-
Notifications
You must be signed in to change notification settings - Fork 1.6k
Commit
This commit does not belong to any branch on this repository, and may belong to a fork outside of the repository.
[Model] Add support for OLMo architecture (#3046)
This PR add support for OLMo architecture. Additional support: add support for clip-qkv. Test: already tested on android(pixel 4) and cuda(setting tensor_parallel_shrads=2)
- Loading branch information
Showing
8 changed files
with
902 additions
and
0 deletions.
There are no files selected for viewing
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
Original file line number | Diff line number | Diff line change |
---|---|---|
|
@@ -20,6 +20,7 @@ | |
llava, | ||
mistral, | ||
oasst, | ||
olmo, | ||
orion, | ||
phi, | ||
qwen2, | ||
|
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
Original file line number | Diff line number | Diff line change |
---|---|---|
@@ -0,0 +1,28 @@ | ||
"""OLMo default templates""" | ||
|
||
from mlc_llm.protocol.conversation_protocol import Conversation, MessagePlaceholders | ||
|
||
from .registry import ConvTemplateRegistry | ||
|
||
# Note that eos_token id is "50279" both in Allenai and AMD version. | ||
# So use the number instead of text. | ||
# Allenai version chat_template and eos_token: | ||
# https://huggingface.co/allenai/OLMo-7B-Instruct/blob/main/tokenizer_config.json | ||
# AMD version chat_template and eos_token: | ||
# https://huggingface.co/amd/AMD-OLMo-1B-SFT-DPO/blob/main/tokenizer_config.json | ||
ConvTemplateRegistry.register_conv_template( | ||
Conversation( | ||
name="olmo", | ||
system_template=f"{MessagePlaceholders.SYSTEM.value}", | ||
system_message="", | ||
system_prefix_token_ids=[50279], | ||
roles={ | ||
"user": "<|user|>", | ||
"assistant": "<|assistant|>", | ||
}, | ||
seps=["\n"], | ||
role_content_sep="\n", | ||
role_empty_sep="\n", | ||
stop_token_ids=[50279], | ||
) | ||
) |
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
Empty file.
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
Original file line number | Diff line number | Diff line change |
---|---|---|
@@ -0,0 +1,172 @@ | ||
""" | ||
This file specifies how MLC's OLMo parameter maps from other formats, for example HuggingFace | ||
PyTorch, HuggingFace safetensors. | ||
""" | ||
|
||
import functools | ||
|
||
import numpy as np | ||
|
||
from mlc_llm.loader import ExternMapping | ||
from mlc_llm.quantization import Quantization | ||
|
||
from .olmo_model import OLMoConfig, OLMoForCausalLM | ||
from .olmo_quantization import awq_quant | ||
|
||
|
||
def huggingface(model_config: OLMoConfig, quantization: Quantization) -> ExternMapping: | ||
"""Returns a parameter mapping that maps from the names of MLC LLM parameters to | ||
the names of HuggingFace PyTorch parameters. | ||
Parameters | ||
---------- | ||
model_config : OLMoConfig | ||
The configuration of the OLMo model. | ||
quantization : Quantization | ||
The quantization configuration. | ||
Returns | ||
------- | ||
param_map : ExternMapping | ||
The parameter mapping from MLC to HuggingFace PyTorch. | ||
""" | ||
model = OLMoForCausalLM(model_config) | ||
if quantization is not None: | ||
model.to(quantization.model_dtype) | ||
_, _named_params, _ = model.export_tvm( # type: ignore[misc] | ||
spec=model.get_default_spec(), | ||
allow_extern=True, | ||
) | ||
named_parameters = dict(_named_params) | ||
|
||
mapping = ExternMapping() | ||
|
||
for i in range(model_config.num_hidden_layers): | ||
# Add QKV in self attention | ||
attn = f"model.layers.{i}.self_attn" | ||
mlc_name = f"{attn}.qkv_proj.weight" | ||
mlc_param = named_parameters[mlc_name] | ||
mapping.add_mapping( | ||
mlc_name, | ||
[ | ||
f"{attn}.q_proj.weight", | ||
f"{attn}.k_proj.weight", | ||
f"{attn}.v_proj.weight", | ||
], | ||
functools.partial( | ||
lambda q, k, v, dtype: np.concatenate([q, k, v], axis=0).astype(dtype), | ||
dtype=mlc_param.dtype, | ||
), | ||
) | ||
# Add gates in MLP | ||
mlp = f"model.layers.{i}.mlp" | ||
mlc_name = f"{mlp}.gate_up_proj.weight" | ||
mlc_param = named_parameters[mlc_name] | ||
mapping.add_mapping( | ||
mlc_name, | ||
[ | ||
f"{mlp}.gate_proj.weight", | ||
f"{mlp}.up_proj.weight", | ||
], | ||
functools.partial( | ||
lambda gate, up, dtype: np.concatenate([gate, up], axis=0).astype(dtype), | ||
dtype=mlc_param.dtype, | ||
), | ||
) | ||
# inv_freq is not used in the model | ||
mapping.add_unused(f"{attn}.rotary_emb.inv_freq") | ||
|
||
for mlc_name, mlc_param in named_parameters.items(): | ||
if mlc_name not in mapping.param_map: | ||
mapping.add_mapping( | ||
mlc_name, | ||
[mlc_name], | ||
functools.partial( | ||
lambda x, dtype: x.astype(dtype), | ||
dtype=mlc_param.dtype, | ||
), | ||
) | ||
return mapping | ||
|
||
|
||
def awq(model_config: OLMoConfig, quantization: Quantization) -> ExternMapping: | ||
"""Returns a parameter mapping that maps from the names of MLC LLM parameters to | ||
the names of AWQ parameters. | ||
Parameters | ||
---------- | ||
model_config : OLMoConfig | ||
The configuration of the OLMo model. | ||
quantization : Quantization | ||
The quantization configuration. | ||
Returns | ||
------- | ||
param_map : ExternMapping | ||
The parameter mapping from MLC to AWQ. | ||
""" | ||
model, _ = awq_quant(model_config, quantization) | ||
_, _named_params, _ = model.export_tvm( # type: ignore[misc] | ||
spec=model.get_default_spec(), # type: ignore[attr-defined] | ||
allow_extern=True, | ||
) | ||
named_parameters = dict(_named_params) | ||
|
||
mapping = ExternMapping() | ||
|
||
for i in range(model_config.num_hidden_layers): | ||
# Add QKV in self attention | ||
attn = f"model.layers.{i}.self_attn" | ||
for quantize_suffix in ["qweight", "qzeros", "scales"]: | ||
mlc_name = f"{attn}.qkv_proj.{quantize_suffix}" | ||
assert mlc_name in named_parameters | ||
mlc_param = named_parameters[mlc_name] | ||
mapping.add_mapping( | ||
mlc_name, | ||
[ | ||
f"{attn}.q_proj.{quantize_suffix}", | ||
f"{attn}.k_proj.{quantize_suffix}", | ||
f"{attn}.v_proj.{quantize_suffix}", | ||
], | ||
functools.partial( | ||
lambda q, k, v, dtype: np.concatenate( | ||
[q, k, v], | ||
axis=1, # AWQ GEMM would transpose the weight | ||
).astype(dtype), | ||
dtype=mlc_param.dtype, | ||
), | ||
) | ||
|
||
# Concat gate and up in MLP | ||
mlp = f"model.layers.{i}.mlp" | ||
for quantize_suffix in ["qweight", "qzeros", "scales"]: | ||
mlc_name = f"{mlp}.gate_up_proj.{quantize_suffix}" | ||
assert mlc_name in named_parameters | ||
mlc_param = named_parameters[mlc_name] | ||
mapping.add_mapping( | ||
mlc_name, | ||
[ | ||
f"{mlp}.gate_proj.{quantize_suffix}", | ||
f"{mlp}.up_proj.{quantize_suffix}", | ||
], | ||
functools.partial( | ||
lambda gate, up, dtype: np.concatenate( | ||
[gate, up], | ||
axis=1, # AWQ GEMM would transpose the weight | ||
).astype(dtype), | ||
dtype=mlc_param.dtype, | ||
), | ||
) | ||
|
||
# inv_freq is not used in the model | ||
mapping.add_unused(f"{attn}.rotary_emb.inv_freq") | ||
|
||
for mlc_name, mlc_param in named_parameters.items(): | ||
if mlc_name not in mapping.param_map: | ||
mapping.add_mapping( | ||
mlc_name, | ||
[mlc_name], | ||
functools.partial(lambda x, dtype: x.astype(dtype), dtype=mlc_param.dtype), | ||
) | ||
return mapping |
Oops, something went wrong.