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https://github.com/ggerganov/llama.cpp.git
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ggml : add support for ChatGLM RoPE
This commit is contained in:
Georgi Gerganov
parent
d38e451578
commit
d9779021bd
82
ggml.c
82
ggml.c
@ -6778,6 +6778,7 @@ struct ggml_tensor * ggml_rope_impl(
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int n_past,
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int n_dims,
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int mode,
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int n_ctx,
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bool inplace) {
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GGML_ASSERT(n_past >= 0);
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bool is_node = false;
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@ -6790,11 +6791,12 @@ struct ggml_tensor * ggml_rope_impl(
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ggml_scratch_save(ctx);
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struct ggml_tensor * b = ggml_new_tensor_1d(ctx, GGML_TYPE_I32, 3);
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struct ggml_tensor * b = ggml_new_tensor_1d(ctx, GGML_TYPE_I32, 4);
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((int32_t *) b->data)[0] = n_past;
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((int32_t *) b->data)[1] = n_dims;
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((int32_t *) b->data)[2] = mode;
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((int32_t *) b->data)[3] = n_ctx;
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ggml_scratch_load(ctx);
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@ -6811,8 +6813,9 @@ struct ggml_tensor * ggml_rope(
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struct ggml_tensor * a,
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int n_past,
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int n_dims,
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int mode) {
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return ggml_rope_impl(ctx, a, n_past, n_dims, mode, false);
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int mode,
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int n_ctx) {
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return ggml_rope_impl(ctx, a, n_past, n_dims, mode, n_ctx, false);
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}
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struct ggml_tensor * ggml_rope_inplace(
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@ -6820,8 +6823,9 @@ struct ggml_tensor * ggml_rope_inplace(
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struct ggml_tensor * a,
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int n_past,
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int n_dims,
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int mode) {
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return ggml_rope_impl(ctx, a, n_past, n_dims, mode, true);
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int mode,
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int n_ctx) {
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return ggml_rope_impl(ctx, a, n_past, n_dims, mode, n_ctx, true);
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}
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// ggml_rope_back
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@ -12440,7 +12444,7 @@ static void ggml_compute_forward_rope_f32(
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const struct ggml_tensor * src1,
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struct ggml_tensor * dst) {
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GGML_ASSERT(src1->type == GGML_TYPE_I32);
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GGML_ASSERT(ggml_nelements(src1) == 3);
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GGML_ASSERT(ggml_nelements(src1) == 4);
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if (params->type == GGML_TASK_INIT || params->type == GGML_TASK_FINALIZE) {
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return;
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@ -12449,6 +12453,7 @@ static void ggml_compute_forward_rope_f32(
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const int n_past = ((int32_t *) src1->data)[0];
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const int n_dims = ((int32_t *) src1->data)[1];
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const int mode = ((int32_t *) src1->data)[2];
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const int n_ctx = ((int32_t *) src1->data)[3];
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assert(n_past >= 0);
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@ -12493,6 +12498,7 @@ static void ggml_compute_forward_rope_f32(
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const float theta_scale = powf(10000.0, -2.0f/n_dims);
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const bool is_neox = mode & 2;
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const bool is_glm = mode & 4;
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for (int64_t i3 = 0; i3 < ne3; i3++) {
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for (int64_t i2 = ((mode & 1) == 0 ? 0 : n_past); i2 < ne2; i2++) {
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@ -12503,7 +12509,32 @@ static void ggml_compute_forward_rope_f32(
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float theta = (float)p;
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if (!is_neox) {
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if (is_glm) {
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theta = MIN(p, n_ctx - 2);
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float block_theta = MAX(p - (n_ctx - 2), 0);
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for (int64_t i0 = 0; i0 < ne0 / 4; i0++) {
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const float cos_theta = cosf(theta);
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const float sin_theta = sinf(theta);
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const float cos_block_theta = cosf(block_theta);
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const float sin_block_theta = sinf(block_theta);
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theta *= theta_scale;
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block_theta *= theta_scale;
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const float * const src = (float *)((char *) src0->data + i3*nb03 + i2*nb02 + i1*nb01 + i0*nb00);
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float * dst_data = (float *)((char *) dst->data + i3*nb3 + i2*nb2 + i1*nb1 + i0*nb0);
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const float x0 = src[0];
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const float x1 = src[n_dims/2];
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const float x2 = src[n_dims];
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const float x3 = src[n_dims/2*3];
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dst_data[0] = x0*cos_theta - x1*sin_theta;
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dst_data[n_dims/2] = x0*sin_theta + x1*cos_theta;
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dst_data[n_dims] = x2*cos_block_theta - x3*sin_block_theta;
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dst_data[n_dims/2*3] = x2*sin_block_theta + x3*cos_block_theta;
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}
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} else if (!is_neox) {
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for (int64_t i0 = 0; i0 < ne0; i0 += 2) {
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const float cos_theta = cosf(theta);
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const float sin_theta = sinf(theta);
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@ -12553,7 +12584,7 @@ static void ggml_compute_forward_rope_f16(
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const struct ggml_tensor * src1,
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struct ggml_tensor * dst) {
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GGML_ASSERT(src1->type == GGML_TYPE_I32);
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GGML_ASSERT(ggml_nelements(src1) == 3);
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GGML_ASSERT(ggml_nelements(src1) == 4);
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if (params->type == GGML_TASK_INIT || params->type == GGML_TASK_FINALIZE) {
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return;
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@ -12562,6 +12593,7 @@ static void ggml_compute_forward_rope_f16(
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const int n_past = ((int32_t *) src1->data)[0];
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const int n_dims = ((int32_t *) src1->data)[1];
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const int mode = ((int32_t *) src1->data)[2];
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const int n_ctx = ((int32_t *) src1->data)[3];
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assert(n_past >= 0);
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@ -12606,6 +12638,7 @@ static void ggml_compute_forward_rope_f16(
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const float theta_scale = powf(10000.0, -2.0f/n_dims);
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const bool is_neox = mode & 2;
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const bool is_glm = mode & 4;
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for (int64_t i3 = 0; i3 < ne3; i3++) {
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for (int64_t i2 = ((mode & 1) == 0 ? 0 : n_past); i2 < ne2; i2++) {
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@ -12616,7 +12649,32 @@ static void ggml_compute_forward_rope_f16(
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float theta = (float)p;
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if (!is_neox) {
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if (is_glm) {
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theta = MIN(p, n_ctx - 2);
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float block_theta = MAX(p - (n_ctx - 2), 0);
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for (int64_t i0 = 0; i0 < ne0 / 4; i0++) {
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const float cos_theta = cosf(theta);
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const float sin_theta = sinf(theta);
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const float cos_block_theta = cosf(block_theta);
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const float sin_block_theta = sinf(block_theta);
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theta *= theta_scale;
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block_theta *= theta_scale;
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const ggml_fp16_t * const src = (ggml_fp16_t *)((char *) src0->data + i3*nb03 + i2*nb02 + i1*nb01 + i0*nb00);
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ggml_fp16_t * dst_data = (ggml_fp16_t *)((char *) dst->data + i3*nb3 + i2*nb2 + i1*nb1 + i0*nb0);
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const float x0 = GGML_FP16_TO_FP32(src[0]);
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const float x1 = GGML_FP16_TO_FP32(src[n_dims/2]);
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const float x2 = GGML_FP16_TO_FP32(src[n_dims]);
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const float x3 = GGML_FP16_TO_FP32(src[n_dims/2*3]);
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dst_data[0] = GGML_FP32_TO_FP16(x0*cos_theta - x1*sin_theta);
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dst_data[n_dims/2] = GGML_FP32_TO_FP16(x0*sin_theta + x1*cos_theta);
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dst_data[n_dims] = GGML_FP32_TO_FP16(x2*cos_block_theta - x3*sin_block_theta);
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dst_data[n_dims/2*3] = GGML_FP32_TO_FP16(x2*sin_block_theta + x3*cos_block_theta);
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}
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} if (!is_neox) {
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for (int64_t i0 = 0; i0 < ne0; i0 += 2) {
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const float cos_theta = cosf(theta);
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const float sin_theta = sinf(theta);
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@ -16189,17 +16247,19 @@ static void ggml_compute_backward(struct ggml_context * ctx, struct ggml_tensor
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{
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if (src0->grad) {
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assert(src1->type == GGML_TYPE_I32);
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assert(ggml_nelements(src1) == 3);
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assert(ggml_nelements(src1) == 4);
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const int n_past = ((int32_t *) src1->data)[0];
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const int n_dims = ((int32_t *) src1->data)[1];
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const int mode = ((int32_t *) src1->data)[2];
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const int n_ctx = ((int32_t *) src1->data)[3];
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src0->grad = ggml_add_impl(ctx,
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src0->grad,
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ggml_rope(ctx,
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tensor->grad,
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n_past,
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n_dims,
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mode),
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mode,
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n_ctx),
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inplace);
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}
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if (src1->grad) {
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7
ggml.h
7
ggml.h
@ -1036,13 +1036,15 @@ extern "C" {
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// rotary position embedding
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// if mode & 1 == 1, skip n_past elements
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// if mode & 2 == 1, GPT-NeoX style
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// if mode & 4 == 1, ChatGLM style
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// TODO: avoid creating a new tensor every time
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GGML_API struct ggml_tensor * ggml_rope(
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struct ggml_context * ctx,
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struct ggml_tensor * a,
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int n_past,
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int n_dims,
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int mode);
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int mode,
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int n_ctx);
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// in-place, returns view(a)
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GGML_API struct ggml_tensor * ggml_rope_inplace(
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@ -1050,7 +1052,8 @@ extern "C" {
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struct ggml_tensor * a,
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int n_past,
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int n_dims,
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int mode);
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int mode,
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int n_ctx);
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// rotary position embedding backward, i.e compute dx from dy
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// a - dy
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