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Unverified Commit 1f88baa5 authored by q.yao's avatar q.yao Committed by GitHub
Browse files

update log info (#131) 

* update log info

* format cuda utils
parent db3b986b
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Inline Side-by-side
Showing with 121 additions and 98 deletions
src/turbomind/utils/cublasMMWrapper.cc
View file @ 1f88baa5
......@@ -647,11 +647,11 @@ void cublasMMWrapper::SpGemm(cublasOperation_t transa,
void* C)
{
if (Atype_ != CUDA_R_16F || Btype_ != CUDA_R_16F || Ctype_ != CUDA_R_16F) {
throw std::runtime_error("\n[FT][ERROR] sparse GEMM only supports FP16 data type now.");
throw std::runtime_error("\n[TM][ERROR] sparse GEMM only supports FP16 data type now.");
}
static bool not_printed_fp32_accumulation_warning = true;
if (computeType_ != CUDA_R_16F && not_printed_fp32_accumulation_warning) {
printf("[FT][WARNING] cublasMMWrapper sets to FP32 compute type, "
printf("[TM][WARNING] cublasMMWrapper sets to FP32 compute type, "
"but sparse gemm will use FP16 compute type since cusparselt "
"supports FP16 accumulation only.\n");
not_printed_fp32_accumulation_warning = false;
......
src/turbomind/utils/cuda_utils.cc
View file @ 1f88baa5
......@@ -38,7 +38,7 @@ void print_to_file(const T* result, const int size, const char* file, cudaStream
delete[] tmp;
}
else {
throw std::runtime_error(std::string("[FT][ERROR] Cannot open file: ") + file + "\n");
throw std::runtime_error(std::string("[TM][ERROR] Cannot open file: ") + file + "\n");
}
cudaDeviceSynchronize();
check_cuda_error(cudaGetLastError());
......@@ -81,7 +81,7 @@ void print_abs_mean(const T* buf, uint size, cudaStream_t stream, std::string na
}
max_val = max_val > abs(float(h_tmp[i])) ? max_val : abs(float(h_tmp[i]));
}
printf("[INFO][FT] %20s size: %u, abs mean: %f, abs sum: %f, abs max: %f, find inf: %s",
printf("[TM][INFO] %20s size: %u, abs mean: %f, abs sum: %f, abs max: %f, find inf: %s",
name.c_str(),
size,
sum / size,
......
src/turbomind/utils/cuda_utils.h
View file @ 1f88baa5
......@@ -119,7 +119,7 @@ template<typename T>
void check(T result, char const* const func, const char* const file, int const line)
{
if (result) {
throw std::runtime_error(std::string("[FT][ERROR] CUDA runtime error: ") + (_cudaGetErrorEnum(result)) + " "
throw std::runtime_error(std::string("[TM][ERROR] CUDA runtime error: ") + (_cudaGetErrorEnum(result)) + " "
+ file + ":" + std::to_string(line) + " \n");
}
}
......@@ -137,7 +137,7 @@ inline void syncAndCheck(const char* const file, int const line)
cudaDeviceSynchronize();
cudaError_t result = cudaGetLastError();
if (result) {
throw std::runtime_error(std::string("[FT][ERROR] CUDA runtime error: ") + (_cudaGetErrorEnum(result))
throw std::runtime_error(std::string("[TM][ERROR] CUDA runtime error: ") + (_cudaGetErrorEnum(result))
+ " " + file + ":" + std::to_string(line) + " \n");
}
TM_LOG_DEBUG(fmtstr("run syncAndCheck at %s:%d", file, line));
......@@ -148,7 +148,7 @@ inline void syncAndCheck(const char* const file, int const line)
cudaDeviceSynchronize();
cudaError_t result = cudaGetLastError();
if (result) {
throw std::runtime_error(std::string("[FT][ERROR] CUDA runtime error: ") + (_cudaGetErrorEnum(result)) + " "
throw std::runtime_error(std::string("[TM][ERROR] CUDA runtime error: ") + (_cudaGetErrorEnum(result)) + " "
+ file + ":" + std::to_string(line) + " \n");
}
#endif
......@@ -194,12 +194,12 @@ void check_abs_mean_val(const T* result, const int size);
#define PRINT_FUNC_NAME_() \
do { \
std::cout << "[FT][CALL] " << __FUNCTION__ << " " << std::endl; \
std::cout << "[TM][CALL] " << __FUNCTION__ << " " << std::endl; \
} while (0)
[[noreturn]] inline void throwRuntimeError(const char* const file, int const line, std::string const& info = "")
{
throw std::runtime_error(std::string("[FT][ERROR] ") + info + " Assertion fail: " + file + ":"
throw std::runtime_error(std::string("[TM][ERROR] ") + info + " Assertion fail: " + file + ":"
+ std::to_string(line) + " \n");
}
......@@ -226,7 +226,7 @@ inline void myAssert(bool result, const char* const file, int const line, std::s
{ \
cusparseStatus_t status = (func); \
if (status != CUSPARSE_STATUS_SUCCESS) { \
throw std::runtime_error(std::string("[FT][ERROR] CUSPARSE API failed at line ") \
throw std::runtime_error(std::string("[TM][ERROR] CUSPARSE API failed at line ") \
+ std::to_string(__LINE__) + " in file " + __FILE__ + ": " \
+ cusparseGetErrorString(status) + " " + std::to_string(status)); \
} \
......
src/turbomind/utils/gemm_test/encoder_igemm_func.cc
View file @ 1f88baa5
......@@ -1252,7 +1252,7 @@ int generate_encoder_igemm_config(
cudaDeviceSynchronize();
cudaError_t result = cudaGetLastError();
if (result) {
throw std::runtime_error(std::string("[FT][ERROR] CUDA runtime error: "));
throw std::runtime_error(std::string("[TM][ERROR] CUDA runtime error: "));
}
float exec_time = 99999.0f;
......
src/turbomind/utils/logger.cc
View file @ 1f88baa5
......@@ -47,7 +47,7 @@ Logger::Logger()
}
else {
fprintf(stderr,
"[FT][WARNING] Invalid logger level TM_LOG_LEVEL=%s. "
"[TM][WARNING] Invalid logger level TM_LOG_LEVEL=%s. "
"Ignore the environment variable and use a default "
"logging level.\n",
level_name);
......
tests/unittests/test_attention_kernels.cu
View file @ 1f88baa5
......@@ -14,13 +14,13 @@
* limitations under the License.
*/
#include "tests/unittests/gtest_utils.h"
#include "src/turbomind/kernels/gen_relative_pos_bias.h"
#include "src/turbomind/kernels/gpt_kernels.h"
#include "src/turbomind/kernels/unfused_attention_kernels.h"
#include "src/turbomind/utils/Tensor.h"
#include "src/turbomind/utils/memory_utils.h"
#include "src/turbomind/utils/nccl_utils.h"
#include "src/turbomind/utils/Tensor.h"
#include "tests/unittests/gtest_utils.h"
#include <curand.h>
#include <sstream>
......@@ -47,12 +47,13 @@ struct AttentionKernelTestParam {
namespace utils {
#define CHECK_CURAND(cmd) do { \
#define CHECK_CURAND(cmd) \
do { \
curandStatus_t err = cmd; \
if (err != CURAND_STATUS_SUCCESS) { \
throw std::runtime_error( \
fmtstr("[FT][ERROR] curand runtime error: %d", err)); \
}} while(0) \
throw std::runtime_error(fmtstr("[TM][ERROR] curand runtime error: %d", err)); \
} \
} while (0)
__global__ void convert_and_copy(half* dst, const float* src, const size_t size)
{
......@@ -193,7 +194,7 @@ void computeQkSoftmax(T* attn_score,
}
template<typename T>
class AttentionKernelTest : public FtTestBase {
class AttentionKernelTest: public FtTestBase {
private:
using FtTestBase::stream;
......@@ -252,10 +253,11 @@ public:
FtTestBase::TearDown();
}
void runTestMaskedSoftmax(AttentionKernelTestParam param, bool is_benchmark = false) {
void runTestMaskedSoftmax(AttentionKernelTestParam param, bool is_benchmark = false)
{
DataType dtype = getTensorType<T>();
std::vector<size_t> qk_shape {param.batch_size, param.head_num, param.q_length, param.k_length};
std::vector<size_t> qk_shape{param.batch_size, param.head_num, param.q_length, param.k_length};
bool use_fp32_qk = param.use_fp32_qk_buf && dtype != TYPE_FP32;
......@@ -332,10 +334,11 @@ public:
}
}
void runTestAlibiMaskedSoftmax(AttentionKernelTestParam param, bool is_benchmark = false) {
void runTestAlibiMaskedSoftmax(AttentionKernelTestParam param, bool is_benchmark = false)
{
DataType dtype = getTensorType<T>();
std::vector<size_t> qk_shape {param.batch_size, param.head_num, param.q_length, param.k_length};
std::vector<size_t> qk_shape{param.batch_size, param.head_num, param.q_length, param.k_length};
bool use_fp32_qk = param.use_fp32_qk_buf && dtype != TYPE_FP32;
......@@ -355,8 +358,8 @@ public:
sync_check_cuda_error();
Tensor h_alibi_slopes = createTensor(MEMORY_CPU, dtype, {param.head_num});
Tensor h_alibi_bias = is_benchmark ? Tensor() :
createTensor(MEMORY_CPU, dtype, {param.head_num, param.q_length, param.k_length});
Tensor h_alibi_bias =
is_benchmark ? Tensor() : createTensor(MEMORY_CPU, dtype, {param.head_num, param.q_length, param.k_length});
// The nearest power of 2 equal to / smaller than num_heads followed by HF's implementation.
T* alibi_slope_ptr = h_alibi_slopes.getPtr<T>();
int num_heads_pow2 = utils::pow2_rounddown(param.head_num);
......@@ -364,7 +367,8 @@ public:
// The slope of linear bias of the attention head
if (h < num_heads_pow2) {
alibi_slope_ptr[h] = static_cast<T>(powf(powf(0.5f, powf(0.5f, log2f(num_heads_pow2) - 3.f)), h + 1));
} else {
}
else {
alibi_slope_ptr[h] = static_cast<T>(
powf(powf(0.5f, powf(0.5f, log2f(num_heads_pow2 << 1) - 3.f)), (h - num_heads_pow2) * 2 + 1));
}
......@@ -448,87 +452,106 @@ public:
TYPED_TEST_SUITE(AttentionKernelTest, SupportTypes);
TYPED_TEST(AttentionKernelTest, MaskedSoftmax_NoPrompt) {
TYPED_TEST(AttentionKernelTest, MaskedSoftmax_NoPrompt)
{
this->runTestMaskedSoftmax({1, 12, 12, 1, 32, false, 0, false});
}
TYPED_TEST(AttentionKernelTest, MaskedSoftmax_NoPrompt2) {
TYPED_TEST(AttentionKernelTest, MaskedSoftmax_NoPrompt2)
{
// q_length is not multiple of 4.
this->runTestMaskedSoftmax({1, 11, 11, 4, 32, false, 0, false});
}
TYPED_TEST(AttentionKernelTest, MaskedSoftmax_HasPrompt) {
TYPED_TEST(AttentionKernelTest, MaskedSoftmax_HasPrompt)
{
this->runTestMaskedSoftmax({1, 12, 24, 2, 32, false, 0, false});
}
TYPED_TEST(AttentionKernelTest, MaskedSoftmax_HasPrompt2) {
TYPED_TEST(AttentionKernelTest, MaskedSoftmax_HasPrompt2)
{
this->runTestMaskedSoftmax({1, 11, 24, 2, 32, false, 0, false});
}
TYPED_TEST(AttentionKernelTest, MaskedSoftmax_LongSequence1024) {
TYPED_TEST(AttentionKernelTest, MaskedSoftmax_LongSequence1024)
{
this->runTestMaskedSoftmax({1, 12, 1024, 2, 32, false, 0, false});
}
TYPED_TEST(AttentionKernelTest, MaskedSoftmax_LongSequence2048) {
TYPED_TEST(AttentionKernelTest, MaskedSoftmax_LongSequence2048)
{
this->runTestMaskedSoftmax({1, 12, 2048, 2, 32, false, 0, false});
}
TYPED_TEST(AttentionKernelTest, MaskedSoftmax_LongSequence3072) {
TYPED_TEST(AttentionKernelTest, MaskedSoftmax_LongSequence3072)
{
this->runTestMaskedSoftmax({1, 12, 3072, 2, 32, false, 0, false});
}
TYPED_TEST(AttentionKernelTest, MaskedSoftmax_LongSequence4096) {
TYPED_TEST(AttentionKernelTest, MaskedSoftmax_LongSequence4096)
{
this->runTestMaskedSoftmax({1, 12, 4096, 2, 32, false, 0, false});
}
TYPED_TEST(AttentionKernelTest, Benchmark_MaskedSoftmax_LongSequence1024) {
TYPED_TEST(AttentionKernelTest, Benchmark_MaskedSoftmax_LongSequence1024)
{
// Assume the bloom 176B model with 8 TP.
this->runTestMaskedSoftmax({8, 1024, 1024, 14, 128, false, 0, false, true}, true);
}
TYPED_TEST(AttentionKernelTest, Benchmark_MaskedSoftmax_LongSequence2048) {
TYPED_TEST(AttentionKernelTest, Benchmark_MaskedSoftmax_LongSequence2048)
{
// Assume the bloom 176B model with 8 TP.
this->runTestMaskedSoftmax({8, 2048, 2048, 14, 128, false, 0, false, true}, true);
}
TYPED_TEST(AttentionKernelTest, Benchmark_MaskedSoftmax_LongSequence4096) {
TYPED_TEST(AttentionKernelTest, Benchmark_MaskedSoftmax_LongSequence4096)
{
// Assume the bloom 176B model with 8 TP.
this->runTestMaskedSoftmax({8, 4096, 4096, 14, 128, false, 0, false, true}, true);
}
TYPED_TEST(AttentionKernelTest, AlibiMaskedSoftmax_ShortSequence1) {
TYPED_TEST(AttentionKernelTest, AlibiMaskedSoftmax_ShortSequence1)
{
this->runTestAlibiMaskedSoftmax({1, 12, 12, 4, 32, false, 0, false});
}
TYPED_TEST(AttentionKernelTest, AlibiMaskedSoftmax_ShortSequence2) {
TYPED_TEST(AttentionKernelTest, AlibiMaskedSoftmax_ShortSequence2)
{
// q_length is not multiple of 4.
this->runTestAlibiMaskedSoftmax({1, 11, 11, 4, 32, false, 0, false});
}
TYPED_TEST(AttentionKernelTest, AlibiMaskedSoftmax_ShortSequence_HasPrompt1) {
TYPED_TEST(AttentionKernelTest, AlibiMaskedSoftmax_ShortSequence_HasPrompt1)
{
this->runTestAlibiMaskedSoftmax({1, 12, 20, 4, 32, false, 0, false});
}
TYPED_TEST(AttentionKernelTest, AlibiMaskedSoftmax_ShortSequence_HasPrompt2) {
TYPED_TEST(AttentionKernelTest, AlibiMaskedSoftmax_ShortSequence_HasPrompt2)
{
// q_length is not multiple of 4.
this->runTestAlibiMaskedSoftmax({1, 11, 20, 4, 32, false, 0, false});
}
// Tests for long sentence generation. Assume the bloom 176B model with 8 TP.
TYPED_TEST(AttentionKernelTest, Benchmark_AlibiMaskedSoftmax_LongSequence1024) {
TYPED_TEST(AttentionKernelTest, Benchmark_AlibiMaskedSoftmax_LongSequence1024)
{
this->runTestAlibiMaskedSoftmax({8, 1024, 1024, 14, 128, false, 0, false, true}, true);
}
TYPED_TEST(AttentionKernelTest, Benchmark_AlibiMaskedSoftmax_LongSequence2048) {
TYPED_TEST(AttentionKernelTest, Benchmark_AlibiMaskedSoftmax_LongSequence2048)
{
this->runTestAlibiMaskedSoftmax({8, 2048, 2048, 14, 128, false, 0, false, true}, true);
}
TYPED_TEST(AttentionKernelTest, Benchmark_AlibiMaskedSoftmax_LongSequence3072) {
TYPED_TEST(AttentionKernelTest, Benchmark_AlibiMaskedSoftmax_LongSequence3072)
{
this->runTestAlibiMaskedSoftmax({8, 3072, 3072, 14, 128, false, 0, false, true}, true);
}
TYPED_TEST(AttentionKernelTest, Benchmark_AlibiMaskedSoftmax_LongSequence4096) {
TYPED_TEST(AttentionKernelTest, Benchmark_AlibiMaskedSoftmax_LongSequence4096)
{
this->runTestAlibiMaskedSoftmax({4, 4096, 4096, 14, 128, false, 0, false, true}, true);
}
......
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