Github user mengxr commented on a diff in the pull request:
https://github.com/apache/spark/pull/5601#discussion_r28750129
--- Diff: python/pyspark/ml/tuning.py ---
@@ -0,0 +1,84 @@
+#
+# Licensed to the Apache Software Foundation (ASF) under one or more
+# contributor license agreements. See the NOTICE file distributed with
+# this work for additional information regarding copyright ownership.
+# The ASF licenses this file to You 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.
+#
+
+__all__ = ['ParamGridBuilder']
+
+
+class ParamGridBuilder(object):
+ """
+ Builder for a param grid used in grid search-based model selection.
+ """
+
+ def __init__(self):
+ self._param_grid = {}
+
+ def addGrid(self, param, values):
+ """
+ Sets the given parameters in this grid to fixed values.
+ """
+ self._param_grid[param] = values
+
+ def baseOn(self, *args):
+ """
+ Sets the given parameters in this grid to fixed values.
+ Accepts either a parameter dictionary or a list of (parameter,
value) pairs.
+ """
+ if isinstance(args[0], dict):
+ self.baseOn(*args[0].items())
+ else:
+ for (param, value) in args:
+ self.addGrid(param, [value])
+
+ def build(self):
+ """
+ Builds and returns all combinations of parameters specified
+ by the param grid.
+ """
+ param_maps = [{}]
+ for (param, values) in self._param_grid.items():
+ new_param_maps = []
+ for value in values:
+ for old_map in param_maps:
+ copied_map = old_map.copy()
+ copied_map[param] = value
+ new_param_maps.append(copied_map)
+ param_maps = new_param_maps
+
+ return param_maps
+
+
+if __name__ == "__main__":
+ grid_test = ParamGridBuilder()
+ from classification import LogisticRegression
+ lr = LogisticRegression()
+ grid_test.addGrid(lr.regParam, [1.0, 2.0, 3.0])
+ grid_test.addGrid(lr.maxIter, [1, 5])
--- End diff --
Use builder pattern.
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