chore: add V1 flux tests (#742)

* make linter happy

* add tests for qwen-image-edit-2509

* update

* update

* flux schnell test runnable

* update the test score

* make linter happy

* add fp4 results

* fix the test score

* add tests for flux_dev

* update the test score

* add flux.1-krea

* fix the krea tests

* update

* update

* add kontext

* update

* fix kontext

* update

* add flux.1-depth

* add flux-tools

* finish flux tools

* add more flux examples

* update

* update3

* update

* update score

* update

* update

.github/workflows/pr-test.yaml

@@ -92,8 +92,8 @@ jobs:
           source $(conda info --base)/etc/profile.d/conda.sh
           conda activate test_env || { echo "Failed to activate conda env"; exit 1; }
           which python
-          pytest -s -x tests/flux/test_flux_examples.py
-          pytest -s -x tests/v1/test_examples.py
+          pytest -vv -x tests/flux/test_flux_examples.py
+          pytest -vv -x tests/v1/test_examples.py
           python .github/workflows/run_all_tests.py
       - name: clean up
         if: always()

.github/workflows/run_all_tests.py

 import subprocess
 from pathlib import Path
 
+from tqdm import tqdm
+
 
 def run_all_tests():
     test_dir = Path("tests")
@@ -21,9 +23,9 @@ def run_all_tests():
         print(f"  {test_file}")
 
     failed_tests = []
-    for test_file in test_files:
+    for test_file in tqdm(test_files):
         print(f"Running {test_file} ...")
-        result = subprocess.run(["pytest", "--reruns", "2", "--reruns-delay", "0", "-s", "-x", test_file])
+        result = subprocess.run(["pytest", "--reruns", "2", "--reruns-delay", "0", "-vv", "-x", test_file])
         if result.returncode != 0:
             print(f"Test failed: {test_file}")
             failed_tests.append(test_file)

docker/Dockerfile

-# Use an NVIDIA base image with CUDA support
-
-ARG CUDA_IMAGE="12.8.1-devel-ubuntu24.04"
-
-FROM nvidia/cuda:${CUDA_IMAGE}
-
-ENV DEBIAN_FRONTEND=noninteractive
-
-ARG PYTHON_VERSION=3.11
-ARG TORCH_VERSION=2.6
-ARG TORCHVISION_VERSION=0.21
-ARG TORCHAUDIO_VERSION=2.6
-ARG CUDA_SHORT_VERSION=12.8
-
-# Set working directory
-WORKDIR /
-
-RUN echo PYTHON_VERSION=${PYTHON_VERSION} \
-    && echo CUDA_SHORT_VERSION=${CUDA_SHORT_VERSION} \
-    && echo TORCH_VERSION=${TORCH_VERSION} \
-    && echo TORCHVISION_VERSION=${TORCHVISION_VERSION} \
-    && echo TORCHAUDIO_VERSION=${TORCHAUDIO_VERSION}
-
-# Setup timezone and install system dependencies
-RUN 'tzdata tzdata/Areas select America' | debconf-set-selections \
-    && echo 'tzdata tzdata/Zones/America select New_York' | debconf-set-selections \
-    && apt update -y \
-    && apt install software-properties-common -y \
-    && add-apt-repository ppa:deadsnakes/ppa -y \
-    && apt update && apt install wget git -y && apt clean
-
-# Install Miniconda
-ENV CONDA_DIR=/opt/conda
-RUN wget --quiet https://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-x86_64.sh -O /tmp/miniconda.sh \
-    && bash /tmp/miniconda.sh -b -p ${CONDA_DIR} \
-    && rm /tmp/miniconda.sh \
-    && ${CONDA_DIR}/bin/conda clean -afy
-
-ENV PATH=${CONDA_DIR}/bin:$PATH
-
-RUN conda init bash
-
-RUN conda create -y -n nunchaku python=${PYTHON_VERSION} \
-    && conda install -y -n nunchaku -c conda-forge gxx=11 gcc=11 \
-    && conda clean -afy
-
-SHELL ["conda", "run", "-n", "nunchaku", "/bin/bash", "-c"]
-
-# Install building dependencies
-RUN pip install torch==${TORCH_VERSION} torchvision==${TORCHVISION_VERSION} torchaudio==${TORCHAUDIO_VERSION} --index-url https://download.pytorch.org/whl/cu124
-RUN pip install ninja wheel diffusers transformers accelerate sentencepiece protobuf huggingface_hub comfy-cli
-
-# Start building
-RUN git clone https://github.com/mit-han-lab/nunchaku.git \
-    && cd nunchaku \
-    && git submodule init \
-    && git submodule update \
-    && NUNCHAKU_INSTALL_MODE=ALL python setup.py develop
-
-RUN cd .. && git clone https://github.com/comfyanonymous/ComfyUI \
-    && cd ComfyUI && pip install -r requirements.txt \
-    && cd custom_nodes && git clone https://github.com/ltdrdata/ComfyUI-Manager comfyui-manager \
-    && git clone https://github.com/mit-han-lab/ComfyUI-nunchaku.git \
-    && cd .. && mkdir -p user/default/workflows/ && cp -r custom_nodes/ComfyUI-nunchaku/workflows/ user/default/workflows/nunchaku_examples

docker/Dockerfile.torch27

-# Use an NVIDIA base image with CUDA support
-
-ARG CUDA_IMAGE="12.8.1-devel-ubuntu24.04"
-
-FROM nvidia/cuda:${CUDA_IMAGE}
-
-ENV DEBIAN_FRONTEND=noninteractive
-
-ARG PYTHON_VERSION=3.11
-ARG TORCH_VERSION=2.7
-ARG TORCHVISION_VERSION=0.21
-ARG TORCHAUDIO_VERSION=2.6
-ARG CUDA_SHORT_VERSION=12.8
-
-# Set working directory
-WORKDIR /
-
-RUN echo PYTHON_VERSION=${PYTHON_VERSION} \
-    && echo CUDA_SHORT_VERSION=${CUDA_SHORT_VERSION} \
-    && echo TORCH_VERSION=${TORCH_VERSION} \
-    && echo TORCHVISION_VERSION=${TORCHVISION_VERSION} \
-    && echo TORCHAUDIO_VERSION=${TORCHAUDIO_VERSION}
-
-# Setup timezone and install system dependencies
-RUN 'tzdata tzdata/Areas select America' | debconf-set-selections \
-    && echo 'tzdata tzdata/Zones/America select New_York' | debconf-set-selections \
-    && apt update -y \
-    && apt install software-properties-common -y \
-    && add-apt-repository ppa:deadsnakes/ppa -y \
-    && apt update && apt install wget git -y && apt clean
-
-# Install Miniconda
-ENV CONDA_DIR=/opt/conda
-RUN wget --quiet https://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-x86_64.sh -O /tmp/miniconda.sh \
-    && bash /tmp/miniconda.sh -b -p ${CONDA_DIR} \
-    && rm /tmp/miniconda.sh \
-    && ${CONDA_DIR}/bin/conda clean -afy
-
-ENV PATH=${CONDA_DIR}/bin:$PATH
-
-RUN conda init bash
-
-RUN conda create -y -n nunchaku python=${PYTHON_VERSION} \
-    && conda install -y -n nunchaku -c conda-forge gxx=11 gcc=11 \
-    && conda clean -afy
-
-SHELL ["conda", "run", "-n", "nunchaku", "/bin/bash", "-c"]
-
-# Install building dependencies
-RUN pip install --pre torch==2.7.0.dev20250307+cu128 torchvision torchaudio --index-url https://download.pytorch.org/whl/nightly/cu128
-RUN pip install ninja wheel diffusers transformers accelerate sentencepiece protobuf huggingface_hub comfy-cli
-
-# Start building
-RUN git clone https://github.com/mit-han-lab/nunchaku.git \
-    && cd nunchaku \
-    && git submodule init \
-    && git submodule update \
-    && NUNCHAKU_INSTALL_MODE=ALL python setup.py develop
-
-RUN cd .. && git clone https://github.com/comfyanonymous/ComfyUI \
-    && cd ComfyUI && pip install -r requirements.txt \
-    && cd custom_nodes && git clone https://github.com/ltdrdata/ComfyUI-Manager comfyui-manager \
-    && git clone https://github.com/mit-han-lab/ComfyUI-nunchaku.git \
-    && cd .. && mkdir -p user/default/workflows/ && cp -r custom_nodes/ComfyUI-nunchaku/workflows/ user/default/workflows/nunchaku_examples

docker/Dockerfile.torch28

-# Use an NVIDIA base image with CUDA support
-
-ARG CUDA_IMAGE="12.8.1-devel-ubuntu24.04"
-
-FROM nvidia/cuda:${CUDA_IMAGE}
-
-ENV DEBIAN_FRONTEND=noninteractive
-
-ARG PYTHON_VERSION=3.11
-ARG TORCH_VERSION=2.8
-ARG TORCHVISION_VERSION=0.21
-ARG TORCHAUDIO_VERSION=2.6
-ARG CUDA_SHORT_VERSION=12.8
-
-# Set working directory
-WORKDIR /
-
-RUN echo PYTHON_VERSION=${PYTHON_VERSION} \
-    && echo CUDA_SHORT_VERSION=${CUDA_SHORT_VERSION} \
-    && echo TORCH_VERSION=${TORCH_VERSION} \
-    && echo TORCHVISION_VERSION=${TORCHVISION_VERSION} \
-    && echo TORCHAUDIO_VERSION=${TORCHAUDIO_VERSION}
-
-# Setup timezone and install system dependencies
-RUN 'tzdata tzdata/Areas select America' | debconf-set-selections \
-    && echo 'tzdata tzdata/Zones/America select New_York' | debconf-set-selections \
-    && apt update -y \
-    && apt install software-properties-common -y \
-    && add-apt-repository ppa:deadsnakes/ppa -y \
-    && apt update && apt install wget git -y && apt clean
-
-# Install Miniconda
-ENV CONDA_DIR=/opt/conda
-RUN wget --quiet https://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-x86_64.sh -O /tmp/miniconda.sh \
-    && bash /tmp/miniconda.sh -b -p ${CONDA_DIR} \
-    && rm /tmp/miniconda.sh \
-    && ${CONDA_DIR}/bin/conda clean -afy
-
-ENV PATH=${CONDA_DIR}/bin:$PATH
-
-RUN conda init bash
-
-RUN conda create -y -n nunchaku python=${PYTHON_VERSION} \
-    && conda install -y -n nunchaku -c conda-forge gxx=11 gcc=11 \
-    && conda clean -afy
-
-SHELL ["conda", "run", "-n", "nunchaku", "/bin/bash", "-c"]
-
-# Install building dependencies
-RUN pip install --pre torch torchvision torchaudio --index-url https://download.pytorch.org/whl/nightly/cu128
-RUN pip install ninja wheel diffusers transformers accelerate sentencepiece protobuf huggingface_hub comfy-cli
-
-# Start building
-RUN git clone https://github.com/mit-han-lab/nunchaku.git \
-    && cd nunchaku \
-    && git submodule init \
-    && git submodule update \
-    && NUNCHAKU_INSTALL_MODE=ALL python setup.py develop
-
-RUN cd .. && git clone https://github.com/comfyanonymous/ComfyUI \
-    && cd ComfyUI && pip install -r requirements.txt \
-    && cd custom_nodes && git clone https://github.com/ltdrdata/ComfyUI-Manager comfyui-manager \
-    && git clone https://github.com/mit-han-lab/ComfyUI-nunchaku.git \
-    && cd .. && mkdir -p user/default/workflows/ && cp -r custom_nodes/ComfyUI-nunchaku/workflows/ user/default/workflows/nunchaku_examples

examples/flux.1-fill-dev.py

@@ -5,8 +5,8 @@ from diffusers.utils import load_image
 from nunchaku import NunchakuFluxTransformer2dModel
 from nunchaku.utils import get_precision
 
-image = load_image("https://huggingface.co/mit-han-lab/svdq-int4-flux.1-fill-dev/resolve/main/example.png")
-mask = load_image("https://huggingface.co/mit-han-lab/svdq-int4-flux.1-fill-dev/resolve/main/mask.png")
+image = load_image("https://huggingface.co/datasets/diffusers/diffusers-images-docs/resolve/main/cup.png")
+mask = load_image("https://huggingface.co/datasets/diffusers/diffusers-images-docs/resolve/main/cup_mask.png")
 
 precision = get_precision()  # auto-detect your precision is 'int4' or 'fp4' based on your GPU
 transformer = NunchakuFluxTransformer2dModel.from_pretrained(
@@ -16,7 +16,7 @@ pipe = FluxFillPipeline.from_pretrained(
     "black-forest-labs/FLUX.1-Fill-dev", transformer=transformer, torch_dtype=torch.bfloat16
 ).to("cuda")
 image = pipe(
-    prompt="A wooden basket of a cat.",
+    prompt="a white paper cup",
     image=image,
     mask_image=mask,
     height=1024,

examples/v1/flux.1-canny-dev.py

+import torch
+from controlnet_aux import CannyDetector
+from diffusers import FluxControlPipeline
+from diffusers.utils import load_image
+
+from nunchaku import NunchakuFluxTransformer2DModelV2
+from nunchaku.utils import get_precision
+
+precision = get_precision()  # auto-detect your precision is 'int4' or 'fp4' based on your GPU
+transformer = NunchakuFluxTransformer2DModelV2.from_pretrained(
+    f"nunchaku-tech/nunchaku-flux.1-canny-dev/svdq-{precision}_r32-flux.1-canny-dev.safetensors"
+)
+pipe = FluxControlPipeline.from_pretrained(
+    "black-forest-labs/FLUX.1-Canny-dev", transformer=transformer, torch_dtype=torch.bfloat16
+).to("cuda")
+
+prompt = (
+    "A robot made of exotic candies and chocolates of different kinds. "
+    "The background is filled with confetti and celebratory gifts."
+)
+control_image = load_image("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/robot.png")
+
+processor = CannyDetector()
+control_image = processor(
+    control_image, low_threshold=50, high_threshold=200, detect_resolution=1024, image_resolution=1024
+)
+
+image = pipe(
+    prompt=prompt, control_image=control_image, height=1024, width=1024, num_inference_steps=20, guidance_scale=30.0
+).images[0]
+image.save(f"flux.1-canny-dev-{precision}.png")

examples/v1/flux.1-depth-dev.py

+import torch
+from diffusers import FluxControlPipeline
+from diffusers.utils import load_image
+from image_gen_aux import DepthPreprocessor
+
+from nunchaku import NunchakuFluxTransformer2DModelV2
+from nunchaku.utils import get_precision
+
+precision = get_precision()  # auto-detect your precision is 'int4' or 'fp4' based on your GPU
+transformer = NunchakuFluxTransformer2DModelV2.from_pretrained(
+    f"nunchaku-tech/nunchaku-flux.1-depth-dev/svdq-{precision}_r32-flux.1-depth-dev.safetensors"
+)
+
+pipe = FluxControlPipeline.from_pretrained(
+    "black-forest-labs/FLUX.1-Depth-dev",
+    transformer=transformer,
+    torch_dtype=torch.bfloat16,
+).to("cuda")
+
+prompt = (
+    "A robot made of exotic candies and chocolates of different kinds. "
+    "The background is filled with confetti and celebratory gifts."
+)
+control_image = load_image("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/robot.png")
+
+processor = DepthPreprocessor.from_pretrained("LiheYoung/depth-anything-large-hf")
+control_image = processor(control_image)[0].convert("RGB")
+
+image = pipe(
+    prompt=prompt, control_image=control_image, height=1024, width=1024, num_inference_steps=20, guidance_scale=10.0
+).images[0]
+image.save(f"flux.1-depth-dev-{precision}.png")

examples/v1/flux1-dev.py → examples/v1/flux.1-dev.py

@@ -11,5 +11,5 @@ transformer = NunchakuFluxTransformer2DModelV2.from_pretrained(
 pipeline = FluxPipeline.from_pretrained(
     "black-forest-labs/FLUX.1-dev", transformer=transformer, torch_dtype=torch.bfloat16
 ).to("cuda")
-image = pipeline("A cat holding a sign that says hello world", num_inference_steps=50, guidance_scale=3.5).images[0]
+image = pipeline("A cat holding a sign that says hello world", num_inference_steps=20, guidance_scale=3.5).images[0]
 image.save(f"flux.1-dev-{precision}.png")

examples/v1/flux.1-fill-dev.py

+import torch
+from diffusers import FluxFillPipeline
+from diffusers.utils import load_image
+
+from nunchaku import NunchakuFluxTransformer2DModelV2
+from nunchaku.utils import get_precision
+
+image = load_image("https://huggingface.co/datasets/diffusers/diffusers-images-docs/resolve/main/cup.png")
+mask = load_image("https://huggingface.co/datasets/diffusers/diffusers-images-docs/resolve/main/cup_mask.png")
+
+precision = get_precision()  # auto-detect your precision is 'int4' or 'fp4' based on your GPU
+transformer = NunchakuFluxTransformer2DModelV2.from_pretrained(
+    f"nunchaku-tech/nunchaku-flux.1-fill-dev/svdq-{precision}_r32-flux.1-fill-dev.safetensors"
+)
+pipe = FluxFillPipeline.from_pretrained(
+    "black-forest-labs/FLUX.1-Fill-dev", transformer=transformer, torch_dtype=torch.bfloat16
+).to("cuda")
+image = pipe(
+    prompt="a white paper cup",
+    image=image,
+    mask_image=mask,
+    height=1024,
+    width=1024,
+    guidance_scale=30,
+    num_inference_steps=50,
+    max_sequence_length=512,
+).images[0]
+image.save(f"flux.1-fill-dev-{precision}.png")

examples/v1/flux.1-kontext-dev.py

+import torch
+from diffusers import FluxKontextPipeline
+from diffusers.utils import load_image
+
+from nunchaku import NunchakuFluxTransformer2DModelV2
+from nunchaku.utils import get_precision
+
+transformer = NunchakuFluxTransformer2DModelV2.from_pretrained(
+    f"nunchaku-tech/nunchaku-flux.1-kontext-dev/svdq-{get_precision()}_r32-flux.1-kontext-dev.safetensors"
+)
+
+pipeline = FluxKontextPipeline.from_pretrained(
+    "black-forest-labs/FLUX.1-Kontext-dev", transformer=transformer, torch_dtype=torch.bfloat16
+).to("cuda")
+
+image = load_image(
+    "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/yarn-art-pikachu.png"
+).convert("RGB")
+
+prompt = "Make Pikachu hold a sign that says 'Nunchaku is awesome', yarn art style, detailed, vibrant colors"
+image = pipeline(image=image, prompt=prompt, num_inference_steps=20, guidance_scale=2.5).images[0]
+image.save("flux-kontext-dev.png")

examples/v1/flux.1-dev_v2.py → examples/v1/flux.1-krea-dev.py

 import torch
 from diffusers import FluxPipeline
 
-from nunchaku.models.transformers.transformer_flux_v2 import NunchakuFluxTransformer2DModelV2
+from nunchaku import NunchakuFluxTransformer2DModelV2
 from nunchaku.utils import get_precision
 
 precision = get_precision()  # auto-detect your precision is 'int4' or 'fp4' based on your GPU
 transformer = NunchakuFluxTransformer2DModelV2.from_pretrained(
-    f"nunchaku-tech/nunchaku-flux.1-dev/svdq-{precision}_r32-flux.1-dev.safetensors"
+    f"nunchaku-tech/nunchaku-flux.1-krea-dev/svdq-{precision}_r32-flux.1-krea-dev.safetensors"
 )
 pipeline = FluxPipeline.from_pretrained(
-    "black-forest-labs/FLUX.1-dev", transformer=transformer, torch_dtype=torch.bfloat16
+    "black-forest-labs/FLUX.1-krea-dev", torch_dtype=torch.bfloat16, transformer=transformer
 ).to("cuda")
-image = pipeline("A cat holding a sign that says hello world", num_inference_steps=50, guidance_scale=3.5).images[0]
-image.save(f"flux.1-dev-{precision}.png")
+prompt = (
+    "Tiny paper origami kingdom, a river flowing through a lush valley, bright saturated image,"
+    "a fox to the left, deer to the right, birds in the sky, bushes and tress all around"
+)
+image = pipeline(prompt, height=1024, width=1024, guidance_scale=4.5, num_inference_steps=20).images[0]
+image.save("flux-krea-dev.png")

examples/v1/flux.1-redux-dev.py

+import torch
+from diffusers import FluxPipeline, FluxPriorReduxPipeline
+from diffusers.utils import load_image
+
+from nunchaku import NunchakuFluxTransformer2DModelV2
+from nunchaku.utils import get_precision
+
+precision = get_precision()
+pipe_prior_redux = FluxPriorReduxPipeline.from_pretrained(
+    "black-forest-labs/FLUX.1-Redux-dev", torch_dtype=torch.bfloat16
+).to("cuda")
+transformer = NunchakuFluxTransformer2DModelV2.from_pretrained(
+    f"nunchaku-tech/nunchaku-flux.1-dev/svdq-{precision}_r32-flux.1-dev.safetensors"
+)
+pipe = FluxPipeline.from_pretrained(
+    "black-forest-labs/FLUX.1-dev",
+    text_encoder=None,
+    text_encoder_2=None,
+    transformer=transformer,
+    torch_dtype=torch.bfloat16,
+).to("cuda")
+
+image = load_image("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/robot.png")
+pipe_prior_output = pipe_prior_redux(image)
+images = pipe(guidance_scale=2.5, num_inference_steps=20, **pipe_prior_output).images
+images[0].save(f"flux.1-redux-dev-{precision}.png")

nunchaku/ops/fused.py

@@ -132,7 +132,7 @@ def fused_qkv_norm_rottary(
     quantized_x, ascales, lora_act = proj.quantize(x)
 
     if output is None:
-        output = torch.empty(quantized_x.shape[0], proj.out_features, dtype=x.dtype, device=x.device)
+        output = torch.empty(batch_size * seq_len, proj.out_features, dtype=x.dtype, device=x.device)
 
     if isinstance(output, tuple):
         assert len(output) == 3
@@ -174,7 +174,5 @@ def fused_qkv_norm_rottary(
             norm_k=norm_k.weight if norm_k is not None else None,
             rotary_emb=rotary_emb,
         )
-        if seq_len * batch_size < output.shape[0]:
-            output = output[: seq_len * batch_size, :]
         output = output.view(batch_size, seq_len, -1)
         return output

nunchaku/test.py

@@ -24,7 +24,9 @@ if __name__ == "__main__":
     torch_dtype = torch.float16 if is_turing() else torch.bfloat16
 
     transformer = NunchakuFluxTransformer2dModel.from_pretrained(
-        f"mit-han-lab/svdq-{precision}-flux.1-schnell", torch_dtype=torch_dtype, offload=True
+        f"nunchaku-tech/nunchaku-flux.1-schnell/svdq-{precision}_r32-flux.1-schnell.safetensors",
+        torch_dtype=torch_dtype,
+        offload=True,
     )
     pipeline = FluxPipeline.from_pretrained(
         "black-forest-labs/FLUX.1-schnell", transformer=transformer, torch_dtype=torch_dtype

pyproject.toml

@@ -34,7 +34,7 @@ dependencies = [
 optional-dependencies.ci = [
   "controlnet-aux==0.0.10",
   "datasets==3.6",
-  "diffusers @ git+https://github.com/huggingface/diffusers@a72bc0c",
+  "diffusers @ git+https://github.com/huggingface/diffusers@041501a",
   "facexlib==0.3",
   "image-gen-aux @ git+https://github.com/asomoza/image_gen_aux.git",
   "insightface==0.7.3",

scripts/build_all_dockers.sh

-#!/bin/bash
-# Define the versions for Python, Torch, and CUDA
-NUNCHAKU_VERSION=$1
-python_versions=("3.10" "3.11" "3.12" "3.13")
-torch_versions=("2.5" "2.6")
-cuda_versions=("12.4" "12.8")
-
-# Loop through all combinations of Python, Torch, and CUDA versions
-for python_version in "${python_versions[@]}"; do
-  for torch_version in "${torch_versions[@]}"; do
-    # Skip building for Python 3.13 and PyTorch 2.5
-    if [[ "$python_version" == "3.13" && "$torch_version" == "2.5" ]]; then
-      echo "Skipping Python 3.13 with PyTorch 2.5"
-      continue
-    fi
-    for cuda_version in "${cuda_versions[@]}"; do
-      bash scripts/build_docker.sh "$python_version" "$torch_version" "$cuda_version" "$NUNCHAKU_VERSION"
-    done
-  done
-done
-
-for python_version in "${python_versions[@]}"; do
-  for cuda_version in "${cuda_versions[@]}"; do
-    bash scripts/build_docker_torch27.sh "$python_version" "2.7" "$cuda_version" "$NUNCHAKU_VERSION"
-    bash scripts/build_docker_torch28.sh "$python_version" "2.8" "$cuda_version" "$NUNCHAKU_VERSION"
-  done
-done