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#: ../source/paddlenlp.metrics.chunk.rst:2
msgid "chunk"
msgstr ""

#: of paddlenlp.metrics.chunk.ChunkEvaluator:1
msgid "基类：:class:`paddle.metric.metrics.Metric`"
msgstr ""

#: of paddlenlp.metrics.chunk.ChunkEvaluator:1
msgid ""
"ChunkEvaluator computes the precision, recall and F1-score for chunk "
"detection. It is often used in sequence tagging tasks, such as Named "
"Entity Recognition(NER)."
msgstr ""

#: of paddlenlp.metrics.chunk.ChunkEvaluator
#: paddlenlp.metrics.chunk.ChunkEvaluator.compute
#: paddlenlp.metrics.chunk.ChunkEvaluator.update
msgid "参数"
msgstr ""

#: of paddlenlp.metrics.chunk.ChunkEvaluator:4
msgid "The label list."
msgstr ""

#: of paddlenlp.metrics.chunk.ChunkEvaluator:6
msgid ""
"If set True, the label ends with '-B', '-I', '-E' or '-S', else the label"
" starts with them. Defaults to `False`."
msgstr ""

#: of paddlenlp.metrics.chunk.ChunkEvaluator:11
msgid "示例"
msgstr ""

#: of paddlenlp.metrics.chunk.ChunkEvaluator.compute:1
msgid "Computes the precision, recall and F1-score for chunk detection."
msgstr ""

#: of paddlenlp.metrics.chunk.ChunkEvaluator.compute:3
msgid "The valid length of every sequence, a tensor with shape `[batch_size]`"
msgstr ""

#: of paddlenlp.metrics.chunk.ChunkEvaluator.compute:5
msgid ""
"The predictions index, a tensor with shape `[batch_size, "
"sequence_length]`."
msgstr ""

#: of paddlenlp.metrics.chunk.ChunkEvaluator.compute:7
msgid "The labels index, a tensor with shape `[batch_size, sequence_length]`."
msgstr ""

#: of paddlenlp.metrics.chunk.ChunkEvaluator.compute:9
msgid ""
"Unnecessary parameter for compatibility with older versions with "
"parameters list `inputs`, `lengths`, `predictions`, `labels`. Defaults to"
" None."
msgstr ""

#: of paddlenlp.metrics.chunk.ChunkEvaluator.accumulate
#: paddlenlp.metrics.chunk.ChunkEvaluator.compute
msgid "返回"
msgstr ""

#: of paddlenlp.metrics.chunk.ChunkEvaluator.compute:12
msgid ""
"Returns tuple (`num_infer_chunks, num_label_chunks, num_correct_chunks`)."
"  With the fields:  - `num_infer_chunks` (Tensor):     The number of the "
"inference chunks.  - `num_label_chunks` (Tensor):     The number of the "
"label chunks.  - `num_correct_chunks` (Tensor):     The number of the "
"correct chunks."
msgstr ""

#: of paddlenlp.metrics.chunk.ChunkEvaluator.compute:12
msgid "Returns tuple (`num_infer_chunks, num_label_chunks, num_correct_chunks`)."
msgstr ""

#: of paddlenlp.metrics.chunk.ChunkEvaluator.compute:14
msgid "With the fields:"
msgstr ""

#: of paddlenlp.metrics.chunk.ChunkEvaluator.compute:17
msgid "`num_infer_chunks` (Tensor):"
msgstr ""

#: of paddlenlp.metrics.chunk.ChunkEvaluator.compute:17
msgid "The number of the inference chunks."
msgstr ""

#: of paddlenlp.metrics.chunk.ChunkEvaluator.compute:20
msgid "`num_label_chunks` (Tensor):"
msgstr ""

#: of paddlenlp.metrics.chunk.ChunkEvaluator.compute:20
msgid "The number of the label chunks."
msgstr ""

#: of paddlenlp.metrics.chunk.ChunkEvaluator.compute:22
msgid "`num_correct_chunks` (Tensor):"
msgstr ""

#: of paddlenlp.metrics.chunk.ChunkEvaluator.compute:23
msgid "The number of the correct chunks."
msgstr ""

#: of paddlenlp.metrics.chunk.ChunkEvaluator.accumulate
#: paddlenlp.metrics.chunk.ChunkEvaluator.compute
msgid "返回类型"
msgstr ""

#: of paddlenlp.metrics.chunk.ChunkEvaluator.update:1
msgid ""
"This function takes (num_infer_chunks, num_label_chunks, "
"num_correct_chunks) as input, to accumulate and update the corresponding "
"status of the ChunkEvaluator object. The update method is as follows:"
msgstr ""

#: of paddlenlp.metrics.chunk.ChunkEvaluator.update:4
msgid ""
"\\\\ \\begin{array}{l}{\\text { self. num_infer_chunks }+=\\text { "
"num_infer_chunks }} \\\\ {\\text { self. num_Label_chunks }+=\\text { "
"num_label_chunks }} \\\\ {\\text { self. num_correct_chunks }+=\\text { "
"num_correct_chunks }}\\end{array} \\\\\n"
"\n"
msgstr ""

#: of paddlenlp.metrics.chunk.ChunkEvaluator.update:7
msgid "The number of chunks in Inference on the given minibatch."
msgstr ""

#: of paddlenlp.metrics.chunk.ChunkEvaluator.update:9
msgid "The number of chunks in Label on the given mini-batch."
msgstr ""

#: of paddlenlp.metrics.chunk.ChunkEvaluator.update:11
msgid "The number of chunks both in Inference and Label on the given mini-batch."
msgstr ""

#: of paddlenlp.metrics.chunk.ChunkEvaluator.accumulate:1
msgid ""
"This function returns the mean precision, recall and f1 score for all "
"accumulated minibatches."
msgstr ""

#: of paddlenlp.metrics.chunk.ChunkEvaluator.accumulate:3
msgid "Returns tuple (`precision, recall, f1 score`)."
msgstr ""

#: of paddlenlp.metrics.chunk.ChunkEvaluator.reset:1
msgid "Reset function empties the evaluation memory for previous mini-batches."
msgstr ""

#: of paddlenlp.metrics.chunk.ChunkEvaluator.name:1
msgid "Return name of metric instance."
msgstr ""

