fix backward pass for add_at and change arguments to have same order as in view
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xaedes
parent
226521a4f1
commit
48bcc4dcf9
3 changed files with 169 additions and 31 deletions
60
ggml.c
60
ggml.c
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@ -5058,10 +5058,10 @@ struct ggml_tensor * ggml_add_at_impl(
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struct ggml_context * ctx,
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struct ggml_tensor * a,
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struct ggml_tensor * b,
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size_t offset,
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size_t nb1,
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size_t nb2,
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size_t nb3,
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size_t offset,
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bool inplace) {
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GGML_ASSERT(ggml_nelements(b) <= ggml_nelements(a));
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GGML_ASSERT(ggml_is_contiguous(a));
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@ -5076,10 +5076,10 @@ struct ggml_tensor * ggml_add_at_impl(
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struct ggml_tensor * result = inplace ? ggml_view_tensor(ctx, a) : ggml_dup_tensor(ctx, a);
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struct ggml_tensor * c = ggml_new_tensor_1d(ctx, GGML_TYPE_I32, 5);
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((int32_t *) c->data)[0] = offset;
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((int32_t *) c->data)[1] = nb1;
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((int32_t *) c->data)[2] = nb2;
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((int32_t *) c->data)[3] = nb3;
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((int32_t *) c->data)[0] = nb1;
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((int32_t *) c->data)[1] = nb2;
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((int32_t *) c->data)[2] = nb3;
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((int32_t *) c->data)[3] = offset;
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((int32_t *) c->data)[4] = inplace ? 1 : 0;
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result->op = GGML_OP_ADD_AT;
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@ -5095,22 +5095,22 @@ struct ggml_tensor * ggml_add_at(
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struct ggml_context * ctx,
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struct ggml_tensor * a,
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struct ggml_tensor * b,
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size_t offset,
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size_t nb1,
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size_t nb2,
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size_t nb3) {
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return ggml_add_at_impl(ctx, a, b, offset, nb1, nb2, nb3, false);
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size_t nb3,
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size_t offset) {
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return ggml_add_at_impl(ctx, a, b, nb1, nb2, nb3, offset, false);
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}
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struct ggml_tensor * ggml_add_at_inplace(
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struct ggml_context * ctx,
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struct ggml_tensor * a,
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struct ggml_tensor * b,
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size_t offset,
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size_t nb1,
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size_t nb2,
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size_t nb3) {
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return ggml_add_at_impl(ctx, a, b, offset, nb1, nb2, nb3, true);
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size_t nb3,
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size_t offset) {
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return ggml_add_at_impl(ctx, a, b, nb1, nb2, nb3, offset, true);
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}
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// ggml_sub
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@ -8135,10 +8135,10 @@ static void ggml_compute_forward_add_at_f32(
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// view src0 and dst with these strides and data offset inbytes during add_at
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// nb0 is implicitely element_size because src0 and dst are contiguous
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size_t offset = ((int32_t *) opt0->data)[0];
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size_t nb1 = ((int32_t *) opt0->data)[1];
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size_t nb2 = ((int32_t *) opt0->data)[2];
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size_t nb3 = ((int32_t *) opt0->data)[3];
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size_t nb1 = ((int32_t *) opt0->data)[0];
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size_t nb2 = ((int32_t *) opt0->data)[1];
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size_t nb3 = ((int32_t *) opt0->data)[2];
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size_t offset = ((int32_t *) opt0->data)[3];
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bool inplace = (bool) ((int32_t *) opt0->data)[4];
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if (!inplace && (params->type == GGML_TASK_INIT)) {
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@ -13187,19 +13187,27 @@ static void ggml_compute_backward(struct ggml_context * ctx, struct ggml_tensor
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src0->grad = ggml_add_impl(ctx, src0->grad, tensor->grad, inplace);
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}
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if (src1->grad) {
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size_t offset;
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memcpy(&offset, tensor->padding, sizeof(size_t));
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GGML_ASSERT(ggml_nelements(tensor->opt[0]) == 5);
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GGML_ASSERT(tensor->opt[0]->type == GGML_TYPE_I32);
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const size_t nb1 = (( int32_t * ) tensor->opt[0]->data)[0];
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const size_t nb2 = (( int32_t * ) tensor->opt[0]->data)[1];
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const size_t nb3 = (( int32_t * ) tensor->opt[0]->data)[2];
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const size_t offset = (( int32_t * ) tensor->opt[0]->data)[3];
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struct ggml_tensor * tensor_grad_view = ggml_view_4d(ctx,
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tensor->grad,
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src1->grad->ne[0],
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src1->grad->ne[1],
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src1->grad->ne[2],
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src1->grad->ne[3],
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nb1, nb2, nb3, offset);
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src1->grad =
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ggml_add_impl(ctx,
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src1->grad,
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ggml_view_3d(ctx,
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tensor->grad,
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tensor->ne[0],
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tensor->ne[1],
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tensor->ne[2],
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tensor->nb[1],
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tensor->nb[2],
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offset),
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ggml_reshape(ctx,
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ggml_cont(ctx, tensor_grad_view),
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src1->grad),
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inplace);
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}
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} break;
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@ -13572,7 +13580,7 @@ static void ggml_compute_backward(struct ggml_context * ctx, struct ggml_tensor
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nb3 = (nb3 / n0) * ng;
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}
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src0->grad = ggml_add_at_impl(ctx, src0->grad, tensor->grad, offset, nb1, nb2, nb3, inplace);
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src0->grad = ggml_add_at_impl(ctx, src0->grad, tensor->grad, nb1, nb2, nb3, offset, inplace);
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}
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} break;
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case GGML_OP_PERMUTE:
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8
ggml.h
8
ggml.h
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@ -499,19 +499,19 @@ extern "C" {
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struct ggml_context * ctx,
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struct ggml_tensor * a,
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struct ggml_tensor * b,
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size_t offset,
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size_t nb1,
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size_t nb2,
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size_t nb3);
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size_t nb3,
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size_t offset);
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GGML_API struct ggml_tensor * ggml_add_at_inplace(
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struct ggml_context * ctx,
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struct ggml_tensor * a,
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struct ggml_tensor * b,
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size_t offset,
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size_t nb1,
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size_t nb2,
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size_t nb3);
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size_t nb3,
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size_t offset);
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GGML_API struct ggml_tensor * ggml_sub(
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struct ggml_context * ctx,
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@ -45,7 +45,8 @@ float frand() {
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}
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int irand(int n) {
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return rand()%n;
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if (n == 0) return 0;
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else return rand()%n;
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}
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void get_random_dims(int64_t * dims, int ndims) {
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@ -696,6 +697,135 @@ int main(int argc, const char ** argv) {
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}
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}
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// add_at 1d
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{
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int64_t ne2[4] = { 1, 1, 1, 1 };
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const int nargs = 2;
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for (int ndims = 1; ndims <= 4; ++ndims) {
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x[0] = get_random_tensor(ctx0, ndims, ne, -1.0f, 1.0f);
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ggml_set_param(ctx0, x[0]);
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get_random_dims(ne2, 1);
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while ((ne2[0] > ne[0]) || (ne2[0] > ggml_nelements(x[0]))) {
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get_random_dims(ne2, 1);
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}
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x[1] = get_random_tensor(ctx0, 1, ne2, -1.0f, 1.0f);
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ggml_set_param(ctx0, x[1]);
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const int max_offset = MAX(0, ggml_nelements(x[0]) - ggml_nelements(x[1]));
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const int offset = irand(max_offset) * ggml_element_size(x[0]);
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struct ggml_tensor * f = ggml_sum(ctx0, ggml_add_at(ctx0, x[0], x[1], x[0]->nb[1], x[0]->nb[2], x[0]->nb[3], offset));
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check_gradient("add_at 1d", ctx0, x, f, ndims, nargs, 1e-3f, 1e-3f, INFINITY);
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}
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}
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// add_at 2d
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{
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int64_t ne2[4] = { 1, 1, 1, 1 };
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int64_t max_offsets[4] = { 0, 0, 0, 0 };
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int64_t offsets[4] = { 0, 0, 0, 0 };
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const int nargs = 2;
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for (int ndims = 2; ndims <= 4; ++ndims) {
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x[0] = get_random_tensor(ctx0, ndims, ne, -1.0f, 1.0f);
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ggml_set_param(ctx0, x[0]);
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get_random_dims(ne2, 2);
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while ((ne2[0] > ne[0]) || (ne2[1] > ne[1]) || (ne2[0]*ne2[1] > ggml_nelements(x[0]))) {
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get_random_dims(ne2, 2);
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}
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x[1] = get_random_tensor(ctx0, 2, ne2, -1.0f, 1.0f);
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ggml_set_param(ctx0, x[1]);
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max_offsets[0] = MAX(0, x[0]->ne[0] - x[1]->ne[0]);
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max_offsets[1] = MAX(0, x[0]->ne[1] - x[1]->ne[1]);
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offsets[0] = irand(max_offsets[0]) * x[0]->nb[0];
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offsets[1] = irand(max_offsets[1]) * x[0]->nb[1];
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const int offset = offsets[0] + offsets[1];
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struct ggml_tensor * f = ggml_sum(ctx0, ggml_add_at(ctx0, x[0], x[1], x[0]->nb[1], x[0]->nb[2], x[0]->nb[3], offset));
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check_gradient("add_at 2d", ctx0, x, f, ndims, nargs, 1e-3f, 1e-3f, INFINITY);
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}
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}
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// add_at 3d
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{
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int64_t ne2[4] = { 1, 1, 1, 1 };
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int64_t max_offsets[4] = { 0, 0, 0, 0 };
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int64_t offsets[4] = { 0, 0, 0, 0 };
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const int nargs = 2;
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for (int ndims = 3; ndims <= 4; ++ndims) {
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x[0] = get_random_tensor(ctx0, ndims, ne, -1.0f, 1.0f);
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ggml_set_param(ctx0, x[0]);
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get_random_dims(ne2, 3);
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while ((ne2[0] > ne[0]) || (ne2[1] > ne[1]) || (ne2[2] > ne[2]) || (ne2[0]*ne2[1]*ne2[2] > ggml_nelements(x[0]))) {
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get_random_dims(ne2, 3);
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}
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x[1] = get_random_tensor(ctx0, 3, ne2, -1.0f, 1.0f);
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ggml_set_param(ctx0, x[1]);
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max_offsets[0] = MAX(0, x[0]->ne[0] - x[1]->ne[0]);
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max_offsets[1] = MAX(0, x[0]->ne[1] - x[1]->ne[1]);
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max_offsets[2] = MAX(0, x[0]->ne[2] - x[1]->ne[2]);
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offsets[0] = irand(max_offsets[0]) * x[0]->nb[0];
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offsets[1] = irand(max_offsets[1]) * x[0]->nb[1];
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offsets[2] = irand(max_offsets[2]) * x[0]->nb[2];
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const int offset = offsets[0] + offsets[1] + offsets[2];
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struct ggml_tensor * f = ggml_sum(ctx0, ggml_add_at(ctx0, x[0], x[1], x[0]->nb[1], x[0]->nb[2], x[0]->nb[3], offset));
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check_gradient("add_at 3d", ctx0, x, f, ndims, nargs, 1e-3f, 1e-3f, INFINITY);
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}
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}
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// add_at 4d
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{
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int64_t ne2[4] = { 1, 1, 1, 1 };
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int64_t max_offsets[4] = { 0, 0, 0, 0 };
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int64_t offsets[4] = { 0, 0, 0, 0 };
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const int nargs = 2;
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for (int ndims = 4; ndims <= 4; ++ndims) {
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x[0] = get_random_tensor(ctx0, ndims, ne, -1.0f, 1.0f);
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ggml_set_param(ctx0, x[0]);
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get_random_dims(ne2, 4);
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while ((ne2[0] > ne[0]) || (ne2[1] > ne[1]) || (ne2[2] > ne[2]) || (ne2[3] > ne[3]) || (ne2[0]*ne2[1]*ne2[2]*ne2[3] > ggml_nelements(x[0]))) {
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get_random_dims(ne2, 4);
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}
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x[1] = get_random_tensor(ctx0, 4, ne2, -1.0f, 1.0f);
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ggml_set_param(ctx0, x[1]);
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max_offsets[0] = MAX(0, x[0]->ne[0] - x[1]->ne[0]);
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max_offsets[1] = MAX(0, x[0]->ne[1] - x[1]->ne[1]);
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max_offsets[2] = MAX(0, x[0]->ne[2] - x[1]->ne[2]);
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max_offsets[3] = MAX(0, x[0]->ne[3] - x[1]->ne[3]);
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offsets[0] = irand(max_offsets[0]) * x[0]->nb[0];
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offsets[1] = irand(max_offsets[1]) * x[0]->nb[1];
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offsets[2] = irand(max_offsets[2]) * x[0]->nb[2];
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offsets[3] = irand(max_offsets[3]) * x[0]->nb[3];
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const int offset = offsets[0] + offsets[1] + offsets[2] + offsets[3];
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struct ggml_tensor * f = ggml_sum(ctx0, ggml_add_at(ctx0, x[0], x[1], x[0]->nb[1], x[0]->nb[2], x[0]->nb[3], offset));
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check_gradient("add_at 4d", ctx0, x, f, ndims, nargs, 1e-3f, 1e-3f, INFINITY);
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}
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}
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// view_1d
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{
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const int nargs = 1;
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