ggml : remove ggml_flash_attn and ggml_flash_ff (#7463)

ggml-ci

1 files changed, 43 insertions, 83 deletions

diff --git a/tests/test-grad0.cpp b/tests/test-grad0.cpp
index 8ff76c89..21ca43be 100644
--- a/tests/test-grad0.cpp
+++ b/tests/test-grad0.cpp
@@ -1515,90 +1515,50 @@ int main(int argc, const char ** argv) {
         }
 
         // flash_attn f32
-        {
-            srand(seed);
-            const int nargs = 3;
-
-            int64_t ne2[4];
-
-            get_random_dims(ne2, 4);
-            int64_t D = ne2[0];
-            int64_t N = ne2[1];
-            int64_t M = ne2[2] + N;
-            int64_t B = ne2[3];
-
-            for (int masked = 0; masked <= 1; ++masked) {
-                for (int ndims = 2; ndims <= 4; ++ndims) {
-                    int max_nrep = (ndims >= 3) ? 2 : 1;
-                    for (int nrep = 1; nrep < max_nrep; ++nrep) {
-                        int64_t neq[4] = { D, N, B*nrep, ne[3] };
-                        int64_t nek[4] = { D, M, B, ne[3] };
-                        int64_t nev[4] = { M, D, B, ne[3] };
-                        if (ndims == 2) {
-                            neq[2] = 1; neq[3] = 1;
-                            nek[2] = 1; nek[3] = 1;
-                            nev[2] = 1; nev[3] = 1;
-                        } else if (ndims == 3) {
-                            neq[3] = 1;
-                            nek[3] = 1;
-                            nev[3] = 1;
-                        }
-                        x[0] = get_random_tensor_f32(ctx0, ndims, neq, -0.1250f, 0.1250f);
-                        x[1] = get_random_tensor_f32(ctx0, ndims, nek, -0.1250f, 0.1250f);
-                        x[2] = get_random_tensor_f32(ctx0, ndims, nev, -0.1250f, 0.1250f);
-                        ggml_set_param(ctx0, x[0]);
-                        ggml_set_param(ctx0, x[1]);
-                        ggml_set_param(ctx0, x[2]);
-
-                        struct ggml_tensor * f = ggml_sum(ctx0, ggml_flash_attn(ctx0, x[0], x[1], x[2], (masked == 0)));
-
-                        check_gradient("flash_attn f32", ctx0, x, f, ndims, nargs, 1.5e-4f, 1e-3f, INFINITY);
-                    }
-                }
-            }
-        }
-
-        // flash_attn f16, not yet fully implemented
-        if(0)
-        {
-            srand(seed);
-            const int nargs = 3;
-
-            int64_t ne2[4];
-
-            get_random_dims(ne2, 4);
-            int64_t D = ne2[0];
-            int64_t N = ne2[1];
-            int64_t M = ne2[2] + N;
-            int64_t B = ne2[3];
-
-            for (int masked = 0; masked <= 1; ++masked) {
-                for (int ndims = 2; ndims <= 4; ++ndims) {
-                    int64_t neq[4] = { D, N, B, ne[3] };
-                    int64_t nek[4] = { D, M, B, ne[3] };
-                    int64_t nev[4] = { M, D, B, ne[3] };
-                    if (ndims == 2) {
-                        neq[2] = 1; neq[3] = 1;
-                        nek[2] = 1; nek[3] = 1;
-                        nev[2] = 1; nev[3] = 1;
-                    } else if (ndims == 3) {
-                        neq[3] = 1;
-                        nek[3] = 1;
-                        nev[3] = 1;
-                    }
-                    x[0] = get_random_tensor_f16(ctx0, ndims, neq, -0.1250f, 0.1250f);
-                    x[1] = get_random_tensor_f16(ctx0, ndims, nek, -0.1250f, 0.1250f);
-                    x[2] = get_random_tensor_f16(ctx0, ndims, nev, -0.1250f, 0.1250f);
-                    ggml_set_param(ctx0, x[0]);
-                    ggml_set_param(ctx0, x[1]);
-                    ggml_set_param(ctx0, x[2]);
-
-                    struct ggml_tensor * f = ggml_sum(ctx0, ggml_flash_attn(ctx0, x[0], x[1], x[2], (masked == 0)));
+        // TODO: adapt to ggml_flash_attn_ext() changes
+        //{
+        //    srand(seed);
+        //    const int nargs = 3;
+
+        //    int64_t ne2[4];
+
+        //    get_random_dims(ne2, 4);
+        //    int64_t D = ne2[0];
+        //    int64_t N = ne2[1];
+        //    int64_t M = ne2[2] + N;
+        //    int64_t B = ne2[3];
+
+        //    for (int masked = 0; masked <= 1; ++masked) {
+        //        for (int ndims = 2; ndims <= 4; ++ndims) {
+        //            int max_nrep = (ndims >= 3) ? 2 : 1;
+        //            for (int nrep = 1; nrep < max_nrep; ++nrep) {
+        //                int64_t neq[4] = { D, N, B*nrep, ne[3] };
+        //                int64_t nek[4] = { D, M, B, ne[3] };
+        //                int64_t nev[4] = { M, D, B, ne[3] };
+        //                if (ndims == 2) {
+        //                    neq[2] = 1; neq[3] = 1;
+        //                    nek[2] = 1; nek[3] = 1;
+        //                    nev[2] = 1; nev[3] = 1;
+        //                } else if (ndims == 3) {
+        //                    neq[3] = 1;
+        //                    nek[3] = 1;
+        //                    nev[3] = 1;
+        //                }
+        //                x[0] = get_random_tensor_f32(ctx0, ndims, neq, -0.1250f, 0.1250f);
+        //                x[1] = get_random_tensor_f32(ctx0, ndims, nek, -0.1250f, 0.1250f);
+        //                x[2] = get_random_tensor_f32(ctx0, ndims, nev, -0.1250f, 0.1250f);
+        //                ggml_set_param(ctx0, x[0]);
+        //                ggml_set_param(ctx0, x[1]);
+        //                ggml_set_param(ctx0, x[2]);
+
+        //                struct ggml_tensor * f = ggml_sum(ctx0, ggml_flash_attn(ctx0, x[0], x[1], x[2], (masked == 0)));
+
+        //                check_gradient("flash_attn f32", ctx0, x, f, ndims, nargs, 1.5e-4f, 1e-3f, INFINITY);
+        //            }
+        //        }
+        //    }
+        //}
 
-                    check_gradient("flash_attn f16", ctx0, x, f, ndims, nargs, 1.5e-4f, 1e-3f, INFINITY);
-                }
-            }
-        }
         ggml_free(ctx0);
     }