float xpos_base,
bool xpos_down,
bool inplace) {
+ GGML_ASSERT((mode & 1) == 0 && "mode & 1 == 1 is no longer supported");
+
GGML_ASSERT(ggml_is_vector(b));
GGML_ASSERT(b->type == GGML_TYPE_I32);
GGML_ASSERT(a->ne[2] == b->ne[0]);
freq_factors = (const float *) src2->data;
}
} else {
- GGML_ASSERT(src2 == NULL && "TODO: freq_factors not implemented for mode 1");
+ GGML_ASSERT(src2 == NULL && "TODO: freq_factors not implemented for !is_neox");
}
// backward process uses inverse rotation by cos and sin.
}
}
+// TODO: deduplicate f16/f32 code
static void ggml_compute_forward_rope_f16(
const struct ggml_compute_params * params,
struct ggml_tensor * dst,
const struct ggml_tensor * src0 = dst->src[0];
const struct ggml_tensor * src1 = dst->src[1];
+ const struct ggml_tensor * src2 = dst->src[2];
if (params->type == GGML_TASK_TYPE_INIT || params->type == GGML_TASK_TYPE_FINALIZE) {
return;
const bool is_neox = mode & 2;
const bool is_glm = mode & 4;
+ const float * freq_factors = NULL;
+ if (is_neox) {
+ if (src2 != NULL) {
+ GGML_ASSERT(src2->type == GGML_TYPE_F32);
+ GGML_ASSERT(src2->ne[0] >= n_dims / 2);
+ freq_factors = (const float *) src2->data;
+ }
+ } else {
+ GGML_ASSERT(src2 == NULL && "TODO: freq_factors not implemented for !is_neox");
+ }
+
// backward process uses inverse rotation by cos and sin.
// cos and sin build a rotation matrix, where the inverse is the transpose.
// this essentially just switches the sign of sin.
// simplified from `(ib * n_dims + ic) * inv_ndims`
float cur_rot = inv_ndims * ic - ib;
+ float freq_factor = freq_factors ? freq_factors[ic/2] : 1.0f;
float cos_theta, sin_theta;
rope_yarn(
- theta_base, freq_scale, corr_dims, cur_rot, ext_factor, attn_factor,
+ theta_base/freq_factor, freq_scale, corr_dims, cur_rot, ext_factor, attn_factor,
&cos_theta, &sin_theta
);
sin_theta *= sin_sign;
int n_dims;
int mode;
int n_ctx;
+ bool ff;
std::string vars() override {
- return VARS_TO_STR5(type, ne, n_dims, mode, n_ctx);
+ return VARS_TO_STR6(type, ne, n_dims, mode, n_ctx, ff);
}
test_rope(ggml_type type = GGML_TYPE_F32,
std::array<int64_t, 4> ne = {10, 10, 10, 1},
- int n_dims = 10, int mode = 0, int n_ctx = 512)
- : type(type), ne(ne), n_dims(n_dims), mode(mode), n_ctx(n_ctx) {}
+ int n_dims = 10, int mode = 0, int n_ctx = 512, bool ff = false)
+ : type(type), ne(ne), n_dims(n_dims), mode(mode), n_ctx(n_ctx), ff(ff) {}
ggml_tensor * build_graph(ggml_context * ctx) override {
ggml_tensor * a = ggml_new_tensor(ctx, type, 4, ne.data());
ggml_tensor * pos = ggml_new_tensor_1d(ctx, GGML_TYPE_I32, ne[2]);
- ggml_tensor * out = ggml_rope(ctx, a, pos, n_dims, mode, n_ctx);
+ ggml_tensor * freq = ff ? ggml_new_tensor_1d(ctx, GGML_TYPE_F32, n_dims/2) : nullptr;
+ ggml_tensor * out = ggml_rope_ext(ctx, a, pos, freq, n_dims, mode, n_ctx, 0, 10000.0f, 1.0f, 0.0f, 1.0f, 0.0f, 0.0f);
return out;
}
}
ggml_backend_tensor_set(t, data.data(), 0, ne[2] * sizeof(int));
} else {
- init_tensor_uniform(t);
+ if (t->ne[0] == n_dims/2) {
+ // frequency factors in the range [0.9f, 1.1f]
+ init_tensor_uniform(t, 0.9f, 1.1f);
+ } else {
+ init_tensor_uniform(t);
+ }
}
}
}
test_cases.emplace_back(new test_soft_max(GGML_TYPE_F32, {32, 2, 32, 1}, true, 0.1f, 8.0f));
for (ggml_type type : {GGML_TYPE_F32, GGML_TYPE_F16}) {
- test_cases.emplace_back(new test_rope(type, {128, 32, 10, 1}, 128, 0, 512)); // llama 7B
- test_cases.emplace_back(new test_rope(type, {128, 40, 10, 1}, 128, 0, 512)); // llama 13B
- test_cases.emplace_back(new test_rope(type, {128, 52, 10, 1}, 128, 0, 512)); // llama 30B
- test_cases.emplace_back(new test_rope(type, {128, 64, 10, 1}, 128, 0, 512)); // llama 65B
- test_cases.emplace_back(new test_rope(type, { 64, 1, 10, 1}, 64, 2, 512)); // neox (falcon 7B)
- test_cases.emplace_back(new test_rope(type, { 64, 71, 10, 1}, 64, 2, 512)); // neox (falcon 7B)
- test_cases.emplace_back(new test_rope(type, { 64, 8, 10, 1}, 64, 2, 512)); // neox (falcon 40B)
- test_cases.emplace_back(new test_rope(type, { 64, 128, 10, 1}, 64, 2, 512)); // neox (falcon 40B)
- test_cases.emplace_back(new test_rope(type, { 80, 32, 10, 1}, 20, 2, 512)); // neox (stablelm)
- test_cases.emplace_back(new test_rope(type, { 80, 32, 10, 1}, 32, 2, 512)); // neox (phi-2)
+ // TODO: ff not supported yet for !neox
+ test_cases.emplace_back(new test_rope(type, {128, 32, 10, 1}, 128, 0, 512, false)); // llama 7B
+ test_cases.emplace_back(new test_rope(type, {128, 40, 10, 1}, 128, 0, 512, false)); // llama 13B
+ test_cases.emplace_back(new test_rope(type, {128, 52, 10, 1}, 128, 0, 512, false)); // llama 30B
+ test_cases.emplace_back(new test_rope(type, {128, 64, 10, 1}, 128, 0, 512, false)); // llama 65B
+
+ for (bool ff : {false, true}) { // freq_factors
+ test_cases.emplace_back(new test_rope(type, { 64, 1, 10, 1}, 64, 2, 512, ff)); // neox (falcon 7B)
+ test_cases.emplace_back(new test_rope(type, { 64, 71, 10, 1}, 64, 2, 512, ff)); // neox (falcon 7B)
+ test_cases.emplace_back(new test_rope(type, { 64, 8, 10, 1}, 64, 2, 512, ff)); // neox (falcon 40B)
+ test_cases.emplace_back(new test_rope(type, { 64, 128, 10, 1}, 64, 2, 512, ff)); // neox (falcon 40B)
+ test_cases.emplace_back(new test_rope(type, { 80, 32, 10, 1}, 20, 2, 512, ff)); // neox (stablelm)
+ test_cases.emplace_back(new test_rope(type, { 80, 32, 10, 1}, 32, 2, 512, ff)); // neox (phi-2)
+ }
}
test_cases.emplace_back(new test_concat(GGML_TYPE_F32));