build turbomind (#35)

* build turbomind

* change namespace fastertransformer to turbomind

* change logger name

src/turbomind/utils/gemm_test/t5_gemm_func.cc

@@ -14,9 +14,9 @@
  * limitations under the License.
  */
 
-#include "src/fastertransformer/utils/gemm_test/t5_gemm_func.h"
+#include "src/turbomind/utils/gemm_test/t5_gemm_func.h"
 
-namespace fastertransformer {
+namespace turbomind {
 
 bool isSparseGemmAvailable(size_t m, size_t n, size_t k)
 {
@@ -830,4 +830,4 @@ size_t calT5GemmTestBufSizeInByte(int            batch_size,
     return buf_size_in_byte;
 }
 
-}  // namespace fastertransformer
+}  // namespace turbomind

src/turbomind/utils/gemm_test/t5_gemm_func.h

@@ -16,10 +16,10 @@
 
 #pragma once
 
-#include "src/fastertransformer/utils/cublasAlgoMap.h"
-#include "src/fastertransformer/utils/cuda_bf16_wrapper.h"
-#include "src/fastertransformer/utils/cuda_utils.h"
-#include "src/fastertransformer/utils/gemm_test/gemm_func.h"
+#include "src/turbomind/utils/cublasAlgoMap.h"
+#include "src/turbomind/utils/cuda_bf16_wrapper.h"
+#include "src/turbomind/utils/cuda_utils.h"
+#include "src/turbomind/utils/gemm_test/gemm_func.h"
 
 #include <cstdio>
 #include <cstdlib>
@@ -31,7 +31,7 @@
 #include <unistd.h>
 #include <vector>
 
-namespace fastertransformer {
+namespace turbomind {
 
 template<typename T>
 void generate_t5_gemm_config(int   batch_size,
@@ -66,4 +66,4 @@ size_t calT5GemmTestBufSizeInByte(int            batch_size,
                                   int            tensor_para_size,
                                   CublasDataType data_type);
 
-}  // namespace fastertransformer
+}  // namespace turbomind

src/turbomind/utils/gemm_test/xlnet_gemm_func.cc

@@ -14,9 +14,9 @@
  * limitations under the License.
  */
 
-#include "src/fastertransformer/utils/gemm_test/xlnet_gemm_func.h"
+#include "src/turbomind/utils/gemm_test/xlnet_gemm_func.h"
 
-namespace fastertransformer {
+namespace turbomind {
 
 template<typename T>
 void generate_xlnet_gemm_config(int   batch_size,
@@ -458,4 +458,4 @@ template void generate_xlnet_gemm_config<__nv_bfloat16>(int   batch_size,
                                                         bool  isAppend);
 #endif
 
-}  // namespace fastertransformer
+}  // namespace turbomind

src/turbomind/utils/gemm_test/xlnet_gemm_func.h

@@ -16,10 +16,10 @@
 
 #pragma once
 
-#include "src/fastertransformer/utils/cublasAlgoMap.h"
-#include "src/fastertransformer/utils/cuda_bf16_wrapper.h"
-#include "src/fastertransformer/utils/cuda_utils.h"
-#include "src/fastertransformer/utils/gemm_test/gemm_func.h"
+#include "src/turbomind/utils/cublasAlgoMap.h"
+#include "src/turbomind/utils/cuda_bf16_wrapper.h"
+#include "src/turbomind/utils/cuda_utils.h"
+#include "src/turbomind/utils/gemm_test/gemm_func.h"
 
 #include <cstdio>
 #include <cstdlib>
@@ -31,7 +31,7 @@
 #include <unistd.h>
 #include <vector>
 
-namespace fastertransformer {
+namespace turbomind {
 
 template<typename T>
 void generate_xlnet_gemm_config(int   batch_size,
@@ -43,4 +43,4 @@ void generate_xlnet_gemm_config(int   batch_size,
                                 void* buffer_in,
                                 bool  isAppend = true);
 
-}  // namespace fastertransformer
+}  // namespace turbomind

src/turbomind/utils/gpu_buf.h

@@ -17,15 +17,15 @@
 #pragma once
 
 #include "cuda_fp16.h"
-#include "src/fastertransformer/utils/cuda_fp8_utils.h"
-#include "src/fastertransformer/utils/memory_utils.h"
+#include "src/turbomind/utils/cuda_fp8_utils.h"
+#include "src/turbomind/utils/memory_utils.h"
 
 #include <cstdlib>
 #include <stdexcept>
 #include <type_traits>
 #include <vector>
 
-namespace fastertransformer {
+namespace turbomind {
 
 template<typename T>
 class GPUBuf {
@@ -84,4 +84,4 @@ public:
     T*     ptr;
 };
 
-}  // namespace fastertransformer
+}  // namespace turbomind

src/turbomind/utils/instance_comm.h

 #pragma once
 
-namespace fastertransformer {
+namespace turbomind {
 
 class AbstractInstanceComm {
 public:
@@ -13,4 +13,4 @@ public:
     virtual void* getSharedObject() = 0;
 };
 
-}  // namespace fastertransformer
+}  // namespace turbomind

src/turbomind/utils/logger.cc

@@ -14,21 +14,21 @@
  * limitations under the License.
  */
 
-#include "src/fastertransformer/utils/logger.h"
+#include "src/turbomind/utils/logger.h"
 #include <cuda_runtime.h>
 
-namespace fastertransformer {
+namespace turbomind {
 
 Logger::Logger()
 {
-    char* is_first_rank_only_char = std::getenv("FT_LOG_FIRST_RANK_ONLY");
+    char* is_first_rank_only_char = std::getenv("TM_LOG_FIRST_RANK_ONLY");
     bool  is_first_rank_only =
         (is_first_rank_only_char != nullptr && std::string(is_first_rank_only_char) == "ON") ? true : false;
 
     int device_id;
     cudaGetDevice(&device_id);
 
-    char* level_name = std::getenv("FT_LOG_LEVEL");
+    char* level_name = std::getenv("TM_LOG_LEVEL");
     if (level_name != nullptr) {
         std::map<std::string, Level> name_to_level = {
             {"TRACE", TRACE},
@@ -38,7 +38,7 @@ Logger::Logger()
             {"ERROR", ERROR},
         };
         auto level = name_to_level.find(level_name);
-        // If FT_LOG_FIRST_RANK_ONLY=ON, set LOG LEVEL of other device to ERROR
+        // If TM_LOG_FIRST_RANK_ONLY=ON, set LOG LEVEL of other device to ERROR
         if (is_first_rank_only && device_id != 0) {
             level = name_to_level.find("ERROR");
         }
@@ -47,7 +47,7 @@ Logger::Logger()
         }
         else {
             fprintf(stderr,
-                    "[FT][WARNING] Invalid logger level FT_LOG_LEVEL=%s. "
+                    "[FT][WARNING] Invalid logger level TM_LOG_LEVEL=%s. "
                     "Ignore the environment variable and use a default "
                     "logging level.\n",
                     level_name);
@@ -56,4 +56,4 @@ Logger::Logger()
     }
 }
 
-}  // namespace fastertransformer
+}  // namespace turbomind

src/turbomind/utils/logger.h

@@ -20,9 +20,9 @@
 #include <map>
 #include <string>
 
-#include "src/fastertransformer/utils/string_utils.h"
+#include "src/turbomind/utils/string_utils.h"
 
-namespace fastertransformer {
+namespace turbomind {
 
 class Logger {
 
@@ -77,7 +77,7 @@ public:
     }
 
 private:
-    const std::string                              PREFIX      = "[FT]";
+    const std::string                              PREFIX      = "[TM]";
     const std::map<const Level, const std::string> level_name_ = {
         {TRACE, "TRACE"}, {DEBUG, "DEBUG"}, {INFO, "INFO"}, {WARNING, "WARNING"}, {ERROR, "ERROR"}};
 
@@ -106,16 +106,16 @@ private:
     }
 };
 
-#define FT_LOG(level, ...)                                                                                             \
+#define TM_LOG(level, ...)                                                                                             \
     do {                                                                                                               \
-        if (fastertransformer::Logger::getLogger().getLevel() <= level) {                                              \
-            fastertransformer::Logger::getLogger().log(level, __VA_ARGS__);                                            \
+        if (turbomind::Logger::getLogger().getLevel() <= level) {                                              \
+            turbomind::Logger::getLogger().log(level, __VA_ARGS__);                                            \
         }                                                                                                              \
     } while (0)
 
-#define FT_LOG_TRACE(...) FT_LOG(fastertransformer::Logger::TRACE, __VA_ARGS__)
-#define FT_LOG_DEBUG(...) FT_LOG(fastertransformer::Logger::DEBUG, __VA_ARGS__)
-#define FT_LOG_INFO(...) FT_LOG(fastertransformer::Logger::INFO, __VA_ARGS__)
-#define FT_LOG_WARNING(...) FT_LOG(fastertransformer::Logger::WARNING, __VA_ARGS__)
-#define FT_LOG_ERROR(...) FT_LOG(fastertransformer::Logger::ERROR, __VA_ARGS__)
-}  // namespace fastertransformer
+#define TM_LOG_TRACE(...) TM_LOG(turbomind::Logger::TRACE, __VA_ARGS__)
+#define TM_LOG_DEBUG(...) TM_LOG(turbomind::Logger::DEBUG, __VA_ARGS__)
+#define TM_LOG_INFO(...) TM_LOG(turbomind::Logger::INFO, __VA_ARGS__)
+#define TM_LOG_WARNING(...) TM_LOG(turbomind::Logger::WARNING, __VA_ARGS__)
+#define TM_LOG_ERROR(...) TM_LOG(turbomind::Logger::ERROR, __VA_ARGS__)
+}  // namespace turbomind

src/turbomind/utils/memory_utils.cu

@@ -14,15 +14,15 @@
  * limitations under the License.
  */
 
-#include "src/fastertransformer/utils/Tensor.h"
-#include "src/fastertransformer/utils/cuda_type_utils.cuh"
-#include "src/fastertransformer/utils/logger.h"
-#include "src/fastertransformer/utils/memory_utils.h"
+#include "src/turbomind/utils/Tensor.h"
+#include "src/turbomind/utils/cuda_type_utils.cuh"
+#include "src/turbomind/utils/logger.h"
+#include "src/turbomind/utils/memory_utils.h"
 #include <curand_kernel.h>
 #include <sys/stat.h>
 #include <unordered_map>
 
-namespace fastertransformer {
+namespace turbomind {
 
 template<typename T>
 void deviceMalloc(T** ptr, size_t size, bool is_random_initialize)
@@ -130,7 +130,7 @@ template<typename T>
 void cudaH2Dcpy(T* tgt, const T* src, const size_t size)
 {
     if (tgt == nullptr || src == nullptr) {
-        FT_LOG_ERROR("cudaH2Dcpy: dst=%p src=%p, size=%d", tgt, src, (int)(sizeof(T) * size));
+        TM_LOG_ERROR("cudaH2Dcpy: dst=%p src=%p, size=%d", tgt, src, (int)(sizeof(T) * size));
     }
     check_cuda_error(cudaMemcpy(tgt, src, sizeof(T) * size, cudaMemcpyHostToDevice));
 }
@@ -313,14 +313,14 @@ std::vector<T> loadWeightFromBinHelper(std::vector<size_t> shape, std::string fi
     }
     size_t size = dim0 * dim1;
     if (size == 0) {
-        FT_LOG_WARNING("shape is zero, skip loading weight from file %s \n", filename.c_str());
+        TM_LOG_WARNING("shape is zero, skip loading weight from file %s \n", filename.c_str());
         return std::vector<T>();
     }
 
     std::vector<T> host_array(size);
     std::ifstream  in(filename, std::ios::in | std::ios::binary);
     if (!in.is_open()) {
-        FT_LOG_WARNING("file %s cannot be opened, loading model fails! \n", filename.c_str());
+        TM_LOG_WARNING("file %s cannot be opened, loading model fails! \n", filename.c_str());
         return std::vector<T>();
     }
 
@@ -328,12 +328,12 @@ std::vector<T> loadWeightFromBinHelper(std::vector<size_t> shape, std::string fi
     in.seekg(0, in.end);
     in.seekg(0, in.beg);
 
-    FT_LOG_DEBUG("Read " + std::to_string(loaded_data_size) + " bytes from " + filename);
+    TM_LOG_DEBUG("Read " + std::to_string(loaded_data_size) + " bytes from " + filename);
     in.read((char*)host_array.data(), loaded_data_size);
 
     size_t in_get_size = in.gcount();
     if (in_get_size != loaded_data_size) {
-        FT_LOG_WARNING("file %s only has %ld, but request %ld, loading model fails! \n",
+        TM_LOG_WARNING("file %s only has %ld, but request %ld, loading model fails! \n",
                        filename.c_str(),
                        in_get_size,
                        loaded_data_size);
@@ -417,7 +417,7 @@ int loadWeightFromBin(T* ptr, std::vector<size_t> shape, std::string filename, F
             break;
 #endif
         default:
-            FT_LOG_ERROR("Does not support FtCudaDataType=%d", model_file_type);
+            TM_LOG_ERROR("Does not support FtCudaDataType=%d", model_file_type);
             FT_CHECK(false);
     }
     return 0;
@@ -839,4 +839,4 @@ bool invokeCheckRange(T* buffer, const size_t size, T min, T max, bool* d_within
 template bool
 invokeCheckRange<int>(int* buffer, const size_t size, int min, int max, bool* d_within_range, cudaStream_t stream);
 
-}  // namespace fastertransformer
+}  // namespace turbomind

src/turbomind/utils/memory_utils.h

@@ -16,11 +16,11 @@
 
 #pragma once
 
-#include "src/fastertransformer/utils/Tensor.h"
-#include "src/fastertransformer/utils/cuda_fp8_utils.h"
-#include "src/fastertransformer/utils/cuda_utils.h"
+#include "src/turbomind/utils/Tensor.h"
+#include "src/turbomind/utils/cuda_fp8_utils.h"
+#include "src/turbomind/utils/cuda_utils.h"
 
-namespace fastertransformer {
+namespace turbomind {
 
 template<typename T>
 void deviceMalloc(T** ptr, size_t size, bool is_random_initialize = true);
@@ -144,4 +144,4 @@ size_t cuda_datatype_size(FtCudaDataType dt);
 template<typename T>
 bool invokeCheckRange(T* buffer, const size_t size, T min, T max, bool* d_within_range, cudaStream_t stream);
 
-}  // namespace fastertransformer
+}  // namespace turbomind

src/turbomind/utils/mpi_utils.cc

@@ -14,9 +14,9 @@
  * limitations under the License.
  */
 
-#include "src/fastertransformer/utils/mpi_utils.h"
+#include "src/turbomind/utils/mpi_utils.h"
 
-namespace fastertransformer {
+namespace turbomind {
 namespace mpi {
 
 #ifdef BUILD_MULTI_GPU
@@ -119,4 +119,4 @@ void bcast(void* buffer, size_t size, MpiType dtype, int root, MpiComm comm)
 }
 
 }  // namespace mpi
-}  // namespace fastertransformer
+}  // namespace turbomind

src/turbomind/utils/mpi_utils.h

@@ -16,7 +16,7 @@
 
 #pragma once
 
-#include "src/fastertransformer/utils/logger.h"
+#include "src/turbomind/utils/logger.h"
 
 #ifdef BUILD_MULTI_GPU
 #include <mpi.h>
@@ -24,7 +24,7 @@
 #include <stdio.h>
 #include <unordered_map>
 
-namespace fastertransformer {
+namespace turbomind {
 
 #ifdef BUILD_MULTI_GPU
 #define MPICHECK(cmd)                                                                                                  \
@@ -91,4 +91,4 @@ int getCommWorldSize();
 void bcast(void* buffer, size_t size, MpiType dtype, int root, MpiComm comm);
 
 }  // namespace mpi
-}  // namespace fastertransformer
+}  // namespace turbomind

src/turbomind/utils/nccl_utils.cc

@@ -14,16 +14,16 @@
  * limitations under the License.
  */
 
-#include "src/fastertransformer/utils/nccl_utils.h"
+#include "src/turbomind/utils/nccl_utils.h"
 #include <atomic>
 
-namespace fastertransformer {
+namespace turbomind {
 
 #ifdef BUILD_MULTI_GPU
 template<typename T>
 ncclDataType_t getNcclDataType()
 {
-    FT_LOG_DEBUG("%s start", __PRETTY_FUNCTION__);
+    TM_LOG_DEBUG("%s start", __PRETTY_FUNCTION__);
     ncclDataType_t nccl_data_type;
     if (std::is_same<T, float>::value) {
         nccl_data_type = ncclFloat;
@@ -56,7 +56,7 @@ ncclDataType_t getNcclDataType()
 template<typename T>
 void ftNcclAllReduceSum(const T* send_buf, T* recv_buf, const int data_size, NcclParam nccl_param, cudaStream_t stream)
 {
-    FT_LOG_DEBUG("%s start", __PRETTY_FUNCTION__);
+    TM_LOG_DEBUG("%s start", __PRETTY_FUNCTION__);
 #ifdef BUILD_MULTI_GPU
     ncclDataType_t nccl_data_type = getNcclDataType<T>();
     NCCLCHECK(ncclGroupStart());
@@ -64,14 +64,14 @@ void ftNcclAllReduceSum(const T* send_buf, T* recv_buf, const int data_size, Ncc
         (const void*)send_buf, (void*)recv_buf, data_size, nccl_data_type, ncclSum, nccl_param.nccl_comm_, stream));
     NCCLCHECK(ncclGroupEnd());
 #endif
-    FT_LOG_DEBUG("%s stop", __PRETTY_FUNCTION__);
+    TM_LOG_DEBUG("%s stop", __PRETTY_FUNCTION__);
 }
 
 template<typename T>
 void ftNcclAllGather(
     const T* send_buf, T* recv_buf, const int data_size, const int rank, NcclParam nccl_param, cudaStream_t stream)
 {
-    FT_LOG_DEBUG("%s start", __PRETTY_FUNCTION__);
+    TM_LOG_DEBUG("%s start", __PRETTY_FUNCTION__);
 #ifdef BUILD_MULTI_GPU
     ncclDataType_t nccl_data_type = getNcclDataType<T>();
     NCCLCHECK(ncclGroupStart());
@@ -79,18 +79,18 @@ void ftNcclAllGather(
         ncclAllGather(send_buf + rank * data_size, recv_buf, data_size, nccl_data_type, nccl_param.nccl_comm_, stream));
     NCCLCHECK(ncclGroupEnd());
 #endif
-    FT_LOG_DEBUG("%s stop", __PRETTY_FUNCTION__);
+    TM_LOG_DEBUG("%s stop", __PRETTY_FUNCTION__);
 }
 
 template<typename T>
 void ftNcclSend(const T* send_buf, const int data_size, const int peer, NcclParam nccl_param, cudaStream_t stream)
 {
-    FT_LOG_DEBUG("%s start", __PRETTY_FUNCTION__);
+    TM_LOG_DEBUG("%s start", __PRETTY_FUNCTION__);
 #ifdef BUILD_MULTI_GPU
     ncclDataType_t nccl_data_type = getNcclDataType<T>();
     NCCLCHECK(ncclSend(send_buf, data_size, nccl_data_type, peer, nccl_param.nccl_comm_, stream));
 #endif
-    FT_LOG_DEBUG("%s stop", __PRETTY_FUNCTION__);
+    TM_LOG_DEBUG("%s stop", __PRETTY_FUNCTION__);
 }
 
 template void
@@ -111,12 +111,12 @@ ftNcclSend(const char* send_buf, const int data_size, const int peer, NcclParam
 template<typename T>
 void ftNcclRecv(T* recv_buf, const int data_size, const int peer, NcclParam nccl_param, cudaStream_t stream)
 {
-    FT_LOG_DEBUG("%s start", __PRETTY_FUNCTION__);
+    TM_LOG_DEBUG("%s start", __PRETTY_FUNCTION__);
 #ifdef BUILD_MULTI_GPU
     ncclDataType_t nccl_data_type = getNcclDataType<T>();
     NCCLCHECK(ncclRecv(recv_buf, data_size, nccl_data_type, peer, nccl_param.nccl_comm_, stream));
 #endif
-    FT_LOG_DEBUG("%s stop", __PRETTY_FUNCTION__);
+    TM_LOG_DEBUG("%s stop", __PRETTY_FUNCTION__);
 }
 
 template void
@@ -136,12 +136,12 @@ ftNcclRecv(char* recv_buf, const int data_size, const int peer, NcclParam nccl_p
 template<typename T>
 void ftNcclBroadCast(T* buff, const int data_size, const int root, NcclParam nccl_param, cudaStream_t stream)
 {
-    FT_LOG_DEBUG("%s start", __PRETTY_FUNCTION__);
+    TM_LOG_DEBUG("%s start", __PRETTY_FUNCTION__);
 #ifdef BUILD_MULTI_GPU
     ncclDataType_t nccl_data_type = getNcclDataType<T>();
     NCCLCHECK(ncclBcast(buff, data_size, nccl_data_type, root, nccl_param.nccl_comm_, stream));
 #endif
-    FT_LOG_DEBUG("%s stop", __PRETTY_FUNCTION__);
+    TM_LOG_DEBUG("%s stop", __PRETTY_FUNCTION__);
 }
 
 template void
@@ -215,7 +215,7 @@ void ftNcclGroupEnd()
 
 void ftNcclStreamSynchronize(NcclParam tensor_para, NcclParam pipeline_para, cudaStream_t stream)
 {
-    FT_LOG_DEBUG("%s start", __PRETTY_FUNCTION__);
+    TM_LOG_DEBUG("%s start", __PRETTY_FUNCTION__);
 #ifdef BUILD_MULTI_GPU
     cudaError_t  cudaErr;
     ncclResult_t tensor_ncclErr = ncclSuccess, tensor_ncclAsyncErr = ncclSuccess, pipeline_ncclErr = ncclSuccess,
@@ -229,7 +229,7 @@ void ftNcclStreamSynchronize(NcclParam tensor_para, NcclParam pipeline_para, cud
     while (1) {
         cudaErr = cudaStreamQuery(stream);
         if (cudaErr == cudaSuccess) {
-            FT_LOG_DEBUG("%s stop", __PRETTY_FUNCTION__);
+            TM_LOG_DEBUG("%s stop", __PRETTY_FUNCTION__);
             return;
         }
 
@@ -282,11 +282,11 @@ void ftNcclGetUniqueId(NcclUid& uid)
 
 void ftNcclCommInitRank(NcclParam& param, const int rank, const int world_size, const NcclUid uid)
 {
-    FT_LOG_DEBUG("%s start", __PRETTY_FUNCTION__);
+    TM_LOG_DEBUG("%s start", __PRETTY_FUNCTION__);
 #ifdef BUILD_MULTI_GPU
     // Initialize a nccl communicator.
     if (param.nccl_comm_ != nullptr) {
-        FT_LOG_WARNING("NcclParam is already initialized.");
+        TM_LOG_WARNING("NcclParam is already initialized.");
         return;
     }
     param.rank_       = rank;
@@ -294,7 +294,7 @@ void ftNcclCommInitRank(NcclParam& param, const int rank, const int world_size,
     param.nccl_uid_   = uid.nccl_uid_;
     NCCLCHECK(ncclCommInitRank(&param.nccl_comm_, param.world_size_, param.nccl_uid_, param.rank_));
 #endif
-    FT_LOG_DEBUG("%s stop", __PRETTY_FUNCTION__);
+    TM_LOG_DEBUG("%s stop", __PRETTY_FUNCTION__);
 }
 
 void ftNcclParamDestroy(NcclParam& param)
@@ -311,7 +311,7 @@ void ftNcclInitialize(NcclParam& tensor_para,
                       const int  tensor_para_size,
                       const int  pipeline_para_size)
 {
-    FT_LOG_DEBUG("%s start", __PRETTY_FUNCTION__);
+    TM_LOG_DEBUG("%s start", __PRETTY_FUNCTION__);
     // Initialize nccl communication grid of tensor and pipeline parallel groups.
 #ifndef BUILD_MULTI_GPU
     FT_CHECK_WITH_INFO(tensor_para_size == 1,
@@ -331,7 +331,7 @@ void ftNcclInitialize(NcclParam& tensor_para,
 #else
     // Initialize a nccl communicator.
     if (tensor_para.nccl_comm_ != nullptr && pipeline_para.nccl_comm_ != nullptr) {
-        FT_LOG_WARNING("NcclParam is already initialized. Skip NCCL initialization.");
+        TM_LOG_WARNING("NcclParam is already initialized. Skip NCCL initialization.");
         return;
     }
     FT_CHECK(tensor_para.nccl_comm_ == nullptr);
@@ -340,7 +340,7 @@ void ftNcclInitialize(NcclParam& tensor_para,
     FT_CHECK(pipeline_para_size > 0);
 
     if (tensor_para_size == 1 && pipeline_para_size == 1) {
-        FT_LOG_WARNING("Skip NCCL initialization since requested tensor/pipeline parallel sizes are equals to 1.");
+        TM_LOG_WARNING("Skip NCCL initialization since requested tensor/pipeline parallel sizes are equals to 1.");
         tensor_para.rank_         = 0;
         tensor_para.world_size_   = tensor_para_size;
         pipeline_para.rank_       = 0;
@@ -384,19 +384,19 @@ void ftNcclInitialize(NcclParam& tensor_para,
     ncclUniqueId pp_uid;
     // The root of each group creates a nccl uid.
     if (tp_rank == 0) {
-        FT_LOG_DEBUG("rank %d pp rank %d creates nccl uid.", rank, tp_rank);
+        TM_LOG_DEBUG("rank %d pp rank %d creates nccl uid.", rank, tp_rank);
         NCCLCHECK(ncclGetUniqueId(&tp_uid));
     }
     if (pp_rank == 0) {
-        FT_LOG_DEBUG("rank %d pp rank %d creates nccl uid.", rank, pp_rank);
+        TM_LOG_DEBUG("rank %d pp rank %d creates nccl uid.", rank, pp_rank);
         NCCLCHECK(ncclGetUniqueId(&pp_uid));
     }
     // Broadcast nccl uid to share the same nccl uid across gpus in the same group.
-    FT_LOG_DEBUG("Broadcast nccl uid to the others in the same parallel groups.");
+    TM_LOG_DEBUG("Broadcast nccl uid to the others in the same parallel groups.");
     MPI_Bcast(&tp_uid, sizeof(tp_uid), MPI_BYTE, 0, tp_comm);
     MPI_Bcast(&pp_uid, sizeof(pp_uid), MPI_BYTE, 0, pp_comm);
 
-    FT_LOG_DEBUG("Initialize NCCL communicators.");
+    TM_LOG_DEBUG("Initialize NCCL communicators.");
     ncclComm_t tp_nccl_comm, pp_nccl_comm;
     NCCLCHECK(ncclCommInitRank(&tp_nccl_comm, tensor_para_size, tp_uid, tp_rank));
     NCCLCHECK(ncclCommInitRank(&pp_nccl_comm, pipeline_para_size, pp_uid, pp_rank));
@@ -409,13 +409,13 @@ void ftNcclInitialize(NcclParam& tensor_para,
     pipeline_para.rank_       = pp_rank;
     pipeline_para.nccl_uid_   = pp_uid;
     pipeline_para.nccl_comm_  = pp_nccl_comm;
-    FT_LOG_INFO("NCCL initialized rank=%d world_size=%d tensor_para=%s pipeline_para=%s",
+    TM_LOG_INFO("NCCL initialized rank=%d world_size=%d tensor_para=%s pipeline_para=%s",
                 rank,
                 world_size,
                 tensor_para.toString().c_str(),
                 pipeline_para.toString().c_str());
 #endif
-    FT_LOG_DEBUG("%s stop", __PRETTY_FUNCTION__);
+    TM_LOG_DEBUG("%s stop", __PRETTY_FUNCTION__);
 }
 
 static std::atomic<int>& ncclGroupCount()
@@ -449,4 +449,4 @@ size_t getLocalBatchSize(const size_t batch_size, const size_t seq_len, const si
     return local_batch_size;
 }
 
-}  // namespace fastertransformer
+}  // namespace turbomind

src/turbomind/utils/nccl_utils.h

@@ -16,9 +16,9 @@
 
 #pragma once
 
-#include "src/fastertransformer/utils/cuda_utils.h"
-#include "src/fastertransformer/utils/logger.h"
-#include "src/fastertransformer/utils/mpi_utils.h"
+#include "src/turbomind/utils/cuda_utils.h"
+#include "src/turbomind/utils/logger.h"
+#include "src/turbomind/utils/mpi_utils.h"
 
 #include <cuda_runtime.h>
 #ifdef BUILD_MULTI_GPU
@@ -32,7 +32,7 @@
 #define ENABLE_BF16_NCCL
 #endif
 
-namespace fastertransformer {
+namespace turbomind {
 #ifdef BUILD_MULTI_GPU
 #define NCCLCHECK(cmd)                                                                                                 \
     do {                                                                                                               \
@@ -128,4 +128,4 @@ int ftNcclGroupCount();
 
 size_t getLocalBatchSize(const size_t batch_size, const size_t seq_len, const size_t pipeline_para_size);
 
-}  // namespace fastertransformer
+}  // namespace turbomind

src/turbomind/utils/prompt_learning.h

@@ -17,7 +17,7 @@
 
 #pragma once
 
-namespace fastertransformer {
+namespace turbomind {
 
 enum class PromptLearningType {
     no_prompt,
@@ -26,4 +26,4 @@ enum class PromptLearningType {
     p_prompt_tuning
 };
 
-}  // namespace fastertransformer
+}  // namespace turbomind

src/turbomind/utils/string_utils.h

@@ -21,7 +21,7 @@
 #include <string>
 #include <vector>
 
-namespace fastertransformer {
+namespace turbomind {
 
 template<typename... Args>
 inline std::string fmtstr(const std::string& format, Args... args)
@@ -81,4 +81,4 @@ inline std::string arr2str(T* arr, size_t size)
     ss << ")";
     return ss.str();
 }
-}  // namespace fastertransformer
+}  // namespace turbomind

src/turbomind/utils/test_utils.h

@@ -20,7 +20,7 @@
 #include <cuda.h>
 #include <cuda_runtime_api.h>
 
-namespace fastertransformer {
+namespace turbomind {
 
 #define TIMEIT(print, n, stream, fn, ...)                                                                              \
     ({                                                                                                                 \
@@ -57,4 +57,4 @@ struct abs_diff {
     }
 };
 
-}  // namespace fastertransformer
+}  // namespace turbomind

src/turbomind/utils/wenet_conv2d.h

@@ -23,7 +23,7 @@
 #include <cuda_fp16.h>
 #include <cudnn.h>
 
-namespace fastertransformer {
+namespace turbomind {
 
 template<typename T>
 void conv2d(T*             output,
@@ -154,7 +154,7 @@ void conv2d(T*             output,
                                                        output_descriptor_,
                                                        convolution_algorithm_,
                                                        &ws_size));
-    FT_LOG_DEBUG("Convolution algorithm: %d with workspace size: %d \n", convolution_algorithm_, ws_size);
+    TM_LOG_DEBUG("Convolution algorithm: %d with workspace size: %d \n", convolution_algorithm_, ws_size);
     FT_CHECK_WITH_INFO(
         ws_size <= (1 << 29),
         "Current workspace used for CuDNN Convolution is fixed as 1 << 29, please increase it in WenetEncoder::allocateBuffer!");
@@ -195,4 +195,4 @@ void conv2d(T*             output,
     checkCUDNN(cudnnDestroyConvolutionDescriptor(convolution_descriptor_));
 }
 
-}  // namespace fastertransformer
+}  // namespace turbomind

src/turbomind/utils/word_list.cc

@@ -19,7 +19,7 @@
 
 #include "assert.h"
 
-namespace fastertransformer {
+namespace turbomind {
 
 int read_word_list(const std::string& filename, std::vector<int>& file_data)
 {
@@ -47,4 +47,4 @@ int read_word_list(const std::string& filename, std::vector<int>& file_data)
     return 0;
 }
 
-}  // namespace fastertransformer
+}  // namespace turbomind

src/turbomind/utils/word_list.h

@@ -19,7 +19,7 @@
 #include "Tensor.h"
 #include "stdlib.h"
 
-namespace fastertransformer {
+namespace turbomind {
 
 int read_word_list(const std::string& filename, std::vector<int>& tensor_data);