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6875369909
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2 changed files with 7 additions and 17 deletions
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@ -2209,7 +2209,7 @@ static bool ggml_cuda_compute_forward(ggml_backend_cuda_context & ctx, struct gg
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cudaError_t err = cudaGetLastError();
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if (err != cudaSuccess) {
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fprintf(stderr, "%s: %s failed\n", __func__, ggml_op_desc(dst));
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GGML_ASSERT(false);
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CUDA_CHECK(err);
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}
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return true;
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22
ggml.c
22
ggml.c
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@ -4573,6 +4573,8 @@ void ggml_mul_mat_set_prec(
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// ggml_mul_mat_id
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// NOTE: id will be removed in the future and instead all the experts listed in ids will be computed
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// this will allow computing all the used experts in a single matrix multiplication
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struct ggml_tensor * ggml_mul_mat_id(
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struct ggml_context * ctx,
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struct ggml_tensor * as,
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@ -4581,12 +4583,11 @@ struct ggml_tensor * ggml_mul_mat_id(
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struct ggml_tensor * b) {
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GGML_ASSERT(ids->type == GGML_TYPE_I32);
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GGML_ASSERT(ids->ne[2] == 1 && ids->ne[3] == 1);
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GGML_ASSERT(ids->ne[1] == b->ne[1]);
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GGML_ASSERT(ids->ne[2] == 1 && ids->ne[3] == 1); // ids is 2d
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GGML_ASSERT(ids->ne[1] == b->ne[1]); // must have an expert per b row
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GGML_ASSERT(ids->ne[2] == b->ne[2] && ids->ne[3] == b->ne[3]);
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//GGML_ASSERT(n_as > 0 && n_as <= GGML_MAX_SRC - 2);
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GGML_ASSERT(id >= 0 && id < ids->ne[0]);
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// TODO: restore checks
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GGML_ASSERT(id >= 0 && id < ids->ne[0]); // valid id
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GGML_ASSERT(as->ne[0] == b->ne[0]); // can_mul_mat
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bool is_node = false;
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@ -4605,14 +4606,6 @@ struct ggml_tensor * ggml_mul_mat_id(
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result->src[1] = b;
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result->src[2] = ids;
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//for (int i = 0; i < n_as; i++) {
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// struct ggml_tensor * a = as[i];
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// GGML_ASSERT(ggml_are_same_shape(as[0], a));
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// GGML_ASSERT(ggml_can_mul_mat(a, b));
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// GGML_ASSERT(!ggml_is_transposed(a));
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// result->src[i + 2] = a;
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//}
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return result;
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}
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@ -10980,9 +10973,6 @@ static void ggml_compute_forward_mul_mat_id(
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GGML_ASSERT(nb1 <= nb2);
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GGML_ASSERT(nb2 <= nb3);
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// broadcast factors
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//const int64_t r2 = ne12/ne02;
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//const int64_t r3 = ne13/ne03;
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// broadcast is not supported with mmid
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assert(ne12 == 1);
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assert(ne13 == 1);
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