add chunk eval layer #6296
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add chunk eval layer #6296
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… trunk-evaluator
guoshengCS
reviewed
Dec 5, 2017
python/paddle/v2/fluid/layers.py
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| @@ -632,6 +632,40 @@ def accuracy(input, label, k=1, correct=None, total=None, **kwargs): | |||
| return acc_out | |||
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| def trunk_eval(input, | |||
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chunk_eval should be better.
| images = layers.data(name='pixel', shape=[784], dtype='float32') | ||
| label = layers.data(name='label', shape=[1], dtype='int32') | ||
| hidden = layers.fc(input=images, size=128) | ||
| crf = layers.linear_chain_crf( | ||
| input=hidden, label=label, param_attr=ParamAttr(name="crfw")) | ||
| crf_decode = layers.crf_decoding( | ||
| input=hidden, param_attr=ParamAttr(name="crfw")) | ||
| layers.trunk_eval( |
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chunk_eval might be better.
| @@ -173,10 +179,13 @@ def main(): | |||
| for data in train_data(): | |||
| outs = exe.run(fluid.default_main_program(), | |||
| feed=feeder.feed(data), | |||
| fetch_list=[avg_cost]) | |||
| fetch_list=[avg_cost, precision]) | |||
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Maybe recall and f1_score can also be added here.
| @@ -130,13 +130,19 @@ def test_word_embedding(self): | |||
| def test_linear_chain_crf(self): | |||
| program = Program() | |||
| with program_guard(program, startup_program=Program()): | |||
| label_dict_len = 10 | |||
| images = layers.data(name='pixel', shape=[784], dtype='float32') | |||
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I personally suggest using NLP related names rather than names for images here, but it has little effect.
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fix: #6280