ChunkEvaluator¶
- class paddle.fluid.evaluator. ChunkEvaluator ( input, label, chunk_scheme, num_chunk_types, excluded_chunk_types=None ) [source]
- 
         Warning: This would be deprecated in the future. Please use fluid.metrics.ChunkEvaluator instead. Accumulate counter numbers output by chunk_eval from mini-batches and compute the precision recall and F1-score using the accumulated counter numbers. For some basics of chunking, please refer to ‘Chunking with Support Vector Machines <https://aclanthology.info/pdf/N/N01/N01-1025.pdf>’. - Parameters
- 
           - input (Variable) – prediction output of the network. 
- label (Variable) – label of the test data set. 
- chunk_scheme (str) – can be IOB/IOE/IOBES and IO. See the chunk_eval op for details. 
- num_chunk_types (int) – the number of chunk type. 
- excluded_chunk_types (list) – A list including chunk type ids, indicating chunk types that are not counted. 
 
- Returns
- 
           tuple containing: precision, recall, f1_score 
- Return type
- 
           tuple 
 Examples exe = fluid.executor(place) evaluator = fluid.Evaluator.ChunkEvaluator(input, label) for epoch in PASS_NUM: evaluator.reset(exe) for data in batches: loss = exe.run(fetch_list=[cost]) distance, instance_error = distance_evaluator.eval(exe) - 
            
           eval
           (
           executor, 
           eval_program=None
           )
           eval¶
- 
           Evaluate the statistics merged by multiple mini-batches. :param executor: a executor for executing the eval_program :type executor: Executor|ParallelExecutor :param eval_program: a single Program for eval process :type eval_program: Program 
 - 
            
           reset
           (
           executor, 
           reset_program=None
           )
           reset¶
- 
           reset metric states at the begin of each pass/user specified batch - Parameters
- 
             - executor (Executor|ParallelExecutor) – a executor for executing the reset_program 
- reset_program (Program) – a single Program for reset process 
 
 
 
