return labels.Everything(), nil
	}
	requirements := make([]labels.Requirement, 0, len(ps.MatchLabels)+len(ps.MatchExpressions))
	for k, v := range ps.MatchLabels {
		r, err := labels.NewRequirement(k, selection.Equals, []string{v})
		if err != nil {
			return nil, err
		}
		requirements = append(requirements, *r)
	}
	for _, expr := range ps.MatchExpressions {
		var op selection.Operator

          path: ${{ env.pythonLocation }}
          key: ${{ runner.os }}-python-docs-${{ env.pythonLocation }}-${{ hashFiles('pyproject.toml', 'requirements-docs.txt', 'requirements-docs-tests.txt') }}-v07
      - name: Install docs extras
        if: steps.cache.outputs.cache-hit != 'true'
        run: pip install -r requirements-docs.txt
      # Install MkDocs Material Insiders here just to put it in the cache for the rest of the steps

    /**
     * Let the toolchain decide if it matches requirements defined
     * in the toolchain plugin configuration.
     *
     * @param requirements key value pair, may not be {@code null}
     * @return {@code true} if the requirements match, otherwise {@code false}
     */
    boolean matchesRequirements(Map<String, String> requirements);

          key: ${{ runner.os }}-python-${{ env.pythonLocation }}-pydantic-v2-${{ hashFiles('pyproject.toml', 'requirements-tests.txt', 'requirements-docs-tests.txt') }}-test-v08
      - name: Install Dependencies
        if: steps.cache.outputs.cache-hit != 'true'
        run: pip install -r requirements-tests.txt
      - name: Install Pydantic v2
        run: pip install "pydantic>=2.0.2,<3.0.0"
      - name: Lint

#   limitations under the License.

FROM python:3.12.1-slim

WORKDIR /opt/microservices
COPY app.py ./
COPY requirements.txt ./

# install the dependencies and packages in the requirements file
RUN pip install --no-cache-dir --require-hashes -r requirements.txt

# old image had curl and could be used as a sample client if desired
RUN apt-get update \
  && apt-get install curl --no-install-recommends -y \

     * @see IsolatedAction for the requirements to isolated actions
     * @since 8.8
     */
    @Incubating
    void beforeProject(IsolatedAction<? super Project> action);

    /**
     * Adds an {@link IsolatedAction isolated action} to be called immediately after a project is evaluated.
     *
     * @param action The action to execute.
     * @see IsolatedAction for the requirements to isolated actions
     * @since 8.8

            .assertHasCause("No matching toolchain could be found in the locally installed toolchains or the configured toolchain download repositories. " +
                "Some toolchain resolvers had provisioning failures: custom (Unable to download toolchain matching the requirements " +

     * If error still persists then, apparently your CPU model does not support AVX instruction sets.
       * Refer [hardware requirements](https://www.tensorflow.org/install/pip#hardware-requirements).
   
   -----------------------------------------------------------------------------------------------
   
   **2. Installing **TensorFlow** (TF) CPU prebuilt binaries**
   
   

## Dependencies errors and return values

You can use the same dependency *functions* you use normally.

### Dependency requirements

They can declare request requirements (like headers) or other sub-dependencies:

=== "Python 3.9+"

    ```Python hl_lines="8  13"
    {!> ../../../docs_src/dependencies/tutorial006_an_py39.py!}
    ```

=== "Python 3.8+"

	// The semantics of the go.mod changed at Go 1.17 to support
	// graph pruning. If see a go.mod without a go line, we have to
	// assume Go 1.16 so that we interpret the requirements correctly.
	// Note that this default must stay at Go 1.16; it cannot be moved forward.
	DefaultGoModVersion = "1.16"

	// DefaultGoWorkVersion is the Go version to assume for go.work files