update

2025-11-10 04:05:18 +01:00
2 changed files with 6 additions and 44 deletions
@@ -76,6 +76,7 @@ jobs:
        run: |
          uv pip install -e ".[quality]"
          uv pip uninstall accelerate && uv pip install -U accelerate@git+https://github.com/huggingface/accelerate.git
+          uv pip uninstall transformers -y && pip uninstall huggingface_hub -y && python -m uv pip install --prerelease allow -U transformers@git+https://github.com/huggingface/transformers.git
      - name: Environment
        run: |
          python utils/print_env.py
@@ -127,7 +128,7 @@ jobs:
        uv pip install -e ".[quality]"
        uv pip install peft@git+https://github.com/huggingface/peft.git
        uv pip uninstall accelerate && uv pip install -U accelerate@git+https://github.com/huggingface/accelerate.git
-
+        uv pip uninstall transformers -y && pip uninstall huggingface_hub -y && python -m uv pip install --prerelease allow -U transformers@git+https://github.com/huggingface/transformers.git
    - name: Environment
      run: |
        python utils/print_env.py
@@ -178,6 +179,7 @@ jobs:
    - name: Install dependencies
      run: |
        uv pip install -e ".[quality,training]"
+        uv pip uninstall transformers -y && pip uninstall huggingface_hub -y && python -m uv pip install --prerelease allow -U transformers@git+https://github.com/huggingface/transformers.git
    - name: Environment
      run: |
        python utils/print_env.py
@@ -198,47 +200,6 @@ jobs:
        name: torch_compile_test_reports
        path: reports

-  run_xformers_tests:
-    name: PyTorch xformers CUDA tests
-
-    runs-on:
-      group: aws-g4dn-2xlarge
-
-    container:
-      image: diffusers/diffusers-pytorch-xformers-cuda
-      options: --gpus all --shm-size "16gb" --ipc host
-
-    steps:
-    - name: Checkout diffusers
-      uses: actions/checkout@v3
-      with:
-        fetch-depth: 2
-
-    - name: NVIDIA-SMI
-      run: |
-        nvidia-smi
-    - name: Install dependencies
-      run: |
-        uv pip install -e ".[quality,training]"
-    - name: Environment
-      run: |
-        python utils/print_env.py
-    - name: Run example tests on GPU
-      env:
-        HF_TOKEN: ${{ secrets.DIFFUSERS_HF_HUB_READ_TOKEN }}
-      run: |
-        pytest -n 1 --max-worker-restart=0 --dist=loadfile -s -v -k "xformers" --make-reports=tests_torch_xformers_cuda tests/
-    - name: Failure short reports
-      if: ${{ failure() }}
-      run: cat reports/tests_torch_xformers_cuda_failures_short.txt
-
-    - name: Test suite reports artifacts
-      if: ${{ always() }}
-      uses: actions/upload-artifact@v4
-      with:
-        name: torch_xformers_test_reports
-        path: reports
-
  run_examples_tests:
    name: Examples PyTorch CUDA tests on Ubuntu

@@ -15,8 +15,9 @@ specific language governing permissions and limitations under the License.

 [ModularPipelineBlocks](./pipeline_block) are the fundamental building blocks of a [`ModularPipeline`]. You can create custom blocks by defining their inputs, outputs, and computation logic. This guide demonstrates how to create and use a custom block.

-> [!TIP]
-> Explore the [Modular Diffusers Custom Blocks](https://huggingface.co/collections/diffusers/modular-diffusers-custom-blocks) collection for official custom modular blocks like Nano Banana.
+<Tip>
+You can find examples of different types of custom blocks in the [Modular Diffusers Custom Blocks collection](https://huggingface.co/collections/diffusers/modular-diffusers-custom-blocks)
+</Tip>

 ## Project Structure