diff --git a/.github/workflows/build-containers.yaml b/.github/workflows/build-containers.yaml
deleted file mode 100644
index 0ab1c9b..0000000
--- a/.github/workflows/build-containers.yaml
+++ /dev/null
@@ -1,37 +0,0 @@
-name: Build Containers
-on:
-  workflow_dispatch:
-    inputs:
-      sha:
-        description: 'the git sha to checkout'
-        required: true
-        type: string
-  workflow_call:
-    inputs:
-      sha:
-        description: 'the git sha to checkout'
-        required: true
-        type: string
-jobs:
-  build-containers:
-    runs-on: "ubuntu-24.04"
-    steps:
-      # Checkout the repository code
-      - name: Checkout Code
-        uses: actions/checkout@v4
-        with:
-          ref: ${{ inputs.sha }}
-          fetch-depth: 0
-          fetch-tags: true
-      - uses: ./.github/actions/setup-environment
-        id: runner-context
-      # Build the Docker image
-      - name: Build Docker Image
-        run: |
-          uv version "$PACKAGE_VERSION" --no-sync
-          echo "building image: snraware:${PACKAGE_VERSION}"
-          docker build -f Containerfile -t snraware:${PACKAGE_VERSION} .
-          echo "testing installation in image"
-          docker run snraware:${PACKAGE_VERSION} python -c "import snraware"
-        env:
-          PACKAGE_VERSION: "${{ steps.runner-context.outputs.package-version }}"
diff --git a/.github/workflows/build-wheels.yaml b/.github/workflows/build-wheels.yaml
deleted file mode 100644
index e3d813f..0000000
--- a/.github/workflows/build-wheels.yaml
+++ /dev/null
@@ -1,38 +0,0 @@
-name: Build Wheels
-on:
-  workflow_dispatch:
-    inputs:
-      sha:
-        description: 'the git sha to checkout'
-        required: true
-        type: string
-  workflow_call:
-    inputs:
-      sha:
-        description: 'the git sha to checkout'
-        required: true
-        type: string
-jobs:
-  build-components:
-    runs-on: "ubuntu-24.04"
-    name: "build-wheels"
-    steps:
-      - uses: actions/checkout@v5
-        with:
-          ref: ${{ inputs.sha }}
-          fetch-depth: 0
-          fetch-tags: true
-      - uses: ./.github/actions/setup-environment
-        id: runner-context
-      - name: build-wheel
-        env:
-          PACKAGE_VERSION: "${{ steps.runner-context.outputs.package-version }}"
-        run: |
-          uv version "$PACKAGE_VERSION"
-          uv sync
-          uv build
-      - name: "upload-artifacts"
-        uses: actions/upload-artifact@v4
-        with:
-          name: "pkg-wheels"
-          path: "dist/*.whl"
diff --git a/.github/workflows/codeql.yaml b/.github/workflows/codeql.yaml
index bd4d96c..310dc7a 100644
--- a/.github/workflows/codeql.yaml
+++ b/.github/workflows/codeql.yaml
@@ -23,7 +23,7 @@ jobs:
     strategy:
       fail-fast: false
       matrix:
-        language: [ "javascript-typescript", "python" ]
+        language: [ "python" ]
     steps:
     - uses: actions/checkout@v5
       with:
diff --git a/.github/workflows/main.yaml b/.github/workflows/main.yaml
index 7d02e93..cdce46e 100644
--- a/.github/workflows/main.yaml
+++ b/.github/workflows/main.yaml
@@ -28,16 +28,6 @@ jobs:
     secrets: inherit
     with:
       sha: ${{ inputs.sha || github.sha }}
-  build-wheels:
-    uses: ./.github/workflows/build-wheels.yaml
-    secrets: inherit
-    with:
-      sha: ${{ inputs.sha || github.sha }}
-  build-containers:
-    uses: ./.github/workflows/build-containers.yaml
-    secrets: inherit
-    with:
-      sha: ${{ inputs.sha || github.sha }}
   build-docs:
     uses: ./.github/workflows/build-docs.yaml
     secrets: inherit
@@ -56,10 +46,8 @@ jobs:
     uses: ./.github/workflows/release.yaml
     secrets: inherit
     needs:
-      - build-containers
       - build-docs
-      - build-wheels
       - checks
       - codeql
     with:
-      publish-docs: ${{ github.ref_name == 'main' }}
+      publish-docs: ${{ github.ref_name == 'main' }}
\ No newline at end of file
diff --git a/docs/images/image.png b/docs/images/image.png
new file mode 100644
index 0000000..12fcaa4
Binary files /dev/null and b/docs/images/image.png differ
diff --git a/docs/index.md b/docs/index.md
index 108ec21..ed36bcd 100644
--- a/docs/index.md
+++ b/docs/index.md
@@ -8,10 +8,10 @@ This repository contains the Pytorch code in our paper [SNRAware: Improved Deep
     author = {Xue, Hui and Hooper, Sarah M. and Pierce, Iain and Davies, Rhodri H. and Stairs, John and Naegele, Joseph and Campbell-Washburn, Adrienne E. and Manisty, Charlotte and Moon, James C. and Treibel, Thomas A. and Hansen, Michael S. and Kellman, Peter},
     title = {SNRAware: Improved Deep Learning MRI Denoising with Signal-to-noise Ratio Unit Training and G-factor Map Augmentation},
     journal = {Radiology: Artificial Intelligence},
-    volume = {0},
-    number = {ja},
+    volume = {7},
+    number = {6},
     pages = {e250227},
-    year = {0},
+    year = {2025},
     doi = {10.1148/ryai.250227},
     note ={PMID: 41123451},
     URL = {https://doi.org/10.1148/ryai.250227}
@@ -23,34 +23,47 @@ This repository contains the Pytorch code in our paper [SNRAware: Improved Deep
 
 ## Get started
 
-[just](https://github.com/casey/just) is used in this project. If not, please install this tool:
+`uv` is used in this project. Please install it as:
 
 ```bash
-# install just
-wget -qO - 'https://proget.makedeb.org/debian-feeds/prebuilt-mpr.pub' | gpg --dearmor | sudo tee /usr/share/keyrings/prebuilt-mpr-archive-keyring.gpg 1> /dev/null
-echo "deb [arch=all,$(dpkg --print-architecture) signed-by=/usr/share/keyrings/prebuilt-mpr-archive-keyring.gpg] https://proget.makedeb.org prebuilt-mpr $(lsb_release -cs)" | sudo tee /etc/apt/sources.list.d/prebuilt-mpr.list
+# install uv
+curl -LsSf https://astral.sh/uv/install.sh | sh
+
+# install git-lfs
 sudo apt update
-sudo apt install just -y
+sudo apt install git-lfs direnv
 ```
 
-Then, please set up the virtual environment and run tests:
+Make sure commands `uv` are on your path.
+
+Also, this project requires NVIDIA GPU. To check whether your GPU is available and is working:
 
 ```bash
-# show the list
-just --list
+nvidia-smi
+```
+If the GPU is working correctly, this command will display detailed information, including driver version, GPU usage, memory usage, and temperature.
 
-# set up virtual environment
-just setup-env
+Make sure the command `uv` are on your path. Then please clone the repo, set up the virtual environment and run tests:
 
-# review documentation
-just serve-docs
+```bash
+# clone the repo
+git clone git@github.com:microsoft/SNRAware.git
 
-# run test
-just test
+# set up env
+direnv allow
+cd ./SNRAware
+uv sync
+
+# pull down test data
+git lfs pull
+
+# run the test
+uv run pytest -m gpu ./test
 ```
 
-## Data
-Dataset for MR denoising training is not opened at this moment.
+## Training data
+
+Dataset for MR denoising training is not opened at this moment. More information will be provided once training data is released.
 
 ## Model
 Three models are released at https://huggingface.co/microsoft/SNRAware
@@ -59,8 +72,34 @@ Three models are released at https://huggingface.co/microsoft/SNRAware
 - SNRAware-medium: 55.1million parameters
 - SNRAware-large: 109million parameters
 
+To test the model, 
+```bash
+# download the model from the huggingface
+# small model
+wget https://huggingface.co/microsoft/SNRAware/resolve/main/small/snraware_small_model.pts
+wget https://huggingface.co/microsoft/SNRAware/resolve/main/small/snraware_small_model.yaml
+
+# a test data is provided at ./test/data/inference
+# input data are [H, W, Frame] 3D complex tensor, input_real.npy and input_imag.npy store the 
+# real and imaginary part
+# gmap.npy is the g-factor map for all frames or for every frame, [H, W, 1 or Frame]
+
+# let's use the small model to run a inference
+export model_file=snraware_small_model.pts
+export config_file=snraware_small_model.yaml
+
+# run the inference
+uv run python3 ./src/snraware/projects/mri/denoising/run_inference.py --input_dir ./test/data/phantom --output_dir /tmp/phantom_res_inference --saved_model_path $model_file --saved_config_path $config_file --batch_size 1 --input_fname input --gmap_fname gmap
+```
+
+After the run, the result is saved in the `/tmp/phantom_res_inference` as numpy files. 
+
+![alt text](./docs/images/image.png)
+
+raw, model output, difference
+
 ## Direct intended uses
-SNRAware is shared for research and technical development purposes only, to denoise MR images.
+SNRAware is shared for research and technical development purposes only, to denoisegit  MR images.
 
 ## License and Usage Notices
 The data, code, and model checkpoints described in this repository is provided for research and technical development use
diff --git a/docs/mri_denoising.md b/docs/mri_denoising.md
index 7269fcb..ce69a8a 100644
--- a/docs/mri_denoising.md
+++ b/docs/mri_denoising.md
@@ -45,14 +45,4 @@ User needs to log into the wandb as `wandb login`. Training and validation sampl
 
 # Run inference
 
-After training the model, user can run inference with `run_inference.py` in the `src/snraware/projects/mri/denoising` folder:
-
-```bash
-export model_file="SNRAware-small.pts"
-export config_file="SNRAware-small_config.yaml"
-export res_dir="res"
-export data_dir="/data"
-
-python3 ./src/snraware/projects/mri/denoising/run_inference.py --input_dir ${data_dir} --output_dir ${data_dir}/${res_dir} --saved_model_path $model_file --saved_config_path $config_file --batch_size 1 --input_fname input --gmap_fname gmap
-
-```
\ No newline at end of file
+After training the model, user can run inference with `run_inference.py` in the `src/snraware/projects/mri/denoising` folder. Examples to run the model inference is given in the [README](../README.md).
\ No newline at end of file
diff --git a/justfile b/justfile
deleted file mode 100644
index 9e4f666..0000000
--- a/justfile
+++ /dev/null
@@ -1,29 +0,0 @@
-set shell := ['bash', '-ceuo', 'pipefail']
-
-@default: lint test
-
-@lint:
-    ruff check
-    ruff format --check
-    ruff check
-    pyright
-
-@test:
-    pytest
-
-@fix:
-    ruff check --fix
-    ruff format
-
-@build-package:
-    uv build
-
-@build-docs:
-    mkdocs build
-
-@serve-docs:
-    mkdocs serve
-
-@setup-env:
-    uv sync
-    direnv allow .
diff --git a/pyproject.toml b/pyproject.toml
index 51dcbd5..2ae7b86 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -3,15 +3,16 @@ name = "snraware"
 description = "A deep learning imaging AI framework"
 version = "0.1.0"
 readme = "README.md"
-requires-python = ">=3.12,<4.0"
+requires-python = ">=3.12,<=3.14"
 authors = [
     {name = "Hui Xue", email = "xueh@microsoft.com"},
 ]
 keywords = []
 license = "MIT"
 dependencies = [
-    "mkl-fft>=2.0.0",
-    "mkl-service>=2.4.2",
+    "mkl",
+    "mkl-fft",
+    "mkl-service",
     "typing_extensions",
     "click",
     "h5py",
@@ -78,15 +79,6 @@ build-backend = "uv_build"
 [tool.uv.build-backend]
 module-name = ["snraware"]
 
-[[tool.uv.index]]
-name = "mkl"
-url = "https://urob.github.io/numpy-mkl"
-
-[tool.uv.sources]
-numpy = { index = "mkl" }
-scipy = { index = "mkl" }
-mkl-service = { index = "mkl" }
-
 [project.scripts]
 
 [tool.pyright]
diff --git a/test/components/test_backbone_hrnet.py b/test/components/test_backbone_hrnet.py
index f5813e4..d521404 100644
--- a/test/components/test_backbone_hrnet.py
+++ b/test/components/test_backbone_hrnet.py
@@ -57,6 +57,9 @@ def test(self, backbone):
         with_timer = True
         device = get_device()
 
+        if device != "cuda":
+            pytest.skip("GPU only test")
+
         _B, C, T, H, W = 1, 2, 16, 16, 16
         test_in = torch.from_numpy(self.test_in).to(dtype=torch.float32, device=device)
         assert np.linalg.norm(self.test_in - test_in.cpu().numpy()) < 1e-3
diff --git a/test/components/test_backbone_soanet.py b/test/components/test_backbone_soanet.py
index 34690d5..4fae7fb 100644
--- a/test/components/test_backbone_soanet.py
+++ b/test/components/test_backbone_soanet.py
@@ -55,6 +55,8 @@ def teardown_class(self):
     def test(self, downsample, backbone):
         with_timer = True
         device = get_device()
+        if device != "cuda":
+            pytest.skip("GPU only test")
 
         _B, C, T, H, W = 1, 4, 8, 32, 32
         test_in = torch.from_numpy(self.test_in).to(dtype=torch.float32, device=device)
diff --git a/test/components/test_backbone_unet.py b/test/components/test_backbone_unet.py
index 60ab945..96d2e7e 100644
--- a/test/components/test_backbone_unet.py
+++ b/test/components/test_backbone_unet.py
@@ -55,6 +55,8 @@ def teardown_class(self):
     def test(self, backbone):
         with_timer = True
         device = get_device()
+        if device != "cuda":
+            pytest.skip("GPU only test")
 
         _B, C, T, H, W = 1, 2, 16, 32, 32
         test_in = torch.from_numpy(self.test_in).to(dtype=torch.float32, device=device)
diff --git a/test/components/test_block.py b/test/components/test_block.py
index 085a51a..cfbeeee 100644
--- a/test/components/test_block.py
+++ b/test/components/test_block.py
@@ -72,6 +72,9 @@ def test(self, block_str):
         test_in = torch.rand(B, T, C, H, W)
 
         device = get_device()
+        if device != "cuda":
+            pytest.skip("GPU only test")
+
         test_in = test_in.to(device=device, dtype=torch.float32)
         test_in = torch.permute(test_in, [0, 2, 1, 3, 4])
 
diff --git a/test/components/test_cell.py b/test/components/test_cell.py
index 73b2c68..f725365 100644
--- a/test/components/test_cell.py
+++ b/test/components/test_cell.py
@@ -31,6 +31,9 @@ def test(self):
         test_in = torch.rand(B, T, C, H, W).to(torch.float32)
 
         device = get_device()
+        if device != "cuda":
+            pytest.skip("GPU only test")
+
         test_in = test_in.to(device=device)
 
         att_types = [
diff --git a/test/components/test_convolution_module.py b/test/components/test_convolution_module.py
index d9de796..cef038e 100644
--- a/test/components/test_convolution_module.py
+++ b/test/components/test_convolution_module.py
@@ -39,6 +39,8 @@ def test(self):
 
         with_timer = True
         device = get_device()
+        if device != "cuda":
+            pytest.skip("GPU only test")
 
         test_in = torch.rand(B, T, C, H, W, device=device)
         assert np.linalg.norm(self.test_in - test_in.cpu().numpy()) < 1e-3
diff --git a/test/components/test_global_3d_attention.py b/test/components/test_global_3d_attention.py
index 356dd70..70133bd 100644
--- a/test/components/test_global_3d_attention.py
+++ b/test/components/test_global_3d_attention.py
@@ -29,6 +29,10 @@ def teardown_class(self):
 
     @pytest.mark.gpu
     def test(self):
+        device = get_device()
+        if device != "cuda":
+            pytest.skip("GPU only test")
+
         t = np.arange(256)
         t = np.reshape(t, (16, 16))
 
@@ -72,8 +76,6 @@ def test(self):
 
         with_timer = True
 
-        device = get_device()
-
         B, T, C, H1, W1 = 1, 16, 2, 64, 64
         C_out = 8
         test_in = torch.rand(B, T, C, H1, W1).to(device=device)
diff --git a/test/components/test_local_3d_attention.py b/test/components/test_local_3d_attention.py
index 1c7f005..a92756b 100644
--- a/test/components/test_local_3d_attention.py
+++ b/test/components/test_local_3d_attention.py
@@ -29,6 +29,10 @@ def teardown_class(self):
 
     @pytest.mark.gpu
     def test(self):
+        device = get_device()
+        if device != "cuda":
+            pytest.skip("GPU only test")
+
         t = np.arange(256)
         t = np.reshape(t, (16, 16))
 
@@ -72,8 +76,6 @@ def test(self):
 
         with_timer = True
 
-        device = get_device()
-
         B, T, C, H1, W1 = 1, 16, 2, 64, 64
         C_out = 8
         test_in = torch.rand(B, T, C, H1, W1).to(device=device)
diff --git a/test/components/test_spatial_global_attention.py b/test/components/test_spatial_global_attention.py
index d361c33..d4f12bf 100644
--- a/test/components/test_spatial_global_attention.py
+++ b/test/components/test_spatial_global_attention.py
@@ -29,7 +29,9 @@ def teardown_class(self):
 
     @pytest.mark.gpu
     def test(self):
-        print("Begin Testing")
+        device = get_device()
+        if device != "cuda":
+            pytest.skip("GPU only test")
 
         t = np.arange(256)
         t = np.reshape(t, (16, 16))
@@ -102,7 +104,6 @@ def test(self):
         stride_qks = [[1, 1]]
 
         with_timer = True
-        device = get_device()
 
         B, C, T, H1, W1 = 1, 2, 16, 64, 64
         C_out = 4
@@ -144,7 +145,7 @@ def test(self):
 
                                 fname = f"{attention_type}_{normalize_Q_K}_{att_with_output_proj}_{cosine_att}_{att_with_relative_position_bias}_{stride_qk}"
                                 gt_fname = os.path.join(self.data_root, f"test_out_{fname}.npy")
-                                np.save(gt_fname, test_out.detach().cpu().numpy())
+                                # np.save(gt_fname, test_out.detach().cpu().numpy())
                                 assert os.path.exists(gt_fname)
                                 test_out_gt = np.load(
                                     os.path.join(self.data_root, f"test_out_{fname}.npy")
diff --git a/test/components/test_spatial_local_attention.py b/test/components/test_spatial_local_attention.py
index 4912c4f..67d4632 100644
--- a/test/components/test_spatial_local_attention.py
+++ b/test/components/test_spatial_local_attention.py
@@ -26,7 +26,9 @@ def teardown_class(self):
 
     @pytest.mark.gpu
     def test(self):
-        print("Begin Testing")
+        device = get_device()
+        if device != "cuda":
+            pytest.skip("GPU only test")
 
         t = np.arange(256)
         t = np.reshape(t, (16, 16))
@@ -102,7 +104,6 @@ def test(self):
         stride_qks = [[1, 1], [2, 2]]
 
         with_timer = True
-        device = get_device()
 
         B, T, C, H1, W1 = 1, 4, 2, 64, 64
         C_out = 16
diff --git a/test/components/test_spatial_vit_attention.py b/test/components/test_spatial_vit_attention.py
index 5f07850..69d6769 100644
--- a/test/components/test_spatial_vit_attention.py
+++ b/test/components/test_spatial_vit_attention.py
@@ -29,7 +29,9 @@ def teardown_class(self):
 
     @pytest.mark.gpu
     def test(self):
-        print("Begin Testing")
+        device = get_device()
+        if device != "cuda":
+            pytest.skip("GPU only test")
 
         t = np.arange(256)
         t = np.reshape(t, (16, 16))
@@ -75,8 +77,6 @@ def test(self):
 
         with_timer = True
 
-        device = get_device()
-
         B, T, C, H1, W1 = 1, 16, 2, 32, 32
         C_out = 8
         test_in = torch.rand(B, T, C, H1, W1).to(device=device)
diff --git a/test/components/test_swin_3d_attention.py b/test/components/test_swin_3d_attention.py
index 7591ca5..ea60cac 100644
--- a/test/components/test_swin_3d_attention.py
+++ b/test/components/test_swin_3d_attention.py
@@ -30,6 +30,10 @@ def teardown_class(self):
 
     @pytest.mark.gpu
     def test(self):
+        device = get_device()
+        if device != "cuda":
+            pytest.skip("GPU only test")
+
         t = np.arange(256)
         t = np.reshape(t, (16, 16))
 
@@ -71,8 +75,6 @@ def test(self):
 
         with_timer = True
 
-        device = get_device()
-
         B, T, C, H1, W1 = 1, 16, 2, 32, 32
         C_out = 32
         test_in = torch.rand(B, T, C, H1, W1).to(device=device)
diff --git a/test/components/test_temporal_attention.py b/test/components/test_temporal_attention.py
index 33bb9d9..6cec977 100644
--- a/test/components/test_temporal_attention.py
+++ b/test/components/test_temporal_attention.py
@@ -28,13 +28,14 @@ def teardown_class(self):
 
     @pytest.mark.gpu
     def test(self):
-        print("Begin Testing")
+        device = get_device()
+        if device != "cuda":
+            pytest.skip("GPU only test")
 
         B, T, C, H, W = 2, 16, 3, 16, 16
         C_out = 32
 
         with_timer = True
-        device = get_device()
 
         test_in = torch.rand(B, T, C, H, W, device=device)
         assert np.linalg.norm(self.test_in - test_in.cpu().numpy()) < 1e-3
diff --git a/test/components/test_vit_3d_attention.py b/test/components/test_vit_3d_attention.py
index d3141d6..58c1ca1 100644
--- a/test/components/test_vit_3d_attention.py
+++ b/test/components/test_vit_3d_attention.py
@@ -29,7 +29,9 @@ def teardown_class(self):
 
     @pytest.mark.gpu
     def test_Vit3D(self):
-        print("Begin Testing")
+        device = get_device()
+        if device != "cuda":
+            pytest.skip("GPU only test")
 
         t = np.arange(256)
         t = np.reshape(t, (16, 16))
@@ -76,8 +78,6 @@ def test_Vit3D(self):
 
         with_timer = True
 
-        device = get_device()
-
         B, T, C, H1, W1 = 1, 16, 2, 32, 32
         C_out = 8
         test_in = torch.rand(B, T, C, H1, W1).to(device=device)
diff --git a/test/data/phantom/gmap.npy b/test/data/phantom/gmap.npy
new file mode 100644
index 0000000..3ef8026
--- /dev/null
+++ b/test/data/phantom/gmap.npy
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
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 size 1048704
diff --git a/test/data/spatial_global/test_out_lin_True_True_False_False_[1, 1].npy b/test/data/spatial_global/test_out_lin_True_True_False_False_[1, 1].npy
index 7e7aac8..3a268fc 100644
--- a/test/data/spatial_global/test_out_lin_True_True_False_False_[1, 1].npy	
+++ b/test/data/spatial_global/test_out_lin_True_True_False_False_[1, 1].npy	
@@ -1,3 +1,3 @@
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-oid sha256:113649a311e22e145f046e29f38bbdcc0fef14bb6be19e463784eb43c704eecb
+oid sha256:5c8b5d9738816ecf330d42fe6c9ee320bb51ba95d1600b28fb343f811061ebec
 size 1048704
diff --git a/test/data/spatial_global/test_out_lin_True_True_False_True_[1, 1].npy b/test/data/spatial_global/test_out_lin_True_True_False_True_[1, 1].npy
index 7ab744d..df1da86 100644
--- a/test/data/spatial_global/test_out_lin_True_True_False_True_[1, 1].npy	
+++ b/test/data/spatial_global/test_out_lin_True_True_False_True_[1, 1].npy	
@@ -1,3 +1,3 @@
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-oid sha256:203a87352a615084f8f68842c9b0c36e019263a70fd7b53cfd8bef94b075f72f
+oid sha256:28d5fae89c047380ea4cfc0cb9d2a18a9a49db3eb0c2dad2d7a0880664fd9efd
 size 1048704
diff --git a/test/data/spatial_global/test_out_lin_True_True_True_False_[1, 1].npy b/test/data/spatial_global/test_out_lin_True_True_True_False_[1, 1].npy
index 5675a35..204ff54 100644
--- a/test/data/spatial_global/test_out_lin_True_True_True_False_[1, 1].npy	
+++ b/test/data/spatial_global/test_out_lin_True_True_True_False_[1, 1].npy	
@@ -1,3 +1,3 @@
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-oid sha256:596b048683b944035a9530cfb54be973e2e1c22bb0534418de345247e2527ff2
+oid sha256:7b206f3df2faea393dd6edb0630e12b4af0d0482432e55c8c86a404b822abdf1
 size 1048704
diff --git a/test/data/spatial_global/test_out_lin_True_True_True_True_[1, 1].npy b/test/data/spatial_global/test_out_lin_True_True_True_True_[1, 1].npy
index 3a31f3b..423841d 100644
--- a/test/data/spatial_global/test_out_lin_True_True_True_True_[1, 1].npy	
+++ b/test/data/spatial_global/test_out_lin_True_True_True_True_[1, 1].npy	
@@ -1,3 +1,3 @@
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-oid sha256:bddf221f501f8398995006b20b900844909fc1580dd99966558ccb8431ad0c53
+oid sha256:7eb141e8f72040b5ded554efcdb608105a7c667d536bea35a4eec8fbb1e811e2
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diff --git a/test/test_e2e_mri_denoising.py b/test/test_e2e_mri_denoising.py
index 87e629f..6af39b5 100644
--- a/test/test_e2e_mri_denoising.py
+++ b/test/test_e2e_mri_denoising.py
@@ -7,7 +7,7 @@
 import torch
 from hydra import compose, initialize
 
-from snraware.components.setup import end_timer, start_timer
+from snraware.components.setup import end_timer, get_device, start_timer
 from snraware.projects.mri.denoising.inference_model import (
     load_lit_model,
     load_model,
@@ -126,6 +126,10 @@ def test_training(self, request):
         if "gpu" not in selected_markers or "slow" not in selected_markers:
             pytest.skip("Skipping because both markers 'gpu' and 'slow' are not set")
 
+        device = get_device()
+        if device != "cuda":
+            pytest.skip("GPU only test")
+
         with initialize(
             version_base=None, config_path="../src/snraware/projects/mri/denoising/configs"
         ):
@@ -167,6 +171,10 @@ def test_training_single_epoch(self, request):
         if os.path.exists(self.data_root) is False or os.path.exists(self.test_root) is False:
             pytest.skip("Skipping because test data not found")
 
+        device = get_device()
+        if device != "cuda":
+            pytest.skip("GPU only test")
+
         with initialize(
             version_base=None, config_path="../src/snraware/projects/mri/denoising/configs"
         ):
diff --git a/test/test_e2e_simple_regression.py b/test/test_e2e_simple_regression.py
index c79325d..50b784c 100644
--- a/test/test_e2e_simple_regression.py
+++ b/test/test_e2e_simple_regression.py
@@ -11,6 +11,7 @@
 from snraware.components.heads import PreConv2D, SimpleConv2d
 from snraware.components.model import HRnet, SOAnet, Unet
 from snraware.components.optim import OptimScheduler
+from snraware.components.setup import get_device
 
 # -----------------------------------------------------------------
 
@@ -217,6 +218,10 @@ def test_trainer(self, backbone, request):
         if "gpu" not in selected_markers:
             pytest.skip("Skipping because marker 'gpu' is not set")
 
+        device = get_device()
+        if device != "cuda":
+            pytest.skip("GPU only test")
+
         overrides = [
             f"backbone={backbone}",
             "backbone.block.cell.window_size=[4,4,1]",
diff --git a/uv.lock b/uv.lock
index 59f20d9..83b016b 100644
--- a/uv.lock
+++ b/uv.lock
@@ -1,6 +1,6 @@
 version = 1
 revision = 3
-requires-python = ">=3.12, <4.0"
+requires-python = ">=3.12, <=3.14"
 resolution-markers = [
     "sys_platform == 'darwin'",
     "platform_machine == 'aarch64' and sys_platform == 'linux'",
@@ -1393,25 +1393,25 @@ wheels = [
 [[package]]
 name = "intel-cmplr-lib-ur"
 version = "2025.3.0"
-source = { registry = "https://urob.github.io/numpy-mkl" }
+source = { registry = "https://pypi.org/simple" }
 dependencies = [
     { name = "umf" },
 ]
 wheels = [
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+    { url = "https://files.pythonhosted.org/packages/c7/a4/a7f61cc9beca3b6aba669381dfcaf3d36cd1f5f5f7716ba32ca091258c3d/intel_cmplr_lib_ur-2025.3.0-py2.py3-none-win_amd64.whl", hash = "sha256:4557a0281128e60628d9fcdca4ce38de40f13b32e8f4bf38ba82045f147c58e2", size = 1256187, upload-time = "2025-10-22T18:00:38.419Z" },
 ]
 
 [[package]]
 name = "intel-openmp"
 version = "2025.3.0"
-source = { registry = "https://urob.github.io/numpy-mkl" }
+source = { registry = "https://pypi.org/simple" }
 dependencies = [
     { name = "intel-cmplr-lib-ur" },
 ]
 wheels = [
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+    { url = "https://files.pythonhosted.org/packages/6a/87/68241d0b532f0e41d5b2928b640b00f9bb48945df9921df1d878f42c1d38/intel_openmp-2025.3.0-py2.py3-none-manylinux_2_28_x86_64.whl", hash = "sha256:948d9d6a22ed7643305a717c2ac2678bae8c11adafd5e4d30f903cf9933b4a60", size = 74331543, upload-time = "2025-10-22T17:59:28.77Z" },
+    { url = "https://files.pythonhosted.org/packages/79/69/05addedd727061b61a85b4fd989754edb628b5be1cd5d161727f98cf4d86/intel_openmp-2025.3.0-py2.py3-none-win_amd64.whl", hash = "sha256:8ff899d01a41b92ffe0e618b221ea633127d16df726086082d381c431c31339d", size = 32083814, upload-time = "2025-10-22T18:00:51.397Z" },
 ]
 
 [[package]]
@@ -2013,15 +2013,15 @@ wheels = [
 [[package]]
 name = "mkl"
 version = "2025.3.0"
-source = { registry = "https://urob.github.io/numpy-mkl" }
+source = { registry = "https://pypi.org/simple" }
 dependencies = [
     { name = "intel-openmp" },
     { name = "onemkl-license" },
     { name = "tbb" },
 ]
 wheels = [
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+    { url = "https://files.pythonhosted.org/packages/6d/b4/ef531295ed33b929c6c5214421eeebe370f1be22536b6956b4aaf18fdbc5/mkl-2025.3.0-py2.py3-none-manylinux_2_28_x86_64.whl", hash = "sha256:7b81f5d2e034637b187ca58666878c4e8889988a78e39e0b6ee92e846568f660", size = 195022935, upload-time = "2025-10-22T17:56:20.854Z" },
+    { url = "https://files.pythonhosted.org/packages/75/0e/b863a60889643e21d5d8d6b619f913703257878979b1df22d344a56276d0/mkl-2025.3.0-py2.py3-none-win_amd64.whl", hash = "sha256:2dbf81b016150c2ce418d80707dcce11d0e3c56f20e1d54813174e7665405561", size = 155530420, upload-time = "2025-10-22T17:57:46.918Z" },
 ]
 
 [[package]]
@@ -2042,17 +2042,15 @@ wheels = [
 [[package]]
 name = "mkl-service"
 version = "2.6.0"
-source = { registry = "https://urob.github.io/numpy-mkl" }
+source = { registry = "https://pypi.org/simple" }
 dependencies = [
     { name = "mkl" },
 ]
 wheels = [
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 [[package]]
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-dependencies = [
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