# -*- coding: utf-8 -*-
from xml.etree import cElementTree
from xml.etree.cElementTree import ParseError

if hasattr(cElementTree, 'ParseError'):
    _ETREE_EXCEPTIONS = (ParseError, AttributeError, ValueError, TypeError)
else:
    _ETREE_EXCEPTIONS = (SyntaxError, AttributeError, ValueError, TypeError)

_STS_NS = {'sts': 'https://sts.amazonaws.com/doc/2011-06-15/'}


class STSElement(object):

# See b/196254385 for more details.
try:
  if _tf_uses_legacy_keras:
    importlib.import_module("tf_keras.src.optimizers")
  else:
    importlib.import_module("keras.src.optimizers")
except (ImportError, AttributeError):
  pass

del importlib

# Delete modules that should be hidden from dir().
# Don't fail if these modules are not available.
# For e.g. this file will be originally placed under tensorflow/_api/v1 which

        if body_to_process is not None:
            try:
                value = body_to_process.get(get_validation_alias(field))
            # If the received body is a list, not a dict
            except AttributeError:
                errors.append(get_missing_field_error(loc))
                continue
        v_, errors_ = _validate_value_with_model_field(
            field=field, value=value, values=values, loc=loc
        )

*   `tf.keras.mixed_precision`
    *   When using mixed precision, calling `RMSprop.apply_gradients` or
        `Nadam.apply_gradients` outside a `tf.function` does not work and will
        raise the AttributeError "Tensor.op is meaningless when eager execution
        is enabled". See this
        [issue](https://github.com/tensorflow/tensorflow/issues/45536) for
        details and a workaround.