baalajimaestro/llama.cpp
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feat: Update llama.cpp

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This commit is contained in:
Andrei Betlen 2024-03-26 22:58:53 -04:00
parent b64fa4e2c0
commit 901fe02461
2 changed files with 21 additions and 11 deletions
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30
llama_cpp/llama_cpp.py
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@ -175,8 +175,8 @@ LLAMA_FILE_MAGIC_GGSN = 0x6767736E
# define LLAMA_SESSION_MAGIC LLAMA_FILE_MAGIC_GGSN # define LLAMA_SESSION_MAGIC LLAMA_FILE_MAGIC_GGSN
LLAMA_SESSION_MAGIC = LLAMA_FILE_MAGIC_GGSN LLAMA_SESSION_MAGIC = LLAMA_FILE_MAGIC_GGSN
# define LLAMA_SESSION_VERSION 4 # define LLAMA_SESSION_VERSION 5
LLAMA_SESSION_VERSION = 4 LLAMA_SESSION_VERSION = 5
# struct llama_model; # struct llama_model;
@ -274,6 +274,7 @@ LLAMA_TOKEN_TYPE_BYTE = 6
# LLAMA_FTYPE_MOSTLY_IQ2_S = 28, // except 1d tensors # LLAMA_FTYPE_MOSTLY_IQ2_S = 28, // except 1d tensors
# LLAMA_FTYPE_MOSTLY_IQ2_M = 29, // except 1d tensors # LLAMA_FTYPE_MOSTLY_IQ2_M = 29, // except 1d tensors
# LLAMA_FTYPE_MOSTLY_IQ4_XS = 30, // except 1d tensors # LLAMA_FTYPE_MOSTLY_IQ4_XS = 30, // except 1d tensors
# LLAMA_FTYPE_MOSTLY_IQ1_M = 31, // except 1d tensors
# LLAMA_FTYPE_GUESSED = 1024, // not specified in the model file # LLAMA_FTYPE_GUESSED = 1024, // not specified in the model file
# }; # };
@ -677,6 +678,7 @@ It might not exist for progress report where '.' is output repeatedly."""
# bool only_copy; // only copy tensors - ftype, allow_requantize and quantize_output_tensor are ignored # bool only_copy; // only copy tensors - ftype, allow_requantize and quantize_output_tensor are ignored
# bool pure; // quantize all tensors to the default type # bool pure; // quantize all tensors to the default type
# void * imatrix; // pointer to importance matrix data # void * imatrix; // pointer to importance matrix data
# void * kv_overrides; // pointer to vector containing overrides
# } llama_model_quantize_params; # } llama_model_quantize_params;
class llama_model_quantize_params(ctypes.Structure): class llama_model_quantize_params(ctypes.Structure):
"""Parameters for llama_model_quantize """Parameters for llama_model_quantize
@ -691,6 +693,7 @@ class llama_model_quantize_params(ctypes.Structure):
only_copy (bool): only copy tensors - ftype, allow_requantize and quantize_output_tensor are ignored only_copy (bool): only copy tensors - ftype, allow_requantize and quantize_output_tensor are ignored
pure (bool): quantize all tensors to the default type pure (bool): quantize all tensors to the default type
imatrix (ctypes.c_void_p): pointer to importance matrix data imatrix (ctypes.c_void_p): pointer to importance matrix data
kv_overrides (ctypes.c_void_p): pointer to vector containing overrides
""" """
_fields_ = [ _fields_ = [
@ -703,6 +706,7 @@ class llama_model_quantize_params(ctypes.Structure):
("only_copy", ctypes.c_bool), ("only_copy", ctypes.c_bool),
("pure", ctypes.c_bool), ("pure", ctypes.c_bool),
("imatrix", ctypes.c_void_p), ("imatrix", ctypes.c_void_p),
("kv_overrides", ctypes.c_void_p),
] ]
@ -1838,9 +1842,9 @@ def llama_synchronize(ctx: llama_context_p, /):
# // Token logits obtained from the last call to llama_decode() # // Token logits obtained from the last call to llama_decode()
# // The logits for the last token are stored in the last row # // The logits for which llama_batch.logits[i] != 0 are stored contiguously
# // Logits for which llama_batch.logits[i] == 0 are undefined # // in the order they have appeared in the batch.
# // Rows: n_tokens provided with llama_batch # // Rows: number of tokens for which llama_batch.logits[i] != 0
# // Cols: n_vocab # // Cols: n_vocab
# LLAMA_API float * llama_get_logits(struct llama_context * ctx); # LLAMA_API float * llama_get_logits(struct llama_context * ctx);
@ctypes_function( @ctypes_function(
@ -1859,7 +1863,8 @@ def llama_get_logits(ctx: llama_context_p, /) -> CtypesArray[ctypes.c_float]:
# // Logits for the ith token. Equivalent to: # // Logits for the ith token. Equivalent to:
# // llama_get_logits(ctx) + i*n_vocab # // llama_get_logits(ctx) + ctx->output_ids[i]*n_vocab
# // returns NULL for invalid ids.
# LLAMA_API float * llama_get_logits_ith(struct llama_context * ctx, int32_t i); # LLAMA_API float * llama_get_logits_ith(struct llama_context * ctx, int32_t i);
@ctypes_function( @ctypes_function(
"llama_get_logits_ith", "llama_get_logits_ith",
@ -1874,8 +1879,12 @@ def llama_get_logits_ith(
... ...
# // Get all output token embeddings # // Get all output token embeddings.
# // shape: [n_tokens*n_embd] (1-dimensional) # // when pooling_type == LLAMA_POOLING_TYPE_NONE or when using a generative model,
# // the embeddings for which llama_batch.logits[i] != 0 are stored contiguously
# // in the order they have appeared in the batch.
# // shape: [n_outputs*n_embd]
# // Otherwise, returns NULL.
# LLAMA_API float * llama_get_embeddings(struct llama_context * ctx); # LLAMA_API float * llama_get_embeddings(struct llama_context * ctx);
@ctypes_function( @ctypes_function(
"llama_get_embeddings", [llama_context_p_ctypes], ctypes.POINTER(ctypes.c_float) "llama_get_embeddings", [llama_context_p_ctypes], ctypes.POINTER(ctypes.c_float)
@ -1886,9 +1895,10 @@ def llama_get_embeddings(ctx: llama_context_p, /) -> CtypesArray[ctypes.c_float]
... ...
# // Get the embeddings for the ith token # // Get the embeddings for the ith token. Equivalent to:
# // llama_get_embeddings(ctx) + i*n_embd # // llama_get_embeddings(ctx) + ctx->output_ids[i]*n_embd
# // shape: [n_embd] (1-dimensional) # // shape: [n_embd] (1-dimensional)
# // returns NULL for invalid ids.
# LLAMA_API float * llama_get_embeddings_ith(struct llama_context * ctx, int32_t i); # LLAMA_API float * llama_get_embeddings_ith(struct llama_context * ctx, int32_t i);
@ctypes_function( @ctypes_function(
"llama_get_embeddings_ith", "llama_get_embeddings_ith",

2
vendor/llama.cpp vendored

@ -1 +1 @@
Subproject commit e190f1fca6f60d80944f9e8709d343a025c4d245 Subproject commit 32c8486e1f0297393cb22ac0a0d26a6b17ad4d54