mirror of
https://github.com/LostRuins/koboldcpp.git
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Merge branch 'upstream' into concedo_experimental
# Conflicts: # .github/workflows/docker.yml # README.md # build-xcframework.sh # examples/llava/CMakeLists.txt # examples/llava/clip.cpp # examples/rpc/rpc-server.cpp # examples/run/run.cpp # ggml/src/ggml-cann/ggml-cann.cpp # scripts/sync-ggml-am.sh # scripts/sync-ggml.last # tests/test-backend-ops.cpp # tests/test-chat.cpp
This commit is contained in:
Concedo
commit
a0ae187563
33 changed files with 2247 additions and 1202 deletions
278
ggml/src/ggml.c
278
ggml/src/ggml.c
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@ -995,23 +995,18 @@ static const char * GGML_OP_NAME[GGML_OP_COUNT] = {
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"UNARY",
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"MAP_UNARY",
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"MAP_BINARY",
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"MAP_CUSTOM1_F32",
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"MAP_CUSTOM2_F32",
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"MAP_CUSTOM3_F32",
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"MAP_CUSTOM1",
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"MAP_CUSTOM2",
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"MAP_CUSTOM3",
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"CUSTOM",
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"CROSS_ENTROPY_LOSS",
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"CROSS_ENTROPY_LOSS_BACK",
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"OPT_STEP_ADAMW",
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};
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static_assert(GGML_OP_COUNT == 85, "GGML_OP_COUNT != 85");
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static_assert(GGML_OP_COUNT == 81, "GGML_OP_COUNT != 81");
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static const char * GGML_OP_SYMBOL[GGML_OP_COUNT] = {
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"none",
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@ -1094,23 +1089,18 @@ static const char * GGML_OP_SYMBOL[GGML_OP_COUNT] = {
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"unary(x)",
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"f(x)",
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"f(x,y)",
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"custom_f32(x)",
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"custom_f32(x,y)",
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"custom_f32(x,y,z)",
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"map_custom(x)",
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"map_custom(x,y)",
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"map_custom(x,y,z)",
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"custom(x)",
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"custom(x,y)",
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"custom(x,y,z)",
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"cross_entropy_loss(x,y)",
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"cross_entropy_loss_back(x,y)",
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"adamw(x)",
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};
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static_assert(GGML_OP_COUNT == 85, "GGML_OP_COUNT != 85");
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static_assert(GGML_OP_COUNT == 81, "GGML_OP_COUNT != 81");
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static_assert(GGML_OP_POOL_COUNT == 2, "GGML_OP_POOL_COUNT != 2");
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@ -4197,7 +4187,8 @@ static struct ggml_tensor * ggml_upscale_impl(
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int ne0,
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int ne1,
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int ne2,
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int ne3) {
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int ne3,
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enum ggml_scale_mode mode) {
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GGML_ASSERT(a->ne[0] <= ne0);
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GGML_ASSERT(a->ne[1] <= ne1);
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GGML_ASSERT(a->ne[2] <= ne2);
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@ -4205,6 +4196,8 @@ static struct ggml_tensor * ggml_upscale_impl(
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struct ggml_tensor * result = ggml_new_tensor_4d(ctx, a->type, ne0, ne1, ne2, ne3);
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ggml_set_op_params_i32(result, 0, mode);
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result->op = GGML_OP_UPSCALE;
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result->src[0] = a;
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@ -4214,8 +4207,9 @@ static struct ggml_tensor * ggml_upscale_impl(
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struct ggml_tensor * ggml_upscale(
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struct ggml_context * ctx,
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struct ggml_tensor * a,
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int scale_factor) {
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return ggml_upscale_impl(ctx, a, a->ne[0] * scale_factor, a->ne[1] * scale_factor, a->ne[2], a->ne[3]);
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int scale_factor,
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enum ggml_scale_mode mode) {
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return ggml_upscale_impl(ctx, a, a->ne[0] * scale_factor, a->ne[1] * scale_factor, a->ne[2], a->ne[3], mode);
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}
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struct ggml_tensor * ggml_upscale_ext(
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@ -4224,8 +4218,9 @@ struct ggml_tensor * ggml_upscale_ext(
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int ne0,
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int ne1,
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int ne2,
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int ne3) {
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return ggml_upscale_impl(ctx, a, ne0, ne1, ne2, ne3);
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int ne3,
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enum ggml_scale_mode mode) {
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return ggml_upscale_impl(ctx, a, ne0, ne1, ne2, ne3, mode);
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}
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// ggml_pad
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@ -4855,179 +4850,6 @@ struct ggml_tensor * ggml_unary_inplace(
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return ggml_unary_impl(ctx, a, op, true);
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}
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// ggml_map_unary
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static struct ggml_tensor * ggml_map_unary_impl_f32(
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struct ggml_context * ctx,
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struct ggml_tensor * a,
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const ggml_unary_op_f32_t fun,
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bool inplace) {
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struct ggml_tensor * result = inplace ? ggml_view_tensor(ctx, a) : ggml_dup_tensor(ctx, a);
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ggml_set_op_params(result, (const void *) &fun, sizeof(fun));
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result->op = GGML_OP_MAP_UNARY;
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result->src[0] = a;
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return result;
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}
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struct ggml_tensor * ggml_map_unary_f32(
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struct ggml_context * ctx,
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struct ggml_tensor * a,
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const ggml_unary_op_f32_t fun) {
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return ggml_map_unary_impl_f32(ctx, a, fun, false);
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}
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struct ggml_tensor * ggml_map_unary_inplace_f32(
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struct ggml_context * ctx,
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struct ggml_tensor * a,
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const ggml_unary_op_f32_t fun) {
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return ggml_map_unary_impl_f32(ctx, a, fun, true);
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}
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// ggml_map_binary
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static struct ggml_tensor * ggml_map_binary_impl_f32(
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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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const ggml_binary_op_f32_t fun,
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bool inplace) {
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GGML_ASSERT(ggml_are_same_shape(a, b));
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struct ggml_tensor * result = inplace ? ggml_view_tensor(ctx, a) : ggml_dup_tensor(ctx, a);
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ggml_set_op_params(result, (const void *) &fun, sizeof(fun));
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result->op = GGML_OP_MAP_BINARY;
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result->src[0] = a;
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result->src[1] = b;
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return result;
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}
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struct ggml_tensor * ggml_map_binary_f32(
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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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const ggml_binary_op_f32_t fun) {
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return ggml_map_binary_impl_f32(ctx, a, b, fun, false);
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}
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struct ggml_tensor * ggml_map_binary_inplace_f32(
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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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const ggml_binary_op_f32_t fun) {
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return ggml_map_binary_impl_f32(ctx, a, b, fun, true);
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}
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// ggml_map_custom1_f32
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static struct ggml_tensor * ggml_map_custom1_impl_f32(
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struct ggml_context * ctx,
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struct ggml_tensor * a,
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const ggml_custom1_op_f32_t fun,
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bool inplace) {
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struct ggml_tensor * result = inplace ? ggml_view_tensor(ctx, a) : ggml_dup_tensor(ctx, a);
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ggml_set_op_params(result, (const void *) &fun, sizeof(fun));
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result->op = GGML_OP_MAP_CUSTOM1_F32;
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result->src[0] = a;
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return result;
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}
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struct ggml_tensor * ggml_map_custom1_f32(
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struct ggml_context * ctx,
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struct ggml_tensor * a,
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const ggml_custom1_op_f32_t fun) {
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return ggml_map_custom1_impl_f32(ctx, a, fun, false);
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}
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struct ggml_tensor * ggml_map_custom1_inplace_f32(
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struct ggml_context * ctx,
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struct ggml_tensor * a,
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const ggml_custom1_op_f32_t fun) {
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return ggml_map_custom1_impl_f32(ctx, a, fun, true);
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}
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// ggml_map_custom2_f32
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static struct ggml_tensor * ggml_map_custom2_impl_f32(
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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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const ggml_custom2_op_f32_t fun,
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bool inplace) {
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struct ggml_tensor * result = inplace ? ggml_view_tensor(ctx, a) : ggml_dup_tensor(ctx, a);
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ggml_set_op_params(result, (const void *) &fun, sizeof(fun));
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result->op = GGML_OP_MAP_CUSTOM2_F32;
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result->src[0] = a;
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result->src[1] = b;
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return result;
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}
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struct ggml_tensor * ggml_map_custom2_f32(
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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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const ggml_custom2_op_f32_t fun) {
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return ggml_map_custom2_impl_f32(ctx, a, b, fun, false);
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}
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struct ggml_tensor * ggml_map_custom2_inplace_f32(
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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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const ggml_custom2_op_f32_t fun) {
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return ggml_map_custom2_impl_f32(ctx, a, b, fun, true);
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}
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// ggml_map_custom3_f32
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static struct ggml_tensor * ggml_map_custom3_impl_f32(
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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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struct ggml_tensor * c,
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const ggml_custom3_op_f32_t fun,
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bool inplace) {
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struct ggml_tensor * result = inplace ? ggml_view_tensor(ctx, a) : ggml_dup_tensor(ctx, a);
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ggml_set_op_params(result, (const void *) &fun, sizeof(fun));
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result->op = GGML_OP_MAP_CUSTOM3_F32;
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result->src[0] = a;
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result->src[1] = b;
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result->src[2] = c;
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return result;
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}
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struct ggml_tensor * ggml_map_custom3_f32(
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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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struct ggml_tensor * c,
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const ggml_custom3_op_f32_t fun) {
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return ggml_map_custom3_impl_f32(ctx, a, b, c, fun, false);
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}
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struct ggml_tensor * ggml_map_custom3_inplace_f32(
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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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struct ggml_tensor * c,
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const ggml_custom3_op_f32_t fun) {
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return ggml_map_custom3_impl_f32(ctx, a, b, c, fun, true);
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}
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// ggml_map_custom1
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static struct ggml_tensor * ggml_map_custom1_impl(
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@ -5046,7 +4868,7 @@ static struct ggml_tensor * ggml_map_custom1_impl(
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/*.n_tasks =*/ n_tasks,
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/*.userdata =*/ userdata
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};
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ggml_set_op_params(result, (const void *) ¶ms, sizeof(params));
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ggml_set_op_params(result, ¶ms, sizeof(params));
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result->op = GGML_OP_MAP_CUSTOM1;
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result->src[0] = a;
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@ -5091,7 +4913,7 @@ static struct ggml_tensor * ggml_map_custom2_impl(
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/*.n_tasks =*/ n_tasks,
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/*.userdata =*/ userdata
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};
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ggml_set_op_params(result, (const void *) ¶ms, sizeof(params));
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ggml_set_op_params(result, ¶ms, sizeof(params));
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result->op = GGML_OP_MAP_CUSTOM2;
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result->src[0] = a;
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@ -5140,7 +4962,7 @@ static struct ggml_tensor * ggml_map_custom3_impl(
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/*.n_tasks =*/ n_tasks,
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/*.userdata =*/ userdata
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};
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ggml_set_op_params(result, (const void *) ¶ms, sizeof(params));
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ggml_set_op_params(result, ¶ms, sizeof(params));
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result->op = GGML_OP_MAP_CUSTOM3;
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result->src[0] = a;
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@ -5172,6 +4994,66 @@ struct ggml_tensor * ggml_map_custom3_inplace(
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return ggml_map_custom3_impl(ctx, a, b, c, fun, n_tasks, userdata, true);
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}
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struct ggml_tensor * ggml_custom_4d(
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struct ggml_context * ctx,
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enum ggml_type type,
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int64_t ne0,
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int64_t ne1,
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int64_t ne2,
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int64_t ne3,
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struct ggml_tensor ** args,
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int n_args,
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ggml_custom_op_t fun,
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int n_tasks,
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void * userdata) {
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GGML_ASSERT(n_args < GGML_MAX_SRC);
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struct ggml_tensor * result = ggml_new_tensor_4d(ctx, type, ne0, ne1, ne2, ne3);
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struct ggml_custom_op_params params = {
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/*.fun =*/ fun,
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/*.n_tasks =*/ n_tasks,
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/*.userdata =*/ userdata
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};
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ggml_set_op_params(result, ¶ms, sizeof(params));
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result->op = GGML_OP_CUSTOM;
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for (int i = 0; i < n_args; i++) {
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result->src[i] = args[i];
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}
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return result;
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}
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struct ggml_tensor * ggml_custom_inplace(
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struct ggml_context * ctx,
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struct ggml_tensor * a,
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struct ggml_tensor ** args,
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int n_args,
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ggml_custom_op_t fun,
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int n_tasks,
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void * userdata) {
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GGML_ASSERT(n_args < GGML_MAX_SRC - 1);
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struct ggml_tensor * result = ggml_view_tensor(ctx, a);
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struct ggml_custom_op_params params = {
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/*.fun =*/ fun,
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/*.n_tasks =*/ n_tasks,
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/*.userdata =*/ userdata
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};
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ggml_set_op_params(result, ¶ms, sizeof(params));
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result->op = GGML_OP_CUSTOM;
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result->src[0] = a;
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for (int i = 0; i < n_args; i++) {
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result->src[i + 1] = args[i];
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}
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return result;
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}
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// ggml_cross_entropy_loss
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struct ggml_tensor * ggml_cross_entropy_loss(
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|
|
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