"ROPE_BACK",
"ALIBI",
"CLAMP",
- "CONV_1D_1S",
- "CONV_1D_2S",
+ "CONV_1D_S1_PH",
+ "CONV_1D_S2_PH",
"FLASH_ATTN",
"FLASH_FF",
const int64_t ne[4] = { b->ne[0], a->ne[2], 1, 1, };
struct ggml_tensor * result = ggml_new_tensor(ctx, GGML_TYPE_F32, 2, ne);
- result->op = GGML_OP_CONV_1D_1S;
+ result->op = GGML_OP_CONV_1D_S1_PH;
result->grad = is_node ? ggml_dup_tensor(ctx, result) : NULL;
result->src0 = a;
result->src1 = b;
const int64_t ne[4] = { b->ne[0]/2, a->ne[2], 1, 1, };
struct ggml_tensor * result = ggml_new_tensor(ctx, GGML_TYPE_F32, 2, ne);
- result->op = GGML_OP_CONV_1D_2S;
+ result->op = GGML_OP_CONV_1D_S2_PH;
result->grad = is_node ? ggml_dup_tensor(ctx, result) : NULL;
result->src0 = a;
result->src1 = b;
{
ggml_compute_forward_clamp(params, tensor->src0, tensor->src1, tensor);
} break;
- case GGML_OP_CONV_1D_1S:
+ case GGML_OP_CONV_1D_S1_PH:
{
ggml_compute_forward_conv_1d_s1_ph(params, tensor->src0, tensor->src1, tensor);
} break;
- case GGML_OP_CONV_1D_2S:
+ case GGML_OP_CONV_1D_S2_PH:
{
ggml_compute_forward_conv_1d_s2_ph(params, tensor->src0, tensor->src1, tensor);
} break;
// noop
}
} break;
- case GGML_OP_CONV_1D_1S:
+ case GGML_OP_CONV_1D_S1_PH:
{
GGML_ASSERT(false); // TODO: not implemented
} break;
- case GGML_OP_CONV_1D_2S:
+ case GGML_OP_CONV_1D_S2_PH:
{
GGML_ASSERT(false); // TODO: not implemented
} break;
{
node->n_tasks = 1; //TODO
} break;
- case GGML_OP_CONV_1D_1S:
- case GGML_OP_CONV_1D_2S:
+ case GGML_OP_CONV_1D_S1_PH:
+ case GGML_OP_CONV_1D_S2_PH:
{
node->n_tasks = n_threads;