CANN: format code using .clang-format (#15863)
This commit applies .clang-format rules to all source files under the ggml-cann directory to ensure consistent coding style and readability. The .clang-format option `SortIncludes: false` has been set to disable automatic reordering of include directives. No functional changes are introduced. Co-authored-by: hipudding <huafengchun@gmail.com>
This commit is contained in:
Chenguang Li
co-authored by
hipudding
hipudding
parent
6f5d924637
commit
7a50cf388a
Executable → Regular
+54
-43
@@ -62,10 +62,12 @@ aclDataType ggml_cann_type_mapping(ggml_type type);
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* @param offset Offset in bytes for the ACL tensor data. Defaults to 0.
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* @return Pointer to the created ACL tensor.
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*/
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aclTensor* ggml_cann_create_tensor(const ggml_tensor* tensor, int64_t* ne = nullptr,
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size_t* nb = nullptr, int64_t dims = 0,
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aclFormat format = ACL_FORMAT_ND,
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size_t offset = 0);
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aclTensor * ggml_cann_create_tensor(const ggml_tensor * tensor,
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int64_t * ne = nullptr,
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size_t * nb = nullptr,
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int64_t dims = 0,
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aclFormat format = ACL_FORMAT_ND,
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size_t offset = 0);
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/**
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* @brief Template for creating an ACL tensor from provided parameters. typename TYPE
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@@ -87,12 +89,15 @@ aclTensor* ggml_cann_create_tensor(const ggml_tensor* tensor, int64_t* ne = null
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* @param offset Offset in bytes for the ACL tensor data. Defaults to 0.
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* @return Pointer to the created ACL tensor.
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*/
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template<typename TYPE>
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aclTensor* ggml_cann_create_tensor(void* data_ptr, aclDataType dtype,
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TYPE type_size, int64_t* ne, TYPE* nb,
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int64_t dims,
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aclFormat format = ACL_FORMAT_ND,
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size_t offset = 0) {
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template <typename TYPE>
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aclTensor * ggml_cann_create_tensor(void * data_ptr,
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aclDataType dtype,
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TYPE type_size,
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int64_t * ne,
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TYPE * nb,
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int64_t dims,
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aclFormat format = ACL_FORMAT_ND,
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size_t offset = 0) {
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int64_t tmp_ne[GGML_MAX_DIMS * 2];
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int64_t tmp_stride[GGML_MAX_DIMS * 2];
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@@ -109,9 +114,8 @@ aclTensor* ggml_cann_create_tensor(void* data_ptr, aclDataType dtype,
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std::reverse(tmp_ne, tmp_ne + dims);
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std::reverse(tmp_stride, tmp_stride + dims);
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aclTensor* acl_tensor =
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aclCreateTensor(tmp_ne, dims, dtype, tmp_stride, offset / type_size,
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format, &acl_storage_len, 1, data_ptr);
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aclTensor * acl_tensor =
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aclCreateTensor(tmp_ne, dims, dtype, tmp_stride, offset / type_size, format, &acl_storage_len, 1, data_ptr);
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return acl_tensor;
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}
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@@ -132,7 +136,7 @@ aclTensor* ggml_cann_create_tensor(void* data_ptr, aclDataType dtype,
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* to 1. If such a dimension is found, broadcasting is required to align t1
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* with t0 for element-wise operations.
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*/
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bool ggml_cann_need_bcast(const ggml_tensor* t0, const ggml_tensor* t1);
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bool ggml_cann_need_bcast(const ggml_tensor * t0, const ggml_tensor * t1);
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/**
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* @brief Computes broadcast shapes and strides for two ggml_tensors.
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@@ -187,19 +191,21 @@ bool ggml_cann_need_bcast(const ggml_tensor* t0, const ggml_tensor* t1);
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* dim1 in a inserted dim, should add nb for dim1,
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* and all other nb moves to next in order.
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*/
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int64_t ggml_cann_get_bcast_shape(const ggml_tensor* src0, const ggml_tensor* src1,
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int64_t* bcast_ne_src0, int64_t* bcast_ne_src1,
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size_t* bcast_nb_src0, size_t* bcast_nb_src1);
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int64_t ggml_cann_get_bcast_shape(const ggml_tensor * src0,
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const ggml_tensor * src1,
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int64_t * bcast_ne_src0,
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int64_t * bcast_ne_src1,
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size_t * bcast_nb_src0,
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size_t * bcast_nb_src1);
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// Bcast macro to avoid duplicate code.
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#define BCAST_SHAPE(src0, src1) \
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int64_t bcast_##src0##_ne[GGML_MAX_DIMS * 2]; \
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int64_t bcast_##src1##_ne[GGML_MAX_DIMS * 2]; \
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size_t bcast_##src0##_nb[GGML_MAX_DIMS * 2]; \
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size_t bcast_##src1##_nb[GGML_MAX_DIMS * 2]; \
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int64_t bcast_dims = ggml_cann_get_bcast_shape( \
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src0, src1, bcast_##src0##_ne, bcast_##src1##_ne, bcast_##src0##_nb, \
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bcast_##src1##_nb);
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#define BCAST_SHAPE(src0, src1) \
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int64_t bcast_##src0##_ne[GGML_MAX_DIMS * 2]; \
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int64_t bcast_##src1##_ne[GGML_MAX_DIMS * 2]; \
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size_t bcast_##src0##_nb[GGML_MAX_DIMS * 2]; \
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size_t bcast_##src1##_nb[GGML_MAX_DIMS * 2]; \
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int64_t bcast_dims = ggml_cann_get_bcast_shape(src0, src1, bcast_##src0##_ne, bcast_##src1##_ne, \
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bcast_##src0##_nb, bcast_##src1##_nb);
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#define BCAST_PARAM(tensor) bcast_##tensor##_ne, bcast_##tensor##_nb, bcast_dims
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@@ -233,26 +239,31 @@ int64_t ggml_cann_get_bcast_shape(const ggml_tensor* src0, const ggml_tensor* sr
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* before cast dim.
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* @sa ggml_cann_get_bcast_shape
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*/
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int64_t ggml_cann_get_mulmat_bcast_shape(
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const int64_t* input_ne, const int64_t* weight_ne, const int64_t* dst_ne,
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const size_t* input_nb, const size_t* weight_nb, const size_t* dst_nb,
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int64_t* bcast_input_ne, int64_t* bcast_weight_ne, int64_t* bcast_dst_ne,
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size_t* bcast_input_nb, size_t* bcast_weight_nb, size_t* bcast_dst_nb);
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int64_t ggml_cann_get_mulmat_bcast_shape(const int64_t * input_ne,
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const int64_t * weight_ne,
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const int64_t * dst_ne,
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const size_t * input_nb,
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const size_t * weight_nb,
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const size_t * dst_nb,
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int64_t * bcast_input_ne,
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int64_t * bcast_weight_ne,
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int64_t * bcast_dst_ne,
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size_t * bcast_input_nb,
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size_t * bcast_weight_nb,
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size_t * bcast_dst_nb);
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// Bcast macro to avoid duplicate code.
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#define BCAST_MUL_MAT_SHAPE(input, weight, dst) \
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int64_t bcast_##input##_ne[GGML_MAX_DIMS * 2]; \
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int64_t bcast_##weight##_ne[GGML_MAX_DIMS * 2]; \
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int64_t bcast_##dst##_ne[GGML_MAX_DIMS * 2]; \
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size_t bcast_##input##_nb[GGML_MAX_DIMS * 2]; \
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size_t bcast_##weight##_nb[GGML_MAX_DIMS * 2]; \
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size_t bcast_##dst##_nb[GGML_MAX_DIMS * 2]; \
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int64_t bcast_dims = ggml_cann_get_mulmat_bcast_shape( \
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input->ne, weight->ne, dst->ne, input->nb, weight->nb, dst->nb, \
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bcast_##input##_ne, bcast_##weight##_ne, bcast_##dst##_ne, \
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bcast_##input##_nb, bcast_##weight##_nb, bcast_##dst##_nb);
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#define BCAST_MUL_MAT_SHAPE(input, weight, dst) \
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int64_t bcast_##input##_ne[GGML_MAX_DIMS * 2]; \
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int64_t bcast_##weight##_ne[GGML_MAX_DIMS * 2]; \
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int64_t bcast_##dst##_ne[GGML_MAX_DIMS * 2]; \
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size_t bcast_##input##_nb[GGML_MAX_DIMS * 2]; \
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size_t bcast_##weight##_nb[GGML_MAX_DIMS * 2]; \
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size_t bcast_##dst##_nb[GGML_MAX_DIMS * 2]; \
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int64_t bcast_dims = ggml_cann_get_mulmat_bcast_shape( \
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input->ne, weight->ne, dst->ne, input->nb, weight->nb, dst->nb, bcast_##input##_ne, bcast_##weight##_ne, \
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bcast_##dst##_ne, bcast_##input##_nb, bcast_##weight##_nb, bcast_##dst##_nb);
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#define BCAST_MUL_MAT_PARAM(tensor) \
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bcast_##tensor##_ne, bcast_##tensor##_nb, bcast_dims
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#define BCAST_MUL_MAT_PARAM(tensor) bcast_##tensor##_ne, bcast_##tensor##_nb, bcast_dims
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#endif // CANN_ACL_TENSOR_H
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