replaced remaining print statements with log.*()

invokeai/app/api/dependencies.py

@@ -3,8 +3,9 @@
 import os
 from argparse import Namespace
 
-from ..services.latent_storage import DiskLatentsStorage, ForwardCacheLatentsStorage
+import invokeai.backend.util.logging as log
 
+from ..services.latent_storage import DiskLatentsStorage, ForwardCacheLatentsStorage
 from ...backend import Globals
 from ..services.model_manager_initializer import get_model_manager
 from ..services.restoration_services import RestorationServices
@@ -47,8 +48,7 @@ class ApiDependencies:
         Globals.disable_xformers = not config.xformers
         Globals.ckpt_convert = config.ckpt_convert
 
-        # TODO: Use a logger
+        log.info(f"Internet connectivity is {Globals.internet_available}")
-        print(f">> Internet connectivity is {Globals.internet_available}")
 
         events = FastAPIEventService(event_handler_id)
 

invokeai/app/api/routers/models.py

@@ -4,6 +4,7 @@ import shutil
 import asyncio
 from typing import Annotated, Any, List, Literal, Optional, Union
 
+import invokeai.backend.util.logging as log
 from fastapi.routing import APIRouter, HTTPException
 from pydantic import BaseModel, Field, parse_obj_as
 from pathlib import Path
@@ -115,16 +116,16 @@ async def delete_model(model_name: str) -> None:
     model_exists = model_name in model_names
 
     # check if model exists
-    print(f">> Checking for model {model_name}...")
+    log.info(f"Checking for model {model_name}...")
            
     if model_exists:
-        print(f">> Deleting Model: {model_name}")
+        log.info(f"Deleting Model: {model_name}")
         ApiDependencies.invoker.services.model_manager.del_model(model_name, delete_files=True)
-        print(f">> Model Deleted: {model_name}")
+        log.info(f"Model Deleted: {model_name}")
         raise HTTPException(status_code=204, detail=f"Model '{model_name}' deleted successfully")
     
     else:
-        print(f">> Model not found")
+        log.error(f"Model not found")
         raise HTTPException(status_code=404, detail=f"Model '{model_name}' not found")
     
 

invokeai/app/cli/commands.py

@@ -7,6 +7,7 @@ from pydantic import BaseModel, Field
 import networkx as nx
 import matplotlib.pyplot as plt
 
+import invokeai.backend.util.logging as log
 from ..models.image import ImageField
 from ..services.graph import GraphExecutionState
 from ..services.invoker import Invoker
@@ -183,7 +184,7 @@ class HistoryCommand(BaseCommand):
         for i in range(min(self.count, len(history))):
             entry_id = history[-1 - i]
             entry = context.get_session().graph.get_node(entry_id)
-            print(f"{entry_id}: {get_invocation_command(entry)}")
+            log.info(f"{entry_id}: {get_invocation_command(entry)}")
 
 
 class SetDefaultCommand(BaseCommand):

invokeai/app/cli/completer.py

@@ -10,6 +10,7 @@ import shlex
 from pathlib import Path
 from typing import List, Dict, Literal, get_args, get_type_hints, get_origin
 
+import invokeai.backend.util.logging as log
 from ...backend import ModelManager, Globals
 from ..invocations.baseinvocation import BaseInvocation
 from .commands import BaseCommand
@@ -160,8 +161,8 @@ def set_autocompleter(model_manager: ModelManager) -> Completer:
         pass
     except OSError:  # file likely corrupted
         newname = f"{histfile}.old"
-        print(
+        log.error(
-            f"## Your history file {histfile} couldn't be loaded and may be corrupted. Renaming it to {newname}"
+            f"Your history file {histfile} couldn't be loaded and may be corrupted. Renaming it to {newname}"
         )
         histfile.replace(Path(newname))
     atexit.register(readline.write_history_file, histfile)

invokeai/app/cli_app.py

@@ -13,6 +13,7 @@ from typing import (
 from pydantic import BaseModel
 from pydantic.fields import Field
 
+import invokeai.backend.util.logging as log
 from .services.latent_storage import DiskLatentsStorage, ForwardCacheLatentsStorage
 
 from ..backend import Args
@@ -125,7 +126,7 @@ def invoke_all(context: CliContext):
     # Print any errors
     if context.session.has_error():
         for n in context.session.errors:
-            print(
+            log.error(
                 f"Error in node {n} (source node {context.session.prepared_source_mapping[n]}): {context.session.errors[n]}"
             )
         
@@ -279,12 +280,12 @@ def invoke_cli():
             invoke_all(context)
 
         except InvalidArgs:
-            print('Invalid command, use "help" to list commands')
+            log.warning('Invalid command, use "help" to list commands')
             continue
 
         except SessionError:
             # Start a new session
-            print("Session error: creating a new session")
+            log.warning("Session error: creating a new session")
             context.session = context.invoker.create_execution_state()
 
         except ExitCli:

invokeai/app/invocations/util/get_model.py

@@ -1,3 +1,4 @@
+import invokeai.backend.util.logging as log
 from invokeai.app.invocations.baseinvocation import InvocationContext
 from invokeai.backend.model_management.model_manager import ModelManager
 
@@ -7,5 +8,5 @@ def choose_model(model_manager: ModelManager, model_name: str):
     if model_manager.valid_model(model_name):
         return model_manager.get_model(model_name)
     else:
-        print(f"* Warning: '{model_name}' is not a valid model name. Using default model instead.")
+        log.warning(f"'{model_name}' is not a valid model name. Using default model instead.")
         return model_manager.get_model()

invokeai/app/services/model_manager_initializer.py

@@ -7,6 +7,7 @@ from omegaconf import OmegaConf
 from pathlib import Path
 
 import invokeai.version
+import invokeai.backend.util.logging as log
 from ...backend import ModelManager
 from ...backend.util import choose_precision, choose_torch_device
 from ...backend import Globals
@@ -20,8 +21,8 @@ def get_model_manager(config: Args) -> ModelManager:
                 config, FileNotFoundError(f"The file {config_file} could not be found.")
             )
 
-    print(f">> {invokeai.version.__app_name__}, version {invokeai.version.__version__}")
+    log.info(f"{invokeai.version.__app_name__}, version {invokeai.version.__version__}")
-    print(f'>> InvokeAI runtime directory is "{Globals.root}"')
+    log.info(f'InvokeAI runtime directory is "{Globals.root}"')
 
     # these two lines prevent a horrible warning message from appearing
     # when the frozen CLIP tokenizer is imported
@@ -66,7 +67,7 @@ def get_model_manager(config: Args) -> ModelManager:
     except (FileNotFoundError, TypeError, AssertionError) as e:
         report_model_error(config, e)
     except (IOError, KeyError) as e:
-        print(f"{e}. Aborting.")
+        log.error(f"{e}. Aborting.")
         sys.exit(-1)
 
     # try to autoconvert new models
@@ -80,14 +81,14 @@ def get_model_manager(config: Args) -> ModelManager:
     return model_manager
 
 def report_model_error(opt: Namespace, e: Exception):
-    print(f'** An error occurred while attempting to initialize the model: "{str(e)}"')
+    log.error(f'An error occurred while attempting to initialize the model: "{str(e)}"')
-    print(
+    log.error(
-        "** This can be caused by a missing or corrupted models file, and can sometimes be fixed by (re)installing the models."
+        "This can be caused by a missing or corrupted models file, and can sometimes be fixed by (re)installing the models."
     )
     yes_to_all = os.environ.get("INVOKE_MODEL_RECONFIGURE")
     if yes_to_all:
-        print(
+        log.warning
-            "** Reconfiguration is being forced by environment variable INVOKE_MODEL_RECONFIGURE"
+            "Reconfiguration is being forced by environment variable INVOKE_MODEL_RECONFIGURE"
         )
     else:
         response = input(
@@ -96,7 +97,7 @@ def report_model_error(opt: Namespace, e: Exception):
         if response.startswith(("n", "N")):
             return
 
-    print("invokeai-configure is launching....\n")
+    log.info("invokeai-configure is launching....\n")
 
     # Match arguments that were set on the CLI
     # only the arguments accepted by the configuration script are parsed

invokeai/app/services/restoration_services.py

@@ -1,6 +1,7 @@
 import sys
 import traceback
 import torch
+import invokeai.backend.util.logging as log
 from ...backend.restoration import Restoration
 from ...backend.util import choose_torch_device, CPU_DEVICE, MPS_DEVICE
 
@@ -20,16 +21,16 @@ class RestorationServices:
                         args.gfpgan_model_path
                     )
                 else:
-                    print(">> Face restoration disabled")
+                    log.info("Face restoration disabled")
                     if args.esrgan:
                         esrgan = restoration.load_esrgan(args.esrgan_bg_tile)
                     else:
-                        print(">> Upscaling disabled")
+                        log.info("Upscaling disabled")
             else:
-                print(">> Face restoration and upscaling disabled")
+                log.info("Face restoration and upscaling disabled")
         except (ModuleNotFoundError, ImportError):
             print(traceback.format_exc(), file=sys.stderr)
-            print(">> You may need to install the ESRGAN and/or GFPGAN modules")
+            log.info("You may need to install the ESRGAN and/or GFPGAN modules")
         self.device = torch.device(choose_torch_device())
         self.gfpgan = gfpgan
         self.codeformer = codeformer
@@ -58,15 +59,15 @@ class RestorationServices:
                     if self.gfpgan is not None or self.codeformer is not None:
                         if facetool == "gfpgan":
                             if self.gfpgan is None:
-                                print(
+                                log.info(
-                                    ">> GFPGAN not found. Face restoration is disabled."
+                                    "GFPGAN not found. Face restoration is disabled."
                                 )
                             else:
                                 image = self.gfpgan.process(image, strength, seed)
                         if facetool == "codeformer":
                             if self.codeformer is None:
-                                print(
+                                log.info(
-                                    ">> CodeFormer not found. Face restoration is disabled."
+                                    "CodeFormer not found. Face restoration is disabled."
                                 )
                             else:
                                 cf_device = (
@@ -80,7 +81,7 @@ class RestorationServices:
                                     fidelity=codeformer_fidelity,
                                 )
                     else:
-                        print(">> Face Restoration is disabled.")
+                        log.info("Face Restoration is disabled.")
                 if upscale is not None:
                     if self.esrgan is not None:
                         if len(upscale) < 2:
@@ -93,10 +94,10 @@ class RestorationServices:
                             denoise_str=upscale_denoise_str,
                         )
                     else:
-                        print(">> ESRGAN is disabled. Image not upscaled.")
+                        log.info("ESRGAN is disabled. Image not upscaled.")
             except Exception as e:
-                print(
+                log.info(
-                    f">> Error running RealESRGAN or GFPGAN. Your image was not upscaled.\n{e}"
+                    f"Error running RealESRGAN or GFPGAN. Your image was not upscaled.\n{e}"
                 )
 
             if image_callback is not None:

invokeai/backend/generate.py

@@ -1088,7 +1088,7 @@ class Generate:
             image = img
             log.info(f"using provided input image of size {image.width}x{image.height}")
         elif isinstance(img, str):
-            assert os.path.exists(img), f">> {img}: File not found"
+            assert os.path.exists(img), f"{img}: File not found"
 
             image = Image.open(img)
             log.info(

invokeai/backend/util/logging.py

@@ -1,5 +1,6 @@
+# Copyright (c) 2023 Lincoln D. Stein and The InvokeAI Development Team
+
 """invokeai.util.logging
-Copyright 2023 The InvokeAI Development Team
 
 Logging class for InvokeAI that produces console messages that follow
 the conventions established in InvokeAI 1.X through 2.X.

invokeai/frontend/install/model_install.py

@@ -22,6 +22,7 @@ import torch
 from npyscreen import widget
 from omegaconf import OmegaConf
 
+import invokeai.backend.logging as log
 from invokeai.backend.globals import Globals, global_config_dir
 
 from ...backend.config.model_install_backend import (
@@ -455,8 +456,8 @@ def main():
     Globals.root = os.path.expanduser(get_root(opt.root) or "")
 
     if not global_config_dir().exists():
-        print(
+        log.info(
-            ">> Your InvokeAI root directory is not set up. Calling invokeai-configure."
+            "Your InvokeAI root directory is not set up. Calling invokeai-configure."
         )
         from invokeai.frontend.install import invokeai_configure
 
@@ -466,18 +467,18 @@ def main():
     try:
         select_and_download_models(opt)
     except AssertionError as e:
-        print(str(e))
+        log.error(e)
         sys.exit(-1)
     except KeyboardInterrupt:
-        print("\nGoodbye! Come back soon.")
+        log.info("Goodbye! Come back soon.")
     except widget.NotEnoughSpaceForWidget as e:
         if str(e).startswith("Height of 1 allocated"):
-            print(
+            log.error(
-                "** Insufficient vertical space for the interface. Please make your window taller and try again"
+                "Insufficient vertical space for the interface. Please make your window taller and try again"
             )
         elif str(e).startswith("addwstr"):
-            print(
+            log.error(
-                "** Insufficient horizontal space for the interface. Please make your window wider and try again."
+                "Insufficient horizontal space for the interface. Please make your window wider and try again."
             )
 
 

invokeai/frontend/merge/merge_diffusers.py

@@ -27,6 +27,8 @@ from ...backend.globals import (
     global_models_dir,
     global_set_root,
 )
+
+import invokeai.backend.util.logging as log
 from ...backend.model_management import ModelManager
 from ...frontend.install.widgets import FloatTitleSlider
 
@@ -113,7 +115,7 @@ def merge_diffusion_models_and_commit(
         model_name=merged_model_name, description=f'Merge of models {", ".join(models)}'
     )
     if vae := model_manager.config[models[0]].get("vae", None):
-        print(f">> Using configured VAE assigned to {models[0]}")
+        log.info(f"Using configured VAE assigned to {models[0]}")
         import_args.update(vae=vae)
     model_manager.import_diffuser_model(dump_path, **import_args)
     model_manager.commit(config_file)
@@ -391,10 +393,8 @@ class mergeModelsForm(npyscreen.FormMultiPageAction):
             for name in self.model_manager.model_names()
             if self.model_manager.model_info(name).get("format") == "diffusers"
         ]
-        print(model_names)
         return sorted(model_names)
 
-
 class Mergeapp(npyscreen.NPSAppManaged):
     def __init__(self):
         super().__init__()
@@ -414,7 +414,7 @@ def run_gui(args: Namespace):
 
     args = mergeapp.merge_arguments
     merge_diffusion_models_and_commit(**args)
-    print(f'>> Models merged into new model: "{args["merged_model_name"]}".')
+    log.info(f'Models merged into new model: "{args["merged_model_name"]}".')
 
 
 def run_cli(args: Namespace):
@@ -425,8 +425,8 @@ def run_cli(args: Namespace):
 
     if not args.merged_model_name:
         args.merged_model_name = "+".join(args.models)
-        print(
+        log.info(
-            f'>> No --merged_model_name provided. Defaulting to "{args.merged_model_name}"'
+            f'No --merged_model_name provided. Defaulting to "{args.merged_model_name}"'
         )
 
         model_manager = ModelManager(OmegaConf.load(global_config_file()))
@@ -435,7 +435,7 @@ def run_cli(args: Namespace):
         ), f'A model named "{args.merged_model_name}" already exists. Use --clobber to overwrite.'
 
         merge_diffusion_models_and_commit(**vars(args))
-        print(f'>> Models merged into new model: "{args.merged_model_name}".')
+        log.info(f'Models merged into new model: "{args.merged_model_name}".')
 
 
 def main():
@@ -455,17 +455,16 @@ def main():
             run_cli(args)
     except widget.NotEnoughSpaceForWidget as e:
         if str(e).startswith("Height of 1 allocated"):
-            print(
+            log.error(
-                "** You need to have at least two diffusers models defined in models.yaml in order to merge"
+                "You need to have at least two diffusers models defined in models.yaml in order to merge"
             )
         else:
-            print(
+            log.error(
-                "** Not enough room for the user interface. Try making this window larger."
+                "Not enough room for the user interface. Try making this window larger."
             )
         sys.exit(-1)
-    except Exception:
+    except Exception as e:
-        print(">> An error occurred:")
+        log.error(e)
-        traceback.print_exc()
         sys.exit(-1)
     except KeyboardInterrupt:
         sys.exit(-1)

invokeai/frontend/training/textual_inversion.py

@@ -20,6 +20,7 @@ import npyscreen
 from npyscreen import widget
 from omegaconf import OmegaConf
 
+import invokeai.backend.util.logging as log
 from invokeai.backend.globals import Globals, global_set_root
 
 from ...backend.training import do_textual_inversion_training, parse_args
@@ -368,14 +369,14 @@ def copy_to_embeddings_folder(args: dict):
     dest_dir_name = args["placeholder_token"].strip("<>")
     destination = Path(Globals.root, "embeddings", dest_dir_name)
     os.makedirs(destination, exist_ok=True)
-    print(f">> Training completed. Copying learned_embeds.bin into {str(destination)}")
+    log.info(f"Training completed. Copying learned_embeds.bin into {str(destination)}")
     shutil.copy(source, destination)
     if (
         input("Delete training logs and intermediate checkpoints? [y] ") or "y"
     ).startswith(("y", "Y")):
         shutil.rmtree(Path(args["output_dir"]))
     else:
-        print(f'>> Keeping {args["output_dir"]}')
+        log.info(f'Keeping {args["output_dir"]}')
 
 
 def save_args(args: dict):
@@ -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:")
+            log.error("An exception occurred during training. The exception was:")
-            print(str(e))
+            log.error(str(e))
-            print("** DETAILS:")
+            log.error("DETAILS:")
-            print(traceback.format_exc())
+            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(
+            log.error(
-                "** You need to have at least one diffusers models defined in models.yaml in order to train"
+                "You need to have at least one diffusers models defined in models.yaml in order to train"
             )
         elif str(e).startswith("addwstr"):
-            print(
+            log.error(
-                "** Not enough window space for the interface. Please make your window larger and try again."
+                "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)