# Requirements for NumPy 1.x
numpy ~= 1.26.0
wheel ~= 0.41.2
h5py >= 3.11.0
lit ~= 17.0.2
opt_einsum == 3.3.0
astunparse == 1.6.3
dill == 0.3.7
astor == 0.7.1
typing_extensions ~= 4.14.1
gast == 0.4.0
termcolor == 2.3.0
wrapt == 1.16.0
tblib == 2.0.0
ml_dtypes >= 0.5.1, < 0.6.0
auditwheel >= 6.1.0
# Install tensorboard, and keras
# Note that here we want the latest version that matches TF major.minor version

# Note that numpy 2.1.0 does not support python 3.9
numpy >= 2.0.0, < 2.2.0
wheel ~= 0.41.2
h5py >= 3.11.0
lit ~= 17.0.2
opt_einsum == 3.3.0
astunparse == 1.6.3
dill == 0.3.7
astor == 0.7.1
typing_extensions ~= 4.14.1
gast == 0.4.0
termcolor == 2.3.0
wrapt == 1.16.0
tblib == 2.0.0
ml_dtypes >= 0.5.1, < 0.6.0
auditwheel >= 6.1.0
# Install tensorboard, and keras

      - name: Checkout repository for releases (skipped for nightly)
        if: ${{ github.event_name == 'push' }}
        uses: actions/checkout@08c6903cd8c0fde910a37f88322edcfb5dd907a8 # v5.0.0
      - name: Build and test pip wheel
        shell: bash
        run: |
          is_nightly=0 && tf_project_name='tensorflow_cpu_aws' && ${{ github.event_name == 'schedule' }} && is_nightly=1 && tf_project_name='tf_nightly_cpu_aws'

# at the scripts of ci/official/ to see how TF's CI uses them.

# PYTHON TESTS run a suite of Python tests intended for verifying that the Python wheel
# will work properly. These are usually run Nightly or upon Release.
# CPU WHEEL
test:linux_cpu_wheel_test_filters --test_tag_filters=-no_oss,-tf_tosa,-oss_excluded,-oss_serial,-gpu,-tpu,-benchmark-test,-v1only,-no_oss_py38,-no_oss_py39,-no_oss_py310,-no_oss_py313

      with:
        python-version: "3.9"
    - name: Install Python dependencies
      run: |
        python -m pip install --upgrade pip
        pip install pylint==2.13.9 numpy wheel
    - name: Run PyLint on changed files
      run: |

werkzeug==3.1.3 \
    --hash=sha256:54b78bf3716d19a65be4fceccc0d1d7b89e608834989dfae50ea87564639213e \
    --hash=sha256:60723ce945c19328679790e3282cc758aa4a6040e4bb330f53d30fa546d44746
    # via tb-nightly
wheel==0.41.3 \
    --hash=sha256:488609bc63a29322326e05560731bf7bfea8e48ad646e1f5e40d366607de0942 \
    --hash=sha256:4d4987ce51a49370ea65c0bfd2234e8ce80a12780820d9dc462597a6e60d0841
    # via

werkzeug==3.1.3 \
    --hash=sha256:54b78bf3716d19a65be4fceccc0d1d7b89e608834989dfae50ea87564639213e \
    --hash=sha256:60723ce945c19328679790e3282cc758aa4a6040e4bb330f53d30fa546d44746
    # via tb-nightly
wheel==0.41.3 \
    --hash=sha256:488609bc63a29322326e05560731bf7bfea8e48ad646e1f5e40d366607de0942 \
    --hash=sha256:4d4987ce51a49370ea65c0bfd2234e8ce80a12780820d9dc462597a6e60d0841
    # via

werkzeug==3.1.3 \
    --hash=sha256:54b78bf3716d19a65be4fceccc0d1d7b89e608834989dfae50ea87564639213e \
    --hash=sha256:60723ce945c19328679790e3282cc758aa4a6040e4bb330f53d30fa546d44746
    # via tb-nightly
wheel==0.41.3 \
    --hash=sha256:488609bc63a29322326e05560731bf7bfea8e48ad646e1f5e40d366607de0942 \
    --hash=sha256:4d4987ce51a49370ea65c0bfd2234e8ce80a12780820d9dc462597a6e60d0841
    # via

werkzeug==3.1.3 \
    --hash=sha256:54b78bf3716d19a65be4fceccc0d1d7b89e608834989dfae50ea87564639213e \
    --hash=sha256:60723ce945c19328679790e3282cc758aa4a6040e4bb330f53d30fa546d44746
    # via tb-nightly
wheel==0.41.3 \
    --hash=sha256:488609bc63a29322326e05560731bf7bfea8e48ad646e1f5e40d366607de0942 \
    --hash=sha256:4d4987ce51a49370ea65c0bfd2234e8ce80a12780820d9dc462597a6e60d0841
    # via

werkzeug==3.1.3 \
    --hash=sha256:54b78bf3716d19a65be4fceccc0d1d7b89e608834989dfae50ea87564639213e \
    --hash=sha256:60723ce945c19328679790e3282cc758aa4a6040e4bb330f53d30fa546d44746
    # via tb-nightly
wheel==0.41.3 \
    --hash=sha256:488609bc63a29322326e05560731bf7bfea8e48ad646e1f5e40d366607de0942 \
    --hash=sha256:4d4987ce51a49370ea65c0bfd2234e8ce80a12780820d9dc462597a6e60d0841
    # via