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"Measures the displayed width of unicode strings in a terminal" optional = false python-versions = "*" files = [ - {file = "wcwidth-0.2.12-py2.py3-none-any.whl", hash = "sha256:f26ec43d96c8cbfed76a5075dac87680124fa84e0855195a6184da9c187f133c"}, - {file = "wcwidth-0.2.12.tar.gz", hash = "sha256:f01c104efdf57971bcb756f054dd58ddec5204dd15fa31d6503ea57947d97c02"}, + {file = "wcwidth-0.2.13-py2.py3-none-any.whl", hash = "sha256:3da69048e4540d84af32131829ff948f1e022c1c6bdb8d6102117aac784f6859"}, + {file = "wcwidth-0.2.13.tar.gz", hash = "sha256:72ea0c06399eb286d978fdedb6923a9eb47e1c486ce63e9b4e64fc18303972b5"}, ] [[package]] @@ -3098,4 +3180,4 @@ testing = ["big-O", "jaraco.functools", "jaraco.itertools", "more-itertools", "p [metadata] lock-version = "2.0" python-versions = ">=3.8,<3.12" -content-hash = "e5c1896a8433643d1b5cd0edf44f9704879b7d9b970fd52e3dd3966b60ab2adf" +content-hash = "c29cd70d49c3c7addb5748948ce786895f31b66531b8367bd43bc39125af2b60" diff --git a/pyproject.toml b/pyproject.toml index 7e81c7a9b..5a01dea62 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -32,7 +32,7 @@ fastapi = "^0.109.1" uvicorn = "^0.24.0" httpx = "^0.24.1" psutil = "^5.9.4" -pydantic = "^1.10.9" +pydantic = "^2.3.0" boto3 = "^1.26.157" rich = "^13.4.2" watchfiles = "^0.19.0" diff --git a/truss/truss_config.py b/truss/truss_config.py index c1d626f5c..30a8e47fd 100644 --- a/truss/truss_config.py +++ b/truss/truss_config.py @@ -5,6 +5,7 @@ from typing import Any, Dict, List, Optional import yaml +from pydantic import BaseModel, model_validator from truss.constants import HTTP_PUBLIC_BLOB_BACKEND from truss.errors import ValidationError from truss.types import ModelFrameworkType @@ -171,6 +172,98 @@ class ModelServer(Enum): TRT_LLM = "TRT_LLM" +class TRTLLMModelArchitecture(Enum): + LLAMA: str = "llama" + MISTRAL: str = "mistral" + + +class TRTLLMQuantizationType(Enum): + NO_QUANT: str = "no_quant" + WEIGHTS_ONLY: str = "weights_only" + WEIGHTS_KV_INT8: str = "weights_kv_int8" + SMOOTH_QUANT: str = "smooth_quant" + + +class TRTLLMBuildConfiguration(BaseModel): + huggingface_ckpt_repository: str + base_model_architecture: TRTLLMModelArchitecture + max_input_len: int + max_output_len: int + max_batch_size: int + quantization_type: TRTLLMQuantizationType = TRTLLMQuantizationType.NO_QUANT + gather_all_token_logits: bool = False + multi_block_mode: bool = False + calibrate_kv_cache: bool = False + + def from_dict(d): + return TRTLLMBuildConfiguration( + huggingface_ckpt_repository=d.get("huggingface_ckpt_repository"), + base_model_architecture=TRTLLMModelArchitecture( + d.get("base_model_architecture") + ), + max_input_len=d.get("max_input_len"), + max_output_len=d.get("max_output_len"), + max_batch_size=d.get("max_batch_size"), + quantization_type=TRTLLMQuantizationType( + d.get("quantization_type", "no_quant") + ), + gather_all_token_logits=d.get("gather_all_token_logits", False), + multi_block_mode=d.get("multi_block_mode", False), + calibrate_kv_cache=d.get("calibrate_kv_cache", False), + ) + + +class TRTLLM(BaseModel): + engine_repository: Optional[str] + tokenizer_repository: Optional[str] + tensor_parallel_count: Optional[int] = 1 + pipeline_parallel_count: Optional[int] = 1 + build_configuration: Optional[TRTLLMBuildConfiguration] = None + + @model_validator(mode="after") + def check_minimum_required_configuration(self): + serve_engine_configuration = ( + self.engine_repository is not None and self.tokenizer_repository is not None + ) + build_engine_configuration = self.build_configuration is not None + if serve_engine_configuration and build_engine_configuration: + logger.warning( + "Both serve and build configurations are provided. Serve configuration will be used." + ) + if (self.engine_repository is None) ^ (self.tokenizer_repository is None): + raise ValueError( + "Both engine_repository and tokenizer_repository must be provided" + ) + + @property + def requires_build(self): + if self.engine_repository is None: + return True + return False + + def from_dict(d): + return TRTLLM( + engine_repository=d.get("engine_repository", None), + tokenizer_repository=d.get("tokenizer_repository", None), + tensor_parallel_count=d.get("tensor_parallel_count", 1), + pipeline_parallel_count=d.get("pipeline_parallel_count", 1), + build_configuration=TRTLLMBuildConfiguration(**d.get("build_configuration")) + if d.get("build_configuration") + else None, + ) + + def to_dict(self): + return { + "engine_repository": self.engine_repository, + "tokenizer_repository": self.tokenizer_repository, + "tensor_parallel_count": self.tensor_parallel_count, + "pipeline_parallel_count": self.pipeline_parallel_count, + "build_configuration": self.build_configuration.model_dump() + if self.build_configuration + else None, + } + + @dataclass class Build: model_server: ModelServer = ModelServer.TrussServer @@ -462,8 +555,8 @@ class TrussConfig: spec_version: str = DEFAULT_SPEC_VERSION train: Train = field(default_factory=Train) base_image: Optional[BaseImage] = None - model_cache: ModelCache = field(default_factory=ModelCache) + trt_llm: Optional[TRTLLM] = None @property def canonical_python_version(self) -> str: @@ -516,6 +609,7 @@ def from_dict(d): d.get("model_cache") or d.get("hf_cache") or [], ModelCache.from_list, ), + trt_llm=transform_optional(d.get("trt_llm"), TRTLLM.from_dict), ) config.validate() return config @@ -606,6 +700,10 @@ def obj_to_dict(obj, verbose: bool = False): d["model_cache"] = transform_optional( field_curr_value, lambda data: data.to_list(verbose=verbose) ) + elif isinstance(field_curr_value, TRTLLM): + d["trt_llm"] = transform_optional( + field_curr_value, lambda data: data.to_dict() + ) else: d[field_name] = field_curr_value From 326efb369f25b3952a688606154e3a2b23b2339c Mon Sep 17 00:00:00 2001 From: Abu Qader <48742992+aspctu@users.noreply.github.com> Date: Tue, 13 Feb 2024 17:34:12 +0000 Subject: [PATCH 2/8] wip --- poetry.lock | 15 +++++++++------ pyproject.toml | 9 ++++----- 2 files changed, 13 insertions(+), 11 deletions(-) diff --git a/poetry.lock b/poetry.lock index ace06eb64..0938e1d73 100644 --- a/poetry.lock +++ b/poetry.lock @@ -2312,22 +2312,25 @@ files = [ [[package]] name = "python-on-whales" -version = "0.46.0" +version = "0.68.0" description = "A Docker client for Python, designed to be fun and intuitive!" optional = false -python-versions = ">=3.7, <4" +python-versions = "<4,>=3.8" files = [ - {file = "python-on-whales-0.46.0.tar.gz", hash = "sha256:8d298323c0a2dc80f4eb21db4b6fade25ee35745bcc35a6a4a97268a6d128433"}, - {file = "python_on_whales-0.46.0-py3-none-any.whl", hash = "sha256:5fad15b28a9a66abc0a6180228b385eb1cf2a35883713b26290344bb6926b89c"}, + {file = "python-on-whales-0.68.0.tar.gz", hash = "sha256:b62924e6ee1b4618976b81093a578296ada4d4110664c064a8dbc9792a7144a9"}, + {file = "python_on_whales-0.68.0-py3-none-any.whl", hash = "sha256:62c547976a3bef3ae9af2e2da131b303bd621ea3879a6231341c130673210f25"}, ] [package.dependencies] -pydantic = "*" +pydantic = ">=1.9,<2.0.dev0 || >=2.1.dev0,<3" requests = "*" tqdm = "*" typer = ">=0.4.1" typing-extensions = "*" +[package.extras] +test = ["pytest"] + [[package]] name = "pywin32" version = "306" @@ -3180,4 +3183,4 @@ testing = ["big-O", "jaraco.functools", "jaraco.itertools", "more-itertools", "p [metadata] lock-version = "2.0" python-versions = ">=3.8,<3.12" -content-hash = "c29cd70d49c3c7addb5748948ce786895f31b66531b8367bd43bc39125af2b60" +content-hash = "bdd72b5efa60f6845e42a66b6a92fb999bac6f4ef472dfb9bf743a21253a4b41" diff --git a/pyproject.toml b/pyproject.toml index 5a01dea62..a32763095 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -1,6 +1,6 @@ [tool.poetry] name = "truss" -version = "0.9.1rc1" +version = "0.9.0rc2" description = "A seamless bridge from model development to model delivery" license = "MIT" readme = "README.md" @@ -24,7 +24,6 @@ packaging = ">=20.9" python-json-logger = ">=2.0.2" PyYAML = "^6.0" Jinja2 = "^3.1.2" -python-on-whales = "^0.46.0" tenacity = "^8.0.1" single-source = "^0.3.0" blake3 = "^0.3.3" @@ -32,7 +31,6 @@ fastapi = "^0.109.1" uvicorn = "^0.24.0" httpx = "^0.24.1" psutil = "^5.9.4" -pydantic = "^2.3.0" boto3 = "^1.26.157" rich = "^13.4.2" watchfiles = "^0.19.0" @@ -40,7 +38,9 @@ huggingface_hub = ">=0.19.4" rich-click = "^1.6.1" inquirerpy = "^0.3.4" google-cloud-storage = "2.10.0" -botocore = ">=1.31.7" +botocore =">=1.31.7" +pydantic = "^2.6.1" +python-on-whales = "^0.68.0" loguru = ">=0.7.2" @@ -62,7 +62,6 @@ psutil = "^5.9.4" huggingface_hub = ">=0.19.4" google-cloud-storage = "2.10.0" boto3 = "^1.26.157" -loguru = ">=0.7.2" [tool.poetry.dev-dependencies] ipython = "^7.16" From 7c8ae8311ef25fd3de1d70026c29399226eed43d Mon Sep 17 00:00:00 2001 From: Abu Qader <48742992+aspctu@users.noreply.github.com> Date: Tue, 13 Feb 2024 20:20:21 +0000 Subject: [PATCH 3/8] wip --- poetry.lock | 2 +- pyproject.toml | 8 ++++---- 2 files changed, 5 insertions(+), 5 deletions(-) diff --git a/poetry.lock b/poetry.lock index 0938e1d73..b75f1c105 100644 --- a/poetry.lock +++ b/poetry.lock @@ -3183,4 +3183,4 @@ testing = ["big-O", "jaraco.functools", "jaraco.itertools", "more-itertools", "p [metadata] lock-version = "2.0" python-versions = ">=3.8,<3.12" -content-hash = "bdd72b5efa60f6845e42a66b6a92fb999bac6f4ef472dfb9bf743a21253a4b41" +content-hash = "31fd17a9e08976d9701c79146d02e9e0a1489ff236ea8d604292c491be2d962f" diff --git a/pyproject.toml b/pyproject.toml index a32763095..c8db65b77 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -1,6 +1,6 @@ [tool.poetry] name = "truss" -version = "0.9.0rc2" +version = "0.9.1rc1" description = "A seamless bridge from model development to model delivery" license = "MIT" readme = "README.md" @@ -24,6 +24,7 @@ packaging = ">=20.9" python-json-logger = ">=2.0.2" PyYAML = "^6.0" Jinja2 = "^3.1.2" +python-on-whales = "^0.68.0" tenacity = "^8.0.1" single-source = "^0.3.0" blake3 = "^0.3.3" @@ -31,6 +32,7 @@ fastapi = "^0.109.1" uvicorn = "^0.24.0" httpx = "^0.24.1" psutil = "^5.9.4" +pydantic = "^2.6.1" boto3 = "^1.26.157" rich = "^13.4.2" watchfiles = "^0.19.0" @@ -38,9 +40,6 @@ huggingface_hub = ">=0.19.4" rich-click = "^1.6.1" inquirerpy = "^0.3.4" google-cloud-storage = "2.10.0" -botocore =">=1.31.7" -pydantic = "^2.6.1" -python-on-whales = "^0.68.0" loguru = ">=0.7.2" @@ -62,6 +61,7 @@ psutil = "^5.9.4" huggingface_hub = ">=0.19.4" google-cloud-storage = "2.10.0" boto3 = "^1.26.157" +loguru = ">=0.7.2" [tool.poetry.dev-dependencies] ipython = "^7.16" From 44dbc167206f1b79b70772d0633c3d70b0b885df Mon Sep 17 00:00:00 2001 From: Abu Qader <48742992+aspctu@users.noreply.github.com> Date: Tue, 13 Feb 2024 20:26:08 +0000 Subject: [PATCH 4/8] wip --- poetry.lock | 46 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"psutil", "pyOpenSSL (>=23.0.0,<23.1.0)", "pycodestyle (>=2.9.0,<2.10.0)"] + [[package]] name = "virtualenv" version = "20.25.0" @@ -3183,4 +3227,4 @@ testing = ["big-O", "jaraco.functools", "jaraco.itertools", "more-itertools", "p [metadata] lock-version = "2.0" python-versions = ">=3.8,<3.12" -content-hash = "31fd17a9e08976d9701c79146d02e9e0a1489ff236ea8d604292c491be2d962f" +content-hash = "54dbe4a5d6765fd101e79912ec8fd6f4241ed6e2621f678661110035a329e1b9" diff --git a/pyproject.toml b/pyproject.toml index c8db65b77..517e81340 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -41,6 +41,7 @@ rich-click = "^1.6.1" inquirerpy = "^0.3.4" google-cloud-storage = "2.10.0" loguru = ">=0.7.2" +uvloop = "^0.19.0" [tool.poetry.group.builder.dependencies] From 260b561af12b959e35ae59298f6fbd6093c2e014 Mon Sep 17 00:00:00 2001 From: Abu Qader <48742992+aspctu@users.noreply.github.com> Date: Tue, 13 Feb 2024 21:40:15 +0000 Subject: [PATCH 5/8] refactor --- truss/trt_llm.py | 61 +++++++++++++++++++++++++ truss/truss_config.py | 104 +++--------------------------------------- 2 files changed, 68 insertions(+), 97 deletions(-) create mode 100644 truss/trt_llm.py diff --git a/truss/trt_llm.py b/truss/trt_llm.py new file mode 100644 index 000000000..88c33d44c --- /dev/null +++ b/truss/trt_llm.py @@ -0,0 +1,61 @@ +import logging +from enum import Enum +from typing import Optional + +from pydantic import BaseModel, model_validator + +logging.basicConfig(level=logging.INFO) +logger = logging.getLogger(__name__) + + +class TRTLLMModelArchitecture(Enum): + LLAMA: str = "llama" + MISTRAL: str = "mistral" + + +class TRTLLMQuantizationType(Enum): + NO_QUANT: str = "no_quant" + WEIGHTS_ONLY: str = "weights_only" + WEIGHTS_KV_INT8: str = "weights_kv_int8" + SMOOTH_QUANT: str = "smooth_quant" + + +class TRTLLMBuildConfiguration(BaseModel): + huggingface_ckpt_repository: str + base_model_architecture: TRTLLMModelArchitecture + max_input_len: int + max_output_len: int + max_batch_size: int + quantization_type: TRTLLMQuantizationType = TRTLLMQuantizationType.NO_QUANT + gather_all_token_logits: bool = False + multi_block_mode: bool = False + calibrate_kv_cache: bool = False + + +class TRTLLMConfiguration(BaseModel): + engine_repository: Optional[str] + tokenizer_repository: Optional[str] + tensor_parallel_count: Optional[int] = 1 + pipeline_parallel_count: Optional[int] = 1 + build_configuration: Optional[TRTLLMBuildConfiguration] = None + + @model_validator(mode="after") + def check_minimum_required_configuration(self): + serve_engine_configuration = ( + self.engine_repository is not None and self.tokenizer_repository is not None + ) + build_engine_configuration = self.build_configuration is not None + if serve_engine_configuration and build_engine_configuration: + logger.warning( + "Both serve and build configurations are provided. Serve configuration will be used." + ) + if (self.engine_repository is None) ^ (self.tokenizer_repository is None): + raise ValueError( + "Both engine_repository and tokenizer_repository must be provided" + ) + + @property + def requires_build(self): + if self.engine_repository is None: + return True + return False diff --git a/truss/truss_config.py b/truss/truss_config.py index 30a8e47fd..6cac1739a 100644 --- a/truss/truss_config.py +++ b/truss/truss_config.py @@ -5,9 +5,9 @@ from typing import Any, Dict, List, Optional import yaml -from pydantic import BaseModel, model_validator from truss.constants import HTTP_PUBLIC_BLOB_BACKEND from truss.errors import ValidationError +from truss.trt_llm import TRTLLMConfiguration from truss.types import ModelFrameworkType from truss.util.data_structures import transform_optional from truss.validation import ( @@ -172,98 +172,6 @@ class ModelServer(Enum): TRT_LLM = "TRT_LLM" -class TRTLLMModelArchitecture(Enum): - LLAMA: str = "llama" - MISTRAL: str = "mistral" - - -class TRTLLMQuantizationType(Enum): - NO_QUANT: str = "no_quant" - WEIGHTS_ONLY: str = "weights_only" - WEIGHTS_KV_INT8: str = "weights_kv_int8" - SMOOTH_QUANT: str = "smooth_quant" - - -class TRTLLMBuildConfiguration(BaseModel): - huggingface_ckpt_repository: str - base_model_architecture: TRTLLMModelArchitecture - max_input_len: int - max_output_len: int - max_batch_size: int - quantization_type: TRTLLMQuantizationType = TRTLLMQuantizationType.NO_QUANT - gather_all_token_logits: bool = False - multi_block_mode: bool = False - calibrate_kv_cache: bool = False - - def from_dict(d): - return TRTLLMBuildConfiguration( - huggingface_ckpt_repository=d.get("huggingface_ckpt_repository"), - base_model_architecture=TRTLLMModelArchitecture( - d.get("base_model_architecture") - ), - max_input_len=d.get("max_input_len"), - max_output_len=d.get("max_output_len"), - max_batch_size=d.get("max_batch_size"), - quantization_type=TRTLLMQuantizationType( - d.get("quantization_type", "no_quant") - ), - gather_all_token_logits=d.get("gather_all_token_logits", False), - multi_block_mode=d.get("multi_block_mode", False), - calibrate_kv_cache=d.get("calibrate_kv_cache", False), - ) - - -class TRTLLM(BaseModel): - engine_repository: Optional[str] - tokenizer_repository: Optional[str] - tensor_parallel_count: Optional[int] = 1 - pipeline_parallel_count: Optional[int] = 1 - build_configuration: Optional[TRTLLMBuildConfiguration] = None - - @model_validator(mode="after") - def check_minimum_required_configuration(self): - serve_engine_configuration = ( - self.engine_repository is not None and self.tokenizer_repository is not None - ) - build_engine_configuration = self.build_configuration is not None - if serve_engine_configuration and build_engine_configuration: - logger.warning( - "Both serve and build configurations are provided. Serve configuration will be used." - ) - if (self.engine_repository is None) ^ (self.tokenizer_repository is None): - raise ValueError( - "Both engine_repository and tokenizer_repository must be provided" - ) - - @property - def requires_build(self): - if self.engine_repository is None: - return True - return False - - def from_dict(d): - return TRTLLM( - engine_repository=d.get("engine_repository", None), - tokenizer_repository=d.get("tokenizer_repository", None), - tensor_parallel_count=d.get("tensor_parallel_count", 1), - pipeline_parallel_count=d.get("pipeline_parallel_count", 1), - build_configuration=TRTLLMBuildConfiguration(**d.get("build_configuration")) - if d.get("build_configuration") - else None, - ) - - def to_dict(self): - return { - "engine_repository": self.engine_repository, - "tokenizer_repository": self.tokenizer_repository, - "tensor_parallel_count": self.tensor_parallel_count, - "pipeline_parallel_count": self.pipeline_parallel_count, - "build_configuration": self.build_configuration.model_dump() - if self.build_configuration - else None, - } - - @dataclass class Build: model_server: ModelServer = ModelServer.TrussServer @@ -556,7 +464,7 @@ class TrussConfig: train: Train = field(default_factory=Train) base_image: Optional[BaseImage] = None model_cache: ModelCache = field(default_factory=ModelCache) - trt_llm: Optional[TRTLLM] = None + trt_llm: Optional[TRTLLMConfiguration] = None @property def canonical_python_version(self) -> str: @@ -609,7 +517,9 @@ def from_dict(d): d.get("model_cache") or d.get("hf_cache") or [], ModelCache.from_list, ), - trt_llm=transform_optional(d.get("trt_llm"), TRTLLM.from_dict), + trt_llm=transform_optional( + d.get("trt_llm"), lambda x: TRTLLMConfiguration(**x) + ), ) config.validate() return config @@ -700,9 +610,9 @@ def obj_to_dict(obj, verbose: bool = False): d["model_cache"] = transform_optional( field_curr_value, lambda data: data.to_list(verbose=verbose) ) - elif isinstance(field_curr_value, TRTLLM): + elif isinstance(field_curr_value, TRTLLMConfiguration): d["trt_llm"] = transform_optional( - field_curr_value, lambda data: data.to_dict() + field_curr_value, lambda data: data.model_dump(mode="json") ) else: d[field_name] = field_curr_value From 401552d16c8938068b5c5aea5aabe9c317d54704 Mon Sep 17 00:00:00 2001 From: Abu Qader <48742992+aspctu@users.noreply.github.com> Date: Tue, 13 Feb 2024 21:57:10 +0000 Subject: [PATCH 6/8] refactor --- truss/{ => config}/trt_llm.py | 0 truss/truss_config.py | 2 +- 2 files changed, 1 insertion(+), 1 deletion(-) rename truss/{ => config}/trt_llm.py (100%) diff --git a/truss/trt_llm.py b/truss/config/trt_llm.py similarity index 100% rename from truss/trt_llm.py rename to truss/config/trt_llm.py diff --git a/truss/truss_config.py b/truss/truss_config.py index 6cac1739a..d316a3bb4 100644 --- a/truss/truss_config.py +++ b/truss/truss_config.py @@ -5,9 +5,9 @@ from typing import Any, Dict, List, Optional import yaml +from truss.config.trt_llm import TRTLLMConfiguration from truss.constants import HTTP_PUBLIC_BLOB_BACKEND from truss.errors import ValidationError -from truss.trt_llm import TRTLLMConfiguration from truss.types import ModelFrameworkType from truss.util.data_structures import transform_optional from truss.validation import ( From e001f1592513fb16057767c872b6814ca5f2b385 Mon Sep 17 00:00:00 2001 From: Abu Qader <48742992+aspctu@users.noreply.github.com> Date: Tue, 20 Feb 2024 16:16:06 +0000 Subject: [PATCH 7/8] updating config spec --- truss/config/trt_llm.py | 68 ++++++++++++++++++++++++++--------------- 1 file changed, 44 insertions(+), 24 deletions(-) diff --git a/truss/config/trt_llm.py b/truss/config/trt_llm.py index 88c33d44c..a6e94323b 100644 --- a/truss/config/trt_llm.py +++ b/truss/config/trt_llm.py @@ -15,47 +15,67 @@ class TRTLLMModelArchitecture(Enum): class TRTLLMQuantizationType(Enum): NO_QUANT: str = "no_quant" - WEIGHTS_ONLY: str = "weights_only" + WEIGHTS_ONLY_INT8: str = "weights_int8" WEIGHTS_KV_INT8: str = "weights_kv_int8" + WEIGHTS_ONLY_INT4: str = "weights_int4" + WEIGHTS_KV_INT4: str = "weights_kv_int4" SMOOTH_QUANT: str = "smooth_quant" + FP8: str = "fp8" + FP8_KV: str = "fp8_kv" -class TRTLLMBuildConfiguration(BaseModel): +class TrussTRTLLMPluginConfiguration(BaseModel): + multi_block_mode: bool = False + paged_kv_cache: bool = False + use_fused_mlp: bool = False + + +class TrussTRTLLMBuildConfiguration(BaseModel): huggingface_ckpt_repository: str base_model_architecture: TRTLLMModelArchitecture max_input_len: int max_output_len: int max_batch_size: int - quantization_type: TRTLLMQuantizationType = TRTLLMQuantizationType.NO_QUANT + max_beam_width: int + max_prompt_embedding_table_size: int gather_all_token_logits: bool = False - multi_block_mode: bool = False - calibrate_kv_cache: bool = False + strongly_typed: bool = False + quantization_type: TRTLLMQuantizationType = TRTLLMQuantizationType.NO_QUANT + tensor_parallel_count: int = 1 + pipeline_parallel_count: int = 1 + plugin_configuration: TrussTRTLLMPluginConfiguration = ( + TrussTRTLLMPluginConfiguration() + ) + + +class TrussTRTLLMServingConfiguration(BaseModel): + engine_repository: str + tokenizer_repository: str + tensor_parallel_count: int = 1 + pipeline_parallel_count: int = 1 -class TRTLLMConfiguration(BaseModel): - engine_repository: Optional[str] - tokenizer_repository: Optional[str] - tensor_parallel_count: Optional[int] = 1 - pipeline_parallel_count: Optional[int] = 1 - build_configuration: Optional[TRTLLMBuildConfiguration] = None +class TrussTRTLLMConfiguration(BaseModel): + serve: Optional[TrussTRTLLMServingConfiguration] = None + build: Optional[TrussTRTLLMBuildConfiguration] = None @model_validator(mode="after") def check_minimum_required_configuration(self): - serve_engine_configuration = ( - self.engine_repository is not None and self.tokenizer_repository is not None - ) - build_engine_configuration = self.build_configuration is not None - if serve_engine_configuration and build_engine_configuration: - logger.warning( - "Both serve and build configurations are provided. Serve configuration will be used." - ) - if (self.engine_repository is None) ^ (self.tokenizer_repository is None): - raise ValueError( - "Both engine_repository and tokenizer_repository must be provided" - ) + if not self.serve and not self.build: + raise ValueError("Either serve or build configurations must be provided") + if self.serve and self.build: + raise ValueError("Both serve and build configurations cannot be provided") + if self.serve is not None: + if (self.serve.engine_repository is None) ^ ( + self.serve.tokenizer_repository is None + ): + raise ValueError( + "Both engine_repository and tokenizer_repository must be provided" + ) + return self @property def requires_build(self): - if self.engine_repository is None: + if self.build is not None: return True return False From 9d70bd3ccf62ee0aa988141626d4f77fdcf55063 Mon Sep 17 00:00:00 2001 From: Abu Qader <48742992+aspctu@users.noreply.github.com> Date: Tue, 20 Feb 2024 16:47:06 +0000 Subject: [PATCH 8/8] fix --- truss/config/trt_llm.py | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/truss/config/trt_llm.py b/truss/config/trt_llm.py index a6e94323b..c223070c8 100644 --- a/truss/config/trt_llm.py +++ b/truss/config/trt_llm.py @@ -36,8 +36,8 @@ class TrussTRTLLMBuildConfiguration(BaseModel): max_input_len: int max_output_len: int max_batch_size: int - max_beam_width: int - max_prompt_embedding_table_size: int + max_beam_width: int = 1 + max_prompt_embedding_table_size: int = 0 gather_all_token_logits: bool = False strongly_typed: bool = False quantization_type: TRTLLMQuantizationType = TRTLLMQuantizationType.NO_QUANT @@ -55,7 +55,7 @@ class TrussTRTLLMServingConfiguration(BaseModel): pipeline_parallel_count: int = 1 -class TrussTRTLLMConfiguration(BaseModel): +class TRTLLMConfiguration(BaseModel): serve: Optional[TrussTRTLLMServingConfiguration] = None build: Optional[TrussTRTLLMBuildConfiguration] = None