mirror of
https://github.com/invoke-ai/InvokeAI
synced 2024-08-30 20:32:17 +00:00
replaced remaining print statements with log.*()
This commit is contained in:
Lincoln Stein
parent
0b0e6fe448
commit
b164330e3c
@ -3,8 +3,9 @@
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import os
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from argparse import Namespace
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from ..services.latent_storage import DiskLatentsStorage, ForwardCacheLatentsStorage
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import invokeai.backend.util.logging as log
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from ..services.latent_storage import DiskLatentsStorage, ForwardCacheLatentsStorage
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from ...backend import Globals
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from ..services.model_manager_initializer import get_model_manager
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from ..services.restoration_services import RestorationServices
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@ -47,8 +48,7 @@ class ApiDependencies:
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Globals.disable_xformers = not config.xformers
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Globals.ckpt_convert = config.ckpt_convert
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# TODO: Use a logger
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print(f">> Internet connectivity is {Globals.internet_available}")
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log.info(f"Internet connectivity is {Globals.internet_available}")
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events = FastAPIEventService(event_handler_id)
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@ -4,6 +4,7 @@ import shutil
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import asyncio
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from typing import Annotated, Any, List, Literal, Optional, Union
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import invokeai.backend.util.logging as log
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from fastapi.routing import APIRouter, HTTPException
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from pydantic import BaseModel, Field, parse_obj_as
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from pathlib import Path
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@ -115,16 +116,16 @@ async def delete_model(model_name: str) -> None:
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model_exists = model_name in model_names
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# check if model exists
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print(f">> Checking for model {model_name}...")
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log.info(f"Checking for model {model_name}...")
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if model_exists:
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print(f">> Deleting Model: {model_name}")
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log.info(f"Deleting Model: {model_name}")
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ApiDependencies.invoker.services.model_manager.del_model(model_name, delete_files=True)
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print(f">> Model Deleted: {model_name}")
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log.info(f"Model Deleted: {model_name}")
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raise HTTPException(status_code=204, detail=f"Model '{model_name}' deleted successfully")
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else:
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print(f">> Model not found")
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log.error(f"Model not found")
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raise HTTPException(status_code=404, detail=f"Model '{model_name}' not found")
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@ -7,6 +7,7 @@ from pydantic import BaseModel, Field
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import networkx as nx
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import matplotlib.pyplot as plt
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import invokeai.backend.util.logging as log
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from ..models.image import ImageField
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from ..services.graph import GraphExecutionState
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from ..services.invoker import Invoker
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@ -183,7 +184,7 @@ class HistoryCommand(BaseCommand):
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for i in range(min(self.count, len(history))):
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entry_id = history[-1 - i]
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entry = context.get_session().graph.get_node(entry_id)
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print(f"{entry_id}: {get_invocation_command(entry)}")
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log.info(f"{entry_id}: {get_invocation_command(entry)}")
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class SetDefaultCommand(BaseCommand):
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@ -10,6 +10,7 @@ import shlex
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from pathlib import Path
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from typing import List, Dict, Literal, get_args, get_type_hints, get_origin
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import invokeai.backend.util.logging as log
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from ...backend import ModelManager, Globals
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from ..invocations.baseinvocation import BaseInvocation
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from .commands import BaseCommand
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@ -160,8 +161,8 @@ def set_autocompleter(model_manager: ModelManager) -> Completer:
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pass
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except OSError: # file likely corrupted
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newname = f"{histfile}.old"
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print(
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f"## Your history file {histfile} couldn't be loaded and may be corrupted. Renaming it to {newname}"
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log.error(
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f"Your history file {histfile} couldn't be loaded and may be corrupted. Renaming it to {newname}"
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)
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histfile.replace(Path(newname))
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atexit.register(readline.write_history_file, histfile)
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@ -13,6 +13,7 @@ from typing import (
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from pydantic import BaseModel
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from pydantic.fields import Field
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import invokeai.backend.util.logging as log
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from .services.latent_storage import DiskLatentsStorage, ForwardCacheLatentsStorage
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from ..backend import Args
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@ -125,7 +126,7 @@ def invoke_all(context: CliContext):
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# Print any errors
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if context.session.has_error():
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for n in context.session.errors:
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print(
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log.error(
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f"Error in node {n} (source node {context.session.prepared_source_mapping[n]}): {context.session.errors[n]}"
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)
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@ -279,12 +280,12 @@ def invoke_cli():
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invoke_all(context)
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except InvalidArgs:
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print('Invalid command, use "help" to list commands')
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log.warning('Invalid command, use "help" to list commands')
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continue
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except SessionError:
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# Start a new session
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print("Session error: creating a new session")
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log.warning("Session error: creating a new session")
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context.session = context.invoker.create_execution_state()
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except ExitCli:
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@ -1,3 +1,4 @@
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import invokeai.backend.util.logging as log
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from invokeai.app.invocations.baseinvocation import InvocationContext
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from invokeai.backend.model_management.model_manager import ModelManager
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@ -7,5 +8,5 @@ def choose_model(model_manager: ModelManager, model_name: str):
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if model_manager.valid_model(model_name):
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return model_manager.get_model(model_name)
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else:
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print(f"* Warning: '{model_name}' is not a valid model name. Using default model instead.")
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log.warning(f"'{model_name}' is not a valid model name. Using default model instead.")
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return model_manager.get_model()
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@ -7,6 +7,7 @@ from omegaconf import OmegaConf
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from pathlib import Path
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import invokeai.version
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import invokeai.backend.util.logging as log
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from ...backend import ModelManager
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from ...backend.util import choose_precision, choose_torch_device
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from ...backend import Globals
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@ -20,8 +21,8 @@ def get_model_manager(config: Args) -> ModelManager:
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config, FileNotFoundError(f"The file {config_file} could not be found.")
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)
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print(f">> {invokeai.version.__app_name__}, version {invokeai.version.__version__}")
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print(f'>> InvokeAI runtime directory is "{Globals.root}"')
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log.info(f"{invokeai.version.__app_name__}, version {invokeai.version.__version__}")
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log.info(f'InvokeAI runtime directory is "{Globals.root}"')
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# these two lines prevent a horrible warning message from appearing
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# when the frozen CLIP tokenizer is imported
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@ -66,7 +67,7 @@ def get_model_manager(config: Args) -> ModelManager:
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except (FileNotFoundError, TypeError, AssertionError) as e:
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report_model_error(config, e)
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except (IOError, KeyError) as e:
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print(f"{e}. Aborting.")
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log.error(f"{e}. Aborting.")
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sys.exit(-1)
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# try to autoconvert new models
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@ -80,14 +81,14 @@ def get_model_manager(config: Args) -> ModelManager:
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return model_manager
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def report_model_error(opt: Namespace, e: Exception):
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print(f'** An error occurred while attempting to initialize the model: "{str(e)}"')
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print(
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"** This can be caused by a missing or corrupted models file, and can sometimes be fixed by (re)installing the models."
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log.error(f'An error occurred while attempting to initialize the model: "{str(e)}"')
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log.error(
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"This can be caused by a missing or corrupted models file, and can sometimes be fixed by (re)installing the models."
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)
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yes_to_all = os.environ.get("INVOKE_MODEL_RECONFIGURE")
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if yes_to_all:
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print(
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"** Reconfiguration is being forced by environment variable INVOKE_MODEL_RECONFIGURE"
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log.warning
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"Reconfiguration is being forced by environment variable INVOKE_MODEL_RECONFIGURE"
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)
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else:
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response = input(
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@ -96,7 +97,7 @@ def report_model_error(opt: Namespace, e: Exception):
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if response.startswith(("n", "N")):
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return
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print("invokeai-configure is launching....\n")
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log.info("invokeai-configure is launching....\n")
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# Match arguments that were set on the CLI
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# only the arguments accepted by the configuration script are parsed
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@ -1,6 +1,7 @@
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import sys
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import traceback
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import torch
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import invokeai.backend.util.logging as log
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from ...backend.restoration import Restoration
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from ...backend.util import choose_torch_device, CPU_DEVICE, MPS_DEVICE
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@ -20,16 +21,16 @@ class RestorationServices:
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args.gfpgan_model_path
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)
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else:
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print(">> Face restoration disabled")
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log.info("Face restoration disabled")
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if args.esrgan:
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esrgan = restoration.load_esrgan(args.esrgan_bg_tile)
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else:
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print(">> Upscaling disabled")
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log.info("Upscaling disabled")
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else:
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print(">> Face restoration and upscaling disabled")
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log.info("Face restoration and upscaling disabled")
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except (ModuleNotFoundError, ImportError):
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print(traceback.format_exc(), file=sys.stderr)
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print(">> You may need to install the ESRGAN and/or GFPGAN modules")
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log.info("You may need to install the ESRGAN and/or GFPGAN modules")
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self.device = torch.device(choose_torch_device())
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self.gfpgan = gfpgan
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self.codeformer = codeformer
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@ -58,15 +59,15 @@ class RestorationServices:
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if self.gfpgan is not None or self.codeformer is not None:
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if facetool == "gfpgan":
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if self.gfpgan is None:
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print(
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">> GFPGAN not found. Face restoration is disabled."
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log.info(
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"GFPGAN not found. Face restoration is disabled."
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)
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else:
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image = self.gfpgan.process(image, strength, seed)
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if facetool == "codeformer":
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if self.codeformer is None:
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print(
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">> CodeFormer not found. Face restoration is disabled."
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log.info(
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"CodeFormer not found. Face restoration is disabled."
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)
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else:
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cf_device = (
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@ -80,7 +81,7 @@ class RestorationServices:
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fidelity=codeformer_fidelity,
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)
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else:
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print(">> Face Restoration is disabled.")
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log.info("Face Restoration is disabled.")
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if upscale is not None:
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if self.esrgan is not None:
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if len(upscale) < 2:
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@ -93,10 +94,10 @@ class RestorationServices:
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denoise_str=upscale_denoise_str,
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)
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else:
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print(">> ESRGAN is disabled. Image not upscaled.")
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log.info("ESRGAN is disabled. Image not upscaled.")
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except Exception as e:
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print(
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f">> Error running RealESRGAN or GFPGAN. Your image was not upscaled.\n{e}"
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log.info(
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f"Error running RealESRGAN or GFPGAN. Your image was not upscaled.\n{e}"
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)
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if image_callback is not None:
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@ -1088,7 +1088,7 @@ class Generate:
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image = img
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log.info(f"using provided input image of size {image.width}x{image.height}")
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elif isinstance(img, str):
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assert os.path.exists(img), f">> {img}: File not found"
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assert os.path.exists(img), f"{img}: File not found"
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image = Image.open(img)
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log.info(
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@ -1,5 +1,6 @@
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# Copyright (c) 2023 Lincoln D. Stein and The InvokeAI Development Team
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"""invokeai.util.logging
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Copyright 2023 The InvokeAI Development Team
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Logging class for InvokeAI that produces console messages that follow
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the conventions established in InvokeAI 1.X through 2.X.
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@ -22,6 +22,7 @@ import torch
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from npyscreen import widget
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from omegaconf import OmegaConf
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import invokeai.backend.logging as log
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from invokeai.backend.globals import Globals, global_config_dir
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from ...backend.config.model_install_backend import (
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@ -455,8 +456,8 @@ def main():
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Globals.root = os.path.expanduser(get_root(opt.root) or "")
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if not global_config_dir().exists():
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print(
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">> Your InvokeAI root directory is not set up. Calling invokeai-configure."
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log.info(
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"Your InvokeAI root directory is not set up. Calling invokeai-configure."
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)
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from invokeai.frontend.install import invokeai_configure
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@ -466,18 +467,18 @@ def main():
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try:
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select_and_download_models(opt)
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except AssertionError as e:
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print(str(e))
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log.error(e)
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sys.exit(-1)
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except KeyboardInterrupt:
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print("\nGoodbye! Come back soon.")
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log.info("Goodbye! Come back soon.")
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except widget.NotEnoughSpaceForWidget as e:
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if str(e).startswith("Height of 1 allocated"):
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print(
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"** Insufficient vertical space for the interface. Please make your window taller and try again"
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log.error(
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"Insufficient vertical space for the interface. Please make your window taller and try again"
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)
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elif str(e).startswith("addwstr"):
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print(
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"** Insufficient horizontal space for the interface. Please make your window wider and try again."
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log.error(
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"Insufficient horizontal space for the interface. Please make your window wider and try again."
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)
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@ -27,6 +27,8 @@ from ...backend.globals import (
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global_models_dir,
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global_set_root,
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)
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import invokeai.backend.util.logging as log
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from ...backend.model_management import ModelManager
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from ...frontend.install.widgets import FloatTitleSlider
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@ -113,7 +115,7 @@ def merge_diffusion_models_and_commit(
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model_name=merged_model_name, description=f'Merge of models {", ".join(models)}'
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)
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if vae := model_manager.config[models[0]].get("vae", None):
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print(f">> Using configured VAE assigned to {models[0]}")
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log.info(f"Using configured VAE assigned to {models[0]}")
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import_args.update(vae=vae)
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model_manager.import_diffuser_model(dump_path, **import_args)
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model_manager.commit(config_file)
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@ -391,10 +393,8 @@ class mergeModelsForm(npyscreen.FormMultiPageAction):
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for name in self.model_manager.model_names()
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if self.model_manager.model_info(name).get("format") == "diffusers"
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]
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print(model_names)
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return sorted(model_names)
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class Mergeapp(npyscreen.NPSAppManaged):
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def __init__(self):
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super().__init__()
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@ -414,7 +414,7 @@ def run_gui(args: Namespace):
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args = mergeapp.merge_arguments
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merge_diffusion_models_and_commit(**args)
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print(f'>> Models merged into new model: "{args["merged_model_name"]}".')
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log.info(f'Models merged into new model: "{args["merged_model_name"]}".')
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def run_cli(args: Namespace):
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@ -425,8 +425,8 @@ def run_cli(args: Namespace):
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if not args.merged_model_name:
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args.merged_model_name = "+".join(args.models)
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print(
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f'>> No --merged_model_name provided. Defaulting to "{args.merged_model_name}"'
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log.info(
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f'No --merged_model_name provided. Defaulting to "{args.merged_model_name}"'
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)
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model_manager = ModelManager(OmegaConf.load(global_config_file()))
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@ -435,7 +435,7 @@ def run_cli(args: Namespace):
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), f'A model named "{args.merged_model_name}" already exists. Use --clobber to overwrite.'
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merge_diffusion_models_and_commit(**vars(args))
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print(f'>> Models merged into new model: "{args.merged_model_name}".')
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log.info(f'Models merged into new model: "{args.merged_model_name}".')
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def main():
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@ -455,17 +455,16 @@ def main():
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run_cli(args)
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except widget.NotEnoughSpaceForWidget as e:
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if str(e).startswith("Height of 1 allocated"):
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print(
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"** You need to have at least two diffusers models defined in models.yaml in order to merge"
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log.error(
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"You need to have at least two diffusers models defined in models.yaml in order to merge"
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)
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else:
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print(
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"** Not enough room for the user interface. Try making this window larger."
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log.error(
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"Not enough room for the user interface. Try making this window larger."
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)
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sys.exit(-1)
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except Exception:
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print(">> An error occurred:")
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traceback.print_exc()
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except Exception as e:
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log.error(e)
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sys.exit(-1)
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except KeyboardInterrupt:
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sys.exit(-1)
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@ -20,6 +20,7 @@ import npyscreen
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from npyscreen import widget
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from omegaconf import OmegaConf
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import invokeai.backend.util.logging as log
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from invokeai.backend.globals import Globals, global_set_root
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from ...backend.training import do_textual_inversion_training, parse_args
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@ -368,14 +369,14 @@ def copy_to_embeddings_folder(args: dict):
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dest_dir_name = args["placeholder_token"].strip("<>")
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destination = Path(Globals.root, "embeddings", dest_dir_name)
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os.makedirs(destination, exist_ok=True)
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print(f">> Training completed. Copying learned_embeds.bin into {str(destination)}")
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log.info(f"Training completed. Copying learned_embeds.bin into {str(destination)}")
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shutil.copy(source, destination)
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if (
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input("Delete training logs and intermediate checkpoints? [y] ") or "y"
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).startswith(("y", "Y")):
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shutil.rmtree(Path(args["output_dir"]))
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else:
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print(f'>> Keeping {args["output_dir"]}')
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log.info(f'Keeping {args["output_dir"]}')
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def save_args(args: dict):
|
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@ -422,10 +423,10 @@ def do_front_end(args: Namespace):
|
||||
do_textual_inversion_training(**args)
|
||||
copy_to_embeddings_folder(args)
|
||||
except Exception as e:
|
||||
print("** An exception occurred during training. The exception was:")
|
||||
print(str(e))
|
||||
print("** DETAILS:")
|
||||
print(traceback.format_exc())
|
||||
log.error("An exception occurred during training. The exception was:")
|
||||
log.error(str(e))
|
||||
log.error("DETAILS:")
|
||||
log.error(traceback.format_exc())
|
||||
|
||||
|
||||
def main():
|
||||
@ -437,21 +438,21 @@ def main():
|
||||
else:
|
||||
do_textual_inversion_training(**vars(args))
|
||||
except AssertionError as e:
|
||||
print(str(e))
|
||||
log.error(e)
|
||||
sys.exit(-1)
|
||||
except KeyboardInterrupt:
|
||||
pass
|
||||
except (widget.NotEnoughSpaceForWidget, Exception) as e:
|
||||
if str(e).startswith("Height of 1 allocated"):
|
||||
print(
|
||||
"** You need to have at least one diffusers models defined in models.yaml in order to train"
|
||||
log.error(
|
||||
"You need to have at least one diffusers models defined in models.yaml in order to train"
|
||||
)
|
||||
elif str(e).startswith("addwstr"):
|
||||
print(
|
||||
"** Not enough window space for the interface. Please make your window larger and try again."
|
||||
log.error(
|
||||
"Not enough window space for the interface. Please make your window larger and try again."
|
||||
)
|
||||
else:
|
||||
print(f"** An error has occurred: {str(e)}")
|
||||
log.error(e)
|
||||
sys.exit(-1)
|
||||
|
||||
|
||||
|
||||
Loading…
Reference in New Issue
Block a user