DeepSeek V4 (#24162)
* convert: add dsv4 conversion * add basic setup * add llm_graph_input_dsv4 * add save-load state * add sinkhorn eps - correction by @fairydreaming * add rope fix * cleanup dead code * fix bugs * support pro model: added by @fairydreaming * remove redundant V cache * Chat template * remove debugging leftovers * Add mechanism for inlining templates based on architecture * s/deepseek-v4-flash/deepseek4/g * s/deepseek-v4-flash/deepseek4/g continued * enable graph reuse * enable FA * fix test llama archs * rename * compatibility with antirez ds4 GGUFs * simplified set_gguf_parameters() by calling super class method, replaced moe.score_func with expert_gating_func. * reserve worst-case kv-cache * revert max split inputs * address review comments * add padding to enable FA * pad only the final value of plan.n_kv to 256 * remove built-in cpp chat template * cont: remove cpp built-in template * rm outdated test * replace ggml_view_3d() with ggml_reshape_3d() Co-authored-by: Georgi Gerganov <ggerganov@gmail.com> * only support n_seq=1 for now * remove unused var * cont: remove unused var * use scale bias * use correct ptr for can_reuse * remove gen-chat-inline-templates.py * simplify graph reuse * cont: cleanup * remove unused inputs * enable partial checkpointing * add correct shape for kq_mask + set llama_model_n_swa to 0 for dsv4 * precompute source_idx + add comment about dummy write * support multi-seq * remove restored_trim_pos * use split_equal when possible * fix indent * address review comments * use LLM_KV * fix ci --------- Co-authored-by: Piotr Wilkin <piotr.wilkin@syndatis.com> Co-authored-by: Stanisław Szymczyk <sszymczy@gmail.com> Co-authored-by: Xuan Son Nguyen <son@huggingface.co> Co-authored-by: fairydreaming <166155368+fairydreaming@users.noreply.github.com> Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
This commit is contained in:
co-authored by
Georgi Gerganov
Piotr Wilkin
Stanisław Szymczyk
Xuan Son Nguyen
fairydreaming
parent
6cb18b2f2e
commit
8c146a8366
+102
-2
@@ -145,6 +145,7 @@ class Keys:
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TOKEN_SHIFT_COUNT = "{arch}.token_shift_count"
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INTERLEAVE_MOE_LAYER_STEP = "{arch}.interleave_moe_layer_step"
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FULL_ATTENTION_INTERVAL = "{arch}.full_attention_interval"
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HASH_LAYER_COUNT = "{arch}.hash_layer_count"
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ACTIVATION_SPARSITY_SCALE = "{arch}.activation_sparsity_scale"
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ALTUP_ACTIVE_IDX = "{arch}.altup.active_idx"
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ALTUP_NUM_INPUTS = "{arch}.altup.num_inputs"
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@@ -180,8 +181,12 @@ class Keys:
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REL_BUCKETS_COUNT = "{arch}.attention.relative_buckets_count"
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SLIDING_WINDOW = "{arch}.attention.sliding_window"
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SCALE = "{arch}.attention.scale"
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OUTPUT_GROUP_COUNT = "{arch}.attention.output_group_count"
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OUTPUT_LORA_RANK = "{arch}.attention.output_lora_rank"
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OUTPUT_SCALE = "{arch}.attention.output_scale"
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VALUE_SCALE = "{arch}.attention.value_scale"
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COMPRESS_RATIOS = "{arch}.attention.compress_ratios"
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COMPRESS_ROPE_FREQ_BASE = "{arch}.attention.compress_rope_freq_base"
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TEMPERATURE_LENGTH = "{arch}.attention.temperature_length"
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KEY_LENGTH_MLA = "{arch}.attention.key_length_mla"
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VALUE_LENGTH_MLA = "{arch}.attention.value_length_mla"
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@@ -196,6 +201,11 @@ class Keys:
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KEY_LENGTH = "{arch}.attention.indexer.key_length"
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TOP_K = "{arch}.attention.indexer.top_k"
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class HyperConnection:
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COUNT = "{arch}.hyper_connection.count"
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SINKHORN_ITERATIONS = "{arch}.hyper_connection.sinkhorn_iterations"
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EPSILON = "{arch}.hyper_connection.epsilon"
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class Rope:
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DIMENSION_COUNT = "{arch}.rope.dimension_count"
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DIMENSION_COUNT_SWA = "{arch}.rope.dimension_count_swa"
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@@ -470,6 +480,7 @@ class MODEL_ARCH(IntEnum):
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DEEPSEEK2 = auto()
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DEEPSEEK2OCR = auto()
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DEEPSEEK32 = auto()
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DEEPSEEK4 = auto()
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CHATGLM = auto()
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GLM4 = auto()
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GLM4_MOE = auto()
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@@ -555,6 +566,9 @@ class MODEL_TENSOR(IntEnum):
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DENSE_2_OUT = auto() # embeddinggemma 2_Dense
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DENSE_3_OUT = auto() # embeddinggemma 3_Dense
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OUTPUT_NORM = auto()
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HC_HEAD_FN = auto()
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HC_HEAD_BASE = auto()
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HC_HEAD_SCALE = auto()
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ROPE_FREQS = auto()
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ROPE_FACTORS_LONG = auto()
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ROPE_FACTORS_SHORT = auto()
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@@ -594,6 +608,7 @@ class MODEL_TENSOR(IntEnum):
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FFN_DOWN_CHEXP = auto()
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FFN_UP_CHEXP = auto()
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FFN_EXP_PROBS_B = auto()
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FFN_GATE_TID2EID = auto()
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MOE_LATENT_DOWN = auto() # nemotron 3 super
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MOE_LATENT_UP = auto() # nemotron 3 super
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ATTN_Q_NORM = auto()
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@@ -681,6 +696,20 @@ class MODEL_TENSOR(IntEnum):
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ATTN_V_B = auto()
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ATTN_Q_A_NORM = auto()
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ATTN_KV_A_NORM = auto()
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ATTN_KV = auto()
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ATTN_KV_NORM = auto()
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ATTN_OUT_A = auto()
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ATTN_OUT_B = auto()
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HC_ATTN_FN = auto()
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HC_ATTN_BASE = auto()
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HC_ATTN_SCALE = auto()
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HC_FFN_FN = auto()
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HC_FFN_BASE = auto()
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HC_FFN_SCALE = auto()
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ATTN_COMPRESSOR_WKV = auto()
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ATTN_COMPRESSOR_WGATE = auto()
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ATTN_COMPRESSOR_APE = auto()
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ATTN_COMPRESSOR_NORM = auto()
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FFN_SUB_NORM = auto()
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ATTN_SUB_NORM = auto()
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DEC_ATTN_NORM = auto()
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@@ -742,6 +771,10 @@ class MODEL_TENSOR(IntEnum):
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INDEXER_PROJ = auto()
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INDEXER_ATTN_K = auto()
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INDEXER_ATTN_Q_B = auto()
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INDEXER_COMPRESSOR_WKV = auto()
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INDEXER_COMPRESSOR_WGATE = auto()
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INDEXER_COMPRESSOR_APE = auto()
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INDEXER_COMPRESSOR_NORM = auto()
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# vision
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V_MMPROJ = auto()
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V_MMPROJ_FC = auto()
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@@ -1027,6 +1060,7 @@ MODEL_ARCH_NAMES: dict[MODEL_ARCH, str] = {
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MODEL_ARCH.DEEPSEEK2: "deepseek2",
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MODEL_ARCH.DEEPSEEK2OCR: "deepseek2-ocr",
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MODEL_ARCH.DEEPSEEK32: "deepseek32",
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MODEL_ARCH.DEEPSEEK4: "deepseek4",
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MODEL_ARCH.CHATGLM: "chatglm",
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MODEL_ARCH.GLM4: "glm4",
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MODEL_ARCH.GLM4_MOE: "glm4moe",
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@@ -1111,6 +1145,9 @@ TENSOR_NAMES: dict[MODEL_TENSOR, str] = {
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MODEL_TENSOR.OUTPUT: "output",
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MODEL_TENSOR.DENSE_2_OUT: "dense_2", # embeddinggemma 2_Dense
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MODEL_TENSOR.DENSE_3_OUT: "dense_3", # embeddinggemma 2_Dense
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MODEL_TENSOR.HC_HEAD_FN: "output_hc_fn",
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MODEL_TENSOR.HC_HEAD_BASE: "output_hc_base",
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MODEL_TENSOR.HC_HEAD_SCALE: "output_hc_scale",
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MODEL_TENSOR.ROPE_FREQS: "rope_freqs",
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MODEL_TENSOR.ROPE_FACTORS_LONG: "rope_factors_long",
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MODEL_TENSOR.ROPE_FACTORS_SHORT: "rope_factors_short",
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@@ -1152,6 +1189,7 @@ TENSOR_NAMES: dict[MODEL_TENSOR, str] = {
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MODEL_TENSOR.FFN_UP_EXP: "blk.{bid}.ffn_up_exps",
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MODEL_TENSOR.FFN_GATE_UP_EXP: "blk.{bid}.ffn_gate_up_exps",
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MODEL_TENSOR.FFN_EXP_PROBS_B: "blk.{bid}.exp_probs_b",
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MODEL_TENSOR.FFN_GATE_TID2EID: "blk.{bid}.ffn_gate_tid2eid",
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MODEL_TENSOR.MOE_LATENT_DOWN: "blk.{bid}.ffn_latent_down", # nemotron 3 super
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MODEL_TENSOR.MOE_LATENT_UP: "blk.{bid}.ffn_latent_up", # nemotron 3 super
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MODEL_TENSOR.LAYER_OUT_NORM: "blk.{bid}.layer_output_norm",
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@@ -1237,6 +1275,20 @@ TENSOR_NAMES: dict[MODEL_TENSOR, str] = {
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MODEL_TENSOR.ATTN_V_B: "blk.{bid}.attn_v_b",
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MODEL_TENSOR.ATTN_Q_A_NORM: "blk.{bid}.attn_q_a_norm",
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MODEL_TENSOR.ATTN_KV_A_NORM: "blk.{bid}.attn_kv_a_norm",
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MODEL_TENSOR.ATTN_KV: "blk.{bid}.attn_kv",
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MODEL_TENSOR.ATTN_KV_NORM: "blk.{bid}.attn_kv_a_norm",
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MODEL_TENSOR.ATTN_OUT_A: "blk.{bid}.attn_output_a",
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MODEL_TENSOR.ATTN_OUT_B: "blk.{bid}.attn_output_b",
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MODEL_TENSOR.HC_ATTN_FN: "blk.{bid}.hc_attn_fn",
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MODEL_TENSOR.HC_ATTN_BASE: "blk.{bid}.hc_attn_base",
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MODEL_TENSOR.HC_ATTN_SCALE: "blk.{bid}.hc_attn_scale",
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MODEL_TENSOR.HC_FFN_FN: "blk.{bid}.hc_ffn_fn",
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MODEL_TENSOR.HC_FFN_BASE: "blk.{bid}.hc_ffn_base",
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MODEL_TENSOR.HC_FFN_SCALE: "blk.{bid}.hc_ffn_scale",
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MODEL_TENSOR.ATTN_COMPRESSOR_WKV: "blk.{bid}.attn_compressor_kv",
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MODEL_TENSOR.ATTN_COMPRESSOR_WGATE: "blk.{bid}.attn_compressor_gate",
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MODEL_TENSOR.ATTN_COMPRESSOR_APE: "blk.{bid}.attn_compressor_ape",
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MODEL_TENSOR.ATTN_COMPRESSOR_NORM: "blk.{bid}.attn_compressor_norm",
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MODEL_TENSOR.ATTN_SUB_NORM: "blk.{bid}.attn_sub_norm",
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MODEL_TENSOR.FFN_SUB_NORM: "blk.{bid}.ffn_sub_norm",
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MODEL_TENSOR.DEC_ATTN_NORM: "dec.blk.{bid}.attn_norm",
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@@ -1298,6 +1350,10 @@ TENSOR_NAMES: dict[MODEL_TENSOR, str] = {
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MODEL_TENSOR.INDEXER_PROJ: "blk.{bid}.indexer.proj",
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MODEL_TENSOR.INDEXER_ATTN_K: "blk.{bid}.indexer.attn_k",
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MODEL_TENSOR.INDEXER_ATTN_Q_B: "blk.{bid}.indexer.attn_q_b",
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MODEL_TENSOR.INDEXER_COMPRESSOR_WKV: "blk.{bid}.indexer_compressor_kv",
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MODEL_TENSOR.INDEXER_COMPRESSOR_WGATE: "blk.{bid}.indexer_compressor_gate",
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MODEL_TENSOR.INDEXER_COMPRESSOR_APE: "blk.{bid}.indexer_compressor_ape",
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MODEL_TENSOR.INDEXER_COMPRESSOR_NORM: "blk.{bid}.indexer_compressor_norm",
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# vision
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MODEL_TENSOR.V_MMPROJ: "mm.{bid}",
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MODEL_TENSOR.V_MMPROJ_FC: "mm.model.fc",
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@@ -3138,6 +3194,49 @@ MODEL_TENSORS: dict[MODEL_ARCH, list[MODEL_TENSOR]] = {
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MODEL_TENSOR.NEXTN_SHARED_HEAD_HEAD,
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MODEL_TENSOR.NEXTN_SHARED_HEAD_NORM,
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],
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MODEL_ARCH.DEEPSEEK4: [
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MODEL_TENSOR.TOKEN_EMBD,
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MODEL_TENSOR.OUTPUT_NORM,
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MODEL_TENSOR.OUTPUT,
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MODEL_TENSOR.HC_HEAD_FN,
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MODEL_TENSOR.HC_HEAD_BASE,
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MODEL_TENSOR.HC_HEAD_SCALE,
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MODEL_TENSOR.ATTN_NORM,
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MODEL_TENSOR.ATTN_SINKS,
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MODEL_TENSOR.ATTN_Q_A,
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MODEL_TENSOR.ATTN_Q_B,
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MODEL_TENSOR.ATTN_Q_A_NORM,
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MODEL_TENSOR.ATTN_KV,
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MODEL_TENSOR.ATTN_KV_NORM,
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MODEL_TENSOR.ATTN_OUT_A,
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MODEL_TENSOR.ATTN_OUT_B,
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MODEL_TENSOR.HC_ATTN_FN,
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MODEL_TENSOR.HC_ATTN_BASE,
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MODEL_TENSOR.HC_ATTN_SCALE,
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MODEL_TENSOR.HC_FFN_FN,
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MODEL_TENSOR.HC_FFN_BASE,
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MODEL_TENSOR.HC_FFN_SCALE,
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MODEL_TENSOR.ATTN_COMPRESSOR_WKV,
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MODEL_TENSOR.ATTN_COMPRESSOR_WGATE,
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MODEL_TENSOR.ATTN_COMPRESSOR_APE,
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MODEL_TENSOR.ATTN_COMPRESSOR_NORM,
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MODEL_TENSOR.INDEXER_PROJ,
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MODEL_TENSOR.INDEXER_ATTN_Q_B,
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MODEL_TENSOR.INDEXER_COMPRESSOR_WKV,
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MODEL_TENSOR.INDEXER_COMPRESSOR_WGATE,
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MODEL_TENSOR.INDEXER_COMPRESSOR_APE,
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MODEL_TENSOR.INDEXER_COMPRESSOR_NORM,
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MODEL_TENSOR.FFN_GATE_INP,
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MODEL_TENSOR.FFN_GATE_TID2EID,
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MODEL_TENSOR.FFN_EXP_PROBS_B,
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MODEL_TENSOR.FFN_NORM,
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MODEL_TENSOR.FFN_GATE_EXP,
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MODEL_TENSOR.FFN_DOWN_EXP,
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MODEL_TENSOR.FFN_UP_EXP,
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MODEL_TENSOR.FFN_GATE_SHEXP,
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MODEL_TENSOR.FFN_DOWN_SHEXP,
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MODEL_TENSOR.FFN_UP_SHEXP,
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],
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MODEL_ARCH.ERNIE4_5_MOE: [
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MODEL_TENSOR.TOKEN_EMBD,
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MODEL_TENSOR.OUTPUT_NORM,
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@@ -4437,8 +4536,9 @@ class GGMLQuantizationType(IntEnum):
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class ExpertGatingFuncType(IntEnum):
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SOFTMAX = 1
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SIGMOID = 2
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SOFTMAX = 1
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SIGMOID = 2
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SQRTSOFTPLUS = 4
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# TODO: add GGMLFileType from ggml_ftype in ggml.h
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