# AnimateDiff prompt travel
[AnimateDiff](https://github.com/guoyww/AnimateDiff) with prompt travel + [ControlNet](https://github.com/lllyasviel/ControlNet) + [IP-Adapter](https://github.com/tencent-ailab/IP-Adapter)
I added a experimental feature to animatediff-cli to change the prompt in the middle of the frame.
It seems to work surprisingly well!
### Example
- [A command to stylization with mask has been added](https://github.com/s9roll7/animatediff-cli-prompt-travel#video-stylization-with-mask).
- [A command to automate video stylization has been added](https://github.com/s9roll7/animatediff-cli-prompt-travel#video-stylization).
- Original / First generation result / Second generation(for upscaling) result
- It took 4 minutes to generate the first one and about 5 minutes to generate the second one (on rtx 4090).
- more example [here](https://github.com/s9roll7/animatediff-cli-prompt-travel/issues/29)
- Numbered from left to right.
- 1.prompt + lora
- 2.prompt + lora + IP-Adapter(scale 0.5)
- 3.prompt + lora + IP-Adapter Plus(scale 0.5)
- 4.prompt + lora + Controlnet Reference Only(style_fidelity 0)
- input image
- controlnet_openpose + controlnet_softedge
- input frames for controlnet(0,16,32 frames)
- result
- In the latest version, generation can now be controlled more precisely through prompts.
- sample 1
```json
"prompt_fixed_ratio": 0.8,
"head_prompt": "1girl, wizard, circlet, earrings, jewelry, purple hair,",
"prompt_map": {
"0": "(standing,full_body),blue_sky, town",
"8": "(sitting,full_body),rain, town",
"16": "(standing,full_body),blue_sky, woods",
"24": "(upper_body), beach",
"32": "(upper_body, smile)",
"40": "(upper_body, angry)",
"48": "(upper_body, smile, from_above)",
"56": "(upper_body, angry, from_side)",
"64": "(upper_body, smile, from_below)",
"72": "(upper_body, angry, from_behind, looking at viewer)",
"80": "face,looking at viewer",
"88": "face,looking at viewer, closed_eyes",
"96": "face,looking at viewer, open eyes, open_mouth",
"104": "face,looking at viewer, closed_eyes, closed_mouth",
"112": "face,looking at viewer, open eyes,eyes, open_mouth, tongue, smile, laughing",
"120": "face,looking at viewer, eating, bowl,chopsticks,holding,food"
},
```
- sample 2
```json
"prompt_fixed_ratio": 1.0,
"head_prompt": "1girl, wizard, circlet, earrings, jewelry, purple hair,",
"prompt_map": {
"0": "",
"8": "((fire magic spell, fire background))",
"16": "((ice magic spell, ice background))",
"24": "((thunder magic spell, thunder background))",
"32": "((skull magic spell, skull background))",
"40": "((wind magic spell, wind background))",
"48": "((stone magic spell, stone background))",
"56": "((holy magic spell, holy background))",
"64": "((star magic spell, star background))",
"72": "((plant magic spell, plant background))",
"80": "((meteor magic spell, meteor background))"
},
```
### Installation(for windows)
Same as the original animatediff-cli
[Python 3.10](https://www.python.org/) and git client must be installed
(A few days ago, PyTorch 2.1 was released, but it is safer to install the older version until things settle down.
[#87](https://github.com/s9roll7/animatediff-cli-prompt-travel/issues/87))
```sh
git clone https://github.com/s9roll7/animatediff-cli-prompt-travel.git
cd animatediff-cli-prompt-travel
py -3.10 -m venv venv
venv\Scripts\activate.bat
set PYTHONUTF8=1
python -m pip install --upgrade pip
# Torch installation must be modified to suit the environment. (https://pytorch.org/get-started/previous-versions/)
python -m pip install torch==2.0.1+cu118 torchvision==0.15.2+cu118 torchaudio==2.0.2 --index-url https://download.pytorch.org/whl/cu118
python -m pip install -e .
python -m pip install xformers
# If you want to use the 'stylize' command, you will also need
python -m pip install -e .[stylize]
# If you want to use use dwpose as a preprocessor for controlnet_openpose, you will also need
python -m pip install -e .[dwpose]
# (DWPose is a more powerful version of Openpose)
# If you want to use the 'stylize create-mask' and 'stylize composite' command, you will also need
python -m pip install -e .[stylize_mask]
```
(https://www.reddit.com/r/StableDiffusion/comments/157c0wl/working_animatediff_cli_windows_install/)
I found a detailed tutorial
(https://www.reddit.com/r/StableDiffusion/comments/16vlk9j/guide_to_creating_videos_with/)
(https://www.youtube.com/watch?v=7_hh3wOD81s)
### How To Use
Almost same as the original animatediff-cli, but with a slight change in config format.
```json
# prompt_travel.json
{
"name": "sample",
"path": "share/Stable-diffusion/mistoonAnime_v20.safetensors", # Specify Checkpoint as a path relative to /animatediff-cli/data
"vae_path":"share/VAE/vae-ft-mse-840000-ema-pruned.ckpt", # Specify vae as a path relative to /animatediff-cli/data
"motion_module": "models/motion-module/mm_sd_v14.ckpt", # Specify motion module as a path relative to /animatediff-cli/data
"compile": false,
"seed": [
341774366206100,-1,-1 # -1 means random. If "--repeats 3" is specified in this setting, The first will be 341774366206100, the second and third will be random.
],
"scheduler": "ddim", # "ddim","euler","euler_a","k_dpmpp_2m", etc...
"steps": 40,
"guidance_scale": 20, # cfg scale
"clip_skip": 2,
"head_prompt": "masterpiece, best quality, a beautiful and detailed portriat of muffet, monster girl,((purple body:1.3)),humanoid, arachnid, anthro,((fangs)),pigtails,hair bows,5 eyes,spider girl,6 arms,solo",
"prompt_map": { # "FRAME" : "PROMPT" format / ex. prompt for frame 32 is "head_prompt" + prompt_map["32"] + "tail_prompt"
"0": "smile standing,((spider webs:1.0))",
"32": "(((walking))),((spider webs:1.0))",
"64": "(((running))),((spider webs:2.0)),wide angle lens, fish eye effect",
"96": "(((sitting))),((spider webs:1.0))"
},
"tail_prompt": "clothed, open mouth, awesome and detailed background, holding teapot, holding teacup, 6 hands,detailed hands,storefront that sells pastries and tea,bloomers,(red and black clothing),inside,pouring into teacup,muffetwear",
"n_prompt": [
"(worst quality, low quality:1.4),nudity,simple background,border,mouth closed,text, patreon,bed,bedroom,white background,((monochrome)),sketch,(pink body:1.4),7 arms,8 arms,4 arms"
],
"lora_map": { # "PATH_TO_LORA" : STRENGTH format
"share/Lora/muffet_v2.safetensors" : 1.0, # Specify lora as a path relative to /animatediff-cli/data
"share/Lora/add_detail.safetensors" : 1.0 # Lora support is limited. Not all formats can be used!!!
},
"motion_lora_map": { # "PATH_TO_LORA" : STRENGTH format
"models/motion_lora/v2_lora_RollingAnticlockwise.ckpt":0.5, # Currently, the officially distributed lora seems to work only for v2 motion modules (mm_sd_v15_v2.ckpt).
"models/motion_lora/v2_lora_ZoomIn.ckpt":0.5
},
"ip_adapter_map": { # config for ip-adapter
# enable/disable (important)
"enable": true,
# Specify input image directory relative to /animatediff-cli/data (important! No need to specify frames in the config file. The effect on generation is exactly the same logic as the placement of the prompt)
"input_image_dir": "ip_adapter_image/test",
# save input image or not
"save_input_image": true,
# Ratio of image prompt vs text prompt (important). Even if you want to emphasize only the image prompt in 1.0, do not leave prompt/neg prompt empty, but specify a general text such as "best quality".
"scale": 0.5,
# IP-Adapter or IP-Adapter Plus or IP-Adapter Plus Face (important) It would be a completely different outcome. Not always PLUS a superior result.
"is_plus_face": true,
"is_plus": true
},
"controlnet_map": { # config for controlnet(for generation)
"input_image_dir" : "controlnet_image/test", # Specify input image directory relative to /animatediff-cli/data (important! Please refer to the directory structure of sample. No need to specify frames in the config file.)
"max_samples_on_vram" : 200, # If you specify a large number of images for controlnet and vram will not be enough, reduce this value. 0 means that everything should be placed in cpu.
"max_models_on_vram" : 3, # Number of controlnet models to be placed in vram
"save_detectmap" : true, # save preprocessed image or not
"preprocess_on_gpu": true, # run preprocess on gpu or not (It probably does not affect vram usage at peak, so it should always set true.)
"is_loop": true, # Whether controlnet effects consider loop
"controlnet_tile":{ # config for controlnet_tile
"enable": true, # enable/disable (important)
"use_preprocessor":true, # Whether to use a preprocessor for each controlnet type
"preprocessor":{ # If not specified, the default preprocessor is selected.(Most of the time the default should be fine.)
# none/blur/tile_resample/upernet_seg/ or key in controlnet_aux.processor.MODELS
# https://github.com/patrickvonplaten/controlnet_aux/blob/2fd027162e7aef8c18d0a9b5a344727d37f4f13d/src/controlnet_aux/processor.py#L20
"type" : "tile_resample",
"param":{
"down_sampling_rate":2.0
}
},
"guess_mode":false,
"controlnet_conditioning_scale": 1.0, # control weight (important)
"control_guidance_start": 0.0, # starting control step
"control_guidance_end": 1.0, # ending control step
"control_scale_list":[0.5,0.4,0.3,0.2,0.1] # list of influences on neighboring frames (important)
}, # This means that there is an impact of 0.5 on both neighboring frames and 0.4 on the one next to it. Try lengthening, shortening, or changing the values inside.
"controlnet_ip2p":{
"enable": true,
"use_preprocessor":true,
"guess_mode":false,
"controlnet_conditioning_scale": 1.0,
"control_guidance_start": 0.0,
"control_guidance_end": 1.0,
"control_scale_list":[0.5,0.4,0.3,0.2,0.1]
},
"controlnet_lineart_anime":{
"enable": true,
"use_preprocessor":true,
"guess_mode":false,
"controlnet_conditioning_scale": 1.0,
"control_guidance_start": 0.0,
"control_guidance_end": 1.0,
"control_scale_list":[0.5,0.4,0.3,0.2,0.1]
},
"controlnet_openpose":{
"enable": true,
"use_preprocessor":true,
"guess_mode":false,
"controlnet_conditioning_scale": 1.0,
"control_guidance_start": 0.0,
"control_guidance_end": 1.0,
"control_scale_list":[0.5,0.4,0.3,0.2,0.1]
},
"controlnet_softedge":{
"enable": true,
"use_preprocessor":true,
"preprocessor":{
"type" : "softedge_pidsafe",
"param":{
}
},
"guess_mode":false,
"controlnet_conditioning_scale": 1.0,
"control_guidance_start": 0.0,
"control_guidance_end": 1.0,
"control_scale_list":[0.5,0.4,0.3,0.2,0.1]
},
"controlnet_ref": {
"enable": false, # enable/disable (important)
"ref_image": "ref_image/ref_sample.png", # path to reference image.
"attention_auto_machine_weight": 1.0,
"gn_auto_machine_weight": 1.0,
"style_fidelity": 0.5, # control weight-like parameter(important)
"reference_attn": true, # [attn=true , adain=false] means "reference_only"
"reference_adain": false,
"scale_pattern":[0.5] # Pattern for applying controlnet_ref to frames
} # ex. [0.5] means [0.5,0.5,0.5,0.5,0.5 .... ]. All frames are affected by 50%
# ex. [1, 0] means [1,0,1,0,1,0,1,0,1,0,1 ....]. Only even frames are affected by 100%.
},
"upscale_config": { # config for tile-upscale
"scheduler": "ddim",
"steps": 20,
"strength": 0.5,
"guidance_scale": 10,
"controlnet_tile": { # config for controlnet tile
"enable": true, # enable/disable (important)
"controlnet_conditioning_scale": 1.0, # control weight (important)
"guess_mode": false,
"control_guidance_start": 0.0, # starting control step
"control_guidance_end": 1.0 # ending control step
},
"controlnet_line_anime": { # config for controlnet line anime
"enable": false,
"controlnet_conditioning_scale": 1.0,
"guess_mode": false,
"control_guidance_start": 0.0,
"control_guidance_end": 1.0
},
"controlnet_ip2p": { # config for controlnet ip2p
"enable": false,
"controlnet_conditioning_scale": 0.5,
"guess_mode": false,
"control_guidance_start": 0.0,
"control_guidance_end": 1.0
},
"controlnet_ref": { # config for controlnet ref
"enable": false, # enable/disable (important)
"use_frame_as_ref_image": false, # use original frames as ref_image for each upscale (important)
"use_1st_frame_as_ref_image": false, # use 1st original frame as ref_image for all upscale (important)
"ref_image": "ref_image/path_to_your_ref_img.jpg", # use specified image file as ref_image for all upscale (important)
"attention_auto_machine_weight": 1.0,
"gn_auto_machine_weight": 1.0,
"style_fidelity": 0.25, # control weight-like parameter(important)
"reference_attn": true, # [attn=true , adain=false] means "reference_only"
"reference_adain": false
}
},
"output":{ # output format
"format" : "gif", # gif/mp4/webm
"fps" : 8,
"encode_param":{
"crf": 10
}
}
}
```
```sh
cd animatediff-cli-prompt-travel
venv\Scripts\activate.bat
# with this setup, it took about a minute to generate in my environment(RTX4090). VRAM usage was 6-7 GB
# width 256 / height 384 / length 128 frames / context 16 frames
animatediff generate -c config/prompts/prompt_travel.json -W 256 -H 384 -L 128 -C 16
# 5min / 9-10GB
animatediff generate -c config/prompts/prompt_travel.json -W 512 -H 768 -L 128 -C 16
# upscale using controlnet (tile, line anime, ip2p, ref)
# specify the directory of the frame generated in the above step
# default config path is 'frames_dir/../prompt.json'
# here, width=512 is specified, but even if the original size is 512, it is effective in increasing detail
animatediff tile-upscale PATH_TO_TARGET_FRAME_DIRECTORY -c config/prompts/prompt_travel.json -W 512
# upscale width to 768 (smoother than tile-upscale)
animatediff refine PATH_TO_TARGET_FRAME_DIRECTORY -W 768
# If generation takes an unusually long time, there is not enough vram.
# Give up large size or reduce the size of the context.
animatediff refine PATH_TO_TARGET_FRAME_DIRECTORY -W 1024 -C 6
# change lora and prompt to make minor changes to the video.
animatediff refine PATH_TO_TARGET_FRAME_DIRECTORY -c config/prompts/some_minor_changed.json
```
#### Video Stylization
```sh
cd animatediff-cli-prompt-travel
venv\Scripts\activate.bat
# If you want to use the 'stylize' command, additional installation required
python -m pip install -e .[stylize]
# create config file from src video
animatediff stylize create-config YOUR_SRC_MOVIE_FILE.mp4
# Edit the config file by referring to the hint displayed in the log when the command finishes
# It is recommended to specify a short length for the test run
# generate(test run)
# 16 frames
animatediff stylize generate STYLYZE_DIR -L 16
# 16 frames from the 200th frame
animatediff stylize generate STYLYZE_DIR -L 16 -FO 200
# If generation takes an unusually long time, there is not enough vram.
# Give up large size or reduce the size of the context.
# generate
animatediff stylize generate STYLYZE_DIR
```
#### Video Stylization with mask
```sh
cd animatediff-cli-prompt-travel
venv\Scripts\activate.bat
# If you want to use the 'stylize create-mask' command, additional installation required
python -m pip install -e .[stylize_mask]
# [1] create config file from src video
animatediff stylize create-config YOUR_SRC_MOVIE_FILE.mp4
```
```json
# in prompt.json (generated in [1])
# [2] write the object you want to mask
# ex.) If you want to mask a person
"stylize_config": {
"create_mask": [
"person"
],
"composite": {
```
```json
# ex.) person, dog, cat
"stylize_config": {
"create_mask": [
"person", "dog", "cat"
],
"composite": {
```
```json
# ex.) boy, girl
"stylize_config": {
"create_mask": [
"boy", "girl"
],
"composite": {
```
```sh
# [3] generate mask
animatediff stylize create-mask STYLYZE_DIR
# If you have less than 12GB of vram, specify low vram mode
animatediff stylize create-mask STYLYZE_DIR -lo
# The foreground is output to the following directory (FG_STYLYZE_DIR)
# STYLYZE_DIR/fg_00_timestamp_str
# The background is output to the following directory (BG_STYLYZE_DIR)
# STYLYZE_DIR/bg_timestamp_str
# [4] generate foreground
animatediff stylize generate FG_STYLYZE_DIR
# Same as normal generate.
# The default is controlnet_tile, so if you want to make a big style change,
# such as changing the character, change to openpose, etc.
# Of course, you can also generate the background here.
```
```json
# in prompt.json (generated in [1])
# [5] composite setup
# enter the directory containing the frames generated in [4] in "fg_list".
# In the "mask_prompt" field, write the object you want to extract from the generated foreground frame.
# If you prepared the mask yourself, specify it in mask_path. If a valid path is set, use it.
# If the shape has not changed when the foreground is generated, FG_STYLYZE_DIR/00_mask can be used
# enter the directory containing the background frames separated in [3] in "bg_frame_dir".
"composite": {
"fg_list": [
{
"path": "FG_STYLYZE_DIR/time_stamp_str/00-341774366206100",
"mask_path": " absolute path to mask dir (this is optional) ",
"mask_prompt": "person"
},
{
"path": " absolute path to frame dir ",
"mask_path": " absolute path to mask dir (this is optional) ",
"mask_prompt": "cat"
}
],
"bg_frame_dir": "BG_STYLYZE_DIR/00_controlnet_image/controlnet_tile",
"hint": ""
},
```
```sh
# [6] composite
animatediff stylize composite STYLYZE_DIR
# See help for detailed options.
```
#### Auto config generation for [Stable-Diffusion-Webui-Civitai-Helper](https://github.com/butaixianran/Stable-Diffusion-Webui-Civitai-Helper) user
```sh
# This command parses the *.civitai.info files and automatically generates config files
# See "animatediff civitai2config -h" for details
animatediff civitai2config PATH_TO_YOUR_A111_LORA_DIR
```
#### Wildcard
- you can pick wildcard up at [civitai](https://civitai.com/models/23799/freecards). then, put them in /wildcards.
- Usage is the same as a1111.( \_\_WILDCARDFILENAME\_\_ format,
ex. \_\_animal\_\_ for animal.txt. \_\_background-color\_\_ for background-color.txt.)
```json
"prompt_map": { # __WILDCARDFILENAME__
"0": "__character-posture__, __character-gesture__, __character-emotion__, masterpiece, best quality, a beautiful and detailed portriat of muffet, monster girl,((purple body:1.3)), __background__",
```
### Recommended setting
- checkpoint : [mistoonAnime_v20](https://civitai.com/models/24149/mistoonanime) for anime, [xxmix9realistic_v40](https://civitai.com/models/47274) for photoreal
- scheduler : "k_dpmpp_sde"
- upscale : Enable controlnet_tile and controlnet_ip2p only. If you can provide a good reference image, controlnet_ref may also be useful.
### Recommended settings for 8-12 GB of vram
- max_samples_on_vram : Set to 0 if vram is insufficient when using controlnet
- max_models_on_vram : 1
- Generate at lower resolution and upscale to higher resolution
```sh
animatediff generate -c config/prompts/your_config.json -W 384 -H 576 -L 48 -C 16
animatediff tile-upscale output/2023-08-25T20-00-00-sample-mistoonanime_v20/00-341774366206100 -W 512
```
### Limitations
- lora support is limited. Not all formats can be used!!!
- It is not possible to specify lora in the prompt.
### Related resources
- [AnimateDiff](https://github.com/guoyww/AnimateDiff)
- [ControlNet](https://github.com/lllyasviel/ControlNet)
- [IP-Adapter](https://github.com/tencent-ailab/IP-Adapter)
- [DWPose](https://github.com/IDEA-Research/DWPose)
- [softmax-splatting](https://github.com/sniklaus/softmax-splatting)
- [sam-hq](https://github.com/SysCV/sam-hq)
- [Grounded-Segment-Anything](https://github.com/IDEA-Research/Grounded-Segment-Anything)
- [ProPainter](https://github.com/sczhou/ProPainter)
Below is the original readme.
----------------------------------------------------------
# animatediff
[](https://results.pre-commit.ci/latest/github/neggles/animatediff-cli/main)
animatediff refactor, ~~because I can.~~ with significantly lower VRAM usage.
Also, **infinite generation length support!** yay!
# LoRA loading is ABSOLUTELY NOT IMPLEMENTED YET!
This can theoretically run on CPU, but it's not recommended. Should work fine on a GPU, nVidia or otherwise,
but I haven't tested on non-CUDA hardware. Uses PyTorch 2.0 Scaled-Dot-Product Attention (aka builtin xformers)
by default, but you can pass `--xformers` to force using xformers if you *really* want.
### How To Use
1. Lie down
2. Try not to cry
3. Cry a lot
### but for real?
Okay, fine. But it's still a little complicated and there's no webUI yet.
```sh
git clone https://github.com/neggles/animatediff-cli
cd animatediff-cli
python3.10 -m venv .venv
source .venv/bin/activate
# install Torch. Use whatever your favourite torch version >= 2.0.0 is, but, good luck on non-nVidia...
python -m pip install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cu118
# install the rest of all the things (probably! I may have missed some deps.)
python -m pip install -e '.[dev]'
# you should now be able to
animatediff --help
# There's a nice pretty help screen with a bunch of info that'll print here.
```
From here you'll need to put whatever checkpoint you want to use into `data/models/sd`, copy
one of the prompt configs in `config/prompts`, edit it with your choices of prompt and model (model
paths in prompt .json files are **relative to `data/`**, e.g. `models/sd/vanilla.safetensors`), and
off you go.
Then it's something like (for an 8GB card):
```sh
animatediff generate -c 'config/prompts/waifu.json' -W 576 -H 576 -L 128 -C 16
```
You may have to drop `-C` down to 8 on cards with less than 8GB VRAM, and you can raise it to 20-24
on cards with more. 24 is max.
N.B. generating 128 frames is _**slow...**_
## RiFE!
I have added experimental support for [rife-ncnn-vulkan](https://github.com/nihui/rife-ncnn-vulkan)
using the `animatediff rife interpolate` command. It has fairly self-explanatory help, and it has
been tested on Linux, but I've **no idea** if it'll work on Windows.
Either way, you'll need ffmpeg installed on your system and present in PATH, and you'll need to
download the rife-ncnn-vulkan release for your OS of choice from the GitHub repo (above). Unzip it, and
place the extracted folder at `data/rife/`. You should have a `data/rife/rife-ncnn-vulkan` executable, or `data\rife\rife-ncnn-vulkan.exe` on Windows.
You'll also need to reinstall the repo/package with:
```py
python -m pip install -e '.[rife]'
```
or just install `ffmpeg-python` manually yourself.
Default is to multiply each frame by 8, turning an 8fps animation into a 64fps one, then encode
that to a 60fps WebM. (If you pick GIF mode, it'll be 50fps, because GIFs are cursed and encode
frame durations as 1/100ths of a second).
Seems to work pretty well...
## TODO:
In no particular order:
- [x] Infinite generation length support
- [x] RIFE support for motion interpolation (`rife-ncnn-vulkan` isn't the greatest implementation)
- [x] Export RIFE interpolated frames to a video file (webm, mp4, animated webp, hevc mp4, gif, etc.)
- [x] Generate infinite length animations on a 6-8GB card (at 512x512 with 8-frame context, but hey it'll do)
- [x] Torch SDP Attention (makes xformers optional)
- [x] Support for `clip_skip` in prompt config
- [x] Experimental support for `torch.compile()` (upstream Diffusers bugs slow this down a little but it's still zippy)
- [x] Batch your generations with `--repeat`! (e.g. `--repeat 10` will repeat all your prompts 10 times)
- [x] Call the `animatediff.cli.generate()` function from another Python program without reloading the model every time
- [x] Drag remaining old Diffusers code up to latest (mostly)
- [ ] Add a webUI (maybe, there are people wrapping this already so maybe not?)
- [ ] img2img support (start from an existing image and continue)
- [ ] Stop using custom modules where possible (should be able to use Diffusers for almost all of it)
- [ ] Automatic generate-then-interpolate-with-RIFE mode
## Credits:
see [guoyww/AnimateDiff](https://github.com/guoyww/AnimateDiff) (very little of this is my work)
n.b. the copyright notice in `COPYING` is missing the original authors' names, solely because
the original repo (as of this writing) has no name attached to the license. I have, however,
used the same license they did (Apache 2.0).