def install_pip(self, package, save=True, save_dev=False):
        """Installs a pip package.

        :param save: if `True`, pins the package to the Hydrogen requirements
            YAML file.
        :param save_dev: if `True`, pins the package as a development
            dependency to the Hydrogen requirements YAML file.
        :param return: a **single** :class:`Requirement` object, representing
            the installed version of the given package.
        """
        requirement = Requirement.coerce(package)
        click.echo("pip install " + requirement.package)
        cmd = envoy.run("pip install {}".format(str(requirement)))
        if cmd.status_code == 0:
            installed_packages = get_installed_pypackages()
            package = installed_packages[requirement.package]
            requirement.version = "=={}".format(package.version)
            if save:
                self.requirements["all"].add(requirement)
            if save_dev:
                self.requirements["dev"].add(requirement)
            if save or save_dev:
                self.requirements.save()
            return requirement
        else:
            fatal(cmd.std_err)
def batch_norm(inputs, training, data_format, name=''):
  """Performs a batch normalization using a standard set of parameters."""
  # We set fused=True for a significant performance boost. See
  # https://www.tensorflow.org/performance/performance_guide#common_fused_ops
  return tf.compat.v1.layers.batch_normalization(
      inputs=inputs,
      axis=1 if data_format == 'channels_first' else 3,
      momentum=_BATCH_NORM_DECAY,
      epsilon=_BATCH_NORM_EPSILON,
      center=True,
      scale=True,
      training=training,
      fused=True,
      name=name)