feat(mm): faster hashing for spinning disk HDDs

BLAKE3 has poor performance on spinning disks when parallelized. See https://github.com/BLAKE3-team/BLAKE3/issues/31

- Replace `skip_model_hash` setting with `hashing_algorithm`. Any algorithm we support is accepted.
- Add `random` algorithm: hashes a UUID with BLAKE3 to create a random "hash". Equivalent to the previous skip functionality.
- Add `blake3_single` algorithm: hashes on a single thread using BLAKE3, fixes the aforementioned performance issue
- Update model probe to accept the algorithm to hash with as an optional arg, defaulting to `blake3`
- Update all calls of the probe to use the app's configured hashing algorithm
- Update an external script that probes models
- Update tests
- Move ModelHash into its own module to avoid circuclar import issues

invokeai/app/services/config/config_default.py

@@ -179,6 +179,8 @@ from pydantic import BaseModel, Field, field_validator
 from pydantic.config import JsonDict
 from pydantic_settings import SettingsConfigDict
 
+from invokeai.backend.model_hash.model_hash import HASHING_ALGORITHMS
+
 from .config_base import InvokeAISettings
 
 INIT_FILE = Path("invokeai.yaml")
@@ -360,7 +362,7 @@ class InvokeAIAppConfig(InvokeAISettings):
     node_cache_size     : int = Field(default=512, description="How many cached nodes to keep in memory.", json_schema_extra=Categories.Nodes)
 
     # MODEL INSTALL
-    skip_model_hash     : bool = Field(default=False, description="Skip model hashing, instead assigning a UUID to models. Useful when using a memory db to reduce model installation time, or if you don't care about storing stable hashes for models.", json_schema_extra=Categories.ModelInstall)
+    hashing_algorithm   : HASHING_ALGORITHMS = Field(default="blake3", description="Model hashing algorthim for model installs. 'blake3' is best for SSDs. 'blake3_single' is best for spinning disk HDDs. 'none' disables hashing, instead assigning a UUID to models. Useful when using a memory db to reduce model installation time, or if you don't care about storing stable hashes for models. Alternatively, any other hashlib algorithm is accepted, though these are not nearly as performant as blake3.", json_schema_extra=Categories.ModelInstall)
     remote_api_tokens   : Optional[list[URLRegexToken]] = Field(
         default=None,
         description="List of regular expression and token pairs used when downloading models from URLs. The download URL is tested against the regex, and if it matches, the token is provided in as a Bearer token.",