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