# Requirements for NumPy 1.x
numpy ~= 1.26.0
wheel ~= 0.41.2
h5py >= 3.10.0
lit ~= 17.0.2
opt_einsum == 3.3.0
astunparse == 1.6.3
dill == 0.3.7
astor == 0.7.1
typing_extensions == 4.8.0
gast == 0.4.0
termcolor == 2.3.0
wrapt == 1.16.0
tblib == 2.0.0
ml_dtypes >= 0.4.0, < 0.5.0
# Install tensorboard, and keras
# Note that here we want the latest version that matches TF major.minor version

fi
# Import tf nightly wheel built with numpy2 from PyPI in numpy1 env for testing.
# This aims to maintain TF compatibility with NumPy 1.x until 2025 b/361369076.
if [[ "$TFCI_WHL_NUMPY_VERSION" == 1 ]]; then
  # Uninstall tf nightly wheel built with numpy1.
  "$python" -m pip uninstall -y tf_nightly_numpy1
  # Install tf nightly cpu wheel built with numpy2.x from PyPI in numpy1.x env.
  "$python" -m pip install tf-nightly-cpu

# 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 == 4.8.0
gast == 0.4.0
termcolor == 2.3.0
wrapt == 1.16.0
tblib == 2.0.0
ml_dtypes >= 0.4.0, < 0.5.0
# Install tensorboard, and keras
# Note that here we want the latest version that matches TF major.minor version

  export TFCI_BUILD_PIP_PACKAGE_ARGS="$(echo $TFCI_BUILD_PIP_PACKAGE_ARGS | sed 's/tensorflow/tf_nightly/')"
fi

# TODO(b/361369076) Remove the following block after TF NumPy 1 is dropped
# Move hermetic requirement lock files for NumPy 1 to the root
if [[ "$TFCI_WHL_NUMPY_VERSION" == 1 ]]; then
  cp ./ci/official/requirements_updater/numpy1_requirements/*.txt .
fi

  PROFILE_JSON_PATH="$PROFILE_JSON_PATH/profile.json.gz"
else
  PROFILE_JSON_PATH="$TFCI_OUTPUT_DIR/profile.json.gz"
fi

# TODO(b/361369076) Remove the following block after TF NumPy 1 is dropped
# Move hermetic requirement lock files for NumPy 1 to the root
if [[ "$TFCI_WHL_NUMPY_VERSION" == 1 ]]; then
  cp ./ci/official/requirements_updater/numpy1_requirements/*.txt .
fi

if [[ $TFCI_PYCPP_SWAP_TO_BUILD_ENABLE == 1 ]]; then

      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: |

  }
  std::string value_string;
  if (!SummarizeValue(value_string).ok()) {
    value_string = "<error computing value>";
  }
  if (value_string.length() > 100) {
    // The default NumPy-style output can be distractingly long in error
    // messages.
    value_string = absl::StrCat(value_string.substr(0, 100), " [...]");
  }
  absl::Status s;
  const char* device_name = DeviceName(&s);
  if (!s.ok()) {

* TensorFlow now supports and is compiled with NumPy 2.0 by default. Please see the [NumPy 2 release notes](https://numpy.org/doc/stable/release/2.0.0-notes.html) and the [NumPy 2 migration guide](https://numpy.org/devdocs/numpy_2_0_migration_guide.html#numpy-2-migration-guide).

namex==0.0.8 \
    --hash=sha256:32a50f6c565c0bb10aa76298c959507abdc0e850efe085dc38f3440fcb3aa90b \
    --hash=sha256:7ddb6c2bb0e753a311b7590f84f6da659dd0c05e65cb89d519d54c0a250c0487
    # via keras-nightly
numpy==1.26.4 \
    --hash=sha256:03a8c78d01d9781b28a6989f6fa1bb2c4f2d51201cf99d3dd875df6fbd96b23b \
    --hash=sha256:08beddf13648eb95f8d867350f6a018a4be2e5ad54c8d8caed89ebca558b2818 \

namex==0.0.8 \
    --hash=sha256:32a50f6c565c0bb10aa76298c959507abdc0e850efe085dc38f3440fcb3aa90b \
    --hash=sha256:7ddb6c2bb0e753a311b7590f84f6da659dd0c05e65cb89d519d54c0a250c0487
    # via keras-nightly
numpy==1.26.4 \
    --hash=sha256:03a8c78d01d9781b28a6989f6fa1bb2c4f2d51201cf99d3dd875df6fbd96b23b \
    --hash=sha256:08beddf13648eb95f8d867350f6a018a4be2e5ad54c8d8caed89ebca558b2818 \