resolve conflicts

invokeai/app/api_app.py

@@ -14,13 +14,12 @@ from fastapi_events.middleware import EventHandlerASGIMiddleware
 from pathlib import Path
 from pydantic.schema import schema
 
-# Do this early so that other modules pick up configuration
+#This should come early so that modules can log their initialization properly
 from .services.config import InvokeAIAppConfig
+from ..backend.util.logging import InvokeAILogger
 app_config = InvokeAIAppConfig.get_config()
 app_config.parse_args()
-
+logger = InvokeAILogger.getLogger(config=app_config)
-from invokeai.backend.util.logging import InvokeAILogger
-logger = InvokeAILogger.getLogger()
 
 import invokeai.frontend.web as web_dir
 

invokeai/app/cli_app.py

@@ -11,19 +11,26 @@ from typing import Union, get_type_hints
 from pydantic import BaseModel, ValidationError
 from pydantic.fields import Field
 
+# This should come early so that the logger can pick up its configuration options
+from .services.config import InvokeAIAppConfig
 from invokeai.backend.util.logging import InvokeAILogger
+config = InvokeAIAppConfig.get_config()
+config.parse_args()
+logger = InvokeAILogger().getLogger(config=config)
+
 from invokeai.app.services.image_record_storage import SqliteImageRecordStorage
 from invokeai.app.services.images import ImageService
 from invokeai.app.services.metadata import CoreMetadataService
 from invokeai.app.services.resource_name import SimpleNameService
 from invokeai.app.services.urls import LocalUrlService
+from .services.default_graphs import (default_text_to_image_graph_id,
+                                      create_system_graphs)
+from .services.latent_storage import DiskLatentsStorage, ForwardCacheLatentsStorage
 
 from .cli.commands import (BaseCommand, CliContext, ExitCli,
                            SortedHelpFormatter, add_graph_parsers, add_parsers)
 from .cli.completer import set_autocompleter
 from .invocations.baseinvocation import BaseInvocation
-from .services.default_graphs import (create_system_graphs,
-                                      default_text_to_image_graph_id)
 from .services.events import EventServiceBase
 from .services.graph import (Edge, EdgeConnection, GraphExecutionState,
                              GraphInvocation, LibraryGraph,
@@ -32,13 +39,11 @@ from .services.image_file_storage import DiskImageFileStorage
 from .services.invocation_queue import MemoryInvocationQueue
 from .services.invocation_services import InvocationServices
 from .services.invoker import Invoker
-from .services.latent_storage import (DiskLatentsStorage,
-                                      ForwardCacheLatentsStorage)
 from .services.model_manager_service import ModelManagerService
 from .services.processor import DefaultInvocationProcessor
 from .services.restoration_services import RestorationServices
 from .services.sqlite import SqliteItemStorage
-from .services.config import InvokeAIAppConfig
+
 
 class CliCommand(BaseModel):
     command: Union[BaseCommand.get_commands() + BaseInvocation.get_invocations()] = Field(discriminator="type")  # type: ignore
@@ -47,7 +52,6 @@ class CliCommand(BaseModel):
 class InvalidArgs(Exception):
     pass
 
-
 def add_invocation_args(command_parser):
     # Add linking capability
     command_parser.add_argument(
@@ -192,11 +196,6 @@ def invoke_all(context: CliContext):
         raise SessionError()
 
 def invoke_cli():
-    # this gets the basic configuration
-    config = InvokeAIAppConfig.get_config()
-    config.parse_args()
-    logger = InvokeAILogger.getLogger()
-
     # get the optional list of invocations to execute on the command line
     parser = config.get_parser()
     parser.add_argument('commands',nargs='*')

invokeai/app/services/graph.py

@@ -859,11 +859,9 @@ class GraphExecutionState(BaseModel):
         if next_node is None:
             prepared_id = self._prepare()
 
-            # TODO: prepare multiple nodes at once?
+            # Prepare as many nodes as we can
-            # while prepared_id is not None and not isinstance(self.graph.nodes[prepared_id], IterateInvocation):
+            while prepared_id is not None:
-            #     prepared_id = self._prepare()
+                prepared_id = self._prepare()
-
-            if prepared_id is not None:
                 next_node = self._get_next_node()
 
         # Get values from edges
@@ -1010,14 +1008,30 @@ class GraphExecutionState(BaseModel):
         # Get flattened source graph
         g = self.graph.nx_graph_flat()
 
-        # Find next unprepared node where all source nodes are executed
+        # Find next node that:
+        # - was not already prepared
+        # - is not an iterate node whose inputs have not been executed
+        # - does not have an unexecuted iterate ancestor
         sorted_nodes = nx.topological_sort(g)
         next_node_id = next(
             (
                 n
                 for n in sorted_nodes
+                # exclude nodes that have already been prepared
                 if n not in self.source_prepared_mapping
-                and all((e[0] in self.executed for e in g.in_edges(n)))
+                # exclude iterate nodes whose inputs have not been executed
+                and not (
+                    isinstance(self.graph.get_node(n), IterateInvocation)  # `n` is an iterate node...
+                    and not all((e[0] in self.executed for e in g.in_edges(n)))  # ...that has unexecuted inputs
+                )
+                # exclude nodes who have unexecuted iterate ancestors
+                and not any(
+                    (
+                        isinstance(self.graph.get_node(a), IterateInvocation)  # `a` is an iterate ancestor of `n`...
+                        and a not in self.executed  # ...that is not executed
+                        for a in nx.ancestors(g, n)  # for all ancestors `a` of node `n`
+                    )
+                )
             ),
             None,
         )
@@ -1114,9 +1128,22 @@ class GraphExecutionState(BaseModel):
         )
 
     def _get_next_node(self) -> Optional[BaseInvocation]:
+        """Gets the deepest node that is ready to be executed"""
         g = self.execution_graph.nx_graph()
-        sorted_nodes = nx.topological_sort(g)
+
-        next_node = next((n for n in sorted_nodes if n not in self.executed), None)
+        # Depth-first search with pre-order traversal is a depth-first topological sort
+        sorted_nodes = nx.dfs_preorder_nodes(g)
+        
+        next_node = next(
+            (
+                n
+                for n in sorted_nodes
+                if n not in self.executed # the node must not already be executed...
+                and all((e[0] in self.executed for e in g.in_edges(n))) # ...and all its inputs must be executed
+            ),
+            None,
+        )
+
         if next_node is None:
             return None
 

invokeai/app/services/invoker.py

@@ -22,7 +22,8 @@ class Invoker:
     def invoke(
         self, graph_execution_state: GraphExecutionState, invoke_all: bool = False
     ) -> str | None:
-        """Determines the next node to invoke and returns the id of the invoked node, or None if there are no nodes to execute"""
+        """Determines the next node to invoke and enqueues it, preparing if needed.
+        Returns the id of the queued node, or `None` if there are no nodes left to enqueue."""
 
         # Get the next invocation
         invocation = graph_execution_state.next()

invokeai/backend/install/invokeai_configure.py

@@ -40,6 +40,7 @@ import invokeai.configs as configs
 from invokeai.app.services.config import (
     InvokeAIAppConfig,
 )
+from invokeai.backend.util.logging import InvokeAILogger
 from invokeai.frontend.install.model_install import addModelsForm, process_and_execute
 from invokeai.frontend.install.widgets import (
     CenteredButtonPress,
@@ -80,6 +81,7 @@ INIT_FILE_PREAMBLE = """# InvokeAI initialization file
 # or renaming it and then running invokeai-configure again.
 """
 
+logger=None
 
 # --------------------------------------------
 def postscript(errors: None):
@@ -824,6 +826,7 @@ def main():
     if opt.full_precision:
         invoke_args.extend(['--precision','float32'])
     config.parse_args(invoke_args)
+    logger = InvokeAILogger().getLogger(config=config)
 
     errors = set()
 

invokeai/backend/util/logging.py

@@ -1,6 +1,7 @@
 # Copyright (c) 2023 Lincoln D. Stein and The InvokeAI Development Team
 
-"""invokeai.util.logging
+"""
+invokeai.util.logging
 
 Logging class for InvokeAI that produces console messages
 
@@ -11,6 +12,7 @@ from invokeai.backend.util.logging import InvokeAILogger
 logger = InvokeAILogger.getLogger(name='InvokeAI') // Initialization
 (or)
 logger = InvokeAILogger.getLogger(__name__) // To use the filename
+logger.configure()
 
 logger.critical('this is critical') // Critical Message
 logger.error('this is an error') // Error Message
@@ -28,6 +30,149 @@ Console messages:
 Alternate Method (in this case the logger name will be set to InvokeAI):
 import invokeai.backend.util.logging as IAILogger
 IAILogger.debug('this is a debugging message')
+
+## Configuration
+
+The default configuration will print to stderr on the console. To add
+additional logging handlers, call getLogger with an initialized InvokeAIAppConfig
+object:
+
+
+ config = InvokeAIAppConfig.get_config()
+ config.parse_args()
+ logger = InvokeAILogger.getLogger(config=config)
+
+### Three command-line options control logging:
+
+`--log_handlers <handler1> <handler2> ...`
+
+This option activates one or more log handlers. Options are "console", "file", "syslog" and "http". To specify more than one, separate them by spaces:
+
+```
+invokeai-web --log_handlers console syslog=/dev/log file=C:\\Users\\fred\\invokeai.log
+```
+
+The format of these options is described below.
+
+### `--log_format {plain|color|legacy|syslog}`
+
+This controls the format of log messages written to the console. Only the "console" log handler is currently affected by this setting.
+
+* "plain" provides formatted messages like this:
+
+```bash
+
+[2023-05-24 23:18:2[2023-05-24 23:18:50,352]::[InvokeAI]::DEBUG --> this is a debug message
+[2023-05-24 23:18:50,352]::[InvokeAI]::INFO --> this is an informational messages
+[2023-05-24 23:18:50,352]::[InvokeAI]::WARNING --> this is a warning
+[2023-05-24 23:18:50,352]::[InvokeAI]::ERROR --> this is an error
+[2023-05-24 23:18:50,352]::[InvokeAI]::CRITICAL --> this is a critical error
+```
+
+* "color" produces similar output, but the text will be color coded to indicate the severity of the message.
+
+* "legacy" produces output similar to InvokeAI versions 2.3 and earlier:
+
+```
+### this is a critical error
+*** this is an error
+** this is a warning
+>> this is an informational messages
+   | this is a debug message
+```
+
+* "syslog" produces messages suitable for syslog entries:
+
+```bash
+InvokeAI [2691178] <CRITICAL> this is a critical error
+InvokeAI [2691178] <ERROR> this is an error
+InvokeAI [2691178] <WARNING> this is a warning
+InvokeAI [2691178] <INFO> this is an informational messages
+InvokeAI [2691178] <DEBUG> this is a debug message
+```
+
+(note that the date, time and hostname will be added by the syslog system)
+
+### `--log_level {debug|info|warning|error|critical}`
+
+Providing this command-line option will cause only messages at the specified level or above to be emitted.
+
+## Console logging
+
+When "console" is provided to `--log_handlers`, messages will be written to the command line window in which InvokeAI was launched. By default, the color formatter will be used unless overridden by `--log_format`.
+
+## File logging
+
+When "file" is provided to `--log_handlers`, entries will be written to the file indicated in the path argument. By default, the "plain" format will be used:
+
+```bash
+invokeai-web --log_handlers file=/var/log/invokeai.log
+```
+
+## Syslog logging
+
+When "syslog" is requested, entries will be sent to the syslog system. There are a variety of ways to control where the log message is sent:
+
+* Send to the local machine using the `/dev/log` socket:
+
+```
+invokeai-web --log_handlers syslog=/dev/log
+```
+
+* Send to the local machine using a UDP message:
+
+```
+invokeai-web --log_handlers syslog=localhost
+```
+
+* Send to the local machine using a UDP message on a nonstandard port:
+
+```
+invokeai-web --log_handlers syslog=localhost:512
+```
+
+* Send to a remote machine named "loghost" on the local LAN using  facility LOG_USER and UDP packets:
+
+```
+invokeai-web --log_handlers syslog=loghost,facility=LOG_USER,socktype=SOCK_DGRAM
+```
+
+This can be abbreviated `syslog=loghost`, as LOG_USER and SOCK_DGRAM are defaults.
+
+* Send to a remote machine named "loghost" using the facility LOCAL0  and using a TCP socket:
+
+```
+invokeai-web --log_handlers syslog=loghost,facility=LOG_LOCAL0,socktype=SOCK_STREAM
+```
+
+If no arguments are specified (just a bare "syslog"), then the logging system will look for a UNIX socket named `/dev/log`, and if not found try to send a UDP message to `localhost`. The Macintosh OS used to support logging to a socket named `/var/run/syslog`, but this feature has since been disabled.
+
+## Web logging
+
+If you have access to a web server that is configured to log messages when a particular URL is requested, you can log using the "http" method:
+
+```
+invokeai-web --log_handlers http=http://my.server/path/to/logger,method=POST
+```
+
+The optional [,method=] part can be used to specify whether the URL accepts GET (default) or POST messages.
+
+Currently password authentication and SSL are not supported.
+
+## Using the configuration file
+
+You can set and forget logging options by adding a "Logging" section to `invokeai.yaml`:
+
+```
+InvokeAI:
+  [... other settings...]
+  Logging:
+    log_handlers:
+       - console
+       - syslog=/dev/log
+    log_level: info
+    log_format: color
+```
 """
 
 import logging.handlers
@@ -180,10 +325,13 @@ class InvokeAILogger(object):
     loggers = dict()
 
     @classmethod
-    def getLogger(cls, name: str = 'InvokeAI') -> logging.Logger:
+    def getLogger(cls,
-        config = get_invokeai_config()
+                  name: str = 'InvokeAI',
-        
+                  config: InvokeAIAppConfig=InvokeAIAppConfig.get_config())->logging.Logger:
-        if name not in cls.loggers:
+        if name in cls.loggers:
+            logger = cls.loggers[name]
+            logger.handlers.clear()
+        else:
             logger = logging.getLogger(name)
         logger.setLevel(config.log_level.upper()) # yes, strings work here
         for ch in cls.getLoggers(config):
@@ -199,9 +347,11 @@ class InvokeAILogger(object):
             handler_name,*args = handler.split('=',2)
             args = args[0] if len(args) > 0 else None
 
-            # console and file are the only handlers that gets a custom formatter
+            # console and file get the fancy formatter.
-            if handler_name=='console':
+            # syslog gets a simple one
+            # http gets no custom formatter
             formatter = LOG_FORMATTERS[config.log_format]
+            if handler_name=='console':
                 ch = logging.StreamHandler()
                 ch.setFormatter(formatter())
                 handlers.append(ch)
@@ -212,7 +362,7 @@ class InvokeAILogger(object):
                 
             elif handler_name=='file':
                 ch = cls._parse_file_args(args)
-                ch.setFormatter(InvokeAISyslogFormatter())
+                ch.setFormatter(formatter())
                 handlers.append(ch)
                 
             elif handler_name=='http':

invokeai/frontend/install/model_install.py

@@ -28,7 +28,7 @@ import torch
 from npyscreen import widget
 from omegaconf import OmegaConf
 
-import invokeai.backend.util.logging as logger
+from invokeai.backend.util.logging import InvokeAILogger
 
 from invokeai.backend.install.model_install_backend import (
     Dataset_path,
@@ -939,6 +939,7 @@ def main():
     if opt.full_precision:
         invoke_args.extend(['--precision','float32'])
     config.parse_args(invoke_args)
+    logger = InvokeAILogger().getLogger(config=config)
 
     if not (config.root_dir / config.conf_path.parent).exists():
         logger.info(

invokeai/frontend/web/src/app/components/App.tsx

@@ -22,6 +22,7 @@ import { APP_HEIGHT, APP_WIDTH } from 'theme/util/constants';
 import GlobalHotkeys from './GlobalHotkeys';
 import Toaster from './Toaster';
 import DeleteImageModal from 'features/gallery/components/DeleteImageModal';
+import { requestCanvasRescale } from 'features/canvas/store/thunks/requestCanvasScale';
 
 const DEFAULT_CONFIG = {};
 
@@ -66,10 +67,17 @@ const App = ({
       setIsReady(true);
     }
 
+    if (isApplicationReady) {
+      // TODO: This is a jank fix for canvas not filling the screen on first load
+      setTimeout(() => {
+        dispatch(requestCanvasRescale());
+      }, 200);
+    }
+
     return () => {
       setIsReady && setIsReady(false);
     };
-  }, [isApplicationReady, setIsReady]);
+  }, [dispatch, isApplicationReady, setIsReady]);
 
   return (
     <>

invokeai/frontend/web/src/app/components/ImageDnd/ImageDndContext.tsx

@@ -40,11 +40,11 @@ const ImageDndContext = (props: ImageDndContextProps) => {
   );
 
   const mouseSensor = useSensor(MouseSensor, {
-    activationConstraint: { delay: 250, tolerance: 5 },
+    activationConstraint: { delay: 150, tolerance: 5 },
   });
 
   const touchSensor = useSensor(TouchSensor, {
-    activationConstraint: { delay: 250, tolerance: 5 },
+    activationConstraint: { delay: 150, tolerance: 5 },
   });
   // TODO: Use KeyboardSensor - needs composition of multiple collisionDetection algos
   // Alternatively, fix `rectIntersection` collection detection to work with the drag overlay

invokeai/frontend/web/src/common/components/IAICustomSelect.tsx

@@ -2,7 +2,6 @@ import { CheckIcon, ChevronUpIcon } from '@chakra-ui/icons';
 import {
   Box,
   Flex,
-  FlexProps,
   FormControl,
   FormControlProps,
   FormLabel,
@@ -16,6 +15,7 @@ import {
 } from '@chakra-ui/react';
 import { autoUpdate, offset, shift, useFloating } from '@floating-ui/react-dom';
 import { useSelect } from 'downshift';
+import { isString } from 'lodash-es';
 import { OverlayScrollbarsComponent } from 'overlayscrollbars-react';
 
 import { memo, useMemo } from 'react';
@@ -23,15 +23,19 @@ import { getInputOutlineStyles } from 'theme/util/getInputOutlineStyles';
 
 export type ItemTooltips = { [key: string]: string };
 
+export type IAICustomSelectOption = {
+  value: string;
+  label: string;
+  tooltip?: string;
+};
+
 type IAICustomSelectProps = {
   label?: string;
-  items: string[];
+  value: string;
-  itemTooltips?: ItemTooltips;
+  data: IAICustomSelectOption[] | string[];
-  selectedItem: string;
+  onChange: (v: string) => void;
-  setSelectedItem: (v: string | null | undefined) => void;
   withCheckIcon?: boolean;
   formControlProps?: FormControlProps;
-  buttonProps?: FlexProps;
   tooltip?: string;
   tooltipProps?: Omit<TooltipProps, 'children'>;
   ellipsisPosition?: 'start' | 'end';
@@ -40,18 +44,33 @@ type IAICustomSelectProps = {
 const IAICustomSelect = (props: IAICustomSelectProps) => {
   const {
     label,
-    items,
-    itemTooltips,
-    setSelectedItem,
-    selectedItem,
     withCheckIcon,
     formControlProps,
     tooltip,
-    buttonProps,
     tooltipProps,
     ellipsisPosition = 'end',
+    data,
+    value,
+    onChange,
   } = props;
 
+  const values = useMemo(() => {
+    return data.map<IAICustomSelectOption>((v) => {
+      if (isString(v)) {
+        return { value: v, label: v };
+      }
+      return v;
+    });
+  }, [data]);
+
+  const stringValues = useMemo(() => {
+    return values.map((v) => v.value);
+  }, [values]);
+
+  const valueData = useMemo(() => {
+    return values.find((v) => v.value === value);
+  }, [values, value]);
+
   const {
     isOpen,
     getToggleButtonProps,
@@ -60,10 +79,11 @@ const IAICustomSelect = (props: IAICustomSelectProps) => {
     highlightedIndex,
     getItemProps,
   } = useSelect({
-    items,
+    items: stringValues,
-    selectedItem,
+    selectedItem: value,
-    onSelectedItemChange: ({ selectedItem: newSelectedItem }) =>
+    onSelectedItemChange: ({ selectedItem: newSelectedItem }) => {
-      setSelectedItem(newSelectedItem),
+      newSelectedItem && onChange(newSelectedItem);
+    },
   });
 
   const { refs, floatingStyles } = useFloating<HTMLButtonElement>({
@@ -93,8 +113,7 @@ const IAICustomSelect = (props: IAICustomSelectProps) => {
       )}
       <Tooltip label={tooltip} {...tooltipProps}>
         <Flex
-          {...getToggleButtonProps({ ref: refs.setReference })}
+          {...getToggleButtonProps({ ref: refs.reference })}
-          {...buttonProps}
           sx={{
             alignItems: 'center',
             userSelect: 'none',
@@ -119,7 +138,7 @@ const IAICustomSelect = (props: IAICustomSelectProps) => {
               direction: labelTextDirection,
             }}
           >
-            {selectedItem}
+            {valueData?.label}
           </Text>
           <ChevronUpIcon
             sx={{
@@ -135,7 +154,7 @@ const IAICustomSelect = (props: IAICustomSelectProps) => {
         {isOpen && (
           <List
             as={Flex}
-            ref={refs.setFloating}
+            ref={refs.floating}
             sx={{
               ...floatingStyles,
               top: 0,
@@ -155,8 +174,8 @@ const IAICustomSelect = (props: IAICustomSelectProps) => {
             }}
           >
             <OverlayScrollbarsComponent>
-              {items.map((item, index) => {
+              {values.map((v, index) => {
-                const isSelected = selectedItem === item;
+                const isSelected = value === v.value;
                 const isHighlighted = highlightedIndex === index;
                 const fontWeight = isSelected ? 700 : 500;
                 const bg = isHighlighted
@@ -166,9 +185,9 @@ const IAICustomSelect = (props: IAICustomSelectProps) => {
                   : undefined;
                 return (
                   <Tooltip
-                    isDisabled={!itemTooltips}
+                    isDisabled={!v.tooltip}
-                    key={`${item}${index}`}
+                    key={`${v.value}${index}`}
-                    label={itemTooltips?.[item]}
+                    label={v.tooltip}
                     hasArrow
                     placement="right"
                   >
@@ -182,8 +201,7 @@ const IAICustomSelect = (props: IAICustomSelectProps) => {
                         transitionProperty: 'common',
                         transitionDuration: '0.15s',
                       }}
-                      key={`${item}${index}`}
+                      {...getItemProps({ item: v.value, index })}
-                      {...getItemProps({ item, index })}
                     >
                       {withCheckIcon ? (
                         <Grid gridTemplateColumns="1.25rem auto">
@@ -198,7 +216,7 @@ const IAICustomSelect = (props: IAICustomSelectProps) => {
                                 fontWeight,
                               }}
                             >
-                              {item}
+                              {v.label}
                             </Text>
                           </GridItem>
                         </Grid>
@@ -210,7 +228,7 @@ const IAICustomSelect = (props: IAICustomSelectProps) => {
                             fontWeight,
                           }}
                         >
-                          {item}
+                          {v.label}
                         </Text>
                       )}
                     </ListItem>

invokeai/frontend/web/src/common/components/IAIDndImage.tsx

@@ -14,7 +14,7 @@ import ImageMetadataOverlay from 'common/components/ImageMetadataOverlay';
 import { AnimatePresence } from 'framer-motion';
 import { ReactElement, SyntheticEvent, useCallback } from 'react';
 import { memo, useRef } from 'react';
-import { FaImage, FaTimes, FaUpload } from 'react-icons/fa';
+import { FaImage, FaTimes, FaUndo, FaUpload } from 'react-icons/fa';
 import { ImageDTO } from 'services/api';
 import { v4 as uuidv4 } from 'uuid';
 import IAIDropOverlay from './IAIDropOverlay';
@@ -174,14 +174,13 @@ const IAIDndImage = (props: IAIDndImageProps) => {
                 position: 'absolute',
                 top: 0,
                 right: 0,
-                p: 2,
               }}
             >
               <IAIIconButton
                 size={resetIconSize}
                 tooltip="Reset Image"
                 aria-label="Reset Image"
-                icon={<FaTimes />}
+                icon={<FaUndo />}
                 onClick={onReset}
               />
             </Box>

invokeai/frontend/web/src/features/canvas/components/IAICanvasToolbar/IAICanvasSettingsButtonPopover.tsx

@@ -16,7 +16,6 @@ import {
   setShouldShowIntermediates,
   setShouldSnapToGrid,
 } from 'features/canvas/store/canvasSlice';
-import EmptyTempFolderButtonModal from 'features/system/components/ClearTempFolderButtonModal';
 import { isEqual } from 'lodash-es';
 
 import { ChangeEvent } from 'react';
@@ -159,7 +158,6 @@ const IAICanvasSettingsButtonPopover = () => {
           onChange={(e) => dispatch(setShouldAntialias(e.target.checked))}
         />
         <ClearCanvasHistoryButtonModal />
-        <EmptyTempFolderButtonModal />
       </Flex>
     </IAIPopover>
   );

invokeai/frontend/web/src/features/canvas/store/canvasSlice.ts

@@ -30,7 +30,10 @@ import {
 } from './canvasTypes';
 import { ImageDTO } from 'services/api';
 import { sessionCanceled } from 'services/thunks/session';
-import { setShouldUseCanvasBetaLayout } from 'features/ui/store/uiSlice';
+import {
+  setActiveTab,
+  setShouldUseCanvasBetaLayout,
+} from 'features/ui/store/uiSlice';
 import { imageUrlsReceived } from 'services/thunks/image';
 
 export const initialLayerState: CanvasLayerState = {
@@ -857,6 +860,11 @@ export const canvasSlice = createSlice({
     builder.addCase(setShouldUseCanvasBetaLayout, (state, action) => {
       state.doesCanvasNeedScaling = true;
     });
+
+    builder.addCase(setActiveTab, (state, action) => {
+      state.doesCanvasNeedScaling = true;
+    });
+
     builder.addCase(imageUrlsReceived.fulfilled, (state, action) => {
       const { image_name, image_origin, image_url, thumbnail_url } =
         action.payload;

invokeai/frontend/web/src/features/controlNet/components/parameters/ParamControlNetModel.tsx

@@ -1,17 +1,26 @@
 import { useAppDispatch } from 'app/store/storeHooks';
-import IAICustomSelect from 'common/components/IAICustomSelect';
+import IAICustomSelect, {
+  IAICustomSelectOption,
+} from 'common/components/IAICustomSelect';
 import {
   CONTROLNET_MODELS,
-  ControlNetModel,
+  ControlNetModelName,
 } from 'features/controlNet/store/constants';
 import { controlNetModelChanged } from 'features/controlNet/store/controlNetSlice';
+import { map } from 'lodash-es';
 import { memo, useCallback } from 'react';
 
 type ParamControlNetModelProps = {
   controlNetId: string;
-  model: ControlNetModel;
+  model: ControlNetModelName;
 };
 
+const DATA: IAICustomSelectOption[] = map(CONTROLNET_MODELS, (m) => ({
+  value: m.type,
+  label: m.label,
+  tooltip: m.type,
+}));
+
 const ParamControlNetModel = (props: ParamControlNetModelProps) => {
   const { controlNetId, model } = props;
   const dispatch = useAppDispatch();
@@ -19,7 +28,7 @@ const ParamControlNetModel = (props: ParamControlNetModelProps) => {
   const handleModelChanged = useCallback(
     (val: string | null | undefined) => {
       // TODO: do not cast
-      const model = val as ControlNetModel;
+      const model = val as ControlNetModelName;
       dispatch(controlNetModelChanged({ controlNetId, model }));
     },
     [controlNetId, dispatch]
@@ -29,9 +38,9 @@ const ParamControlNetModel = (props: ParamControlNetModelProps) => {
     <IAICustomSelect
       tooltip={model}
       tooltipProps={{ placement: 'top', hasArrow: true }}
-      items={CONTROLNET_MODELS}
+      data={DATA}
-      selectedItem={model}
+      value={model}
-      setSelectedItem={handleModelChanged}
+      onChange={handleModelChanged}
       ellipsisPosition="start"
       withCheckIcon
     />

invokeai/frontend/web/src/features/controlNet/components/parameters/ParamControlNetProcessorSelect.tsx

@@ -1,4 +1,6 @@
-import IAICustomSelect from 'common/components/IAICustomSelect';
+import IAICustomSelect, {
+  IAICustomSelectOption,
+} from 'common/components/IAICustomSelect';
 import { memo, useCallback } from 'react';
 import {
   ControlNetProcessorNode,
@@ -7,15 +9,28 @@ import {
 import { controlNetProcessorTypeChanged } from '../../store/controlNetSlice';
 import { useAppDispatch } from 'app/store/storeHooks';
 import { CONTROLNET_PROCESSORS } from '../../store/constants';
+import { map } from 'lodash-es';
 
 type ParamControlNetProcessorSelectProps = {
   controlNetId: string;
   processorNode: ControlNetProcessorNode;
 };
 
-const CONTROLNET_PROCESSOR_TYPES = Object.keys(
+const CONTROLNET_PROCESSOR_TYPES: IAICustomSelectOption[] = map(
-  CONTROLNET_PROCESSORS
+  CONTROLNET_PROCESSORS,
-) as ControlNetProcessorType[];
+  (p) => ({
+    value: p.type,
+    label: p.label,
+    tooltip: p.description,
+  })
+).sort((a, b) =>
+  // sort 'none' to the top
+  a.value === 'none'
+    ? -1
+    : b.value === 'none'
+    ? 1
+    : a.label.localeCompare(b.label)
+);
 
 const ParamControlNetProcessorSelect = (
   props: ParamControlNetProcessorSelectProps
@@ -36,9 +51,9 @@ const ParamControlNetProcessorSelect = (
   return (
     <IAICustomSelect
       label="Processor"
-      items={CONTROLNET_PROCESSOR_TYPES}
+      value={processorNode.type ?? 'canny_image_processor'}
-      selectedItem={processorNode.type ?? 'canny_image_processor'}
+      data={CONTROLNET_PROCESSOR_TYPES}
-      setSelectedItem={handleProcessorTypeChanged}
+      onChange={handleProcessorTypeChanged}
       withCheckIcon
     />
   );

invokeai/frontend/web/src/features/controlNet/store/constants.ts

@@ -5,12 +5,12 @@ import {
 } from './types';
 
 type ControlNetProcessorsDict = Record<
-  ControlNetProcessorType,
+  string,
   {
-    type: ControlNetProcessorType;
+    type: ControlNetProcessorType | 'none';
     label: string;
     description: string;
-    default: RequiredControlNetProcessorNode;
+    default: RequiredControlNetProcessorNode | { type: 'none' };
   }
 >;
 
@@ -23,10 +23,10 @@ type ControlNetProcessorsDict = Record<
  *
  * TODO: Generate from the OpenAPI schema
  */
-export const CONTROLNET_PROCESSORS = {
+export const CONTROLNET_PROCESSORS: ControlNetProcessorsDict = {
   none: {
     type: 'none',
-    label: 'None',
+    label: 'none',
     description: '',
     default: {
       type: 'none',
@@ -116,7 +116,7 @@ export const CONTROLNET_PROCESSORS = {
   },
   mlsd_image_processor: {
     type: 'mlsd_image_processor',
-    label: 'MLSD',
+    label: 'M-LSD',
     description: '',
     default: {
       id: 'mlsd_image_processor',
@@ -174,39 +174,84 @@ export const CONTROLNET_PROCESSORS = {
   },
 };
 
-export const CONTROLNET_MODELS = [
+type ControlNetModel = {
-  'lllyasviel/control_v11p_sd15_canny',
+  type: string;
-  'lllyasviel/control_v11p_sd15_inpaint',
+  label: string;
-  'lllyasviel/control_v11p_sd15_mlsd',
+  description?: string;
-  'lllyasviel/control_v11f1p_sd15_depth',
+  defaultProcessor?: ControlNetProcessorType;
-  'lllyasviel/control_v11p_sd15_normalbae',
-  'lllyasviel/control_v11p_sd15_seg',
-  'lllyasviel/control_v11p_sd15_lineart',
-  'lllyasviel/control_v11p_sd15s2_lineart_anime',
-  'lllyasviel/control_v11p_sd15_scribble',
-  'lllyasviel/control_v11p_sd15_softedge',
-  'lllyasviel/control_v11e_sd15_shuffle',
-  'lllyasviel/control_v11p_sd15_openpose',
-  'lllyasviel/control_v11f1e_sd15_tile',
-  'lllyasviel/control_v11e_sd15_ip2p',
-  'CrucibleAI/ControlNetMediaPipeFace',
-];
-
-export type ControlNetModel = (typeof CONTROLNET_MODELS)[number];
-
-export const CONTROLNET_MODEL_MAP: Record<
-  ControlNetModel,
-  ControlNetProcessorType
-> = {
-  'lllyasviel/control_v11p_sd15_canny': 'canny_image_processor',
-  'lllyasviel/control_v11p_sd15_mlsd': 'mlsd_image_processor',
-  'lllyasviel/control_v11f1p_sd15_depth': 'midas_depth_image_processor',
-  'lllyasviel/control_v11p_sd15_normalbae': 'normalbae_image_processor',
-  'lllyasviel/control_v11p_sd15_lineart': 'lineart_image_processor',
-  'lllyasviel/control_v11p_sd15s2_lineart_anime':
-    'lineart_anime_image_processor',
-  'lllyasviel/control_v11p_sd15_softedge': 'hed_image_processor',
-  'lllyasviel/control_v11e_sd15_shuffle': 'content_shuffle_image_processor',
-  'lllyasviel/control_v11p_sd15_openpose': 'openpose_image_processor',
-  'CrucibleAI/ControlNetMediaPipeFace': 'mediapipe_face_processor',
 };
+
+export const CONTROLNET_MODELS: Record<string, ControlNetModel> = {
+  'lllyasviel/control_v11p_sd15_canny': {
+    type: 'lllyasviel/control_v11p_sd15_canny',
+    label: 'Canny',
+    defaultProcessor: 'canny_image_processor',
+  },
+  'lllyasviel/control_v11p_sd15_inpaint': {
+    type: 'lllyasviel/control_v11p_sd15_inpaint',
+    label: 'Inpaint',
+  },
+  'lllyasviel/control_v11p_sd15_mlsd': {
+    type: 'lllyasviel/control_v11p_sd15_mlsd',
+    label: 'M-LSD',
+    defaultProcessor: 'mlsd_image_processor',
+  },
+  'lllyasviel/control_v11f1p_sd15_depth': {
+    type: 'lllyasviel/control_v11f1p_sd15_depth',
+    label: 'Depth',
+    defaultProcessor: 'midas_depth_image_processor',
+  },
+  'lllyasviel/control_v11p_sd15_normalbae': {
+    type: 'lllyasviel/control_v11p_sd15_normalbae',
+    label: 'Normal Map (BAE)',
+    defaultProcessor: 'normalbae_image_processor',
+  },
+  'lllyasviel/control_v11p_sd15_seg': {
+    type: 'lllyasviel/control_v11p_sd15_seg',
+    label: 'Segment Anything',
+  },
+  'lllyasviel/control_v11p_sd15_lineart': {
+    type: 'lllyasviel/control_v11p_sd15_lineart',
+    label: 'Lineart',
+    defaultProcessor: 'lineart_image_processor',
+  },
+  'lllyasviel/control_v11p_sd15s2_lineart_anime': {
+    type: 'lllyasviel/control_v11p_sd15s2_lineart_anime',
+    label: 'Lineart Anime',
+    defaultProcessor: 'lineart_anime_image_processor',
+  },
+  'lllyasviel/control_v11p_sd15_scribble': {
+    type: 'lllyasviel/control_v11p_sd15_scribble',
+    label: 'Scribble',
+  },
+  'lllyasviel/control_v11p_sd15_softedge': {
+    type: 'lllyasviel/control_v11p_sd15_softedge',
+    label: 'Soft Edge',
+    defaultProcessor: 'hed_image_processor',
+  },
+  'lllyasviel/control_v11e_sd15_shuffle': {
+    type: 'lllyasviel/control_v11e_sd15_shuffle',
+    label: 'Content Shuffle',
+    defaultProcessor: 'content_shuffle_image_processor',
+  },
+  'lllyasviel/control_v11p_sd15_openpose': {
+    type: 'lllyasviel/control_v11p_sd15_openpose',
+    label: 'Openpose',
+    defaultProcessor: 'openpose_image_processor',
+  },
+  'lllyasviel/control_v11f1e_sd15_tile': {
+    type: 'lllyasviel/control_v11f1e_sd15_tile',
+    label: 'Tile (experimental)',
+  },
+  'lllyasviel/control_v11e_sd15_ip2p': {
+    type: 'lllyasviel/control_v11e_sd15_ip2p',
+    label: 'Pix2Pix (experimental)',
+  },
+  'CrucibleAI/ControlNetMediaPipeFace': {
+    type: 'CrucibleAI/ControlNetMediaPipeFace',
+    label: 'Mediapipe Face',
+    defaultProcessor: 'mediapipe_face_processor',
+  },
+};
+
+export type ControlNetModelName = keyof typeof CONTROLNET_MODELS;

invokeai/frontend/web/src/features/controlNet/store/controlNetSlice.ts

@@ -9,9 +9,8 @@ import {
 } from './types';
 import {
   CONTROLNET_MODELS,
-  CONTROLNET_MODEL_MAP,
   CONTROLNET_PROCESSORS,
-  ControlNetModel,
+  ControlNetModelName,
 } from './constants';
 import { controlNetImageProcessed } from './actions';
 import { imageDeleted, imageUrlsReceived } from 'services/thunks/image';
@@ -21,7 +20,7 @@ import { appSocketInvocationError } from 'services/events/actions';
 
 export const initialControlNet: Omit<ControlNetConfig, 'controlNetId'> = {
   isEnabled: true,
-  model: CONTROLNET_MODELS[0],
+  model: CONTROLNET_MODELS['lllyasviel/control_v11p_sd15_canny'].type,
   weight: 1,
   beginStepPct: 0,
   endStepPct: 1,
@@ -36,7 +35,7 @@ export const initialControlNet: Omit<ControlNetConfig, 'controlNetId'> = {
 export type ControlNetConfig = {
   controlNetId: string;
   isEnabled: boolean;
-  model: ControlNetModel;
+  model: ControlNetModelName;
   weight: number;
   beginStepPct: number;
   endStepPct: number;
@@ -138,14 +137,17 @@ export const controlNetSlice = createSlice({
     },
     controlNetModelChanged: (
       state,
-      action: PayloadAction<{ controlNetId: string; model: ControlNetModel }>
+      action: PayloadAction<{
+        controlNetId: string;
+        model: ControlNetModelName;
+      }>
     ) => {
       const { controlNetId, model } = action.payload;
       state.controlNets[controlNetId].model = model;
       state.controlNets[controlNetId].processedControlImage = null;
 
       if (state.controlNets[controlNetId].shouldAutoConfig) {
-        const processorType = CONTROLNET_MODEL_MAP[model];
+        const processorType = CONTROLNET_MODELS[model].defaultProcessor;
         if (processorType) {
           state.controlNets[controlNetId].processorType = processorType;
           state.controlNets[controlNetId].processorNode = CONTROLNET_PROCESSORS[
@@ -225,7 +227,8 @@ export const controlNetSlice = createSlice({
       if (newShouldAutoConfig) {
         // manage the processor for the user
         const processorType =
-          CONTROLNET_MODEL_MAP[state.controlNets[controlNetId].model];
+          CONTROLNET_MODELS[state.controlNets[controlNetId].model]
+            .defaultProcessor;
         if (processorType) {
           state.controlNets[controlNetId].processorType = processorType;
           state.controlNets[controlNetId].processorNode = CONTROLNET_PROCESSORS[

invokeai/frontend/web/src/features/nodes/util/graphBuilders/buildImageToImageGraph.ts

@@ -342,7 +342,10 @@ export const buildImageToImageGraph = (state: RootState): Graph => {
     });
   }
 
-  if (shouldFitToWidthHeight) {
+  if (
+    shouldFitToWidthHeight &&
+    (initialImage.width !== width || initialImage.height !== height)
+  ) {
     // The init image needs to be resized to the specified width and height before being passed to `IMAGE_TO_LATENTS`
 
     // Create a resize node, explicitly setting its image

invokeai/frontend/web/src/features/parameters/components/Parameters/Core/ParamScheduler.tsx

@@ -14,9 +14,11 @@ const selector = createSelector(
   (ui, generation) => {
     // TODO: DPMSolverSinglestepScheduler is fixed in https://github.com/huggingface/diffusers/pull/3413
     // but we need to wait for the next release before removing this special handling.
-    const allSchedulers = ui.schedulers.filter((scheduler) => {
+    const allSchedulers = ui.schedulers
+      .filter((scheduler) => {
         return !['dpmpp_2s'].includes(scheduler);
-    });
+      })
+      .sort((a, b) => a.localeCompare(b));
 
     return {
       scheduler: generation.scheduler,
@@ -45,9 +47,9 @@ const ParamScheduler = () => {
   return (
     <IAICustomSelect
       label={t('parameters.scheduler')}
-      selectedItem={scheduler}
+      value={scheduler}
-      setSelectedItem={handleChange}
+      data={allSchedulers}
-      items={allSchedulers}
+      onChange={handleChange}
       withCheckIcon
     />
   );

invokeai/frontend/web/src/features/parameters/components/Parameters/ImageToImage/InitialImagePreview.tsx

@@ -58,6 +58,7 @@ const InitialImagePreview = () => {
         onReset={handleReset}
         fallback={<IAIImageFallback sx={{ bg: 'none' }} />}
         postUploadAction={{ type: 'SET_INITIAL_IMAGE' }}
+        withResetIcon
       />
     </Flex>
   );

invokeai/frontend/web/src/features/system/components/ClearTempFolderButtonModal.tsx

@@ -1,41 +0,0 @@
-// import { emptyTempFolder } from 'app/socketio/actions';
-import { useAppDispatch, useAppSelector } from 'app/store/storeHooks';
-import IAIAlertDialog from 'common/components/IAIAlertDialog';
-import IAIButton from 'common/components/IAIButton';
-import { isStagingSelector } from 'features/canvas/store/canvasSelectors';
-import {
-  clearCanvasHistory,
-  resetCanvas,
-} from 'features/canvas/store/canvasSlice';
-import { useTranslation } from 'react-i18next';
-import { FaTrash } from 'react-icons/fa';
-
-const EmptyTempFolderButtonModal = () => {
-  const isStaging = useAppSelector(isStagingSelector);
-  const dispatch = useAppDispatch();
-  const { t } = useTranslation();
-
-  const acceptCallback = () => {
-    dispatch(emptyTempFolder());
-    dispatch(resetCanvas());
-    dispatch(clearCanvasHistory());
-  };
-
-  return (
-    <IAIAlertDialog
-      title={t('unifiedCanvas.emptyTempImageFolder')}
-      acceptCallback={acceptCallback}
-      acceptButtonText={t('unifiedCanvas.emptyFolder')}
-      triggerComponent={
-        <IAIButton leftIcon={<FaTrash />} size="sm" isDisabled={isStaging}>
-          {t('unifiedCanvas.emptyTempImageFolder')}
-        </IAIButton>
-      }
-    >
-      <p>{t('unifiedCanvas.emptyTempImagesFolderMessage')}</p>
-      <br />
-      <p>{t('unifiedCanvas.emptyTempImagesFolderConfirm')}</p>
-    </IAIAlertDialog>
-  );
-};
-export default EmptyTempFolderButtonModal;

invokeai/frontend/web/src/features/system/components/ModelSelect.tsx

@@ -4,34 +4,29 @@ import { isEqual } from 'lodash-es';
 import { useTranslation } from 'react-i18next';
 
 import { useAppDispatch, useAppSelector } from 'app/store/storeHooks';
-import {
+import { selectModelsAll, selectModelsById } from '../store/modelSlice';
-  selectModelsAll,
-  selectModelsById,
-  selectModelsIds,
-} from '../store/modelSlice';
 import { RootState } from 'app/store/store';
 import { modelSelected } from 'features/parameters/store/generationSlice';
 import { generationSelector } from 'features/parameters/store/generationSelectors';
 import IAICustomSelect, {
-  ItemTooltips,
+  IAICustomSelectOption,
 } from 'common/components/IAICustomSelect';
 
 const selector = createSelector(
   [(state: RootState) => state, generationSelector],
   (state, generation) => {
     const selectedModel = selectModelsById(state, generation.model);
-    const allModelNames = selectModelsIds(state).map((id) => String(id));
+
-    const allModelTooltips = selectModelsAll(state).reduce(
+    const modelData = selectModelsAll(state)
-      (allModelTooltips, model) => {
+      .map<IAICustomSelectOption>((m) => ({
-        allModelTooltips[model.name] = model.description ?? '';
+        value: m.name,
-        return allModelTooltips;
+        label: m.name,
-      },
+        tooltip: m.description,
-      {} as ItemTooltips
+      }))
-    );
+      .sort((a, b) => a.label.localeCompare(b.label));
     return {
-      allModelNames,
-      allModelTooltips,
       selectedModel,
+      modelData,
     };
   },
   {
@@ -44,8 +39,7 @@ const selector = createSelector(
 const ModelSelect = () => {
   const dispatch = useAppDispatch();
   const { t } = useTranslation();
-  const { allModelNames, allModelTooltips, selectedModel } =
+  const { selectedModel, modelData } = useAppSelector(selector);
-    useAppSelector(selector);
   const handleChangeModel = useCallback(
     (v: string | null | undefined) => {
       if (!v) {
@@ -60,10 +54,9 @@ const ModelSelect = () => {
     <IAICustomSelect
       label={t('modelManager.model')}
       tooltip={selectedModel?.description}
-      items={allModelNames}
+      data={modelData}
-      itemTooltips={allModelTooltips}
+      value={selectedModel?.name ?? ''}
-      selectedItem={selectedModel?.name ?? ''}
+      onChange={handleChangeModel}
-      setSelectedItem={handleChangeModel}
       withCheckIcon={true}
       tooltipProps={{ placement: 'top', hasArrow: true }}
     />

invokeai/frontend/web/src/features/ui/components/InvokeTabs.tsx

@@ -14,7 +14,7 @@ import { useAppDispatch, useAppSelector } from 'app/store/storeHooks';
 import { setIsLightboxOpen } from 'features/lightbox/store/lightboxSlice';
 import { InvokeTabName } from 'features/ui/store/tabMap';
 import { setActiveTab, togglePanels } from 'features/ui/store/uiSlice';
-import { memo, ReactNode, useCallback, useMemo } from 'react';
+import { memo, MouseEvent, ReactNode, useCallback, useMemo } from 'react';
 import { useHotkeys } from 'react-hotkeys-hook';
 import { MdDeviceHub, MdGridOn } from 'react-icons/md';
 import { GoTextSize } from 'react-icons/go';
@@ -47,22 +47,22 @@ export interface InvokeTabInfo {
 const tabs: InvokeTabInfo[] = [
   {
     id: 'txt2img',
-    icon: <Icon as={GoTextSize} sx={{ boxSize: 6 }} />,
+    icon: <Icon as={GoTextSize} sx={{ boxSize: 6, pointerEvents: 'none' }} />,
     content: <TextToImageTab />,
   },
   {
     id: 'img2img',
-    icon: <Icon as={FaImage} sx={{ boxSize: 6 }} />,
+    icon: <Icon as={FaImage} sx={{ boxSize: 6, pointerEvents: 'none' }} />,
     content: <ImageTab />,
   },
   {
     id: 'unifiedCanvas',
-    icon: <Icon as={MdGridOn} sx={{ boxSize: 6 }} />,
+    icon: <Icon as={MdGridOn} sx={{ boxSize: 6, pointerEvents: 'none' }} />,
     content: <UnifiedCanvasTab />,
   },
   {
     id: 'nodes',
-    icon: <Icon as={MdDeviceHub} sx={{ boxSize: 6 }} />,
+    icon: <Icon as={MdDeviceHub} sx={{ boxSize: 6, pointerEvents: 'none' }} />,
     content: <NodesTab />,
   },
 ];
@@ -119,6 +119,12 @@ const InvokeTabs = () => {
     }
   }, [dispatch, activeTabName]);
 
+  const handleClickTab = useCallback((e: MouseEvent<HTMLElement>) => {
+    if (e.target instanceof HTMLElement) {
+      e.target.blur();
+    }
+  }, []);
+
   const tabs = useMemo(
     () =>
       enabledTabs.map((tab) => (
@@ -128,7 +134,7 @@ const InvokeTabs = () => {
           label={String(t(`common.${tab.id}` as ResourceKey))}
           placement="end"
         >
-          <Tab>
+          <Tab onClick={handleClickTab}>
             <VisuallyHidden>
               {String(t(`common.${tab.id}` as ResourceKey))}
             </VisuallyHidden>
@@ -136,7 +142,7 @@ const InvokeTabs = () => {
           </Tab>
         </Tooltip>
       )),
-    [t, enabledTabs]
+    [enabledTabs, t, handleClickTab]
   );
 
   const tabPanels = useMemo(

invokeai/frontend/web/src/features/ui/components/tabs/UnifiedCanvas/UnifiedCanvasBeta/UnifiedCanvasToolSettings/UnifiedCanvasSettings.tsx

@@ -12,7 +12,6 @@ import {
   setShouldShowCanvasDebugInfo,
   setShouldShowIntermediates,
 } from 'features/canvas/store/canvasSlice';
-import EmptyTempFolderButtonModal from 'features/system/components/ClearTempFolderButtonModal';
 
 import { FaWrench } from 'react-icons/fa';
 
@@ -105,7 +104,6 @@ const UnifiedCanvasSettings = () => {
           onChange={(e) => dispatch(setShouldAntialias(e.target.checked))}
         />
         <ClearCanvasHistoryButtonModal />
-        <EmptyTempFolderButtonModal />
       </Flex>
     </IAIPopover>
   );

invokeai/frontend/web/src/features/ui/components/tabs/UnifiedCanvas/UnifiedCanvasContent.tsx

@@ -55,8 +55,6 @@ const UnifiedCanvasContent = () => {
   });
 
   useLayoutEffect(() => {
-    dispatch(requestCanvasRescale());
-
     const resizeCallback = () => {
       dispatch(requestCanvasRescale());
     };

tests/nodes/test_graph_execution_state.py

@@ -121,3 +121,78 @@ def test_graph_state_collects(mock_services):
     assert isinstance(n6[0], CollectInvocation)
 
     assert sorted(g.results[n6[0].id].collection) == sorted(test_prompts)
+
+
+def test_graph_state_prepares_eagerly(mock_services):
+    """Tests that all prepareable nodes are prepared"""
+    graph = Graph()
+
+    test_prompts = ["Banana sushi", "Cat sushi"]
+    graph.add_node(PromptCollectionTestInvocation(id="prompt_collection", collection=list(test_prompts)))
+    graph.add_node(IterateInvocation(id="iterate"))
+    graph.add_node(PromptTestInvocation(id="prompt_iterated"))
+    graph.add_edge(create_edge("prompt_collection", "collection", "iterate", "collection"))
+    graph.add_edge(create_edge("iterate", "item", "prompt_iterated", "prompt"))
+
+    # separated, fully-preparable chain of nodes
+    graph.add_node(PromptTestInvocation(id="prompt_chain_1", prompt="Dinosaur sushi"))
+    graph.add_node(PromptTestInvocation(id="prompt_chain_2"))
+    graph.add_node(PromptTestInvocation(id="prompt_chain_3"))
+    graph.add_edge(create_edge("prompt_chain_1", "prompt", "prompt_chain_2", "prompt"))
+    graph.add_edge(create_edge("prompt_chain_2", "prompt", "prompt_chain_3", "prompt"))
+
+    g = GraphExecutionState(graph=graph)
+    g.next()
+
+    assert "prompt_collection" in g.source_prepared_mapping
+    assert "prompt_chain_1" in g.source_prepared_mapping
+    assert "prompt_chain_2" in g.source_prepared_mapping
+    assert "prompt_chain_3" in g.source_prepared_mapping
+    assert "iterate" not in g.source_prepared_mapping
+    assert "prompt_iterated" not in g.source_prepared_mapping
+
+
+def test_graph_executes_depth_first(mock_services):
+    """Tests that the graph executes depth-first, executing a branch as far as possible before moving to the next branch"""
+    graph = Graph()
+
+    test_prompts = ["Banana sushi", "Cat sushi"]
+    graph.add_node(PromptCollectionTestInvocation(id="prompt_collection", collection=list(test_prompts)))
+    graph.add_node(IterateInvocation(id="iterate"))
+    graph.add_node(PromptTestInvocation(id="prompt_iterated"))
+    graph.add_node(PromptTestInvocation(id="prompt_successor"))
+    graph.add_edge(create_edge("prompt_collection", "collection", "iterate", "collection"))
+    graph.add_edge(create_edge("iterate", "item", "prompt_iterated", "prompt"))
+    graph.add_edge(create_edge("prompt_iterated", "prompt", "prompt_successor", "prompt"))
+
+    g = GraphExecutionState(graph=graph)
+    n1 = invoke_next(g, mock_services)
+    n2 = invoke_next(g, mock_services)
+    n3 = invoke_next(g, mock_services)
+    n4 = invoke_next(g, mock_services)
+
+    # Because ordering is not guaranteed, we cannot compare results directly.
+    # Instead, we must count the number of results.
+    def get_completed_count(g, id):
+        ids = [i for i in g.source_prepared_mapping[id]]
+        completed_ids = [i for i in g.executed if i in ids]
+        return len(completed_ids)
+
+    # Check at each step that the number of executed nodes matches the expectation for depth-first execution
+    assert get_completed_count(g, "prompt_iterated") == 1
+    assert get_completed_count(g, "prompt_successor") == 0
+
+    n5 = invoke_next(g, mock_services)
+
+    assert get_completed_count(g, "prompt_iterated") == 1
+    assert get_completed_count(g, "prompt_successor") == 1
+
+    n6 = invoke_next(g, mock_services)
+
+    assert get_completed_count(g, "prompt_iterated") == 2
+    assert get_completed_count(g, "prompt_successor") == 1
+
+    n7 = invoke_next(g, mock_services)
+
+    assert get_completed_count(g, "prompt_iterated") == 2
+    assert get_completed_count(g, "prompt_successor") == 2