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RoPE: fix back, CUDA support for back + noncont. #11240

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merged 2 commits into from
Jan 15, 2025
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RoPE: fix back, CUDA support for back + noncont. #11240

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aee5ac4
RoPE: fix back, CUDA support for back + noncont.
JohannesGaessler Jan 13, 2025
c87818e
fix comments reg. non-cont. RoPE support [no-ci]
JohannesGaessler Jan 15, 2025
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19 changes: 18 additions & 1 deletion ggml/include/ggml.h
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Original file line number Diff line number Diff line change
Expand Up @@ -1500,7 +1500,7 @@ extern "C" {

// rotary position embedding backward, i.e compute dx from dy
// a - dy
GGML_API struct ggml_tensor * ggml_rope_back(
GGML_API struct ggml_tensor * ggml_rope_ext_back(
struct ggml_context * ctx,
struct ggml_tensor * a, // gradients of ggml_rope result
struct ggml_tensor * b, // positions
Expand All @@ -1515,6 +1515,23 @@ extern "C" {
float beta_fast,
float beta_slow);

GGML_API struct ggml_tensor * ggml_rope_multi_back(
struct ggml_context * ctx,
struct ggml_tensor * a,
struct ggml_tensor * b,
struct ggml_tensor * c,
int n_dims,
int sections[4],
int mode,
int n_ctx_orig,
float freq_base,
float freq_scale,
float ext_factor,
float attn_factor,
float beta_fast,
float beta_slow);


// clamp
// in-place, returns view(a)
GGML_API struct ggml_tensor * ggml_clamp(
Expand Down
1 change: 1 addition & 0 deletions ggml/src/ggml-cpu/ggml-cpu.c
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Expand Up @@ -13668,6 +13668,7 @@ struct ggml_cplan ggml_graph_plan(
} break;
case GGML_OP_SOFT_MAX:
case GGML_OP_ROPE:
case GGML_OP_ROPE_BACK:
{
cur = ggml_type_size(GGML_TYPE_F32) * node->ne[0] * n_tasks;
} break;
Expand Down
2 changes: 0 additions & 2 deletions ggml/src/ggml-cpu/ggml-cpu.cpp
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Expand Up @@ -403,8 +403,6 @@ static bool ggml_backend_cpu_device_supports_op(ggml_backend_dev_t dev, const st
op->type != GGML_TYPE_IQ1_M; // missing type_traits.from_float
case GGML_OP_MUL_MAT:
return src1->type == GGML_TYPE_F32 || src1->type == ggml_get_type_traits_cpu(src0->type)->vec_dot_type;
case GGML_OP_ROPE_BACK:
return op->src[2] == NULL && (op->op_params[2] & 4) == 0;
case GGML_OP_IM2COL_BACK:
return src0->type == GGML_TYPE_F32 && src1->type == GGML_TYPE_F32;
case GGML_OP_OUT_PROD:
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10 changes: 9 additions & 1 deletion ggml/src/ggml-cuda/ggml-cuda.cu
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Expand Up @@ -2141,6 +2141,9 @@ static bool ggml_cuda_compute_forward(ggml_backend_cuda_context & ctx, struct gg
case GGML_OP_ROPE:
ggml_cuda_op_rope(ctx, dst);
break;
case GGML_OP_ROPE_BACK:
ggml_cuda_op_rope_back(ctx, dst);
break;
case GGML_OP_IM2COL:
ggml_cuda_op_im2col(ctx, dst);
break;
Expand Down Expand Up @@ -3025,7 +3028,11 @@ static bool ggml_backend_cuda_device_supports_op(ggml_backend_dev_t dev, const g
case GGML_OP_SOFT_MAX:
return true;
case GGML_OP_ROPE:
return ggml_is_contiguous(op->src[0]);
case GGML_OP_ROPE_BACK: {
const size_t ts = ggml_type_size(op->src[0]->type);
const int64_t ne0_012 = op->src[0]->ne[0] * op->src[0]->ne[1] * op->src[0]->ne[2];
return op->src[0]->nb[0] == ts && op->src[0]->nb[3] == ne0_012*ts;
}
case GGML_OP_IM2COL:
case GGML_OP_POOL_2D:
case GGML_OP_SUM:
Expand Down Expand Up @@ -3081,6 +3088,7 @@ static int64_t get_op_batch_size(const ggml_tensor * op) {
return op->ne[1];
case GGML_OP_MUL_MAT_ID:
case GGML_OP_ROPE:
case GGML_OP_ROPE_BACK:
return op->ne[2];
default:
return ggml_nrows(op);
Expand Down
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