Change parallel_do to parallel_executor. #833
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qingqing01
reviewed
Apr 13, 2018
fluid/ocr_recognition/ctc_train.py
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| add_arg('learning_rate', float, 1.0e-3, "Learning rate.") | ||
| add_arg('l2', float, 0.0004, "L2 regularizer.") | ||
| add_arg('max_clip', float, 10.0, "Max clip threshold.") | ||
| add_arg('min_clip', float, -10.0, "Min clip threshold.") |
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max_clip and min_clip are not removed.
fluid/ocr_recognition/ctc_train.py
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| add_arg('test_list', str, None, "The list file of training images." | ||
| "None means using the default test_list file of reader.") | ||
| add_arg('num_classes', int, None, "The number of classes." | ||
| "None means using the default num_classes from reader.") |
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如之前线下讨论，一些使用频率低的参数需要去掉。
fluid/ocr_recognition/ctc_train.py
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| def save_model(args, exe, pass_id, batch_id): | ||
| filename = "model_%05d_%d" % (pass_id, batch_id) | ||
| fluid.io.save_params(exe, dirname=args.save_model_dir, filename=filename) | ||
| print "Saved model to: %s/%s." %(args.save_model_dir, filename) |
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train_one_batch、test、save_model会被其他文件用到吗？如果没有，是不是放在 def train()里好些，这样也可以减少参数的传递，比如args, exe, test_reader等都不用传了。
… parallel_executor And some fix: 1. Remove some arguments 2. Rename 'inference' to 'infer' 3. Refine document
qingqing01
reviewed
Apr 20, 2018
| casted_label = fluid.layers.cast(x=label, dtype='int64') | ||
| error_evaluator = fluid.evaluator.EditDistance( | ||
| input=decoded_out, label=casted_label) | ||
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| # error_evaluator = None |
fluid/ocr_recognition/ctc_train.py
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| data_shape = data_reader.data_shape() | ||
| # define network | ||
| images = fluid.layers.data(name='pixel', shape=data_shape, dtype='float32') | ||
| label = fluid.layers.data( | ||
| name='label', shape=[1], dtype='int32', lod_level=1) | ||
| sum_cost, error_evaluator, inference_program, model_average = ctc_train_net( | ||
| images, label, args, num_classes) | ||
| # sys.exit(0) |
qingqing01
approved these changes
Apr 25, 2018
… parallel_executor
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