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import os
import json
import torch
from deepdiff import DeepDiff
from ..core import CONFIG, logger
# just a helper function to set the widget values (or clear them)
def setWidgetValues(value=None, unique_id=None, extra_pnginfo=None) -> None:
if unique_id and extra_pnginfo:
workflow = extra_pnginfo["workflow"]
node = next((x for x in workflow["nodes"] if str(x["id"]) == unique_id), None)
if node:
node["widgets_values"] = value
return None
# find difference between two jsons
def findJsonStrDiff(json1, json2):
msgError = "Could not compare jsons"
returnJson = {"error": msgError}
try:
# TODO review this
# dict1 = json.loads(json1)
# dict2 = json.loads(json2)
returnJson = findJsonsDiff(json1, json2)
returnJson = json.dumps(returnJson, indent=CONFIG["indent"])
except Exception as e:
logger.warn(f"{msgError}: {e}")
return returnJson
def findJsonsDiff(json1, json2):
msgError = "Could not compare jsons"
returnJson = {"error": msgError}
try:
diff = DeepDiff(json1, json2, ignore_order=True, verbose_level=2)
returnJson = {k: v for k, v in diff.items() if
k in ('dictionary_item_added', 'dictionary_item_removed', 'values_changed')}
# just for print "values_changed" at first
returnJson = dict(reversed(returnJson.items()))
except Exception as e:
logger.warn(f"{msgError}: {e}")
return returnJson
# powered by:
# https://github.com/WASasquatch/was-node-suite-comfyui/blob/main/WAS_Node_Suite.py
# class: WAS_Samples_Passthrough_Stat_System
def get_system_stats():
import psutil
# RAM
ram = psutil.virtual_memory()
ram_used = ram.used / (1024 ** 3)
ram_total = ram.total / (1024 ** 3)
ram_stats = f"Used RAM: {ram_used:.2f} GB / Total RAM: {ram_total:.2f} GB"
# VRAM (with PyTorch)
device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
vram_used = torch.cuda.memory_allocated(device) / (1024 ** 3)
vram_total = torch.cuda.get_device_properties(device).total_memory / (1024 ** 3)
vram_stats = f"Used VRAM: {vram_used:.2f} GB / Total VRAM: {vram_total:.2f} GB"
# Hard Drive Space
hard_drive = psutil.disk_usage("/")
used_space = hard_drive.used / (1024 ** 3)
total_space = hard_drive.total / (1024 ** 3)
hard_drive_stats = f"Used Space: {used_space:.2f} GB / Total Space: {total_space:.2f} GB"
return [ram_stats, vram_stats, hard_drive_stats]
# return x and y resolution of an image (torch tensor)
def getResolutionByTensor(image=None) -> dict:
res = {"x": 0, "y": 0}
if image is not None:
img = image.movedim(-1, 1)
res["x"] = img.shape[3]
res["y"] = img.shape[2]
return res
# by https://stackoverflow.com/questions/6080477/how-to-get-the-size-of-tar-gz-in-mb-file-in-python
def get_size(path):
size = os.path.getsize(path)
if size < 1024:
return f"{size} bytes"
elif size < pow(1024, 2):
return f"{round(size / 1024, 2)} KB"
elif size < pow(1024, 3):
return f"{round(size / (pow(1024, 2)), 2)} MB"
elif size < pow(1024, 4):
return f"{round(size / (pow(1024, 3)), 2)} GB"
def get_nested_value(data, dotted_key, default=None):
keys = dotted_key.split('.')
for key in keys:
if isinstance(data, dict) and key in data:
data = data[key]
else:
return default
return data
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