text: # Copyright 2020 IBM Corporation
  #
  # Licensed under the Apache License, Version 2.0 (the "License");
  # you may not use this file except in compliance with the License.
  # You may obtain a copy of the License at
  #
  # http://www.apache.org/licenses/LICENSE-2.0
  #
  # Unless required by applicable law or agreed to in writing, software
  # distributed under the License is distributed on an "AS IS" BASIS,
  # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
  # See the License for the specific language governing permissions and
  # limitations under the License.
  
  import lale.docstrings
  import lale.operators
  import autoai_libs.transformers.exportable
  
  class NumpyReplaceUnknownValuesImpl():
      def __init__(self, known_values_list=None, filling_values=None, missing_values_reference_list=None, 
                  filling_values_list=None):
          self._hyperparams = {
              'known_values_list': known_values_list,
              'filling_values': filling_values,
              'missing_values_reference_list': missing_values_reference_list,
              'filling_values_list': filling_values_list}
          self._wrapped_model = autoai_libs.transformers.exportable.NumpyReplaceUnknownValues(**self._hyperparams)
  
      def fit(self, X, y=None):
          self._wrapped_model.fit(X, y)
          return self
  
      def transform(self, X):
          return self._wrapped_model.transform(X)
  
  _hyperparams_schema = {
      'allOf': [{
          'description': 'This first object lists all constructor arguments with their types, but omits constraints for conditional hyperparameters.',
          'type': 'object',
          'additionalProperties': False,
          'required': ['known_values_list', 'filling_values', 'missing_values_reference_list', 'filling_values_list'],
          'relevantToOptimizer': [],
          'properties': {
              'known_values_list': {
                  'description': 'Reference list of lists of known values for each column.',
                  'anyOf': [
                  {   'type': 'array',
                      'items': {'laleType': 'Any'}},
                  {   'enum': [None]}],
                  'default': None},
              'filling_values': {
                  'description': 'Special value assigned to unknown values.',
                  'laleType': 'Any',
                  'default': None},
              'missing_values_reference_list': {
                  'description': 'Reference list of missing values.',
                  'anyOf': [
                  {   'type': 'array',
                      'items': {'laleType': 'Any'}},
                  {   'enum': [None]}],
                  'default': None},
              'filling_values_list': {
                  'description': 'list of special value assigned to unknown values.',
                  'anyOf': [
                  {   'type': 'array',
                      'items': {'laleType': 'Any'}},
                  {   'enum': [None]}],
                  'default': None}}}]}
  
  _input_fit_schema = {
      'type': 'object',
      'required': ['X'],
      'additionalProperties': False,
      'properties': {
          'X': {#Handles 1-D arrays as well
              'anyOf': [
                  {'type': 'array', 'items': {'laleType': 'Any'}},
                  {'type': 'array', 'items': {'type': 'array', 'items': {'laleType': 'Any'}}}]},
          'y': {
              'laleType': 'Any'}}}
  
  _input_transform_schema = {
      'type': 'object',
      'required': ['X'],
      'additionalProperties': False,
      'properties': {
          'X': {#Handles 1-D arrays as well
              'anyOf': [
                  {'type': 'array', 'items': {'laleType': 'Any'}},
                  {'type': 'array', 'items': {'type': 'array', 'items': {'laleType': 'Any'}}}]}}}
  
  _output_transform_schema = {
      'description': 'Features; the outer array is over samples.',
      'anyOf': [
          {'type': 'array', 'items': {'laleType': 'Any'}},
          {'type': 'array', 'items': {'type': 'array', 'items': {'laleType': 'Any'}}}]}
  
  _combined_schemas = {
      '$schema': 'http://json-schema.org/draft-04/schema#',
      'description': """Operator from `autoai_libs`_. Given a numpy array and a reference list of known values for each column, replaces values that are not part of a reference list with a special value (typically np.nan). This is typically used to remove labels for columns in a test dataset that have not been seen in the corresponding columns of the training dataset.
  
  .. _`autoai_libs`: https://pypi.org/project/autoai-libs""",
      'documentation_url': 'https://lale.readthedocs.io/en/latest/modules/lale.lib.autoai_libs.numpy_replace_unknown_values.html',
      'type': 'object',
      'tags': {
          'pre': [],
          'op': ['transformer'],
          'post': []},
      'properties': {
          'hyperparams': _hyperparams_schema,
          'input_fit': _input_fit_schema,
          'input_transform': _input_transform_schema,
          'output_transform': _output_transform_schema}}
  
  lale.docstrings.set_docstrings(NumpyReplaceUnknownValuesImpl, _combined_schemas)
  
  NumpyReplaceUnknownValues = lale.operators.make_operator(NumpyReplaceUnknownValuesImpl, _combined_schemas)
  