma clang diagnostic pop
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#endif
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#endif // GGML_SYCL_GEMM_HPP
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@ -47,7 +47,7 @@ static ggml_sycl_device_info ggml_sycl_init() {
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info.device_count = dpct::dev_mgr::instance().device_count();
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if (info.device_count == 0) {
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GGML_LOG_ERROR("%s: failed to initialize " GGML_SYCL_NAME ": %s\n", __func__);
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GGML_LOG_ERROR("%s: failed to initialize: %s\n", GGML_SYCL_NAME, __func__);
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return info;
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}
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@ -64,7 +64,7 @@ static ggml_sycl_device_info ggml_sycl_init() {
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#else
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GGML_LOG_INFO("%s: SYCL_USE_XMX: no\n", __func__);
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#endif
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GGML_LOG_INFO("%s: found %d " GGML_SYCL_NAME " devices:\n", __func__, info.device_count);
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GGML_LOG_INFO("%s: found %d %s devices:\n", __func__, info.device_count, GGML_SYCL_NAME);
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for (int i = 0; i < info.device_count; ++i) {
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info.devices[i].vmm = 0;
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@ -137,7 +137,8 @@ void ggml_backend_sycl_print_sycl_devices() {
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for (int id = 0; id < device_count; ++id) {
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sycl::device device = dpct::dev_mgr::instance().get_device(id);
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sycl::backend backend = device.get_backend();
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// TODO: backend variable is unused here!
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// sycl::backend backend = device.get_backend();
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std::string backend_type = get_device_backend_and_type(device);
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int type_id = DeviceNums[backend_type]++;
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std::stringstream device_type;
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@ -420,13 +421,12 @@ ggml_backend_sycl_buffer_cpy_tensor(ggml_backend_buffer_t buffer,
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return true;
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}
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return false;
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// TODO: Buffer is unused
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(void) buffer;
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} catch (const sycl::exception & exc) {
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std::cerr << exc.what() << "Exception caught at file:" << __FILE__ << ", line:" << __LINE__ << std::endl;
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std::exit(1);
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}
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catch (sycl::exception const &exc) {
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std::cerr << exc.what() << "Exception caught at file:" << __FILE__
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<< ", line:" << __LINE__ << std::endl;
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std::exit(1);
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}
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static void ggml_backend_sycl_buffer_clear(ggml_backend_buffer_t buffer,
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uint8_t value) try {
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@ -1092,10 +1092,7 @@ struct ggml_sycl_pool_leg : public ggml_sycl_pool {
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ggml_sycl_buffer buffer_pool[MAX_SYCL_BUFFERS] = {};
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size_t pool_size = 0;
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explicit ggml_sycl_pool_leg(queue_ptr qptr_, int device_) :
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qptr(qptr_),
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device(device_) {
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}
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explicit ggml_sycl_pool_leg(queue_ptr qptr_, int device_) : device(device_), qptr(qptr_) {}
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~ggml_sycl_pool_leg() {
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for (int i = 0; i < MAX_SYCL_BUFFERS; ++i) {
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@ -1238,7 +1235,7 @@ static void quantize_q8_1(const float * __restrict__ x, void * __restrict__ vy,
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zeros[i] = 0.f;
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qzeros[i] = 0;
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}
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const TC xi = ix < kx ? *(TC *)&x[iy * kx + ix] : zeros;
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const TC xi = ix < kx ? *(const TC *)&x[iy * kx + ix] : zeros;
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float sum = xi[0];
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float amax = sycl::fabs(xi[0]);
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#pragma unroll
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@ -1799,6 +1796,8 @@ static void pool2d_nchw_kernel(
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switch (op) {
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case GGML_OP_POOL_AVG: res = 0; break;
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case GGML_OP_POOL_MAX: res = -FLT_MAX; break;
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default:
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break; // TODO: handle this properly
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}
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for (int i = bh; i < eh; i += 1) {
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@ -1817,6 +1816,8 @@ static void pool2d_nchw_kernel(
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switch (op) {
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case GGML_OP_POOL_AVG: res += (cur / (kh * kw)); break;
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case GGML_OP_POOL_MAX: res = sycl::max(res, (To)cur); break;
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default:
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break; // TODO: handle this properly
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}
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}
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}
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@ -1856,6 +1857,7 @@ static void get_rows_sycl(ggml_backend_sycl_context & ctx, const ggml_tensor *sr
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});
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(void) dst;
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(void) ctx;
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}
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template <typename src0_t>
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@ -1894,9 +1896,9 @@ static void get_rows_sycl_float(ggml_backend_sycl_context & ctx, const ggml_tens
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}
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(void) dst;
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(void) ctx;
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}
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static void quantize_row_q8_1_sycl(const float *x, void *vy, const int kx,
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const int ky, const int kx_padded,
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queue_ptr stream) {
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@ -2484,17 +2486,19 @@ inline void ggml_sycl_op_mul_mat_sycl(
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const int64_t ne00 = src0->ne[0];
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const int64_t ne10 = src1->ne[0];
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const int64_t ne0 = dst->ne[0];
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const int64_t row_diff = row_high - row_low;
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int id;
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SYCL_CHECK(
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CHECK_TRY_ERROR(id = get_current_device_id()));
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#if !GGML_SYCL_DNNL
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const int64_t ne0 = dst->ne[0];
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// the main device has a larger memory buffer to hold the results from all GPUs
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// ldc == nrows of the matrix that cuBLAS writes into
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int ldc = id == ctx.device ? ne0 : row_diff;
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#endif
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#ifdef GGML_SYCL_F16
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bool use_fp16 = true; // TODO(Yu) SYCL capability check
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@ -2531,9 +2535,9 @@ inline void ggml_sycl_op_mul_mat_sycl(
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: src1_as_f16.get();
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ggml_sycl_pool_alloc<sycl::half> dst_f16(ctx.pool(), row_diff * src1_ncols);
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const sycl::half alpha_f16 = 1.0f;
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const sycl::half beta_f16 = 0.0f;
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#if !GGML_SYCL_DNNL
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const sycl::half alpha_f16 = 1.0f;
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const sycl::half beta_f16 = 0.0f;
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SYCL_CHECK(CHECK_TRY_ERROR(dpct::gemm(
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*stream, oneapi::mkl::transpose::trans,
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oneapi::mkl::transpose::nontrans, row_diff, src1_ncols, ne10,
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@ -2570,9 +2574,9 @@ inline void ggml_sycl_op_mul_mat_sycl(
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const float * src0_ddf_i = src0->type == GGML_TYPE_F32 ? (const float *) src0_dd_i : src0_ddq_as_f32.get();
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const float * src1_ddf1_i = src1->type == GGML_TYPE_F32 ? (const float *) src1_ddf_i : src1_ddq_as_f32.get();
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const float alpha = 1.0f;
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const float beta = 0.0f;
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#if !GGML_SYCL_DNNL
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const float alpha = 1.0f;
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const float beta = 0.0f;
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# ifdef GGML_SYCL_NVIDIA
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SYCL_CHECK(CHECK_TRY_ERROR(oneapi::mkl::blas::column_major::gemm(
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oneapi::mkl::backend_selector<oneapi::mkl::backend::cublas>{ *stream }, oneapi::mkl::transpose::trans,
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@ -2870,7 +2874,8 @@ static void ggml_sycl_op_mul_mat(ggml_backend_sycl_context & ctx, const ggml_ten
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ggml_tensor_extra_gpu * src0_extra = (ggml_tensor_extra_gpu *) src0->extra;
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ggml_tensor_extra_gpu * src1_extra = (ggml_tensor_extra_gpu *) src1->extra;
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ggml_tensor_extra_gpu * dst_extra = (ggml_tensor_extra_gpu *) dst->extra;
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// TODO: What's the use of this?
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// ggml_tensor_extra_gpu * dst_extra = (ggml_tensor_extra_gpu *) dst->extra;
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const bool src0_is_contiguous = ggml_is_contiguous(src0);
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const bool src1_is_contiguous = ggml_is_contiguous(src1);
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@ -3296,8 +3301,8 @@ static void ggml_sycl_mul_mat_batched_sycl(ggml_backend_sycl_context & ctx,
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GGML_ASSERT(src0->type == GGML_TYPE_F16);
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GGML_TENSOR_BINARY_OP_LOCALS
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const int64_t ne_dst = ggml_nelements(dst);
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// TODO: What's the use of this?
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//const int64_t ne_dst = ggml_nelements(dst);
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SYCL_CHECK(ggml_sycl_set_device(ctx.device));
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queue_ptr main_stream = ctx.stream();;
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@ -3405,6 +3410,7 @@ catch (sycl::exception const &exc) {
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inline bool ggml_sycl_supports_mmq(enum ggml_type type) {
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// TODO: accuracy issues in MMQ
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(void) type;
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return false;
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}
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@ -3836,13 +3842,17 @@ static void ggml_sycl_argmax(ggml_backend_sycl_context & ctx, const ggml_tensor
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}
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static void ggml_sycl_nop(ggml_backend_sycl_context & ctx, const ggml_tensor * src0, const ggml_tensor * src1, ggml_tensor * dst) {
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// TODO: Why this function even exists?
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(void) src0;
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(void) src1;
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(void) dst;
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(void) ctx;
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}
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void ggml_sycl_set_main_device(const int main_device) try {
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if (dpct::get_current_device_id() == main_device) return;
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if (dpct::get_current_device_id() == static_cast<unsigned int> (main_device)) {
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return;
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}
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check_allow_gpu_index(main_device);
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dpct::select_device(main_device);
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@ -4210,6 +4220,7 @@ try
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{
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ggml_backend_sycl_context *sycl_ctx =
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(ggml_backend_sycl_context *)backend->context;
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sycl::event *sycl_event = static_cast<sycl::event *>(event->context);
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const queue_ptr &stream = sycl_ctx->stream(sycl_ctx->device, 0);
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@ -4224,7 +4235,8 @@ catch (sycl::exception const &exc)
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}
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static void ggml_backend_sycl_event_wait(ggml_backend_t backend, ggml_backend_event_t event) try {
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ggml_backend_sycl_context* sycl_ctx = static_cast<ggml_backend_sycl_context*>(backend->context);
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// TODO: sycl_ctx is unused here
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// ggml_backend_sycl_context* sycl_ctx = static_cast<ggml_backend_sycl_context*>(backend->context);
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sycl::event* sycl_event = static_cast<sycl::event*>(event->context);
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if (ggml_backend_is_sycl(backend)) {
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@ -4632,6 +4644,8 @@ static void *ggml_backend_sycl_reg_get_proc_address(ggml_backend_reg_t reg, cons
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// SYCL doesn't support registering host memory, left here for reference
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// "ggml_backend_register_host_buffer"
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// "ggml_backend_unregister_host_buffer"
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// doing this to make the compiler happy
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(void) name;
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return nullptr;
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}
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@ -13,6 +13,11 @@
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#include "mmq.hpp"
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#include "vecdotq.hpp"
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// Just to make the compiler happy
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// TODO: Remove it when needed
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#pragma clang diagnostic push
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#pragma clang diagnostic ignored "-Wdivision-by-zero"
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typedef void (*allocate_tiles_sycl_t)(
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int** x_ql,
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sycl::half2** x_dm,
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@ -3029,3 +3034,4 @@ catch (sycl::exception const &exc) {
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<< ", line:" << __LINE__ << std::endl;
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std::exit(1);
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}
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#pragma clang diagnostic pop
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@ -1031,4 +1031,5 @@ void ggml_sycl_op_mul_mat_vec_q(
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(void) src1;
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(void) dst;
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(void) src1_ddf_i;
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(void) ctx;
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}
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@ -32,7 +32,7 @@ static void norm_f32(const float* x, float* dst, const int ncols, const float ep
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item_ct1.barrier(sycl::access::fence_space::local_space);
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mean_var = 0.f;
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int nreduce = nwarps / WARP_SIZE;
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for (size_t i = 0; i < nreduce; i += 1)
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for (size_t i = 0; i < (size_t) nreduce; i += 1)
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{
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mean_var += s_sum[lane_id + i * WARP_SIZE];
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}
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@ -86,7 +86,7 @@ static void group_norm_f32(const float* x, float* dst, const int group_size, con
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*/
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item_ct1.barrier();
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tmp = 0.f;
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for (size_t i = 0; i < nreduce; i += 1)
|
||||
for (size_t i = 0; i < (size_t) nreduce; i += 1)
|
||||
{
|
||||
tmp += s_sum[lane_id + i * WARP_SIZE];
|
||||
}
|
||||
|
|
@ -121,7 +121,7 @@ static void group_norm_f32(const float* x, float* dst, const int group_size, con
|
|||
*/
|
||||
item_ct1.barrier();
|
||||
tmp = 0.f;
|
||||
for (size_t i = 0; i < nreduce; i += 1)
|
||||
for (size_t i = 0; i < (size_t) nreduce; i += 1)
|
||||
{
|
||||
tmp += s_sum[lane_id + i * WARP_SIZE];
|
||||
}
|
||||
|
|
|
|||
|
|
@ -68,4 +68,5 @@ void ggml_sycl_op_timestep_embedding(ggml_backend_sycl_context & ctx, const ggml
|
|||
const int max_period = dst->op_params[1];
|
||||
|
||||
timestep_embedding_f32_sycl(src0_d, dst_d, src0->ne[0], dst->nb[1], dim, max_period, stream);
|
||||
(void) src1;
|
||||
}
|
||||
|
|
|
|||
Loading…
Add table
Add a link
Reference in a new issue