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add some new ops, fix some operators and add batch operations to certain operators. (ggml/747)

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* cuda: fix group_norm

* cuda: add batch inference support for ggml_pad/ggml_upscale

* add ggml_arrange

* add ggml_timestep_embedding

* update ggml_arange/ggml_timestep_embedding tests

* cuda: fix im2col

* add ggml_arange/ggml_timestep_embbeding support for metal backend

* fix some bugs

* fix some bugs

* Update ggml.h

Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>

* Update ggml-cuda.cu

Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>

* Update ggml-metal.m

Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>

* Update ggml-metal.m

Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>

* Update ggml-metal.metal

Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>

* modify according to the review comments

* ggml : fix compile warnings + code style

* ggml : normalize compute_forward calls + fix seg fault in debug

* minor

---------

Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
Co-authored-by: slaren <slarengh@gmail.com>
This commit is contained in:
leejet 2024-03-03 20:23:52 +08:00 • committed by Georgi Gerganov
parent 82f3e668ad
commit 7d43c585dc
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6 changed files with 550 additions and 52 deletions
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17
ggml.h
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@ -454,6 +454,8 @@ extern "C" {
GGML_OP_POOL_2D,
GGML_OP_UPSCALE, // nearest interpolate
GGML_OP_PAD,
GGML_OP_ARANGE,
GGML_OP_TIMESTEP_EMBEDDING,
GGML_OP_ARGSORT,
GGML_OP_LEAKY_RELU,
@ -1661,6 +1663,15 @@ extern "C" {
int p2,
int p3);
// Ref: https://github.com/CompVis/stable-diffusion/blob/main/ldm/modules/diffusionmodules/util.py#L151
// timesteps: [N,]
// return: [N, dim]
GGML_API struct ggml_tensor * ggml_timestep_embedding(
struct ggml_context * ctx,
struct ggml_tensor * timesteps,
int dim,
int max_period);
// sort rows
enum ggml_sort_order {
GGML_SORT_ORDER_ASC,
@ -1672,6 +1683,12 @@ extern "C" {
struct ggml_tensor * a,
enum ggml_sort_order order);
GGML_API struct ggml_tensor * ggml_arange(
struct ggml_context * ctx,
float start,
float stop,
float step);
// top k elements per row
GGML_API struct ggml_tensor * ggml_top_k(
struct ggml_context * ctx,