b6c5f49b78
* whisper : add whisper_batch * whisper : move kv_self to whisper_state * whisper : full batched decoding support * whisper : fix memory leak in whisper_batch * whisper : fix mem leak again + remove oboslete function * whisper : clear kv cache when using whisper_decode API * whisper : speed-up sampling * whisper : fix decoders initializer * bench : add batch size 5 bench * whisper : add comment about the KV cache size * whisper : add check for max number of decoders * whisper : avoid starting sampling threads with bs=1 * whisper : enable beam-search by default * cuda : sync llama.cpp fixes
57 lines
2.1 KiB
C
57 lines
2.1 KiB
C
#pragma once
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#include "ggml.h"
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#include "ggml-backend.h"
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#ifdef GGML_USE_HIPBLAS
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#define GGML_CUDA_NAME "ROCm"
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#define GGML_CUBLAS_NAME "hipBLAS"
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#else
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#define GGML_CUDA_NAME "CUDA"
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#define GGML_CUBLAS_NAME "cuBLAS"
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#endif
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#ifdef __cplusplus
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extern "C" {
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#endif
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#define GGML_CUDA_MAX_DEVICES 16
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// Always success. To check if CUDA is actually loaded, use `ggml_cublas_loaded`.
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GGML_API void ggml_init_cublas(void);
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// Returns `true` if there are available CUDA devices and cublas loads successfully; otherwise, it returns `false`.
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GGML_API bool ggml_cublas_loaded(void);
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GGML_API void * ggml_cuda_host_malloc(size_t size);
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GGML_API void ggml_cuda_host_free(void * ptr);
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GGML_API bool ggml_cuda_can_mul_mat(const struct ggml_tensor * src0, const struct ggml_tensor * src1, struct ggml_tensor * dst);
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GGML_API void ggml_cuda_set_tensor_split(const float * tensor_split);
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GGML_API void ggml_cuda_transform_tensor(void * data, struct ggml_tensor * tensor);
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GGML_API void ggml_cuda_free_data(struct ggml_tensor * tensor);
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GGML_API void ggml_cuda_assign_buffers(struct ggml_tensor * tensor);
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GGML_API void ggml_cuda_assign_buffers_no_scratch(struct ggml_tensor * tensor);
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GGML_API void ggml_cuda_assign_buffers_force_inplace(struct ggml_tensor * tensor);
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GGML_API void ggml_cuda_assign_buffers_no_alloc(struct ggml_tensor * tensor);
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GGML_API void ggml_cuda_assign_scratch_offset(struct ggml_tensor * tensor, size_t offset);
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GGML_API void ggml_cuda_copy_to_device(struct ggml_tensor * tensor);
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GGML_API void ggml_cuda_set_main_device(int main_device);
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GGML_API void ggml_cuda_set_mul_mat_q(bool mul_mat_q);
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GGML_API void ggml_cuda_set_scratch_size(size_t scratch_size);
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GGML_API void ggml_cuda_free_scratch(void);
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GGML_API bool ggml_cuda_compute_forward(struct ggml_compute_params * params, struct ggml_tensor * tensor);
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GGML_API int ggml_cuda_get_device_count(void);
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GGML_API void ggml_cuda_get_device_description(int device, char * description, size_t description_size);
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// backend API
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GGML_API ggml_backend_t ggml_backend_cuda_init(void); // TODO: take a list of devices to use
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#ifdef __cplusplus
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}
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#endif
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