98 lines
3.7 KiB
Python
98 lines
3.7 KiB
Python
from logging import getLogger
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from os import environ, path
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from secrets import token_urlsafe
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from typing import List, Optional
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import torch
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from ..utils import get_boolean
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from .model_cache import ModelCache
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logger = getLogger(__name__)
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DEFAULT_CACHE_LIMIT = 5
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DEFAULT_JOB_LIMIT = 10
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DEFAULT_IMAGE_FORMAT = "png"
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DEFAULT_SERVER_VERSION = "v0.10.0"
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class ServerContext:
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def __init__(
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self,
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bundle_path: str = ".",
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model_path: str = ".",
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output_path: str = ".",
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params_path: str = ".",
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cors_origin: str = "*",
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any_platform: bool = True,
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block_platforms: Optional[List[str]] = None,
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default_platform: Optional[str] = None,
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image_format: str = DEFAULT_IMAGE_FORMAT,
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cache_limit: int = DEFAULT_CACHE_LIMIT,
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cache_path: Optional[str] = None,
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show_progress: bool = True,
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optimizations: Optional[List[str]] = None,
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extra_models: Optional[List[str]] = None,
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job_limit: int = DEFAULT_JOB_LIMIT,
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memory_limit: Optional[int] = None,
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admin_token: Optional[str] = None,
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server_version: Optional[str] = DEFAULT_SERVER_VERSION,
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) -> None:
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self.bundle_path = bundle_path
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self.model_path = model_path
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self.output_path = output_path
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self.params_path = params_path
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self.cors_origin = cors_origin
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self.any_platform = any_platform
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self.block_platforms = block_platforms or []
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self.default_platform = default_platform
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self.image_format = image_format
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self.cache_limit = cache_limit
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self.cache_path = cache_path or path.join(model_path, ".cache")
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self.show_progress = show_progress
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self.optimizations = optimizations or []
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self.extra_models = extra_models or []
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self.job_limit = job_limit
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self.memory_limit = memory_limit
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self.admin_token = admin_token or token_urlsafe()
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self.server_version = server_version
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self.cache = ModelCache(self.cache_limit)
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@classmethod
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def from_environ(cls):
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memory_limit = environ.get("ONNX_WEB_MEMORY_LIMIT", None)
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if memory_limit is not None:
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memory_limit = int(memory_limit)
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return cls(
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bundle_path=environ.get(
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"ONNX_WEB_BUNDLE_PATH", path.join("..", "gui", "out")
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),
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model_path=environ.get("ONNX_WEB_MODEL_PATH", path.join("..", "models")),
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output_path=environ.get("ONNX_WEB_OUTPUT_PATH", path.join("..", "outputs")),
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params_path=environ.get("ONNX_WEB_PARAMS_PATH", "."),
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# others
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cors_origin=environ.get("ONNX_WEB_CORS_ORIGIN", "*").split(","),
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any_platform=get_boolean(environ, "ONNX_WEB_ANY_PLATFORM", True),
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block_platforms=environ.get("ONNX_WEB_BLOCK_PLATFORMS", "").split(","),
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default_platform=environ.get("ONNX_WEB_DEFAULT_PLATFORM", None),
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image_format=environ.get("ONNX_WEB_IMAGE_FORMAT", "png"),
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cache_limit=int(environ.get("ONNX_WEB_CACHE_MODELS", DEFAULT_CACHE_LIMIT)),
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show_progress=get_boolean(environ, "ONNX_WEB_SHOW_PROGRESS", True),
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optimizations=environ.get("ONNX_WEB_OPTIMIZATIONS", "").split(","),
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extra_models=environ.get("ONNX_WEB_EXTRA_MODELS", "").split(","),
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job_limit=int(environ.get("ONNX_WEB_JOB_LIMIT", DEFAULT_JOB_LIMIT)),
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memory_limit=memory_limit,
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admin_token=environ.get("ONNX_WEB_ADMIN_TOKEN", None),
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server_version=environ.get(
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"ONNX_WEB_SERVER_VERSION", DEFAULT_SERVER_VERSION
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),
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)
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def torch_dtype(self):
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if "torch-fp16" in self.optimizations:
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return torch.float16
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else:
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return torch.float32
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