repo stringclasses 454
values | file_path stringlengths 5 201 | extension stringclasses 1
value | content stringlengths 8 509k | num_lines int64 3 16.9k | size_bytes int64 8 511k |
|---|---|---|---|---|---|
InvokeAI | invokeai/backend/image_util/normal_bae/nets/baseline.py | .py | import torch
import torch.nn as nn
import torch.nn.functional as F
from .submodules.submodules import UpSampleBN, norm_normalize
# This is the baseline encoder-decoder we used in the ablation study
class NNET(nn.Module):
def __init__(self, args=None):
super(NNET, self).__init__()
self.encoder = E... | 86 | 2,980 |
InvokeAI | invokeai/backend/image_util/normal_bae/nets/submodules/submodules.py | .py | import torch
import torch.nn as nn
import torch.nn.functional as F
########################################################################################################################
# Upsample + BatchNorm
class UpSampleBN(nn.Module):
def __init__(self, skip_input, output_features):
super(UpSampleB... | 140 | 5,703 |
InvokeAI | invokeai/backend/image_util/normal_bae/nets/submodules/encoder.py | .py | import os
import torch
import torch.nn as nn
import torch.nn.functional as F
class Encoder(nn.Module):
def __init__(self):
super(Encoder, self).__init__()
basemodel_name = 'tf_efficientnet_b5_ap'
print('Loading base model ()...'.format(basemodel_name), end='')
repo_path = os.path.... | 35 | 1,060 |
InvokeAI | invokeai/backend/image_util/normal_bae/nets/submodules/decoder.py | .py | import torch
import torch.nn as nn
import torch.nn.functional as F
from .submodules import UpSampleBN, UpSampleGN, norm_normalize, sample_points
class Decoder(nn.Module):
def __init__(self, args):
super(Decoder, self).__init__()
# hyper-parameter for sampling
self.sampling_ratio = args.sa... | 203 | 10,480 |
InvokeAI | invokeai/backend/image_util/normal_bae/nets/submodules/efficientnet_repo/onnx_optimize.py | .py | """ ONNX optimization script
Run ONNX models through the optimizer to prune unneeded nodes, fuse batchnorm layers into conv, etc.
NOTE: This isn't working consistently in recent PyTorch/ONNX combos (ie PyTorch 1.6 and ONNX 1.7),
it seems time to switch to using the onnxruntime online optimizer (can also be saved for ... | 85 | 2,932 |
InvokeAI | invokeai/backend/image_util/normal_bae/nets/submodules/efficientnet_repo/utils.py | .py | import os
class AverageMeter:
"""Computes and stores the average and current value"""
def __init__(self):
self.reset()
def reset(self):
self.val = 0
self.avg = 0
self.sum = 0
self.count = 0
def update(self, val, n=1):
self.val = val
self.sum +=... | 53 | 1,297 |
InvokeAI | invokeai/backend/image_util/normal_bae/nets/submodules/efficientnet_repo/caffe2_validate.py | .py | """ Caffe2 validation script
This script is created to verify exported ONNX models running in Caffe2
It utilizes the same PyTorch dataloader/processing pipeline for a
fair comparison against the originals.
Copyright 2020 Ross Wightman
"""
import argparse
import numpy as np
from caffe2.python import core, workspace, m... | 139 | 5,993 |
InvokeAI | invokeai/backend/image_util/normal_bae/nets/submodules/efficientnet_repo/setup.py | .py | """ Setup
"""
from setuptools import setup, find_packages
from codecs import open
from os import path
here = path.abspath(path.dirname(__file__))
# Get the long description from the README file
with open(path.join(here, 'README.md'), encoding='utf-8') as f:
long_description = f.read()
exec(open('geffnet/version.... | 48 | 1,737 |
InvokeAI | invokeai/backend/image_util/normal_bae/nets/submodules/efficientnet_repo/caffe2_benchmark.py | .py | """ Caffe2 validation script
This script runs Caffe2 benchmark on exported ONNX model.
It is a useful tool for reporting model FLOPS.
Copyright 2020 Ross Wightman
"""
import argparse
from caffe2.python import core, workspace, model_helper
from caffe2.proto import caffe2_pb2
parser = argparse.ArgumentParser(descript... | 66 | 2,428 |
InvokeAI | invokeai/backend/image_util/normal_bae/nets/submodules/efficientnet_repo/onnx_to_caffe.py | .py | import argparse
import onnx
from caffe2.python.onnx.backend import Caffe2Backend
parser = argparse.ArgumentParser(description="Convert ONNX to Caffe2")
parser.add_argument("model", help="The ONNX model")
parser.add_argument("--c2-prefix", required=True,
help="The output file prefix for the caffe2 model init and... | 28 | 843 |
InvokeAI | invokeai/backend/image_util/normal_bae/nets/submodules/efficientnet_repo/validate.py | .py | from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import argparse
import time
import torch
import torch.nn as nn
import torch.nn.parallel
from contextlib import suppress
import geffnet
from data import Dataset, create_loader, resolve_data_config
from utils im... | 167 | 6,632 |
InvokeAI | invokeai/backend/image_util/normal_bae/nets/submodules/efficientnet_repo/onnx_validate.py | .py | """ ONNX-runtime validation script
This script was created to verify accuracy and performance of exported ONNX
models running with the onnxruntime. It utilizes the PyTorch dataloader/processing
pipeline for a fair comparison against the originals.
Copyright 2020 Ross Wightman
"""
import argparse
import numpy as np
im... | 113 | 4,905 |
InvokeAI | invokeai/backend/image_util/normal_bae/nets/submodules/efficientnet_repo/onnx_export.py | .py | """ ONNX export script
Export PyTorch models as ONNX graphs.
This export script originally started as an adaptation of code snippets found at
https://pytorch.org/tutorials/advanced/super_resolution_with_onnxruntime.html
The default parameters work with PyTorch 1.6 and ONNX 1.7 and produce an optimal ONNX graph
for h... | 121 | 5,821 |
InvokeAI | invokeai/backend/image_util/normal_bae/nets/submodules/efficientnet_repo/geffnet/model_factory.py | .py | from .config import set_layer_config
from .helpers import load_checkpoint
from .gen_efficientnet import *
from .mobilenetv3 import *
def create_model(
model_name='mnasnet_100',
pretrained=None,
num_classes=1000,
in_chans=3,
checkpoint_path='',
**kwargs):
model_kwa... | 28 | 707 |
InvokeAI | invokeai/backend/image_util/normal_bae/nets/submodules/efficientnet_repo/geffnet/mobilenetv3.py | .py | """ MobileNet-V3
A PyTorch impl of MobileNet-V3, compatible with TF weights from official impl.
Paper: Searching for MobileNetV3 - https://arxiv.org/abs/1905.02244
Hacked together by / Copyright 2020 Ross Wightman
"""
import torch.nn as nn
import torch.nn.functional as F
from .activations import get_act_fn, get_act... | 367 | 15,238 |
InvokeAI | invokeai/backend/image_util/normal_bae/nets/submodules/efficientnet_repo/geffnet/gen_efficientnet.py | .py | """ Generic Efficient Networks
A generic MobileNet class with building blocks to support a variety of models:
* EfficientNet (B0-B8, L2 + Tensorflow pretrained AutoAug/RandAug/AdvProp/NoisyStudent ports)
- EfficientNet: Rethinking Model Scaling for CNNs - https://arxiv.org/abs/1905.11946
- CondConv: Conditionally... | 1,453 | 60,154 |
InvokeAI | invokeai/backend/image_util/normal_bae/nets/submodules/efficientnet_repo/geffnet/helpers.py | .py | """ Checkpoint loading / state_dict helpers
Copyright 2020 Ross Wightman
"""
import torch
import os
from collections import OrderedDict
try:
from torch.hub import load_state_dict_from_url
except ImportError:
from torch.utils.model_zoo import load_url as load_state_dict_from_url
def load_checkpoint(model, chec... | 72 | 2,833 |
InvokeAI | invokeai/backend/image_util/normal_bae/nets/submodules/efficientnet_repo/geffnet/config.py | .py | """ Global layer config state
"""
from typing import Any, Optional
__all__ = [
'is_exportable', 'is_scriptable', 'is_no_jit', 'layer_config_kwargs',
'set_exportable', 'set_scriptable', 'set_no_jit', 'set_layer_config'
]
# Set to True if prefer to have layers with no jit optimization (includes activations)
_NO... | 124 | 3,350 |
InvokeAI | invokeai/backend/image_util/normal_bae/nets/submodules/efficientnet_repo/geffnet/conv2d_layers.py | .py | """ Conv2D w/ SAME padding, CondConv, MixedConv
A collection of conv layers and padding helpers needed by EfficientNet, MixNet, and
MobileNetV3 models that maintain weight compatibility with original Tensorflow models.
Copyright 2020 Ross Wightman
"""
import collections.abc
import math
from functools import partial
f... | 305 | 12,120 |
InvokeAI | invokeai/backend/image_util/normal_bae/nets/submodules/efficientnet_repo/geffnet/efficientnet_builder.py | .py | """ EfficientNet / MobileNetV3 Blocks and Builder
Copyright 2020 Ross Wightman
"""
import re
from copy import deepcopy
from .conv2d_layers import CondConv2d, get_condconv_initializer, math, partial, select_conv2d
from geffnet.activations import F, get_act_layer, nn, sigmoid, torch
__all__ = ['get_bn_args_tf', 'resol... | 684 | 26,614 |
InvokeAI | invokeai/backend/image_util/normal_bae/nets/submodules/efficientnet_repo/geffnet/activations/activations_jit.py | .py | """ Activations (jit)
A collection of jit-scripted activations fn and modules with a common interface so that they can
easily be swapped. All have an `inplace` arg even if not used.
All jit scripted activations are lacking in-place variations on purpose, scripted kernel fusion does not
currently work across in-place ... | 80 | 2,294 |
InvokeAI | invokeai/backend/image_util/normal_bae/nets/submodules/efficientnet_repo/geffnet/activations/__init__.py | .py | from geffnet import config
from geffnet.activations.activations_me import *
from geffnet.activations.activations_jit import *
from geffnet.activations.activations import *
import torch
_has_silu = 'silu' in dir(torch.nn.functional)
_ACT_FN_DEFAULT = dict(
silu=F.silu if _has_silu else swish,
swish=F.silu if _... | 138 | 4,170 |
InvokeAI | invokeai/backend/image_util/normal_bae/nets/submodules/efficientnet_repo/geffnet/activations/activations.py | .py | """ Activations
A collection of activations fn and modules with a common interface so that they can
easily be swapped. All have an `inplace` arg even if not used.
Copyright 2020 Ross Wightman
"""
from torch import nn as nn
from torch.nn import functional as F
def swish(x, inplace: bool = False):
"""Swish - Desc... | 103 | 2,690 |
InvokeAI | invokeai/backend/image_util/normal_bae/nets/submodules/efficientnet_repo/geffnet/activations/activations_me.py | .py | """ Activations (memory-efficient w/ custom autograd)
A collection of activations fn and modules with a common interface so that they can
easily be swapped. All have an `inplace` arg even if not used.
These activations are not compatible with jit scripting or ONNX export of the model, please use either
the JIT or bas... | 175 | 4,549 |
InvokeAI | invokeai/backend/image_util/basicsr/__init__.py | .py | """
Adapted from https://github.com/XPixelGroup/BasicSR
License: Apache-2.0
As of Feb 2024, `basicsr` appears to be unmaintained. It imports a function from `torchvision` that is removed in
`torchvision` 0.17. Here is the deprecation warning:
UserWarning: The torchvision.transforms.functional_tensor module is dep... | 19 | 871 |
InvokeAI | invokeai/backend/image_util/basicsr/rrdbnet_arch.py | .py | import torch
from torch import nn as nn
from torch.nn import functional as F
from invokeai.backend.image_util.basicsr.arch_util import default_init_weights, make_layer, pixel_unshuffle
class ResidualDenseBlock(nn.Module):
"""Residual Dense Block.
Used in RRDB block in ESRGAN.
Args:
num_feat (in... | 126 | 4,822 |
InvokeAI | invokeai/backend/image_util/basicsr/arch_util.py | .py | from typing import Type
import torch
from torch import nn as nn
from torch.nn import init as init
from torch.nn.modules.batchnorm import _BatchNorm
@torch.no_grad()
def default_init_weights(
module_list: list[nn.Module] | nn.Module, scale: float = 1, bias_fill: float = 0, **kwargs
) -> None:
"""Initialize ne... | 76 | 2,493 |
InvokeAI | invokeai/backend/image_util/pidi/model.py | .py | """
Author: Zhuo Su, Wenzhe Liu
Date: Feb 18, 2021
"""
import math
import cv2
import numpy as np
import torch
import torch.nn as nn
import torch.nn.functional as F
def img2tensor(imgs, bgr2rgb=True, float32=True):
"""Numpy array to tensor.
Args:
imgs (list[ndarray] | ndarray): Input images.
... | 682 | 21,813 |
InvokeAI | invokeai/backend/image_util/pidi/__init__.py | .py | # Adapted from https://github.com/huggingface/controlnet_aux
import pathlib
import cv2
import huggingface_hub
import numpy as np
import torch
from einops import rearrange
from PIL import Image
from invokeai.backend.image_util.pidi.model import PiDiNet, pidinet
from invokeai.backend.image_util.util import nms, normal... | 81 | 2,599 |
InvokeAI | invokeai/backend/qwen3/qwen3_tokenizer.py | .py | """Bundled Qwen3 tokenizer for single-file / GGUF Qwen3 encoders.
Single-file (safetensors) and GGUF Qwen3 encoder checkpoints ship weights only —
no tokenizer files. Previously the tokenizer was pulled from HuggingFace
(``Qwen/Qwen3-4B``) on first use, which fails in offline / airgapped setups and
whenever the HF cac... | 38 | 1,749 |
InvokeAI | invokeai/backend/qwen3/__init__.py | .py | """Qwen3 encoder backend module.
Shared assets for the standalone Qwen3 text encoders used by Z-Image (4B/8B) and
Anima (0.6B). The Qwen3 BPE tokenizer is identical across all variants, so a single
vendored copy is bundled here and reused by every Qwen3 encoder loader.
"""
| 7 | 275 |
InvokeAI | invokeai/backend/hidiffusion/utils.py | .py | import torch
def isinstance_str(x: object, cls_name: str, prefix: bool = False, contains: bool = False):
"""
Checks whether x has any class equal to, prefixed with, or contains (cls_name) in its ancestry.
Doesn't require access to the class's implementation.
Useful for patching!
"""
for _cls... | 36 | 1,103 |
InvokeAI | invokeai/backend/hidiffusion/__init__.py | .py | from invokeai.backend.hidiffusion.hidiffusion import apply_hidiffusion, remove_hidiffusion
__all__ = ["apply_hidiffusion", "remove_hidiffusion"]
| 4 | 146 |
InvokeAI | invokeai/backend/hidiffusion/hidiffusion.py | .py | import importlib.resources
import math
import warnings
from typing import Any, Callable, Dict, List, Optional, Tuple, Type, Union
import diffusers
import torch
import torch.nn.functional as F
from diffusers.image_processor import PipelineImageInput
from diffusers.models import ControlNetModel
from diffusers.models.att... | 2,249 | 118,949 |
InvokeAI | invokeai/backend/flux/custom_block_processor.py | .py | import einops
import torch
from invokeai.backend.flux.extensions.regional_prompting_extension import RegionalPromptingExtension
from invokeai.backend.flux.extensions.xlabs_ip_adapter_extension import XLabsIPAdapterExtension
from invokeai.backend.flux.math import attention
from invokeai.backend.flux.modules.layers impo... | 139 | 5,670 |
InvokeAI | invokeai/backend/flux/flux_state_dict_utils.py | .py | from typing import Any
def get_flux_in_channels_from_state_dict(state_dict: dict[str | int, Any]) -> int | None:
"""Gets the in channels from the state dict."""
# "Standard" FLUX models use "img_in.weight", but some community fine tunes use
# "model.diffusion_model.img_in.weight". Known models that use t... | 21 | 752 |
InvokeAI | invokeai/backend/flux/model.py | .py | # Initially pulled from https://github.com/black-forest-labs/flux
from dataclasses import dataclass
from typing import Optional
import torch
from torch import Tensor, nn
from invokeai.backend.flux.custom_block_processor import (
CustomDoubleStreamBlockProcessor,
CustomSingleStreamBlockProcessor,
)
from invok... | 169 | 6,188 |
InvokeAI | invokeai/backend/flux/util.py | .py | # Initially pulled from https://github.com/black-forest-labs/flux
from dataclasses import dataclass
from typing import Literal
from invokeai.backend.flux.model import FluxParams
from invokeai.backend.flux.modules.autoencoder import AutoEncoderParams
from invokeai.backend.model_manager.taxonomy import AnyVariant, Flux... | 196 | 5,742 |
InvokeAI | invokeai/backend/flux/denoise.py | .py | import inspect
import math
from typing import Callable
import torch
from diffusers.schedulers.scheduling_utils import SchedulerMixin
from tqdm import tqdm
from invokeai.backend.flux.controlnet.controlnet_flux_output import ControlNetFluxOutput, sum_controlnet_flux_outputs
from invokeai.backend.flux.extensions.dype_ex... | 413 | 20,943 |
InvokeAI | invokeai/backend/flux/math.py | .py | # Initially pulled from https://github.com/black-forest-labs/flux
import torch
from einops import rearrange
from torch import Tensor
def attention(q: Tensor, k: Tensor, v: Tensor, pe: Tensor, attn_mask: Tensor | None = None) -> Tensor:
q, k = apply_rope(q, k, pe)
x = torch.nn.functional.scaled_dot_product_a... | 36 | 1,365 |
InvokeAI | invokeai/backend/flux/sampling_utils.py | .py | # Initially pulled from https://github.com/black-forest-labs/flux
import math
from typing import Callable
import torch
from einops import rearrange, repeat
def get_noise(
num_samples: int,
height: int,
width: int,
device: torch.device,
dtype: torch.dtype,
seed: int,
):
# We always genera... | 187 | 6,531 |
InvokeAI | invokeai/backend/flux/schedulers.py | .py | """Flow Matching scheduler definitions and mapping.
This module provides the scheduler types and mapping for Flow Matching models
(Flux and Z-Image), supporting multiple schedulers from the diffusers library.
"""
from typing import Any, Literal, Type
from diffusers import (
DPMSolverMultistepScheduler,
FlowM... | 151 | 4,996 |
InvokeAI | invokeai/backend/flux/text_conditioning.py | .py | from dataclasses import dataclass
import torch
from invokeai.backend.stable_diffusion.diffusion.conditioning_data import Range
@dataclass
class FluxTextConditioning:
t5_embeddings: torch.Tensor
clip_embeddings: torch.Tensor
# If mask is None, the prompt is a global prompt.
mask: torch.Tensor | None
... | 44 | 1,332 |
InvokeAI | invokeai/backend/flux/redux/flux_redux_model.py | .py | import torch
# This model definition is based on:
# https://github.com/black-forest-labs/flux/blob/716724eb276d94397be99710a0a54d352664e23b/src/flux/modules/image_embedders.py#L66
class FluxReduxModel(torch.nn.Module):
def __init__(self, redux_dim: int = 1152, txt_in_features: int = 4096) -> None:
super(... | 18 | 654 |
InvokeAI | invokeai/backend/flux/redux/flux_redux_state_dict_utils.py | .py | from typing import Any
def is_state_dict_likely_flux_redux(state_dict: dict[str | int, Any]) -> bool:
"""Checks if the provided state dict is likely a FLUX Redux model."""
expected_keys = {"redux_down.bias", "redux_down.weight", "redux_up.bias", "redux_up.weight"}
if set(state_dict.keys()) == expected_ke... | 12 | 362 |
InvokeAI | invokeai/backend/flux/extensions/instantx_controlnet_extension.py | .py | import math
from typing import List, Union
import torch
from PIL.Image import Image
from invokeai.app.invocations.constants import LATENT_SCALE_FACTOR
from invokeai.app.invocations.flux_vae_encode import FluxVaeEncodeInvocation
from invokeai.app.util.controlnet_utils import CONTROLNET_RESIZE_VALUES, prepare_control_i... | 195 | 7,813 |
InvokeAI | invokeai/backend/flux/extensions/kontext_extension.py | .py | import torch
import torch.nn.functional as F
import torchvision.transforms as T
from einops import repeat
from invokeai.app.invocations.fields import FluxKontextConditioningField
from invokeai.app.invocations.model import VAEField
from invokeai.app.services.shared.invocation_context import InvocationContext
from invok... | 219 | 9,815 |
InvokeAI | invokeai/backend/flux/extensions/xlabs_ip_adapter_extension.py | .py | import math
from typing import List, Union
import einops
import torch
from PIL import Image
from transformers import CLIPImageProcessor, CLIPVisionModelWithProjection
from invokeai.backend.flux.ip_adapter.xlabs_ip_adapter_flux import XlabsIpAdapterFlux
from invokeai.backend.flux.modules.layers import DoubleStreamBloc... | 91 | 3,547 |
InvokeAI | invokeai/backend/flux/extensions/dype_extension.py | .py | """DyPE extension for FLUX denoising pipeline."""
from dataclasses import dataclass
from typing import TYPE_CHECKING, Sequence
import torch
from invokeai.backend.flux.dype.base import DyPEConfig
from invokeai.backend.flux.dype.embed import DyPEEmbedND
if TYPE_CHECKING:
from invokeai.backend.flux.model import Fl... | 114 | 3,460 |
InvokeAI | invokeai/backend/flux/extensions/regional_prompting_extension.py | .py | from typing import Optional
import torch
import torchvision
from invokeai.backend.flux.text_conditioning import (
FluxReduxConditioning,
FluxRegionalTextConditioning,
FluxTextConditioning,
)
from invokeai.backend.stable_diffusion.diffusion.conditioning_data import Range
from invokeai.backend.util.devices ... | 296 | 14,123 |
InvokeAI | invokeai/backend/flux/extensions/base_controlnet_extension.py | .py | import math
from abc import ABC, abstractmethod
from typing import List, Union
import torch
from invokeai.backend.flux.controlnet.controlnet_flux_output import ControlNetFluxOutput
class BaseControlNetExtension(ABC):
def __init__(
self,
weight: Union[float, List[float]],
begin_step_perce... | 46 | 1,330 |
InvokeAI | invokeai/backend/flux/extensions/xlabs_controlnet_extension.py | .py | from typing import List, Union
import torch
from PIL.Image import Image
from invokeai.app.invocations.constants import LATENT_SCALE_FACTOR
from invokeai.app.util.controlnet_utils import CONTROLNET_RESIZE_VALUES, prepare_control_image
from invokeai.backend.flux.controlnet.controlnet_flux_output import ControlNetFluxOu... | 151 | 5,380 |
InvokeAI | invokeai/backend/flux/controlnet/controlnet_flux_output.py | .py | from dataclasses import dataclass
import torch
@dataclass
class ControlNetFluxOutput:
single_block_residuals: list[torch.Tensor] | None
double_block_residuals: list[torch.Tensor] | None
def apply_weight(self, weight: float):
if self.single_block_residuals is not None:
for i in range(... | 59 | 2,116 |
InvokeAI | invokeai/backend/flux/controlnet/state_dict_utils.py | .py | from typing import Any, Dict
import torch
from invokeai.backend.flux.model import FluxParams
def is_state_dict_xlabs_controlnet(sd: dict[str | int, Any]) -> bool:
"""Is the state dict for an XLabs ControlNet model?
This is intended to be a reasonably high-precision detector, but it is not guaranteed to hav... | 296 | 11,961 |
InvokeAI | invokeai/backend/flux/controlnet/xlabs_controlnet_flux.py | .py | # This file was initially based on:
# https://github.com/XLabs-AI/x-flux/blob/47495425dbed499be1e8e5a6e52628b07349cba2/src/flux/controlnet.py
from dataclasses import dataclass
import torch
from einops import rearrange
from invokeai.backend.flux.controlnet.zero_module import zero_module
from invokeai.backend.flux.mo... | 131 | 5,677 |
InvokeAI | invokeai/backend/flux/controlnet/zero_module.py | .py | from typing import TypeVar
import torch
T = TypeVar("T", bound=torch.nn.Module)
def zero_module(module: T) -> T:
"""Initialize the parameters of a module to zero."""
for p in module.parameters():
torch.nn.init.zeros_(p)
return module
| 13 | 258 |
InvokeAI | invokeai/backend/flux/controlnet/instantx_controlnet_flux.py | .py | # This file was initially copied from:
# https://github.com/huggingface/diffusers/blob/99f608218caa069a2f16dcf9efab46959b15aec0/src/diffusers/models/controlnet_flux.py
from dataclasses import dataclass
import torch
import torch.nn as nn
from invokeai.backend.flux.controlnet.zero_module import zero_module
from invok... | 181 | 7,620 |
InvokeAI | invokeai/backend/flux/ip_adapter/state_dict_utils.py | .py | from typing import Any
import torch
from invokeai.backend.flux.ip_adapter.xlabs_ip_adapter_flux import XlabsIpAdapterParams
def is_state_dict_xlabs_ip_adapter(sd: dict[str | int, Any]) -> bool:
"""Is the state dict for an XLabs FLUX IP-Adapter model?
This is intended to be a reasonably high-precision detec... | 53 | 2,167 |
InvokeAI | invokeai/backend/flux/ip_adapter/xlabs_ip_adapter_flux.py | .py | from dataclasses import dataclass
import torch
from invokeai.backend.ip_adapter.ip_adapter import ImageProjModel
class IPDoubleStreamBlock(torch.nn.Module):
def __init__(self, context_dim: int, hidden_dim: int):
super().__init__()
self.context_dim = context_dim
self.hidden_dim = hidden_... | 71 | 2,783 |
InvokeAI | invokeai/backend/flux/ip_adapter/ip_double_stream_block_processor.py | .py | # This file is based on:
# https://github.com/XLabs-AI/x-flux/blob/47495425dbed499be1e8e5a6e52628b07349cba2/src/flux/modules/layers.py#L221
import einops
import torch
from invokeai.backend.flux.math import attention
from invokeai.backend.flux.modules.layers import DoubleStreamBlock
class IPDoubleStreamBlockProcessor... | 94 | 3,939 |
InvokeAI | invokeai/backend/flux/dype/presets.py | .py | """DyPE presets and automatic configuration."""
import math
from dataclasses import dataclass
from typing import Literal
from invokeai.backend.flux.dype.base import DyPEConfig
# DyPE preset type - using Literal for proper frontend dropdown support
DyPEPreset = Literal["off", "manual", "auto", "area", "4k"]
# Consta... | 199 | 6,141 |
InvokeAI | invokeai/backend/flux/dype/embed.py | .py | """DyPE-enhanced position embedding module."""
import torch
from torch import Tensor, nn
from invokeai.backend.flux.dype.base import DyPEConfig
from invokeai.backend.flux.dype.rope import rope_dype
class DyPEEmbedND(nn.Module):
"""N-dimensional position embedding with DyPE support.
This class replaces the ... | 117 | 3,726 |
InvokeAI | invokeai/backend/flux/dype/__init__.py | .py | """Dynamic Position Extrapolation (DyPE) for FLUX models.
DyPE enables high-resolution image generation with pretrained FLUX models by
dynamically modulating RoPE extrapolation during denoising.
Based on the official DyPE project: https://github.com/guyyariv/DyPE
"""
from invokeai.backend.flux.dype.base import DyPEC... | 36 | 934 |
InvokeAI | invokeai/backend/flux/dype/rope.py | .py | """DyPE-enhanced RoPE (Rotary Position Embedding) functions."""
import torch
from einops import rearrange
from torch import Tensor
from invokeai.backend.flux.dype.base import (
DyPEConfig,
compute_vision_yarn_freqs,
)
def rope_dype(
pos: Tensor,
dim: int,
theta: int,
current_sigma: float,
... | 87 | 2,645 |
InvokeAI | invokeai/backend/flux/dype/base.py | .py | """DyPE base configuration and utilities for FLUX vision_yarn RoPE."""
from dataclasses import dataclass
import torch
from torch import Tensor
@dataclass
class DyPEConfig:
"""Configuration for Dynamic Position Extrapolation."""
enable_dype: bool = True
base_resolution: int = 1024 # Native training res... | 116 | 3,737 |
InvokeAI | invokeai/backend/flux/modules/autoencoder.py | .py | # Initially pulled from https://github.com/black-forest-labs/flux
from dataclasses import dataclass
import torch
from einops import rearrange
from torch import Tensor, nn
@dataclass
class AutoEncoderParams:
resolution: int
in_channels: int
ch: int
out_ch: int
ch_mult: list[int]
num_res_block... | 325 | 11,435 |
InvokeAI | invokeai/backend/flux/modules/conditioner.py | .py | # Initially pulled from https://github.com/black-forest-labs/flux
import torch
from torch import Tensor, nn
from transformers import PreTrainedModel, PreTrainedTokenizer, PreTrainedTokenizerFast
from invokeai.backend.model_manager.load.model_cache.utils import get_effective_device
class HFEncoder(nn.Module):
de... | 52 | 2,095 |
InvokeAI | invokeai/backend/flux/modules/layers.py | .py | # Initially pulled from https://github.com/black-forest-labs/flux
import math
from dataclasses import dataclass
import torch
from einops import rearrange
from torch import Tensor, nn
from invokeai.backend.flux.math import attention, rope
class EmbedND(nn.Module):
def __init__(self, dim: int, theta: int, axes_d... | 251 | 9,350 |
InvokeAI | invokeai/app/api_app.py | .py | import asyncio
import inspect
import logging
from collections.abc import Awaitable, Callable
from contextlib import asynccontextmanager
from pathlib import Path
from fastapi import FastAPI, Request
from fastapi.middleware.cors import CORSMiddleware
from fastapi.middleware.gzip import GZipMiddleware
from fastapi.openap... | 467 | 20,672 |
InvokeAI | invokeai/app/run_app.py | .py | import os
from typing import Any
# Suppress the HuggingFace tokenizers fork-after-parallelism warning. The Rust
# ``tokenizers`` library warms a thread pool the first time a tokenizer is used
# (e.g. the UMT5 / T5 text encoder during Wan / FLUX / SD3 conditioning), then
# complains every time we fork() afterwards — wh... | 180 | 8,283 |
InvokeAI | invokeai/app/shared/models.py | .py | from pydantic import BaseModel, Field
from invokeai.app.invocations.fields import FieldDescriptions
class FreeUConfig(BaseModel):
"""
Configuration for the FreeU hyperparameters.
- https://huggingface.co/docs/diffusers/main/en/using-diffusers/freeu
- https://github.com/ChenyangSi/FreeU
"""
s... | 17 | 615 |
InvokeAI | invokeai/app/shared/__init__.py | .py | """
This module contains various classes, functions and models which are shared across the app, particularly by invocations.
Lifting these classes, functions and models into this shared module helps to reduce circular imports.
"""
| 6 | 232 |
InvokeAI | invokeai/app/services/invocation_services.py | .py | # Copyright (c) 2022 Kyle Schouviller (https://github.com/kyle0654) and the InvokeAI Team
from __future__ import annotations
from typing import TYPE_CHECKING
from invokeai.app.services.object_serializer.object_serializer_base import ObjectSerializerBase
from invokeai.app.services.style_preset_images.style_preset_imag... | 135 | 7,408 |
InvokeAI | invokeai/app/services/invoker.py | .py | # Copyright (c) 2022 Kyle Schouviller (https://github.com/kyle0654)
from invokeai.app.services.invocation_services import InvocationServices
class Invoker:
"""The invoker, used to execute invocations"""
services: InvocationServices
def __init__(self, services: InvocationServices):
self.service... | 38 | 1,279 |
InvokeAI | invokeai/app/services/urls/urls_default.py | .py | import os
from invokeai.app.services.urls.urls_base import UrlServiceBase
class LocalUrlService(UrlServiceBase):
def __init__(self, base_url: str = "api/v1", base_url_v2: str = "api/v2"):
self._base_url = base_url
self._base_url_v2 = base_url_v2
def get_image_url(self, image_name: str, thumb... | 37 | 1,453 |
InvokeAI | invokeai/app/services/urls/urls_base.py | .py | from abc import ABC, abstractmethod
class UrlServiceBase(ABC):
"""Responsible for building URLs for resources."""
@abstractmethod
def get_image_url(self, image_name: str, thumbnail: bool = False) -> str:
"""Gets the URL for an image or thumbnail."""
pass
@abstractmethod
def get_v... | 31 | 914 |
InvokeAI | invokeai/app/services/external_generation/errors.py | .py | class ExternalGenerationError(Exception):
"""Base error for external generation."""
class ExternalProviderNotFoundError(ExternalGenerationError):
"""Raised when no provider is registered for a model."""
class ExternalProviderNotConfiguredError(ExternalGenerationError):
"""Raised when a provider is missi... | 29 | 954 |
InvokeAI | invokeai/app/services/external_generation/external_generation_default.py | .py | from __future__ import annotations
import dataclasses
import time
from logging import Logger
from typing import TYPE_CHECKING
from PIL import Image
from PIL.Image import Image as PILImageType
from invokeai.app.services.external_generation.errors import (
ExternalProviderCapabilityError,
ExternalProviderNotCo... | 370 | 14,194 |
InvokeAI | invokeai/app/services/external_generation/external_generation_base.py | .py | from __future__ import annotations
from abc import ABC, abstractmethod
from logging import Logger
from invokeai.app.services.config import InvokeAIAppConfig
from invokeai.app.services.external_generation.external_generation_common import (
ExternalGenerationRequest,
ExternalGenerationResult,
ExternalProvi... | 41 | 1,237 |
InvokeAI | invokeai/app/services/external_generation/__init__.py | .py | from invokeai.app.services.external_generation.external_generation_base import (
ExternalGenerationServiceBase,
ExternalProvider,
)
from invokeai.app.services.external_generation.external_generation_common import (
ExternalGeneratedImage,
ExternalGenerationRequest,
ExternalGenerationResult,
Exte... | 24 | 742 |
InvokeAI | invokeai/app/services/external_generation/startup.py | .py | from logging import Logger
from typing import TYPE_CHECKING
from invokeai.app.services.model_records.model_records_base import ModelRecordChanges
from invokeai.backend.model_manager.configs.external_api import ExternalApiModelConfig
from invokeai.backend.model_manager.starter_models import STARTER_MODELS
from invokeai... | 60 | 2,150 |
InvokeAI | invokeai/app/services/external_generation/external_generation_common.py | .py | from __future__ import annotations
from dataclasses import dataclass
from typing import Any
from PIL.Image import Image as PILImageType
from invokeai.backend.model_manager.configs.external_api import ExternalApiModelConfig, ExternalGenerationMode
@dataclass(frozen=True)
class ExternalReferenceImage:
image: PIL... | 53 | 1,295 |
InvokeAI | invokeai/app/services/external_generation/image_utils.py | .py | from __future__ import annotations
import base64
import io
from PIL import Image
from PIL.Image import Image as PILImageType
def encode_image_base64(image: PILImageType, format: str = "PNG") -> str:
buffer = io.BytesIO()
image.save(buffer, format=format)
return base64.b64encode(buffer.getvalue()).decode... | 20 | 497 |
InvokeAI | invokeai/app/services/external_generation/providers/openai.py | .py | from __future__ import annotations
import io
import requests
from PIL.Image import Image as PILImageType
from invokeai.app.services.external_generation.errors import (
ExternalProviderRateLimitError,
ExternalProviderRequestError,
)
from invokeai.app.services.external_generation.external_generation_base impor... | 163 | 6,640 |
InvokeAI | invokeai/app/services/external_generation/providers/seedream.py | .py | from __future__ import annotations
import requests
from invokeai.app.services.external_generation.errors import (
ExternalProviderCapabilityError,
ExternalProviderRateLimitError,
ExternalProviderRequestError,
)
from invokeai.app.services.external_generation.external_generation_base import ExternalProvider... | 172 | 7,131 |
InvokeAI | invokeai/app/services/external_generation/providers/gemini.py | .py | from __future__ import annotations
import requests
from invokeai.app.services.external_generation.errors import (
ExternalProviderRateLimitError,
ExternalProviderRequestError,
)
from invokeai.app.services.external_generation.external_generation_base import ExternalProvider
from invokeai.app.services.external_... | 249 | 9,930 |
InvokeAI | invokeai/app/services/external_generation/providers/alibabacloud.py | .py | from __future__ import annotations
import io
import time
import requests
from PIL import Image
from PIL.Image import Image as PILImageType
from invokeai.app.services.external_generation.errors import ExternalProviderRequestError
from invokeai.app.services.external_generation.external_generation_base import ExternalP... | 411 | 15,929 |
InvokeAI | invokeai/app/services/style_preset_records/style_preset_records_common.py | .py | import codecs
import csv
import json
from enum import Enum
from typing import Any, Optional
import pydantic
from fastapi import UploadFile
from pydantic import AliasChoices, BaseModel, ConfigDict, Field, TypeAdapter
from invokeai.app.util.metaenum import MetaEnum
class StylePresetNotFoundError(Exception):
"""Ra... | 142 | 5,063 |
InvokeAI | invokeai/app/services/style_preset_records/style_preset_records_sqlite.py | .py | import json
from pathlib import Path
from invokeai.app.services.invoker import Invoker
from invokeai.app.services.shared.sqlite.sqlite_database import SqliteDatabase
from invokeai.app.services.style_preset_records.style_preset_records_base import StylePresetRecordsStorageBase
from invokeai.app.services.style_preset_re... | 189 | 6,663 |
InvokeAI | invokeai/app/services/style_preset_records/style_preset_records_base.py | .py | from abc import ABC, abstractmethod
from invokeai.app.services.style_preset_records.style_preset_records_common import (
PresetType,
StylePresetChanges,
StylePresetRecordDTO,
StylePresetWithoutId,
)
class StylePresetRecordsStorageBase(ABC):
"""Base class for style preset storage services."""
... | 54 | 1,773 |
InvokeAI | invokeai/app/services/session_processor/session_processor_default.py | .py | import gc
import traceback
from contextlib import contextmanager, suppress
from threading import BoundedSemaphore, Thread
from threading import Event as ThreadEvent
from typing import Iterator, Optional
import torch
from invokeai.app.invocations.baseinvocation import BaseInvocation, BaseInvocationOutput
from invokeai... | 848 | 42,457 |
InvokeAI | invokeai/app/services/session_processor/workflow_call_batch.py | .py | from __future__ import annotations
import copy
import json
import random
from collections.abc import Mapping, Sequence
from dataclasses import dataclass
from typing import Any
from dynamicprompts.generators import CombinatorialPromptGenerator, RandomPromptGenerator
from invokeai.app.invocations.fields import ImageFi... | 726 | 30,271 |
InvokeAI | invokeai/app/services/session_processor/workflow_call_runtime.py | .py | from __future__ import annotations
from typing import TYPE_CHECKING, Any
from invokeai.app.invocations.call_saved_workflow import (
CallSavedWorkflowInvocation,
is_call_saved_workflow_dynamic_input,
)
from invokeai.app.invocations.workflow_return import WorkflowReturnOutput
from invokeai.app.services.session_... | 297 | 16,020 |
InvokeAI | invokeai/app/services/session_processor/session_processor_base.py | .py | from abc import ABC, abstractmethod
from threading import Event
from typing import Optional, Protocol
from invokeai.app.invocations.baseinvocation import BaseInvocation, BaseInvocationOutput
from invokeai.app.services.invocation_services import InvocationServices
from invokeai.app.services.session_processor.session_pr... | 154 | 4,726 |
InvokeAI | invokeai/app/services/session_processor/session_processor_common.py | .py | from PIL.Image import Image as PILImageType
from pydantic import BaseModel, Field
from invokeai.backend.util.util import image_to_dataURL
class SessionProcessorStatus(BaseModel):
is_started: bool = Field(description="Whether the session processor is started")
is_processing: bool = Field(description="Whether ... | 34 | 1,159 |
InvokeAI | invokeai/app/services/image_files/image_files_disk.py | .py | # Copyright (c) 2022 Kyle Schouviller (https://github.com/kyle0654) and the InvokeAI Team
import io
import json
import os
import shutil
import tempfile
import threading
import zlib
from dataclasses import dataclass
from pathlib import Path
from queue import Queue
from typing import Optional, Union
from PIL import Imag... | 362 | 15,981 |
InvokeAI | invokeai/app/services/image_files/image_subfolder_strategy.py | .py | from abc import ABC, abstractmethod
from datetime import datetime
from invokeai.app.services.image_records.image_records_common import ImageCategory
class ImageSubfolderStrategy(ABC):
"""Base class for image subfolder strategies."""
@abstractmethod
def get_subfolder(self, image_name: str, image_category... | 59 | 2,164 |
InvokeAI | invokeai/app/services/image_files/image_files_base.py | .py | from abc import ABC, abstractmethod
from pathlib import Path
from typing import Optional
from PIL.Image import Image as PILImageType
class ImageFileStorageBase(ABC):
"""Low-level service responsible for storing and retrieving image files."""
@abstractmethod
def get(self, image_name: str, image_subfolder... | 88 | 2,847 |
InvokeAI | invokeai/app/services/image_files/image_files_common.py | .py | # TODO: Should these excpetions subclass existing python exceptions?
class ImageFileNotFoundException(Exception):
"""Raised when an image file is not found in storage."""
def __init__(self, message="Image file not found"):
super().__init__(message)
class ImageFileSaveException(Exception):
"""Rais... | 21 | 636 |
InvokeAI | invokeai/app/services/image_records/image_records_common.py | .py | # TODO: Should these excpetions subclass existing python exceptions?
import datetime
from enum import Enum
from typing import Optional, Union
from pydantic import BaseModel, Field, StrictBool, StrictStr
from invokeai.app.util.metaenum import MetaEnum
from invokeai.app.util.misc import get_iso_timestamp
from invokeai.... | 236 | 9,122 |
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