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

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Matthias Wild 2022-11-04 16:25:00 +01:00 committed by GitHub
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32
.github/workflows/build-container.yml vendored
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@ -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
cache-from: type=local,src=/tmp/.buildx-cache
cache-to: type=local,dest=/tmp/.buildx-cache
tags: ${{ env.dockertag }}:${{ matrix.arch }}
build-args: |
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 }}

10
.github/workflows/test-invoke-conda.yml vendored
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@ -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

15
docker-build/Dockerfile
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@ -39,12 +39,13 @@ RUN apt-get update \
&& apt-get clean \
&& rm -rf /var/lib/apt/lists/*
# clone repository and create symlinks
ARG invokeai_git=https://github.com/invoke-ai/InvokeAI.git
# clone repository, create models.yaml and create symlinks
ARG invokeai_git=invoke-ai/InvokeAI
ARG invokeai_branch=main
ARG project_name=invokeai
RUN git clone ${invokeai_git} /${project_name} \
&& mkdir /${project_name}/models/ldm/stable-diffusion-v1 \
&& ln -s /data/models/sd-v1-4.ckpt /${project_name}/models/ldm/stable-diffusion-v1/model.ckpt \
RUN git clone -b ${invokeai_branch} https://github.com/${invokeai_git}.git /${project_name} \
&& cp /${project_name}/configs/models.yaml.example /${project_name}/configs/models.yaml \
&& ln -s /data/models/v1-5-pruned-emaonly.ckpt /${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}

15
docker-build/build.sh
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@ -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"
_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
echo "downloading v1-5-pruned-emaonly.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 \
.

6
environment-linux-aarch64.yml
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@ -3,15 +3,14 @@ channels:
- pytorch
- conda-forge
dependencies:
- python>=3.9
- pip>=20.3
- python=3.9.*
- 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

501
frontend/dist/assets/index.8eb7dfe4.js vendored Normal file
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50
frontend/src/features/system/SettingsModal/SettingsModalItem.tsx
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@ -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))}
/>
);
}

16
ldm/invoke/generator/base.py
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@ -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
v1_4_latent_rgb_factors = torch.tensor([
# these updated numbers for v1.5 are from @torridgristle
v1_5_latent_rgb_factors = torch.tensor([
# R G B
[ 0.298, 0.207, 0.208], # L1
[ 0.187, 0.286, 0.173], # L2
[-0.158, 0.189, 0.264], # L3
[-0.184, -0.271, -0.473], # L4
[ 0.3444, 0.1385, 0.0670], # L1
[ 0.1247, 0.4027, 0.1494], # L2
[-0.3192, 0.2513, 0.2103], # L3
[-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

477
ldm/invoke/prompt_parser.py
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@ -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):
self.original = original
self.edited = edited
def __init__(self, original: list, edited: list, options: dict=None):
self.original = original if len(original)>0 else [Fragment('')]
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, "...")
if type(node) is pp.ParseResults:
verbose and print(prefix + "flattening", node, "...")
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()
rparen = pp.Literal(")").suppress()
quotes = pp.Literal('"').suppress()
comma = pp.Literal(",").suppress()
raise PromptParser.UnrecognizedOperatorException(operator)
# 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))
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):
def parse_fragment_str(x, expression: pp.ParseExpression, 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([
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)
result = (expression + pp.StringEnd()).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: '"')
escaped_lparen = pp.Literal('\\(')#.set_parse_action(lambda x: '(')
escaped_rparen = pp.Literal('\\)')#.set_parse_action(lambda x: ')')
escaped_backslash = pp.Literal('\\\\')#.set_parse_action(lambda x: '"')
# a fragment inside parentheses (may be nested)
parenthesized_fragment << (lparen + fragment_including_commas + rparen)
parenthesized_fragment.set_name('parenthesized_fragment')
parenthesized_fragment.set_debug(False)
empty = (
(lparen + pp.ZeroOrMore(pp.Word(string.whitespace)) + rparen) |
(quotes + pp.ZeroOrMore(pp.Word(string.whitespace)) + quotes)).set_debug(False).set_name('empty')
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()
# a string of the form (<keyword>=<float|keyword> | <float> | <keyword>) where keyword is alphanumeric + '_'
option = pp.Group(pp.MatchFirst([
keyword + equals + (number | keyword), # option=value
number.copy().set_parse_action(pp.token_map(str)), # weight
keyword # flag
]))
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,
attention_without_parens
])
# a fragment whose weight has been increased or decreased by a given amount
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):
#print("entered make_attention with", x)
children = x[0][:-1]
weight_raw = x[0][-1]
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))
#print("making Attention from", children, "with weight", weight)
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)
# cross-attention control by swapping one fragment for another
cross_attention_substitute << (
pp.Group(potential_operator_target).set_name('ca-target').set_debug(False)
+ pp.Literal(".swap").set_name('ca-operator').set_debug(False)
+ lparen
+ pp.Group(fragment_excluding_commas).set_name('ca-replacement').set_debug(False)
+ pp.Optional(comma + options).set_name('ca-options').set_debug(False)
+ rparen
)
cross_attention_substitute.set_name('cross_attention_substitute')
cross_attention_substitute.set_debug(False)
cross_attention_substitute.set_parse_action(make_operator_object)
# root prompt definition
debug_root_prompt = False
prompt = (pp.OneOrMore(pp.MatchFirst([cross_attention_substitute.set_debug(debug_root_prompt),
attention.set_debug(debug_root_prompt),
quoted_fragment.set_debug(debug_root_prompt),
parenthesized_fragment.set_debug(debug_root_prompt),
unquoted_word.set_debug(debug_root_prompt),
empty.set_parse_action(make_text_fragment).set_debug(debug_root_prompt)])
) + pp.StringEnd()) \
.set_name('prompt') \
.set_parse_action(lambda x: Prompt(x)) \
.set_debug(debug_root_prompt)
# an entire self-contained prompt, which can be used in a Blend or Conjunction
prompt = pp.ZeroOrMore(pp.MatchFirst([
cross_attention_substitute,
attention,
quoted_fragment,
parenthesized_fragment,
free_word,
pp.White().suppress()
]))
quoted_prompt = quoted_fragment.copy().set_parse_action(lambda x: parse_fragment_str(x, prompt, in_quotes=True))
#print("parsing test:", prompt.parse_string("spaced eyes--"))
#print("parsing test:", prompt.parse_string("eyes--"))
# weighted blend of prompts
# ("promptA", "promptB").blend(a, b) where "promptA" and "promptB" are valid prompts and a and b are float or
# int weights.
# can specify more terms eg ("promptA", "promptB", "promptC").blend(a,b,c)
# a blend/lerp between the feature vectors for two or more prompts
blend = (
lparen
+ 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):
#print(' got quoted prompt', x)
# an operator to direct stable diffusion to step multiple times, once for each target, and then add the results together with different weights
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]
if len(x_unquoted.strip()) == 0:
# 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')
# by default a prompt consists of a Conjunction with a single term
implicit_conjunction = (blend | pp.Group(prompt)) + pp.StringEnd()
implicit_conjunction.set_parse_action(lambda x: Conjunction(x))
conjunction = conjunction_with_parens_and_quotes | implicit_conjunction
conjunction.set_debug(False)
conjunction = (explicit_conjunction | implicit_conjunction)
# 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.

5
ldm/modules/diffusionmodules/util.py
View File

@ -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}')

16
scripts/preload_models.py
View File

@ -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()

135
tests/test_prompt_parser.py
View File

@ -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):
parse_prompt('a badly (formed test prompt')
assert_if_prompt_string_not_untouched('a badly (formed test prompt')
#with self.assertRaises(pyparsing.ParseException):
with self.assertRaises(pyparsing.ParseException):
parse_prompt('a badly (formed +test prompt')
assert_if_prompt_string_not_untouched('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):
parse_prompt('(((a badly (formed +test )prompt')
with self.assertRaises(pyparsing.ParseException):
parse_prompt('(a (ba)dly (f)ormed +test prompt')
with self.assertRaises(pyparsing.ParseException):
parse_prompt('(a (ba)dly (f)ormed +test +prompt')
with self.assertRaises(pyparsing.ParseException):
parse_prompt('("((a badly (formed +test ").blend(1.0)')
self.assertEqual(Conjunction([FlattenedPrompt([Fragment('(((a badly formed +test prompt',1)])]) , parse_prompt('(((a badly (formed +test )prompt'))
self.assertEqual(Conjunction([FlattenedPrompt([Fragment('(a ba dly f ormed +test prompt',1)])]) , 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'))
self.assertEqual(Conjunction([Blend([FlattenedPrompt([Fragment('((a badly (formed +test', 1)])], [1.0])]),
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)]),
FlattenedPrompt([('face, teeth,', 1), ('eyes', 0.9*0.9)])], weights=[1.0,-1.0])]),
Conjunction([Blend([FlattenedPrompt([('mountain , man , hairy', 1)]),
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 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, 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', 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*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, \"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 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 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([('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([('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 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), ('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([('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 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 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([('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 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 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 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\(h a (beard)2.0)+ hairy'))
self.assertEqual(make_weighted_conjunction([('mountain , \"man w)ith a', 1.1), ('beard', 1.1*2.0), ('hai(ry', 1)]), parse_prompt('("mountain, \\\"man\" w\)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\(\( '))
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