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https://github.com/ggml-org/llama.cpp.git
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cpu : add FLOOR, CEIL, ROUND and TRUNC unary operators (#16083)
* CPU: Add support for FLOOR,CEIL,ROUND and TRUNC unary operators - Added the operators to unary op enum - Implemented API functions - Implemented forward and unary-op logic in CPU backend - Updated ggml_get_n_tasks - Updated operators names array and static_assert - Updated docs and enabled automatic tests * docs: add documentation for ggml_trunc and ggml_trunc_inplace in ggml.h * chore: remove trailing whitespace from ggml.h * Remove unresolved merge markers * Apply review suggestions: cleanup formatting, enum order and leftover artifacts * Regenerate ops.md using create_ops_docs.py
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@@ -577,6 +577,10 @@ extern "C" {
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GGML_UNARY_OP_EXP,
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GGML_UNARY_OP_GELU_ERF,
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GGML_UNARY_OP_XIELU,
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GGML_UNARY_OP_FLOOR,
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GGML_UNARY_OP_CEIL,
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GGML_UNARY_OP_ROUND,
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GGML_UNARY_OP_TRUNC,
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GGML_UNARY_OP_COUNT,
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};
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@@ -1151,6 +1155,46 @@ extern "C" {
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struct ggml_context * ctx,
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struct ggml_tensor * a);
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GGML_API struct ggml_tensor * ggml_floor(
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struct ggml_context * ctx,
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struct ggml_tensor * a);
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GGML_API struct ggml_tensor * ggml_floor_inplace(
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struct ggml_context * ctx,
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struct ggml_tensor * a);
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GGML_API struct ggml_tensor * ggml_ceil(
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struct ggml_context * ctx,
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struct ggml_tensor * a);
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GGML_API struct ggml_tensor * ggml_ceil_inplace(
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struct ggml_context * ctx,
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struct ggml_tensor * a);
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GGML_API struct ggml_tensor * ggml_round(
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struct ggml_context * ctx,
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struct ggml_tensor * a);
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GGML_API struct ggml_tensor * ggml_round_inplace(
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struct ggml_context * ctx,
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struct ggml_tensor * a);
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/**
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* Truncates the fractional part of each element in the tensor (towards zero).
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* For example: trunc(3.7) = 3.0, trunc(-2.9) = -2.0
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* Similar to std::trunc in C/C++.
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*/
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GGML_API struct ggml_tensor * ggml_trunc(
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struct ggml_context * ctx,
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struct ggml_tensor * a);
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GGML_API struct ggml_tensor * ggml_trunc_inplace(
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struct ggml_context * ctx,
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struct ggml_tensor * a);
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// xIELU activation function
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// x = x * (c_a(alpha_n) + c_b(alpha_p, beta) * sigmoid(beta * x)) + eps * (x > 0)
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// where c_a = softplus and c_b(a, b) = softplus(a) + b are constraining functions
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@@ -2184,6 +2184,10 @@ static int ggml_get_n_tasks(struct ggml_tensor * node, int n_threads) {
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case GGML_UNARY_OP_HARDSWISH:
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case GGML_UNARY_OP_HARDSIGMOID:
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case GGML_UNARY_OP_EXP:
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case GGML_UNARY_OP_FLOOR:
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case GGML_UNARY_OP_CEIL:
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case GGML_UNARY_OP_ROUND:
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case GGML_UNARY_OP_TRUNC:
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{
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n_tasks = 1;
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} break;
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@@ -8993,6 +8993,22 @@ void ggml_compute_forward_unary(
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{
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ggml_compute_forward_exp(params, dst);
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} break;
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case GGML_UNARY_OP_FLOOR:
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{
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ggml_compute_forward_floor(params, dst);
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} break;
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case GGML_UNARY_OP_CEIL:
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{
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ggml_compute_forward_ceil(params, dst);
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} break;
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case GGML_UNARY_OP_ROUND:
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{
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ggml_compute_forward_round(params, dst);
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} break;
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case GGML_UNARY_OP_TRUNC:
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{
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ggml_compute_forward_trunc(params, dst);
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} break;
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case GGML_UNARY_OP_XIELU:
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{
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ggml_compute_forward_xielu(params, dst);
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@@ -73,6 +73,22 @@ static inline float op_log(float x) {
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return logf(x);
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}
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static inline float op_floor(float x) {
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return floorf(x);
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}
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static inline float op_ceil(float x) {
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return ceilf(x);
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}
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static inline float op_round(float x) {
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return roundf(x);
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}
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static inline float op_trunc(float x) {
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return truncf(x);
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}
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template <float (*op)(float), typename src0_t, typename dst_t>
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static inline void vec_unary_op(int64_t n, dst_t * y, const src0_t * x) {
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constexpr auto src0_to_f32 = type_conversion_table<src0_t>::to_f32;
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@@ -274,6 +290,22 @@ void ggml_compute_forward_log(const ggml_compute_params * params, ggml_tensor *
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unary_op<op_log>(params, dst);
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}
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void ggml_compute_forward_floor(const ggml_compute_params * params, ggml_tensor * dst) {
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unary_op<op_floor>(params, dst);
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}
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void ggml_compute_forward_ceil(const ggml_compute_params * params, ggml_tensor * dst) {
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unary_op<op_ceil>(params, dst);
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}
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void ggml_compute_forward_round(const ggml_compute_params * params, ggml_tensor * dst) {
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unary_op<op_round>(params, dst);
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}
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void ggml_compute_forward_trunc(const ggml_compute_params * params, ggml_tensor * dst) {
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unary_op<op_trunc>(params, dst);
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}
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void ggml_compute_forward_xielu(const ggml_compute_params * params, ggml_tensor * dst) {
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const float alpha_n = ggml_get_op_params_f32(dst, 1);
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const float alpha_p = ggml_get_op_params_f32(dst, 2);
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@@ -22,6 +22,10 @@ void ggml_compute_forward_sqrt(const struct ggml_compute_params * params, struct
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void ggml_compute_forward_sin(const struct ggml_compute_params * params, struct ggml_tensor * dst);
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void ggml_compute_forward_cos(const struct ggml_compute_params * params, struct ggml_tensor * dst);
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void ggml_compute_forward_log(const struct ggml_compute_params * params, struct ggml_tensor * dst);
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void ggml_compute_forward_floor(const struct ggml_compute_params * params, struct ggml_tensor * dst);
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void ggml_compute_forward_ceil(const struct ggml_compute_params * params, struct ggml_tensor * dst);
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void ggml_compute_forward_round(const struct ggml_compute_params * params, struct ggml_tensor * dst);
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void ggml_compute_forward_trunc(const struct ggml_compute_params * params, struct ggml_tensor * dst);
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void ggml_compute_forward_xielu(const struct ggml_compute_params * params, struct ggml_tensor * dst);
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#ifdef __cplusplus
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@@ -1144,9 +1144,13 @@ static const char * GGML_UNARY_OP_NAME[GGML_UNARY_OP_COUNT] = {
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"EXP",
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"GELU_ERF",
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"XIELU",
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"FLOOR",
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"CEIL",
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"ROUND",
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"TRUNC",
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};
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static_assert(GGML_UNARY_OP_COUNT == 16, "GGML_UNARY_OP_COUNT != 16");
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static_assert(GGML_UNARY_OP_COUNT == 20, "GGML_UNARY_OP_COUNT != 20");
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static const char * GGML_GLU_OP_NAME[GGML_GLU_OP_COUNT] = {
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"REGLU",
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@@ -2749,6 +2753,62 @@ static struct ggml_tensor * ggml_glu_impl(
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return result;
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}
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// ggml_floor
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struct ggml_tensor * ggml_floor(
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struct ggml_context * ctx,
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struct ggml_tensor * a) {
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return ggml_unary(ctx, a, GGML_UNARY_OP_FLOOR);
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}
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struct ggml_tensor * ggml_floor_inplace(
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struct ggml_context * ctx,
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struct ggml_tensor * a) {
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return ggml_unary_inplace(ctx, a, GGML_UNARY_OP_FLOOR);
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}
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// ggml_ceil
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struct ggml_tensor * ggml_ceil(
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struct ggml_context * ctx,
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struct ggml_tensor * a) {
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return ggml_unary(ctx, a, GGML_UNARY_OP_CEIL);
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}
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struct ggml_tensor * ggml_ceil_inplace(
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struct ggml_context * ctx,
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struct ggml_tensor * a) {
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return ggml_unary_inplace(ctx, a, GGML_UNARY_OP_CEIL);
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}
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//ggml_round
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struct ggml_tensor * ggml_round(
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struct ggml_context * ctx,
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struct ggml_tensor * a) {
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return ggml_unary(ctx, a, GGML_UNARY_OP_ROUND);
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}
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struct ggml_tensor * ggml_round_inplace(
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struct ggml_context * ctx,
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struct ggml_tensor * a) {
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return ggml_unary_inplace(ctx, a, GGML_UNARY_OP_ROUND);
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}
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//ggml_trunc
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struct ggml_tensor * ggml_trunc(
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struct ggml_context * ctx,
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struct ggml_tensor * a) {
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return ggml_unary(ctx, a, GGML_UNARY_OP_TRUNC);
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}
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struct ggml_tensor * ggml_trunc_inplace(
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struct ggml_context * ctx,
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struct ggml_tensor * a) {
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return ggml_unary_inplace(ctx, a, GGML_UNARY_OP_TRUNC);
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}
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struct ggml_tensor * ggml_glu(
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struct ggml_context * ctx,
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struct ggml_tensor * a,
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