Merge branch 'development' into merge-main-into-development

.github/workflows/build-container.yml

@@ -6,14 +6,22 @@ on:
     branches:
       - 'main'
       - 'development'
-  pull_request:
-    branches:
-      - 'main'
-      - 'development'
 
 jobs:
   docker:
+    strategy:
+      fail-fast: false
+      matrix:
+        arch:
+          - x86_64
+          - aarch64
+        include:
+          - arch: x86_64
+            conda-env-file: environment.yml
+          - arch: aarch64
+            conda-env-file: environment-linux-aarch64.yml
     runs-on: ubuntu-latest
+    name: ${{ matrix.arch }}
     steps:
       - name: prepare docker-tag
         env:
@@ -25,18 +33,16 @@ jobs:
         uses: docker/setup-qemu-action@v2
       - name: Set up Docker Buildx
         uses: docker/setup-buildx-action@v2
-      - name: Cache Docker layers
-        uses: actions/cache@v2
-        with:
-          path: /tmp/.buildx-cache
-          key: buildx-${{ hashFiles('docker-build/Dockerfile') }}
       - name: Build container
         uses: docker/build-push-action@v3
         with:
           context: .
           file: docker-build/Dockerfile
-          platforms: linux/amd64
+          platforms: Linux/${{ matrix.arch }}
           push: false
-          tags: ${{ env.dockertag }}:latest
+          tags: ${{ env.dockertag }}:${{ matrix.arch }}
-          cache-from: type=local,src=/tmp/.buildx-cache
+          build-args: |
-          cache-to: type=local,dest=/tmp/.buildx-cache
+            conda_env_file=${{ matrix.conda-env-file }}
+            conda_version=py39_4.12.0-Linux-${{ matrix.arch }}
+            invokeai_git=${{ github.repository }}
+            invokeai_branch=${{ github.ref_name }}

.github/workflows/test-invoke-conda.yml

@@ -76,8 +76,18 @@ jobs:
         if: ${{ github.ref != 'refs/heads/main' && github.ref != 'refs/heads/development' }}
         run: echo "TEST_PROMPTS=tests/validate_pr_prompt.txt" >> $GITHUB_ENV
 
+      - name: Use Cached Stable Diffusion Model
+        id: cache-sd-model
+        uses: actions/cache@v3
+        env:
+          cache-name: cache-${{ matrix.stable-diffusion-model-switch }}
+        with:
+          path: ${{ matrix.stable-diffusion-model-dl-path }}
+          key: ${{ env.cache-name }}
+
       - name: Download ${{ matrix.stable-diffusion-model-switch }}
         id: download-stable-diffusion-model
+        if: ${{ steps.cache-sd-model.outputs.cache-hit != 'true' }}
         run: |
           [[ -d models/ldm/stable-diffusion-v1 ]] \
             || mkdir -p models/ldm/stable-diffusion-v1

docker-build/Dockerfile

@@ -39,12 +39,13 @@ RUN apt-get update \
   && apt-get clean \
   && rm -rf /var/lib/apt/lists/*
 
-# clone repository and create symlinks
+# clone repository, create models.yaml and create symlinks
-ARG invokeai_git=https://github.com/invoke-ai/InvokeAI.git
+ARG invokeai_git=invoke-ai/InvokeAI
+ARG invokeai_branch=main
 ARG project_name=invokeai
-RUN git clone ${invokeai_git} /${project_name} \
+RUN git clone -b ${invokeai_branch} https://github.com/${invokeai_git}.git /${project_name} \
-  && mkdir /${project_name}/models/ldm/stable-diffusion-v1 \
+  && cp /${project_name}/configs/models.yaml.example /${project_name}/configs/models.yaml \
-  && ln -s /data/models/sd-v1-4.ckpt /${project_name}/models/ldm/stable-diffusion-v1/model.ckpt \
+  && ln -s /data/models/v1-5-pruned-emaonly.ckpt /${project_name}/models/ldm/stable-diffusion-v1/v1-5-pruned-emaonly.ckpt \
   && ln -s /data/outputs/ /${project_name}/outputs
 
 # set workdir
@@ -63,9 +64,9 @@ RUN source ${conda_prefix}/etc/profile.d/conda.sh \
   && rm -Rf ~/.cache \
   && conda clean -afy \
   && echo "conda activate ${project_name}" >> ~/.bashrc \
-  && ln -s /data/models/GFPGANv1.4.pth ./src/gfpgan/experiments/pretrained_models/GFPGANv1.4.pth \
   && conda activate ${project_name} \
-  && python scripts/preload_models.py
+  && python scripts/preload_models.py \
+    --no-interactive
 
 # Copy entrypoint and set env
 ENV CONDA_PREFIX=${conda_prefix}

docker-build/build.sh

@@ -9,7 +9,8 @@ source ./docker-build/env.sh || echo "please run from repository root" || exit 1
 invokeai_conda_version=${INVOKEAI_CONDA_VERSION:-py39_4.12.0-${platform/\//-}}
 invokeai_conda_prefix=${INVOKEAI_CONDA_PREFIX:-\/opt\/conda}
 invokeai_conda_env_file=${INVOKEAI_CONDA_ENV_FILE:-environment.yml}
-invokeai_git=${INVOKEAI_GIT:-https://github.com/invoke-ai/InvokeAI.git}
+invokeai_git=${INVOKEAI_GIT:-invoke-ai/InvokeAI}
+invokeai_branch=${INVOKEAI_BRANCH:-main}
 huggingface_token=${HUGGINGFACE_TOKEN?}
 
 # print the settings
@@ -38,11 +39,12 @@ _copyCheckpoints() {
   echo "creating subfolders for models and outputs"
   _runAlpine mkdir models
   _runAlpine mkdir outputs
-  echo -n "downloading sd-v1-4.ckpt"
+  echo "downloading v1-5-pruned-emaonly.ckpt"
-  _runAlpine wget --header="Authorization: Bearer ${huggingface_token}" -O models/sd-v1-4.ckpt https://huggingface.co/CompVis/stable-diffusion-v-1-4-original/resolve/main/sd-v1-4.ckpt
+  _runAlpine wget \
+    --header="Authorization: Bearer ${huggingface_token}" \
+    -O models/v1-5-pruned-emaonly.ckpt \
+    https://huggingface.co/runwayml/stable-diffusion-v1-5/resolve/main/v1-5-pruned-emaonly.ckpt
   echo "done"
-  echo "downloading GFPGANv1.4.pth"
-  _runAlpine wget -O models/GFPGANv1.4.pth https://github.com/TencentARC/GFPGAN/releases/download/v1.3.0/GFPGANv1.4.pth
 }
 
 _checkVolumeContent() {
@@ -51,7 +53,7 @@ _checkVolumeContent() {
 
 _getModelMd5s() {
   _runAlpine  \
-    alpine sh -c "md5sum /data/models/*"
+    alpine sh -c "md5sum /data/models/*.ckpt"
 }
 
 if [[ -n "$(docker volume ls -f name="${volumename}" -q)" ]]; then
@@ -77,5 +79,6 @@ docker build \
   --build-arg conda_prefix="${invokeai_conda_prefix}" \
   --build-arg conda_env_file="${invokeai_conda_env_file}" \
   --build-arg invokeai_git="${invokeai_git}" \
+  --build-arg invokeai_branch="${invokeai_branch}" \
   --file ./docker-build/Dockerfile \
   .

environment-linux-aarch64.yml

@@ -3,15 +3,14 @@ channels:
   - pytorch
   - conda-forge
 dependencies:
-  - python>=3.9
+  - python=3.9.*
-  - pip>=20.3
+  - pip>=22.2.2
   - cudatoolkit
   - pytorch
   - torchvision
   - numpy=1.19
   - imageio=2.9.0
   - opencv=4.6.0
-  - getpass_asterisk
   - pillow=8.*
   - flask=2.1.*
   - flask_cors=3.0.10
@@ -30,6 +29,7 @@ dependencies:
   - torch-fidelity=0.3.0
   - tokenizers>=0.11.1,!=0.11.3,<0.13
   - pip:
+      - getpass_asterisk
       - omegaconf==2.1.1
       - realesrgan==0.2.5.0
       - test-tube>=0.7.5

frontend/src/features/system/SettingsModal/SettingsModalItem.tsx

@@ -1,50 +0,0 @@
-import { useAppDispatch } from '../../../app/store';
-import IAISelect from '../../../common/components/IAISelect';
-import IAISwitch from '../../../common/components/IAISwitch';
-
-export function SettingsModalItem({
-  settingTitle,
-  isChecked,
-  dispatcher,
-}: {
-  settingTitle: string;
-  isChecked: boolean;
-  dispatcher: any;
-}) {
-  const dispatch = useAppDispatch();
-  return (
-    <IAISwitch
-      styleClass="settings-modal-item"
-      label={settingTitle}
-      isChecked={isChecked}
-      onChange={(e) => dispatch(dispatcher(e.target.checked))}
-    />
-  );
-}
-
-
-export function SettingsModalSelectItem({
-  settingTitle,
-  validValues,
-  defaultValue,
-  dispatcher,
-}: {
-  settingTitle: string;
-  validValues: 
-      Array<number | string>
-    | Array<{ key: string; value: string | number }>;
-  defaultValue: string;
-  dispatcher: any;
-}) {
-  const dispatch = useAppDispatch();
-  return (
-    <IAISelect
-      styleClass="settings-modal-item"
-      label={settingTitle}
-      validValues={validValues}
-      defaultValue={defaultValue}
-      onChange={(e) => dispatch(dispatcher(e.target.value))}
-    />
-  );
-}
-

ldm/invoke/generator/base.py

@@ -119,19 +119,19 @@ class Generator():
         # write an approximate RGB image from latent samples for a single step to PNG
 
     def sample_to_lowres_estimated_image(self,samples):
-        # adapted from code by @erucipe and @keturn here:
+        # origingally adapted from code by @erucipe and @keturn here:
         # https://discuss.huggingface.co/t/decoding-latents-to-rgb-without-upscaling/23204/7
 
-        # these numbers were determined empirically by @keturn
+        # these updated numbers for v1.5 are from @torridgristle
-        v1_4_latent_rgb_factors = torch.tensor([
+        v1_5_latent_rgb_factors = torch.tensor([
             #    R        G        B
-                    [ 0.298, 0.207, 0.208],  # L1
+            [ 0.3444,  0.1385,  0.0670], # L1
-                    [ 0.187, 0.286, 0.173],  # L2
+            [ 0.1247,  0.4027,  0.1494], # L2
-                    [-0.158, 0.189, 0.264],  # L3
+            [-0.3192,  0.2513,  0.2103], # L3
-                    [-0.184, -0.271, -0.473],  # L4
+            [-0.1307, -0.1874, -0.7445]  # L4
         ], dtype=samples.dtype, device=samples.device)
 
-        latent_image = samples[0].permute(1, 2, 0) @ v1_4_latent_rgb_factors
+        latent_image = samples[0].permute(1, 2, 0) @ v1_5_latent_rgb_factors
         latents_ubyte = (((latent_image + 1) / 2)
                          .clamp(0, 1)  # change scale from -1..1 to 0..1
                          .mul(0xFF)  # to 0..255

ldm/invoke/prompt_parser.py

@@ -28,7 +28,7 @@ class Prompt():
     def __init__(self, parts: list):
         for c in parts:
             if type(c) is not Attention and not issubclass(type(c), BaseFragment) and type(c) is not pp.ParseResults:
-                raise PromptParser.ParsingException(f"Prompt cannot contain {type(c).__name__} {c}, only {BaseFragment.__subclasses__()} are allowed")
+                raise PromptParser.ParsingException(f"Prompt cannot contain {type(c).__name__} ({c}), only {[c.__name__ for c in BaseFragment.__subclasses__()]} are allowed")
         self.children = parts
     def __repr__(self):
         return f"Prompt:{self.children}"
@@ -102,12 +102,18 @@ class Attention():
     Do not traverse directly; instead obtain a FlattenedPrompt by calling Flatten() on a top-level Conjunction object.
     """
     def __init__(self, weight: float, children: list):
+        if type(weight) is not float:
+            raise PromptParser.ParsingException(
+                f"Attention weight must be float (got {type(weight).__name__} {weight})")
         self.weight = weight
+        if type(children) is not list:
+            raise PromptParser.ParsingException(f"cannot make Attention with non-list of children (got {type(children)})")
+        assert(type(children) is list)
         self.children = children
         #print(f"A: requested attention '{children}' to {weight}")
 
     def __repr__(self):
-        return f"Attention:'{self.children}' @ {self.weight}"
+        return f"Attention:{self.children} * {self.weight}"
     def __eq__(self, other):
         return type(other) is Attention and other.weight == self.weight and other.fragment == self.fragment
 
@@ -136,9 +142,9 @@ class CrossAttentionControlSubstitute(CrossAttentionControlledFragment):
             Fragment('sitting on a car')
         ])
     """
-    def __init__(self, original: Union[Fragment, list], edited: Union[Fragment, list], options: dict=None):
+    def __init__(self, original: list, edited: list, options: dict=None):
-        self.original = original
+        self.original = original if len(original)>0 else [Fragment('')]
-        self.edited = edited
+        self.edited = edited if len(edited)>0 else [Fragment('')]
 
         default_options = {
             's_start': 0.0,
@@ -190,12 +196,12 @@ class Conjunction():
     """
     def __init__(self, prompts: list, weights: list = None):
         # force everything to be a Prompt
-        #print("making conjunction with", parts)
+        #print("making conjunction with", prompts, "types", [type(p).__name__ for p in prompts])
         self.prompts = [x if (type(x) is Prompt
                           or type(x) is Blend
                           or type(x) is FlattenedPrompt)
                       else Prompt(x) for x in prompts]
-        self.weights = [1.0]*len(self.prompts) if weights is None else list(weights)
+        self.weights = [1.0]*len(self.prompts) if (weights is None or len(weights)==0) else list(weights)
         if len(self.weights) != len(self.prompts):
             raise PromptParser.ParsingException(f"while parsing Conjunction: mismatched parts/weights counts {prompts}, {weights}")
         self.type = 'AND'
@@ -216,6 +222,7 @@ class Blend():
     """
     def __init__(self, prompts: list, weights: list[float], normalize_weights: bool=True):
         #print("making Blend with prompts", prompts, "and weights", weights)
+        weights = [1.0]*len(prompts) if (weights is None or len(weights)==0) else list(weights)
         if len(prompts) != len(weights):
             raise PromptParser.ParsingException(f"while parsing Blend: mismatched prompts/weights counts {prompts}, {weights}")
         for p in prompts:
@@ -244,6 +251,10 @@ class PromptParser():
     class ParsingException(Exception):
         pass
 
+    class UnrecognizedOperatorException(ParsingException):
+        def __init__(self, operator:str):
+            super().__init__("Unrecognized operator: " + operator)
+
     def __init__(self, attention_plus_base=1.1, attention_minus_base=0.9):
 
         self.conjunction, self.prompt = build_parser_syntax(attention_plus_base, attention_minus_base)
@@ -279,7 +290,7 @@ class PromptParser():
         return Blend(prompts=flattened_prompts, weights=weights, normalize_weights=True)
 
 
-    def flatten(self, root: Conjunction) -> Conjunction:
+    def flatten(self, root: Conjunction, verbose = False) -> Conjunction:
         """
         Flattening a Conjunction traverses all of the nested tree-like structures in each of its Prompts or Blends,
         producing from each of these walks a linear sequence of Fragment or CrossAttentionControlSubstitute objects
@@ -289,8 +300,6 @@ class PromptParser():
         :return: A Conjunction containing the result of flattening each of the prompts in the passed-in root.
         """
 
-        #print("flattening", root)
-
         def fuse_fragments(items):
             # print("fusing fragments in ", items)
             result = []
@@ -313,8 +322,8 @@ class PromptParser():
             return result
 
         def flatten_internal(node, weight_scale, results, prefix):
-            #print(prefix + "flattening", node, "...")
+            verbose and print(prefix + "flattening", node, "...")
-            if type(node) is pp.ParseResults:
+            if type(node) is pp.ParseResults or type(node) is list:
                 for x in node:
                     results = flatten_internal(x, weight_scale, results, prefix+' pr ')
                 #print(prefix, " ParseResults expanded, results is now", results)
@@ -345,67 +354,59 @@ class PromptParser():
                 #print(prefix + "after flattening Prompt, results is", results)
             else:
                 raise PromptParser.ParsingException(f"unhandled node type {type(node)} when flattening {node}")
-            #print(prefix + "-> after flattening", type(node).__name__, "results is", results)
+            verbose and print(prefix + "-> after flattening", type(node).__name__, "results is", results)
             return results
 
+        verbose and print("flattening", root)
 
         flattened_parts = []
         for part in root.prompts:
             flattened_parts += flatten_internal(part, 1.0, [], ' C| ')
 
-        #print("flattened to", flattened_parts)
+        verbose and print("flattened to", flattened_parts)
 
         weights = root.weights
         return Conjunction(flattened_parts, weights)
 
 
 
+
 def build_parser_syntax(attention_plus_base: float, attention_minus_base: float):
+    def make_operator_object(x):
+        #print('making operator for', x)
+        target = x[0]
+        operator = x[1]
+        arguments = x[2]
+        if operator == '.attend':
+            weight_raw = arguments[0]
+            weight = 1.0
+            if type(weight_raw) is float or type(weight_raw) is int:
+                weight = weight_raw
+            elif type(weight_raw) is str:
+                base = attention_plus_base if weight_raw[0] == '+' else attention_minus_base
+                weight = pow(base, len(weight_raw))
+            return Attention(weight=weight, children=[x for x in x[0]])
+        elif operator == '.swap':
+            return CrossAttentionControlSubstitute(target, arguments, x.as_dict())
+        elif operator == '.blend':
+            prompts = [Prompt(p) for p in x[0]]
+            weights_raw = x[2]
+            normalize_weights = True
+            if len(weights_raw) > 0 and weights_raw[-1][0] == 'no_normalize':
+                normalize_weights = False
+                weights_raw = weights_raw[:-1]
+            weights = [float(w[0]) for w in weights_raw]
+            return Blend(prompts=prompts, weights=weights, normalize_weights=normalize_weights)
+        elif operator == '.and' or operator == '.add':
+            prompts = [Prompt(p) for p in x[0]]
+            weights = [float(w[0]) for w in x[2]]
+            return Conjunction(prompts=prompts, weights=weights)
 
-    lparen = pp.Literal("(").suppress()
+        raise PromptParser.UnrecognizedOperatorException(operator)
-    rparen = pp.Literal(")").suppress()
-    quotes = pp.Literal('"').suppress()
-    comma = pp.Literal(",").suppress()
 
-    # accepts int or float notation, always maps to float
+    def parse_fragment_str(x, expression: pp.ParseExpression, in_quotes: bool = False, in_parens: bool = False):
-    number = pp.pyparsing_common.real | \
-             pp.Combine(pp.Optional("-")+pp.Word(pp.nums)).set_parse_action(pp.token_map(float))
-
-    attention = pp.Forward()
-    quoted_fragment = pp.Forward()
-    parenthesized_fragment = pp.Forward()
-    cross_attention_substitute = pp.Forward()
-
-    def make_text_fragment(x):
-        #print("### making fragment for", x)
-        if type(x[0]) is Fragment:
-            assert(False)
-        if type(x) is str:
-            return Fragment(x)
-        elif type(x) is pp.ParseResults or type(x) is list:
-            #print(f'converting {type(x).__name__} to Fragment')
-            return Fragment(' '.join([s for s in x]))
-        else:
-            raise PromptParser.ParsingException("Cannot make fragment from " + str(x))
-
-    def build_escaped_word_parser_charbychar(escaped_chars_to_ignore: str):
-        escapes = []
-        for c in escaped_chars_to_ignore:
-            escapes.append(pp.Literal('\\'+c))
-        return pp.Combine(pp.OneOrMore(
-            pp.MatchFirst(escapes + [pp.CharsNotIn(
-                string.whitespace + escaped_chars_to_ignore,
-                exact=1
-            )])
-        ))
-
-
-
-    def parse_fragment_str(x, in_quotes: bool=False, in_parens: bool=False):
         #print(f"parsing fragment string for {x}")
         fragment_string = x[0]
-        #print(f"ppparsing fragment string \"{fragment_string}\"")
-
         if len(fragment_string.strip()) == 0:
             return Fragment('')
 
@@ -413,234 +414,198 @@ def build_parser_syntax(attention_plus_base: float, attention_minus_base: float)
             # escape unescaped quotes
             fragment_string = fragment_string.replace('"', '\\"')
 
-        #fragment_parser = pp.Group(pp.OneOrMore(attention | cross_attention_substitute | (greedy_word.set_parse_action(make_text_fragment))))
         try:
-            result = pp.Group(pp.MatchFirst([
+            result = (expression + pp.StringEnd()).parse_string(fragment_string)
-                    pp.OneOrMore(quoted_fragment | attention | unquoted_word).set_name('pf_str_qfuq'),
-                    pp.Empty().set_parse_action(make_text_fragment) + pp.StringEnd()
-            ])).set_name('blend-result').set_debug(False).parse_string(fragment_string)
             #print("parsed to", result)
             return result
         except pp.ParseException as e:
             #print("parse_fragment_str couldn't parse prompt string:", e)
             raise
 
+    # meaningful symbols
+    lparen = pp.Literal("(").suppress()
+    rparen = pp.Literal(")").suppress()
+    quote = pp.Literal('"').suppress()
+    comma = pp.Literal(",").suppress()
+    dot = pp.Literal(".").suppress()
+    equals = pp.Literal("=").suppress()
+
+    escaped_lparen = pp.Literal('\\(')
+    escaped_rparen = pp.Literal('\\)')
+    escaped_quote = pp.Literal('\\"')
+    escaped_comma = pp.Literal('\\,')
+    escaped_dot = pp.Literal('\\.')
+    escaped_plus = pp.Literal('\\+')
+    escaped_minus = pp.Literal('\\-')
+    escaped_equals = pp.Literal('\\=')
+
+    syntactic_symbols = {
+        '(': escaped_lparen,
+        ')': escaped_rparen,
+        '"': escaped_quote,
+        ',': escaped_comma,
+        '.': escaped_dot,
+        '+': escaped_plus,
+        '-': escaped_minus,
+        '=': escaped_equals,
+    }
+    syntactic_chars = "".join(syntactic_symbols.keys())
+
+    # accepts int or float notation, always maps to float
+    number = pp.pyparsing_common.real | \
+             pp.Combine(pp.Optional("-")+pp.Word(pp.nums)).set_parse_action(pp.token_map(float))
+
+    # for options
+    keyword = pp.Word(pp.alphanums + '_')
+
+    # a word that absolutely does not contain any meaningful syntax
+    non_syntax_word = pp.Combine(pp.OneOrMore(pp.MatchFirst([
+            pp.Or(syntactic_symbols.values()),
+            pp.one_of(['-', '+']) + pp.NotAny(pp.White() | pp.Char(syntactic_chars) | pp.StringEnd()),
+            # build character-by-character
+            pp.CharsNotIn(string.whitespace + syntactic_chars, exact=1)
+        ])))
+    non_syntax_word.set_parse_action(lambda x: [Fragment(t) for t in x])
+    non_syntax_word.set_name('non_syntax_word')
+    non_syntax_word.set_debug(False)
+
+    # a word that can contain any character at all - greedily consumes syntax, so use with care
+    free_word = pp.CharsNotIn(string.whitespace).set_parse_action(lambda x: Fragment(x[0]))
+    free_word.set_name('free_word')
+    free_word.set_debug(False)
+
+
+    # ok here we go. forward declare some things..
+    attention = pp.Forward()
+    cross_attention_substitute = pp.Forward()
+    parenthesized_fragment = pp.Forward()
+    quoted_fragment = pp.Forward()
+
+    # the types of things that can go into a fragment, consisting of syntax-full and/or strictly syntax-free components
+    fragment_part_expressions = [
+        attention,
+        cross_attention_substitute,
+        parenthesized_fragment,
+        quoted_fragment,
+        non_syntax_word
+    ]
+    # a fragment that is permitted to contain commas
+    fragment_including_commas = pp.ZeroOrMore(pp.MatchFirst(
+        fragment_part_expressions + [
+            pp.Literal(',').set_parse_action(lambda x: Fragment(x[0]))
+        ]
+    ))
+    # a fragment that is not permitted to contain commas
+    fragment_excluding_commas = pp.ZeroOrMore(pp.MatchFirst(
+        fragment_part_expressions
+    ))
+
+    # a fragment in double quotes (may be nested)
     quoted_fragment << pp.QuotedString(quote_char='"', esc_char=None, esc_quote='\\"')
-    quoted_fragment.set_parse_action(lambda x: parse_fragment_str(x, in_quotes=True)).set_name('quoted_fragment')
+    quoted_fragment.set_parse_action(lambda x: parse_fragment_str(x, fragment_including_commas, in_quotes=True))
 
-    escaped_quote = pp.Literal('\\"')#.set_parse_action(lambda x: '"')
+    # a fragment inside parentheses (may be nested)
-    escaped_lparen = pp.Literal('\\(')#.set_parse_action(lambda x: '(')
+    parenthesized_fragment << (lparen + fragment_including_commas + rparen)
-    escaped_rparen = pp.Literal('\\)')#.set_parse_action(lambda x: ')')
+    parenthesized_fragment.set_name('parenthesized_fragment')
-    escaped_backslash = pp.Literal('\\\\')#.set_parse_action(lambda x: '"')
+    parenthesized_fragment.set_debug(False)
 
-    empty = (
+    # a string of the form (<keyword>=<float|keyword> | <float> | <keyword>) where keyword is alphanumeric + '_'
-            (lparen + pp.ZeroOrMore(pp.Word(string.whitespace)) + rparen) |
+    option = pp.Group(pp.MatchFirst([
-            (quotes + pp.ZeroOrMore(pp.Word(string.whitespace)) + quotes)).set_debug(False).set_name('empty')
+        keyword + equals + (number | keyword),  # option=value
-
+        number.copy().set_parse_action(pp.token_map(str)), # weight
-
+        keyword  # flag
-    def not_ends_with_swap(x):
-        #print("trying to match:", x)
-        return not x[0].endswith('.swap')
-
-    unquoted_word = (pp.Combine(pp.OneOrMore(
-            escaped_rparen | escaped_lparen | escaped_quote | escaped_backslash |
-            (pp.CharsNotIn(string.whitespace + '\\"()', exact=1)
-    )))
-            # don't whitespace when the next word starts with +, eg "badly +formed"
-         + (pp.White().suppress() |
-            # don't eat +/-
-            pp.NotAny(pp.Word('+') | pp.Word('-'))
-            )
-                     )
-
-    unquoted_word.set_parse_action(make_text_fragment).set_name('unquoted_word').set_debug(False)
-    #print(unquoted_fragment.parse_string("cat.swap(dog)"))
-
-    parenthesized_fragment << (lparen +
-       pp.Or([
-        (parenthesized_fragment),
-        (quoted_fragment.copy().set_parse_action(lambda x: parse_fragment_str(x, in_quotes=True)).set_debug(False)).set_name('-quoted_paren_internal').set_debug(False),
-        (pp.Combine(pp.OneOrMore(
-            escaped_quote | escaped_lparen | escaped_rparen | escaped_backslash |
-            pp.CharsNotIn(string.whitespace + '\\"()', exact=1) |
-            pp.White()
-        )).set_name('--combined').set_parse_action(lambda x: parse_fragment_str(x, in_parens=True)).set_debug(False)),
-        pp.Empty()
-       ]) + rparen)
-    parenthesized_fragment.set_name('parenthesized_fragment').set_debug(False)
-
-    debug_attention = False
-    # attention control of the form (phrase)+ / (phrase)+ / (phrase)<weight>
-    # phrase can be multiple words, can have multiple +/- signs to increase the effect or type a floating point or integer weight
-    attention_with_parens = pp.Forward()
-    attention_without_parens = pp.Forward()
-
-    attention_with_parens_foot = (number | pp.Word('+') | pp.Word('-'))\
-        .set_name("attention_foot")\
-        .set_debug(False)
-    attention_with_parens <<= pp.Group(
-        lparen +
-        pp.ZeroOrMore(quoted_fragment | attention_with_parens | parenthesized_fragment | cross_attention_substitute | attention_without_parens |
-                      (pp.Empty() + build_escaped_word_parser_charbychar('()')).set_name('undecorated_word').set_debug(debug_attention)#.set_parse_action(lambda t: t[0])
-                  )
-        + rparen + attention_with_parens_foot)
-    attention_with_parens.set_name('attention_with_parens').set_debug(debug_attention)
-
-    attention_without_parens_foot = (pp.NotAny(pp.White()) + pp.Or([pp.Word('+'), pp.Word('-')]) + pp.FollowedBy(pp.StringEnd() | pp.White() | pp.Literal('(') | pp.Literal(')') | pp.Literal(',') | pp.Literal('"')) ).set_name('attention_without_parens_foots')
-    attention_without_parens <<= pp.Group(pp.MatchFirst([
-        quoted_fragment.copy().set_name('attention_quoted_fragment_without_parens').set_debug(debug_attention) + attention_without_parens_foot,
-        pp.Combine(build_escaped_word_parser_charbychar('()+-')).set_name('attention_word_without_parens').set_debug(debug_attention)#.set_parse_action(lambda x: print('escapéd', x))
-                                 + attention_without_parens_foot#.leave_whitespace()
     ]))
-    attention_without_parens.set_name('attention_without_parens').set_debug(debug_attention)
+    # options for an operator, eg "s_start=0.1, 0.3, no_normalize"
+    options = pp.Dict(pp.Optional(pp.delimited_list(option)))
+    options.set_name('options')
+    options.set_debug(False)
 
+    # a fragment which can be used as the target for an operator - either quoted or in parentheses, or a bare vanilla word
+    potential_operator_target = (quoted_fragment | parenthesized_fragment | non_syntax_word)
 
-    attention << pp.MatchFirst([attention_with_parens,
+    # a fragment whose weight has been increased or decreased by a given amount
-                  attention_without_parens
+    attention_weight_operator = pp.Word('+') | pp.Word('-') | number
-                  ])
+    attention_explicit = (
+        pp.Group(potential_operator_target)
+        + pp.Literal('.attend')
+        + lparen
+        + pp.Group(attention_weight_operator)
+        + rparen
+    )
+    attention_explicit.set_parse_action(make_operator_object)
+    attention_implicit = (
+        pp.Group(potential_operator_target)
+        + pp.NotAny(pp.White()) # do not permit whitespace between term and operator
+        + pp.Group(attention_weight_operator)
+    )
+    attention_implicit.set_parse_action(lambda x: make_operator_object([x[0], '.attend', x[1]]))
+    attention << (attention_explicit | attention_implicit)
     attention.set_name('attention')
+    attention.set_debug(False)
 
-    def make_attention(x):
+    # cross-attention control by swapping one fragment for another
-        #print("entered make_attention with", x)
+    cross_attention_substitute << (
-        children = x[0][:-1]
+        pp.Group(potential_operator_target).set_name('ca-target').set_debug(False)
-        weight_raw = x[0][-1]
+        + pp.Literal(".swap").set_name('ca-operator').set_debug(False)
-        weight = 1.0
+        + lparen
-        if type(weight_raw) is float or type(weight_raw) is int:
+        + pp.Group(fragment_excluding_commas).set_name('ca-replacement').set_debug(False)
-            weight = weight_raw
+        + pp.Optional(comma + options).set_name('ca-options').set_debug(False)
-        elif type(weight_raw) is str:
+        + rparen
-            base = attention_plus_base if weight_raw[0] == '+' else attention_minus_base
+    )
-            weight = pow(base, len(weight_raw))
+    cross_attention_substitute.set_name('cross_attention_substitute')
-
+    cross_attention_substitute.set_debug(False)
-        #print("making Attention from", children, "with weight", weight)
+    cross_attention_substitute.set_parse_action(make_operator_object)
-
-        return Attention(weight=weight, children=[(Fragment(x) if type(x) is str else x) for x in children])
-
-    attention_with_parens.set_parse_action(make_attention)
-    attention_without_parens.set_parse_action(make_attention)
-
-    #print("parsing test:", attention_with_parens.parse_string("mountain (man)1.1"))
-
-    # cross-attention control
-    empty_string = ((lparen + rparen) |
-                    pp.Literal('""').suppress() |
-                    (lparen + pp.Literal('""').suppress() + rparen)
-                    ).set_parse_action(lambda x: Fragment(""))
-    empty_string.set_name('empty_string')
-
-    # cross attention control
-    debug_cross_attention_control = False
-    original_fragment = pp.MatchFirst([
-                        quoted_fragment.set_debug(debug_cross_attention_control),
-                        parenthesized_fragment.set_debug(debug_cross_attention_control),
-                        pp.Combine(pp.OneOrMore(pp.CharsNotIn(string.whitespace + '.', exact=1))).set_parse_action(make_text_fragment) + pp.FollowedBy(".swap"),
-                        empty_string.set_debug(debug_cross_attention_control),
-               ])
-    # support keyword=number arguments
-    cross_attention_option_keyword = pp.Or([pp.Keyword("s_start"), pp.Keyword("s_end"), pp.Keyword("t_start"), pp.Keyword("t_end"), pp.Keyword("shape_freedom")])
-    cross_attention_option = pp.Group(cross_attention_option_keyword + pp.Literal("=").suppress() + number)
-    edited_fragment = pp.MatchFirst([
-        (lparen + rparen).set_parse_action(lambda x: Fragment('')),
-        lparen +
-            (quoted_fragment | attention |
-                pp.Group(pp.ZeroOrMore(build_escaped_word_parser_charbychar(',)').set_parse_action(make_text_fragment)))
-            ) +
-            pp.Dict(pp.ZeroOrMore(comma + cross_attention_option)) +
-        rparen,
-        parenthesized_fragment
-    ])
-    cross_attention_substitute << original_fragment + pp.Literal(".swap").set_debug(False).suppress() + edited_fragment
-
-    original_fragment.set_name('original_fragment').set_debug(debug_cross_attention_control)
-    edited_fragment.set_name('edited_fragment').set_debug(debug_cross_attention_control)
-    cross_attention_substitute.set_name('cross_attention_substitute').set_debug(debug_cross_attention_control)
-
-    def make_cross_attention_substitute(x):
-        #print("making cacs for", x[0], "->", x[1], "with options", x.as_dict())
-        #if len(x>2):
-        cacs = CrossAttentionControlSubstitute(x[0], x[1], options=x.as_dict())
-        #print("made", cacs)
-        return cacs
-    cross_attention_substitute.set_parse_action(make_cross_attention_substitute)
 
 
-    # root prompt definition
+    # an entire self-contained prompt, which can be used in a Blend or Conjunction
-    debug_root_prompt = False
+    prompt = pp.ZeroOrMore(pp.MatchFirst([
-    prompt = (pp.OneOrMore(pp.MatchFirst([cross_attention_substitute.set_debug(debug_root_prompt),
+        cross_attention_substitute,
-                                  attention.set_debug(debug_root_prompt),
+        attention,
-                                  quoted_fragment.set_debug(debug_root_prompt),
+        quoted_fragment,
-                                  parenthesized_fragment.set_debug(debug_root_prompt),
+        parenthesized_fragment,
-                                  unquoted_word.set_debug(debug_root_prompt),
+        free_word,
-                                  empty.set_parse_action(make_text_fragment).set_debug(debug_root_prompt)])
+        pp.White().suppress()
-                           ) + pp.StringEnd()) \
+    ]))
-        .set_name('prompt') \
+    quoted_prompt = quoted_fragment.copy().set_parse_action(lambda x: parse_fragment_str(x, prompt, in_quotes=True))
-        .set_parse_action(lambda x: Prompt(x)) \
-        .set_debug(debug_root_prompt)
 
-    #print("parsing test:", prompt.parse_string("spaced eyes--"))
-    #print("parsing test:", prompt.parse_string("eyes--"))
 
-    # weighted blend of prompts
+    # a blend/lerp between the feature vectors for two or more prompts
-    # ("promptA", "promptB").blend(a, b) where "promptA" and "promptB" are valid prompts and a and b are float or
+    blend = (
-    # int weights.
+        lparen
-    # can specify more terms eg ("promptA", "promptB", "promptC").blend(a,b,c)
+        + pp.Group(pp.delimited_list(pp.Group(potential_operator_target | quoted_prompt), min=1)).set_name('bl-target').set_debug(False)
+        + rparen
+        + pp.Literal(".blend").set_name('bl-operator').set_debug(False)
+        + lparen
+        + pp.Group(options).set_name('bl-options').set_debug(False)
+        + rparen
+    )
+    blend.set_name('blend')
+    blend.set_debug(False)
+    blend.set_parse_action(make_operator_object)
 
-    def make_prompt_from_quoted_string(x):
+    # an operator to direct stable diffusion to step multiple times, once for each target, and then add the results together with different weights
-        #print(' got quoted prompt', x)
+    explicit_conjunction = (
+        lparen
+        + pp.Group(pp.delimited_list(pp.Group(potential_operator_target | quoted_prompt), min=1)).set_name('cj-target').set_debug(False)
+        + rparen
+        + pp.one_of([".and", ".add"]).set_name('cj-operator').set_debug(False)
+        + lparen
+        + pp.Group(options).set_name('cj-options').set_debug(False)
+        + rparen
+    )
+    explicit_conjunction.set_name('explicit_conjunction')
+    explicit_conjunction.set_debug(False)
+    explicit_conjunction.set_parse_action(make_operator_object)
 
-        x_unquoted = x[0][1:-1]
+    # by default a prompt consists of a Conjunction with a single term
-        if len(x_unquoted.strip()) == 0:
+    implicit_conjunction = (blend | pp.Group(prompt)) + pp.StringEnd()
-            # print(' b : just an empty string')
-            return Prompt([Fragment('')])
-        #print(f' b parsing \'{x_unquoted}\'')
-        x_parsed = prompt.parse_string(x_unquoted)
-        #print(" quoted prompt was parsed to", type(x_parsed),":", x_parsed)
-        return x_parsed[0]
-
-    quoted_prompt = pp.dbl_quoted_string.set_parse_action(make_prompt_from_quoted_string)
-    quoted_prompt.set_name('quoted_prompt')
-
-    debug_blend=False
-    blend_terms = pp.delimited_list(quoted_prompt).set_name('blend_terms').set_debug(debug_blend)
-    blend_weights = (pp.delimited_list(number) + pp.Optional(pp.Char(",").suppress() + "no_normalize")).set_name('blend_weights').set_debug(debug_blend)
-    blend = pp.Group(lparen + pp.Group(blend_terms) + rparen
-                     + pp.Literal(".blend").suppress()
-                     + lparen + pp.Group(blend_weights) + rparen).set_name('blend')
-    blend.set_debug(debug_blend)
-
-    def make_blend(x):
-        prompts = x[0][0]
-        weights = x[0][1]
-        normalize = True
-        if weights[-1] == 'no_normalize':
-            normalize = False
-            weights = weights[:-1]
-        return Blend(prompts=prompts, weights=weights, normalize_weights=normalize)
-
-    blend.set_parse_action(make_blend)
-
-    conjunction_terms = blend_terms.copy().set_name('conjunction_terms')
-    conjunction_weights = blend_weights.copy().set_name('conjunction_weights')
-    conjunction_with_parens_and_quotes = pp.Group(lparen + pp.Group(conjunction_terms) + rparen
-                     + pp.Literal(".and").suppress()
-                     + lparen + pp.Optional(pp.Group(conjunction_weights)) + rparen).set_name('conjunction')
-    def make_conjunction(x):
-        parts_raw = x[0][0]
-        weights = x[0][1] if len(x[0])>1 else [1.0]*len(parts_raw)
-        parts = [part for part in parts_raw]
-        return Conjunction(parts, weights)
-    conjunction_with_parens_and_quotes.set_parse_action(make_conjunction)
-
-    implicit_conjunction = pp.OneOrMore(blend | prompt).set_name('implicit_conjunction')
     implicit_conjunction.set_parse_action(lambda x: Conjunction(x))
 
-    conjunction = conjunction_with_parens_and_quotes | implicit_conjunction
+    conjunction = (explicit_conjunction | implicit_conjunction)
-    conjunction.set_debug(False)
 
-    # top-level is a conjunction of one or more blends or prompts
     return conjunction, prompt
 
 
-
 def split_weighted_subprompts(text, skip_normalize=False)->list:
     """
     Legacy blend parsing.

ldm/modules/diffusionmodules/util.py

@@ -66,7 +66,9 @@ def make_ddim_timesteps(
         c = num_ddpm_timesteps // num_ddim_timesteps
         if c < 1:
             c = 1
-        ddim_timesteps = (np.arange(0, num_ddim_timesteps) * c).astype(int)
+        
+        # remove 1 final step to prevent index out of bound error
+        ddim_timesteps = np.asarray(list(range(0, num_ddpm_timesteps, c)))[:-1]
     elif ddim_discr_method == 'quad':
         ddim_timesteps = (
             (
@@ -84,7 +86,6 @@ def make_ddim_timesteps(
     # assert ddim_timesteps.shape[0] == num_ddim_timesteps
     # add one to get the final alpha values right (the ones from first scale to data during sampling)
     steps_out = ddim_timesteps + 1
-    # steps_out = ddim_timesteps
 
     if verbose:
         print(f'Selected timesteps for ddim sampler: {steps_out}')

scripts/preload_models.py

@@ -17,6 +17,7 @@ from omegaconf import OmegaConf
 from huggingface_hub import HfFolder, hf_hub_url
 from pathlib import Path
 from getpass_asterisk import getpass_asterisk
+from transformers import CLIPTokenizer, CLIPTextModel
 import traceback
 import requests
 import clip
@@ -30,10 +31,6 @@ warnings.filterwarnings('ignore')
 #warnings.filterwarnings('ignore',category=DeprecationWarning)
 #warnings.filterwarnings('ignore',category=UserWarning)
 
-# deferred loading so that help message can be printed quickly
-def load_libs():
-    pass
-
 #--------------------------globals--
 Model_dir = './models/ldm/stable-diffusion-v1/'
 Default_config_file = './configs/models.yaml'
@@ -347,7 +344,7 @@ def update_config_file(successfully_downloaded:dict,opt:dict):
 
     try:
         if os.path.exists(Config_file):
-            print(f'* {Config_file} exists. Renaming to {Config_file}.orig')
+            print(f'** {Config_file} exists. Renaming to {Config_file}.orig')
             os.rename(Config_file,f'{Config_file}.orig')
         tmpfile = os.path.join(os.path.dirname(Config_file),'new_config.tmp')
         with open(tmpfile, 'w') as outfile:
@@ -419,9 +416,6 @@ def download_kornia():
 #---------------------------------------------
 def download_clip():
     print('Loading CLIP model...',end='')
-    with warnings.catch_warnings():
-        warnings.filterwarnings('ignore', category=DeprecationWarning)
-        from transformers import CLIPTokenizer, CLIPTextModel
     sys.stdout.flush()
     version = 'openai/clip-vit-large-patch14'
     tokenizer = CLIPTokenizer.from_pretrained(version)
@@ -550,7 +544,6 @@ if __name__ == '__main__':
                         default='./configs/models.yaml',
                         help='path to configuration file to create')
     opt = parser.parse_args()
-    load_libs()
     
     try:
         if opt.interactive:
@@ -562,16 +555,11 @@ if __name__ == '__main__':
                 if models is None:
                     if yes_or_no('Quit?',default_yes=False):
                         sys.exit(0)
-
-                done = False
-                while not done:
                 print('** LICENSE AGREEMENT FOR WEIGHT FILES **')
                 access_token = authenticate()
                 print('\n** DOWNLOADING WEIGHTS **')
                 successfully_downloaded = download_weight_datasets(models, access_token)
-                    done = successfully_downloaded is not None
                 update_config_file(successfully_downloaded,opt)
-
         print('\n** DOWNLOADING SUPPORT MODELS **')
         download_bert()
         download_kornia()

tests/test_prompt_parser.py

@@ -28,8 +28,8 @@ class PromptParserTestCase(unittest.TestCase):
         self.assertEqual(make_weighted_conjunction([('', 1)]), parse_prompt(''))
 
     def test_basic(self):
-        self.assertEqual(make_weighted_conjunction([('fire flames', 1)]), parse_prompt("fire (flames)"))
         self.assertEqual(make_weighted_conjunction([("fire flames", 1)]), parse_prompt("fire flames"))
+        self.assertEqual(make_weighted_conjunction([('fire flames', 1)]), parse_prompt("fire (flames)"))
         self.assertEqual(make_weighted_conjunction([("fire, flames", 1)]), parse_prompt("fire, flames"))
         self.assertEqual(make_weighted_conjunction([("fire, flames , fire", 1)]), parse_prompt("fire, flames , fire"))
         self.assertEqual(make_weighted_conjunction([("cat hot-dog eating", 1)]), parse_prompt("cat hot-dog eating"))
@@ -37,14 +37,25 @@ class PromptParserTestCase(unittest.TestCase):
 
     def test_attention(self):
         self.assertEqual(make_weighted_conjunction([('flames', 0.5)]), parse_prompt("(flames)0.5"))
+        self.assertEqual(make_weighted_conjunction([('flames', 0.5)]), parse_prompt("(flames).attend(0.5)"))
+        self.assertEqual(make_weighted_conjunction([('flames', 0.5)]), parse_prompt("flames.attend(0.5)"))
+        self.assertEqual(make_weighted_conjunction([('flames', 0.5)]), parse_prompt("\"flames\".attend(0.5)"))
         self.assertEqual(make_weighted_conjunction([('fire flames', 0.5)]), parse_prompt("(fire flames)0.5"))
+        self.assertEqual(make_weighted_conjunction([('fire flames', 0.5)]), parse_prompt("(fire flames).attend(0.5)"))
+
         self.assertEqual(make_weighted_conjunction([('flames', 1.1)]), parse_prompt("(flames)+"))
         self.assertEqual(make_weighted_conjunction([('flames', 1.1)]), parse_prompt("flames+"))
         self.assertEqual(make_weighted_conjunction([('flames', 1.1)]), parse_prompt("\"flames\"+"))
+        self.assertEqual(make_weighted_conjunction([('flames', 1.1)]), parse_prompt("flames.attend(+)"))
+        self.assertEqual(make_weighted_conjunction([('flames', 1.1)]), parse_prompt("(flames).attend(+)"))
+        self.assertEqual(make_weighted_conjunction([('flames', 1.1)]), parse_prompt("\"flames\".attend(+)"))
         self.assertEqual(make_weighted_conjunction([('flames', 0.9)]), parse_prompt("(flames)-"))
         self.assertEqual(make_weighted_conjunction([('flames', 0.9)]), parse_prompt("flames-"))
         self.assertEqual(make_weighted_conjunction([('flames', 0.9)]), parse_prompt("\"flames\"-"))
         self.assertEqual(make_weighted_conjunction([('fire', 1), ('flames', 0.5)]), parse_prompt("fire (flames)0.5"))
+        self.assertEqual(make_weighted_conjunction([('fire', 1), ('flames', 0.5)]), parse_prompt("fire flames.attend(0.5)"))
+        self.assertEqual(make_weighted_conjunction([('fire', 1), ('flames', 0.5)]), parse_prompt("fire (flames).attend(0.5)"))
+        self.assertEqual(make_weighted_conjunction([('fire', 1), ('flames', 0.5)]), parse_prompt("fire \"flames\".attend(0.5)"))
         self.assertEqual(make_weighted_conjunction([('flames', pow(1.1, 2))]), parse_prompt("(flames)++"))
         self.assertEqual(make_weighted_conjunction([('flames', pow(0.9, 2))]), parse_prompt("(flames)--"))
         self.assertEqual(make_weighted_conjunction([('flowers', pow(0.9, 3)), ('flames', pow(1.1, 3))]), parse_prompt("(flowers)--- flames+++"))
@@ -102,20 +113,17 @@ class PromptParserTestCase(unittest.TestCase):
 
         assert_if_prompt_string_not_untouched('a test prompt')
         assert_if_prompt_string_not_untouched('a badly formed +test prompt')
-        with self.assertRaises(pyparsing.ParseException):
+        assert_if_prompt_string_not_untouched('a badly (formed test prompt')
-            parse_prompt('a badly (formed test prompt')
+
         #with self.assertRaises(pyparsing.ParseException):
-        with self.assertRaises(pyparsing.ParseException):
+        assert_if_prompt_string_not_untouched('a badly (formed +test prompt')
-            parse_prompt('a badly (formed +test prompt')
         self.assertEqual(Conjunction([FlattenedPrompt([Fragment('a badly formed +test prompt',1)])]) , parse_prompt('a badly (formed +test )prompt'))
-        with self.assertRaises(pyparsing.ParseException):
+        self.assertEqual(Conjunction([FlattenedPrompt([Fragment('(((a badly formed +test prompt',1)])]) , parse_prompt('(((a badly (formed +test )prompt'))
-            parse_prompt('(((a badly (formed +test )prompt')
+
-        with self.assertRaises(pyparsing.ParseException):
+        self.assertEqual(Conjunction([FlattenedPrompt([Fragment('(a ba dly f ormed +test prompt',1)])]) , parse_prompt('(a (ba)dly (f)ormed +test prompt'))
-            parse_prompt('(a (ba)dly (f)ormed +test prompt')
+        self.assertEqual(Conjunction([FlattenedPrompt([Fragment('(a ba dly f ormed +test +prompt',1)])]) , parse_prompt('(a (ba)dly (f)ormed +test +prompt'))
-        with self.assertRaises(pyparsing.ParseException):
+        self.assertEqual(Conjunction([Blend([FlattenedPrompt([Fragment('((a badly (formed +test', 1)])], [1.0])]),
-            parse_prompt('(a (ba)dly (f)ormed +test +prompt')
+                         parse_prompt('("((a badly (formed +test ").blend(1.0)'))
-        with self.assertRaises(pyparsing.ParseException):
-            parse_prompt('("((a badly (formed +test ").blend(1.0)')
 
         self.assertEqual(Conjunction([FlattenedPrompt([Fragment('hamburger bun', 1)])]),
             parse_prompt("hamburger ((bun))"))
@@ -128,6 +136,26 @@ class PromptParserTestCase(unittest.TestCase):
 
 
     def test_blend(self):
+        self.assertEqual(Conjunction(
+            [Blend([FlattenedPrompt([('mountain', 1.0)]), FlattenedPrompt([('man', 1.0)])], [1.0, 1.0])]),
+                         parse_prompt("(\"mountain\", \"man\").blend()")
+                         )
+        self.assertEqual(Conjunction(
+            [Blend([FlattenedPrompt([('mountain', 1.0)]), FlattenedPrompt([('man', 1.0)])], [1.0, 1.0])]),
+                         parse_prompt("(mountain, man).blend()")
+                         )
+        self.assertEqual(Conjunction(
+            [Blend([FlattenedPrompt([('mountain', 1.0)]), FlattenedPrompt([('man', 1.0)])], [1.0, 1.0])]),
+                         parse_prompt("((mountain), (man)).blend()")
+                         )
+        self.assertEqual(Conjunction(
+            [Blend([FlattenedPrompt([('mountain', 1.0)]), FlattenedPrompt([('tall man', 1.0)])], [1.0, 1.0])]),
+                         parse_prompt("((mountain), (tall man)).blend()")
+                         )
+
+        with self.assertRaises(PromptParser.ParsingException):
+             print(parse_prompt("((mountain), \"cat.swap(dog)\").blend()"))
+
         self.assertEqual(Conjunction(
             [Blend([FlattenedPrompt([('fire', 1.0)]), FlattenedPrompt([('fire flames', 1.0)])], [0.7, 0.3])]),
                          parse_prompt("(\"fire\", \"fire flames\").blend(0.7, 0.3)")
@@ -166,10 +194,20 @@ class PromptParserTestCase(unittest.TestCase):
             )
 
         self.assertEqual(
-            Conjunction([Blend([FlattenedPrompt([('mountain, man, hairy', 1)]),
+            Conjunction([Blend([FlattenedPrompt([('mountain , man , hairy', 1)]),
-                                FlattenedPrompt([('face, teeth,', 1), ('eyes', 0.9*0.9)])], weights=[1.0,-1.0])]),
+                                FlattenedPrompt([('face , teeth ,', 1), ('eyes', 0.9*0.9)])], weights=[1.0,-1.0], normalize_weights=True)]),
             parse_prompt('("mountain, man, hairy", "face, teeth, eyes--").blend(1,-1)')
         )
+        self.assertEqual(
+            Conjunction([Blend([FlattenedPrompt([('mountain , man , hairy', 1)]),
+                                FlattenedPrompt([('face , teeth ,', 1), ('eyes', 0.9 * 0.9)])], weights=[1.0, -1.0], normalize_weights=False)]),
+            parse_prompt('("mountain, man, hairy", "face, teeth, eyes--").blend(1,-1,no_normalize)')
+        )
+
+        with self.assertRaises(PromptParser.ParsingException):
+             parse_prompt("(\"fire\", \"fire flames\").blend(0.7, 0.3, 0.1)")
+        with self.assertRaises(PromptParser.ParsingException):
+             parse_prompt("(\"fire\", \"fire flames\").blend(0.7)")
 
 
     def test_nested(self):
@@ -182,6 +220,9 @@ class PromptParserTestCase(unittest.TestCase):
 
     def test_cross_attention_control(self):
 
+        self.assertEqual(Conjunction([FlattenedPrompt([CrossAttentionControlSubstitute([Fragment('sun')], [Fragment('moon')])])]),
+                         parse_prompt("sun.swap(moon)"))
+
         self.assertEqual(Conjunction([
             FlattenedPrompt([Fragment('a', 1),
                              CrossAttentionControlSubstitute([Fragment('cat', 1)], [Fragment('dog', 1)]),
@@ -231,6 +272,9 @@ class PromptParserTestCase(unittest.TestCase):
         self.assertEqual(Conjunction([FlattenedPrompt([Fragment('a forest landscape', 1),
                                                                    CrossAttentionControlSubstitute([Fragment('',1)], [Fragment('in winter',1)])])]),
                          parse_prompt('a forest landscape "".swap("in winter")'))
+        self.assertEqual(Conjunction([FlattenedPrompt([Fragment('a forest landscape', 1),
+                                                                   CrossAttentionControlSubstitute([Fragment('',1)], [Fragment('in winter',1)])])]),
+                         parse_prompt('a forest landscape ().swap(in winter)'))
         self.assertEqual(Conjunction([FlattenedPrompt([Fragment('a forest landscape', 1),
                                                                    CrossAttentionControlSubstitute([Fragment('',1)], [Fragment('in winter',1)])])]),
                          parse_prompt('a forest landscape " ".swap("in winter")'))
@@ -259,6 +303,12 @@ class PromptParserTestCase(unittest.TestCase):
                                                         Fragment(',', 1), Fragment('fire', 2.0)])])
         self.assertEqual(flames_to_trees_fire, parse_prompt('"(fire (flames)0.5)0.5".swap("(trees)0.7 houses"), (fire)2.0'))
 
+        self.assertEqual(Conjunction([FlattenedPrompt([Fragment('a', 1),
+                                                       CrossAttentionControlSubstitute([Fragment('cat',1)], [Fragment('dog',1)]),
+                                                       Fragment('eating a', 1),
+                                                       CrossAttentionControlSubstitute([Fragment('hotdog',1)], [Fragment('hotdog', pow(1.1,4))])
+                                                       ])]),
+            parse_prompt("a cat.swap(dog) eating a hotdog.swap(hotdog++++)"))
         self.assertEqual(Conjunction([FlattenedPrompt([Fragment('a', 1),
                                                        CrossAttentionControlSubstitute([Fragment('cat',1)], [Fragment('dog',1)]),
                                                        Fragment('eating a', 1),
@@ -343,31 +393,31 @@ class PromptParserTestCase(unittest.TestCase):
         self.assertEqual(make_weighted_conjunction([('hairy', 1), ('mountain', 1.1), ('\(man\)', 1.1*1.1)]),parse_prompt('hairy (mountain (\(man\))+)+'))
         self.assertEqual(make_weighted_conjunction([('hairy', 1), ('\(man\)', 1.1*1.1), ('mountain', 1.1)]),parse_prompt('hairy ((\(man\))1.1 "mountain")+'))
         self.assertEqual(make_weighted_conjunction([('hairy', 1), ('mountain', 1.1), ('\(man\)', 1.1*1.1)]),parse_prompt('hairy ("mountain" (\(man\))1.1 )+'))
-        self.assertEqual(make_weighted_conjunction([('hairy', 1), ('mountain, man', 1.1)]),parse_prompt('hairy ("mountain, man")+'))
+        self.assertEqual(make_weighted_conjunction([('hairy', 1), ('mountain , man', 1.1)]),parse_prompt('hairy ("mountain, man")+'))
-        self.assertEqual(make_weighted_conjunction([('hairy', 1), ('mountain, man with a', 1.1), ('beard', 1.1*1.1)]), parse_prompt('hairy ("mountain, man" with a beard+)+'))
+        self.assertEqual(make_weighted_conjunction([('hairy', 1), ('mountain , man with a', 1.1), ('beard', 1.1*1.1)]), parse_prompt('hairy ("mountain, man" with a beard+)+'))
-        self.assertEqual(make_weighted_conjunction([('hairy', 1), ('mountain, man with a', 1.1), ('beard', 1.1*2.0)]), parse_prompt('hairy ("mountain, man" with a (beard)2.0)+'))
+        self.assertEqual(make_weighted_conjunction([('hairy', 1), ('mountain , man with a', 1.1), ('beard', 1.1*2.0)]), parse_prompt('hairy ("mountain, man" with a (beard)2.0)+'))
-        self.assertEqual(make_weighted_conjunction([('hairy', 1), ('mountain, \"man\" with a', 1.1), ('beard', 1.1*2.0)]), parse_prompt('hairy ("mountain, \\"man\\"" with a (beard)2.0)+'))
+        self.assertEqual(make_weighted_conjunction([('hairy', 1), ('mountain , \"man\" with a', 1.1), ('beard', 1.1*2.0)]), parse_prompt('hairy ("mountain, \\"man\\"" with a (beard)2.0)+'))
-        self.assertEqual(make_weighted_conjunction([('hairy', 1), ('mountain, m\"an\" with a', 1.1), ('beard', 1.1*2.0)]), parse_prompt('hairy ("mountain, m\\"an\\"" with a (beard)2.0)+'))
+        self.assertEqual(make_weighted_conjunction([('hairy', 1), ('mountain , m\"an\" with a', 1.1), ('beard', 1.1*2.0)]), parse_prompt('hairy ("mountain, m\\"an\\"" with a (beard)2.0)+'))
 
-        self.assertEqual(make_weighted_conjunction([('hairy', 1), ('mountain, \"man (with a', 1.1), ('beard', 1.1*2.0)]), parse_prompt('hairy ("mountain, \\\"man\" \(with a (beard)2.0)+'))
+        self.assertEqual(make_weighted_conjunction([('hairy', 1), ('mountain , \"man (with a', 1.1), ('beard', 1.1*2.0)]), parse_prompt('hairy ("mountain, \\\"man\" \(with a (beard)2.0)+'))
-        self.assertEqual(make_weighted_conjunction([('hairy', 1), ('mountain, \"man w(ith a', 1.1), ('beard', 1.1*2.0)]), parse_prompt('hairy ("mountain, \\\"man\" w\(ith a (beard)2.0)+'))
+        self.assertEqual(make_weighted_conjunction([('hairy', 1), ('mountain , \"man w(ith a', 1.1), ('beard', 1.1*2.0)]), parse_prompt('hairy ("mountain, \\\"man\" w\(ith a (beard)2.0)+'))
-        self.assertEqual(make_weighted_conjunction([('hairy', 1), ('mountain, \"man with( a', 1.1), ('beard', 1.1*2.0)]), parse_prompt('hairy ("mountain, \\\"man\" with\( a (beard)2.0)+'))
+        self.assertEqual(make_weighted_conjunction([('hairy', 1), ('mountain , \"man with( a', 1.1), ('beard', 1.1*2.0)]), parse_prompt('hairy ("mountain, \\\"man\" with\( a (beard)2.0)+'))
-        self.assertEqual(make_weighted_conjunction([('hairy', 1), ('mountain, \"man )with a', 1.1), ('beard', 1.1*2.0)]), parse_prompt('hairy ("mountain, \\\"man\" \)with a (beard)2.0)+'))
+        self.assertEqual(make_weighted_conjunction([('hairy', 1), ('mountain , \"man )with a', 1.1), ('beard', 1.1*2.0)]), parse_prompt('hairy ("mountain, \\\"man\" \)with a (beard)2.0)+'))
-        self.assertEqual(make_weighted_conjunction([('hairy', 1), ('mountain, \"man w)ith a', 1.1), ('beard', 1.1*2.0)]), parse_prompt('hairy ("mountain, \\\"man\" w\)ith a (beard)2.0)+'))
+        self.assertEqual(make_weighted_conjunction([('hairy', 1), ('mountain , \"man w)ith a', 1.1), ('beard', 1.1*2.0)]), parse_prompt('hairy ("mountain, \\\"man\" w\)ith a (beard)2.0)+'))
-        self.assertEqual(make_weighted_conjunction([('hairy', 1), ('mountain, \"man with) a', 1.1), ('beard', 1.1*2.0)]), parse_prompt('hairy ("mountain, \\\"man\" with\) a (beard)2.0)+'))
+        self.assertEqual(make_weighted_conjunction([('hairy', 1), ('mountain , \"man with) a', 1.1), ('beard', 1.1*2.0)]), parse_prompt('hairy ("mountain, \\\"man\" with\) a (beard)2.0)+'))
-        self.assertEqual(make_weighted_conjunction([('hairy', 1), ('mou)ntain, \"man (wit(h a', 1.1), ('beard', 1.1*2.0)]), parse_prompt('hairy ("mou\)ntain, \\\"man\" \(wit\(h a (beard)2.0)+'))
+        self.assertEqual(make_weighted_conjunction([('hairy', 1), ('mou)ntain , \"man (wit(h a', 1.1), ('beard', 1.1*2.0)]), parse_prompt('hairy ("mou\)ntain, \\\"man\" \(wit\(h a (beard)2.0)+'))
-        self.assertEqual(make_weighted_conjunction([('hai(ry', 1), ('mountain, \"man w)ith a', 1.1), ('beard', 1.1*2.0)]), parse_prompt('hai\(ry ("mountain, \\\"man\" w\)ith a (beard)2.0)+'))
+        self.assertEqual(make_weighted_conjunction([('hai(ry', 1), ('mountain , \"man w)ith a', 1.1), ('beard', 1.1*2.0)]), parse_prompt('hai\(ry ("mountain, \\\"man\" w\)ith a (beard)2.0)+'))
-        self.assertEqual(make_weighted_conjunction([('hairy((', 1), ('mountain, \"man with a', 1.1), ('beard', 1.1*2.0)]), parse_prompt('hairy\(\( ("mountain, \\\"man\" with a (beard)2.0)+'))
+        self.assertEqual(make_weighted_conjunction([('hairy((', 1), ('mountain , \"man with a', 1.1), ('beard', 1.1*2.0)]), parse_prompt('hairy\(\( ("mountain, \\\"man\" with a (beard)2.0)+'))
 
-        self.assertEqual(make_weighted_conjunction([('mountain, \"man (with a', 1.1), ('beard', 1.1*2.0), ('hairy', 1)]), parse_prompt('("mountain, \\\"man\" \(with a (beard)2.0)+ hairy'))
+        self.assertEqual(make_weighted_conjunction([('mountain , \"man (with a', 1.1), ('beard', 1.1*2.0), ('hairy', 1)]), parse_prompt('("mountain, \\\"man\" \(with a (beard)2.0)+ hairy'))
-        self.assertEqual(make_weighted_conjunction([('mountain, \"man w(ith a', 1.1), ('beard', 1.1*2.0), ('hairy', 1)]), parse_prompt('("mountain, \\\"man\" w\(ith a (beard)2.0)+hairy'))
+        self.assertEqual(make_weighted_conjunction([('mountain , \"man w(ith a', 1.1), ('beard', 1.1*2.0), ('hairy', 1)]), parse_prompt('("mountain, \\\"man\" w\(ith a (beard)2.0)+hairy'))
-        self.assertEqual(make_weighted_conjunction([('mountain, \"man with( a', 1.1), ('beard', 1.1*2.0), ('hairy', 1)]), parse_prompt('("mountain, \\\"man\" with\( a (beard)2.0)+ hairy'))
+        self.assertEqual(make_weighted_conjunction([('mountain , \"man with( a', 1.1), ('beard', 1.1*2.0), ('hairy', 1)]), parse_prompt('("mountain, \\\"man\" with\( a (beard)2.0)+ hairy'))
-        self.assertEqual(make_weighted_conjunction([('mountain, \"man )with a', 1.1), ('beard', 1.1*2.0), ('hairy', 1)]), parse_prompt('("mountain, \\\"man\" \)with a (beard)2.0)+ hairy'))
+        self.assertEqual(make_weighted_conjunction([('mountain , \"man )with a', 1.1), ('beard', 1.1*2.0), ('hairy', 1)]), parse_prompt('("mountain, \\\"man\" \)with a (beard)2.0)+ hairy'))
-        self.assertEqual(make_weighted_conjunction([('mountain, \"man w)ith a', 1.1), ('beard', 1.1*2.0), ('hairy', 1)]), parse_prompt('("mountain, \\\"man\" w\)ith a (beard)2.0)+ hairy'))
+        self.assertEqual(make_weighted_conjunction([('mountain , \"man w)ith a', 1.1), ('beard', 1.1*2.0), ('hairy', 1)]), parse_prompt('("mountain, \\\"man\" w\)ith a (beard)2.0)+ hairy'))
-        self.assertEqual(make_weighted_conjunction([('mountain, \"man with) a', 1.1), ('beard', 1.1*2.0), ('hairy', 1)]), parse_prompt(' ("mountain, \\\"man\" with\) a (beard)2.0)+ hairy'))
+        self.assertEqual(make_weighted_conjunction([('mountain , \"man with) a', 1.1), ('beard', 1.1*2.0), ('hairy', 1)]), parse_prompt(' ("mountain, \\\"man\" with\) a (beard)2.0)+ hairy'))
-        self.assertEqual(make_weighted_conjunction([('mou)ntain, \"man (wit(h a', 1.1), ('beard', 1.1*2.0), ('hairy', 1)]), parse_prompt('("mou\)ntain, \\\"man\" \(wit\(h a (beard)2.0)+ hairy'))
+        self.assertEqual(make_weighted_conjunction([('mou)ntain , \"man (wit(h a', 1.1), ('beard', 1.1*2.0), ('hairy', 1)]), parse_prompt('("mou\)ntain, \\\"man\" \(wit\(h a (beard)2.0)+ hairy'))
-        self.assertEqual(make_weighted_conjunction([('mountain, \"man w)ith a', 1.1), ('beard', 1.1*2.0), ('hai(ry', 1)]), parse_prompt('("mountain, \\\"man\" w\)ith a (beard)2.0)+ hai\(ry '))
+        self.assertEqual(make_weighted_conjunction([('mountain , \"man w)ith a', 1.1), ('beard', 1.1*2.0), ('hai(ry', 1)]), parse_prompt('("mountain, \\\"man\" w\)ith a (beard)2.0)+ hai\(ry '))
-        self.assertEqual(make_weighted_conjunction([('mountain, \"man with a', 1.1), ('beard', 1.1*2.0), ('hairy((', 1)]), parse_prompt('("mountain, \\\"man\" with a (beard)2.0)+ hairy\(\( '))
+        self.assertEqual(make_weighted_conjunction([('mountain , \"man with a', 1.1), ('beard', 1.1*2.0), ('hairy((', 1)]), parse_prompt('("mountain, \\\"man\" with a (beard)2.0)+ hairy\(\( '))
 
     def test_cross_attention_escaping(self):
 
@@ -433,6 +483,15 @@ class PromptParserTestCase(unittest.TestCase):
 
 
     def test_single(self):
+        self.assertEqual(Conjunction([FlattenedPrompt([("mountain man", 1.0)]),
+                                      FlattenedPrompt([("a person with a hat", 1.0),
+                                                       ("riding a", 1.1*1.1),
+                                                       CrossAttentionControlSubstitute(
+                                                           [Fragment("bicycle", pow(1.1,2))],
+                                                           [Fragment("skateboard", pow(1.1,2))])
+                                                       ])
+                                      ], weights=[0.5, 0.5]),
+                         parse_prompt("(\"mountain man\", \"a person with a hat (riding a bicycle.swap(skateboard))++\").and(0.5, 0.5)"))
         pass