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Update pytorch_nn
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@@ -193,7 +193,6 @@ class DNNModelPytorch(Model):
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w_val_auto = w_val_auto.cuda()
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for step in range(self.max_steps):
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self.logger.info(step)
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if stop_steps >= self.early_stop_rounds:
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if verbose:
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self.logger.info("\tearly stop")
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@@ -201,7 +200,6 @@ class DNNModelPytorch(Model):
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loss = AverageMeter()
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self.dnn_model.train()
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self.train_optimizer.zero_grad()
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self.logger.info("INIT")
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choice = np.random.choice(train_num, self.batch_size)
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x_batch_auto = x_train_values[choice]
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