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.Jenkinsfile 添加 shm-size 设置;test_seq2seq_model 调整训练参数
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@ -46,7 +46,7 @@ pipeline {
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agent {
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docker {
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image 'fnlp:torch-1.6'
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args '-u root:root -v ${JENKINS_HOME}/html/docs:/docs -v ${JENKINS_HOME}/html/_ci:/ci --gpus all'
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args '-u root:root -v ${JENKINS_HOME}/html/docs:/docs -v ${JENKINS_HOME}/html/_ci:/ci --gpus all --shm-size 1G'
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}
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}
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steps {
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@ -62,7 +62,7 @@ pipeline {
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agent {
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docker {
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image 'fnlp:paddle'
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args '-u root:root -v ${JENKINS_HOME}/html/docs:/docs -v ${JENKINS_HOME}/html/_ci:/ci --gpus all'
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args '-u root:root -v ${JENKINS_HOME}/html/docs:/docs -v ${JENKINS_HOME}/html/_ci:/ci --gpus all --shm-size 1G'
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}
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}
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steps {
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@ -82,7 +82,7 @@ pipeline {
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// agent {
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// docker {
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// image 'fnlp:jittor'
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// args '-u root:root -v ${JENKINS_HOME}/html/docs:/docs -v ${JENKINS_HOME}/html/_ci:/ci --gpus all'
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// args '-u root:root -v ${JENKINS_HOME}/html/docs:/docs -v ${JENKINS_HOME}/html/_ci:/ci --gpus all --shm-size 1G'
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// }
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// }
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// steps {
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@ -25,11 +25,11 @@ def prepare_env():
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def train_model(model, src_words_idx, tgt_words_idx, tgt_seq_len, src_seq_len):
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optimizer = optim.Adam(model.parameters(), lr=1e-2)
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optimizer = optim.Adam(model.parameters(), lr=5e-3)
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mask = seq_len_to_mask(tgt_seq_len).eq(0)
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target = tgt_words_idx.masked_fill(mask, -100)
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for i in range(100):
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for i in range(50):
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optimizer.zero_grad()
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pred = model(src_words_idx, tgt_words_idx, src_seq_len)['pred'] # bsz x max_len x vocab_size
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loss = F.cross_entropy(pred.transpose(1, 2), target)
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