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Code Issues Activity

Make default hash lib configurable without code changes via CLI argument (#3947)

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* cli_args: Add --duplicate-check-hash-function.

* server.py: compare_image_hash configurable hash function

Uses an argument added in cli_args to specify the type of hashing to default to for duplicate hash checking.  Uses an `eval()` to identify the specific hashlib class to utilize, but ultimately safely operates because we have specific options and only those options/choices in the arg parser.  So we don't have any unsafe input there.

* Add hasher() to node_helpers

* hashlib selection moved to node_helpers

* default-hashing-function instead of dupe checking hasher

This makes a default-hashing-function option instead of previous selected option.

* Use args.default_hashing_function

* Use safer handling for node_helpers.hasher()

Uses a safer handling method than `eval` to evaluate default hashing function.

* Stray parentheses are evil.

* Indentation fix.

Somehow when I hit save I didn't notice I missed a space to make indentation work proper.  Oops!
This commit is contained in:
Thomas Ward
2024-07-16 18:27:09 -04:00
committed by GitHub
parent f2298799ba
commit c5a48b15bd
3 changed files with 19 additions and 2 deletions
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comfy/cli_args.py
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@@ -112,6 +112,7 @@ vram_group.add_argument("--lowvram", action="store_true", help="Split the unet i
vram_group.add_argument("--novram", action="store_true", help="When lowvram isn't enough.")
vram_group.add_argument("--cpu", action="store_true", help="To use the CPU for everything (slow).")
parser.add_argument("--default-hashing-function", type=str, choices=['md5', 'sha1', 'sha256', 'sha512'], default='sha256', help="Allows you to choose the hash function to use for duplicate filename / contents comparison. Default is sha256.")
parser.add_argument("--disable-smart-memory", action="store_true", help="Force ComfyUI to agressively offload to regular ram instead of keeping models in vram when it can.")
parser.add_argument("--deterministic", action="store_true", help="Make pytorch use slower deterministic algorithms when it can. Note that this might not make images deterministic in all cases.")