Python bulk_extract_features示例

示例#1

 def from_positions_w_context(positions_w_context, is_test=False):
     positions, next_moves, results = zip(*positions_w_context)
     extracted_features = bulk_extract_features(positions)
     encoded_moves = make_onehot(next_moves)
     return DataSet(extracted_features,
                    encoded_moves,
                    results,
                    is_test=is_test)

示例#2

文件： policy.py 项目： winning1120xx/MuGo

 def run_many(self, positions):
     processed_positions = features.bulk_extract_features(positions)
     probabilities = self.session.run(self.output, feed_dict={self.x:processed_positions})
     return probabilities.reshape([-1, go.N, go.N])

示例#3

文件： load_data_sets.py 项目： lygztq/MuGo

 def from_positions_w_context(positions_w_context, is_test=False):
     positions, next_moves, results = zip(*positions_w_context)
     extracted_features = bulk_extract_features(positions)
     encoded_moves = make_onehot(next_moves)
     return DataSet(extracted_features, encoded_moves, results, is_test=is_test)

示例#4

文件： policy.py 项目： lygztq/MuGo

 def run_many(self, positions):
     processed_positions = features.bulk_extract_features(positions)
     probabilities = self.session.run(self.output, feed_dict={self.x:processed_positions})
     return probabilities.reshape([-1, go.N, go.N])