[GitHub] ThomasDelteil commented on a change in pull request #13735: update wavenet codes

[GitBox <gi...@apache.org>]

ThomasDelteil commented on a change in pull request #13735: update wavenet codes
URL: https://github.com/apache/incubator-mxnet/pull/13735#discussion_r250018491
 
 

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 File path: example/gluon/wavenet/trainer.py
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 @@ -0,0 +1,130 @@
+# Licensed to the Apache Software Foundation (ASF) under one
+# or more contributor license agreements.  See the NOTICE file
+# distributed with this work for additional information
+# regarding copyright ownership.  The ASF licenses this file
+# to you under the Apache License, Version 2.0 (the
+# "License"); you may not use this file except in compliance
+# with the License.  You may obtain a copy of the License at
+#
+#   http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing,
+# software distributed under the License is distributed on an
+# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+# KIND, either express or implied.  See the License for the
+# specific language governing permissions and limitations
+# under the License.
+"""
+Module: WaveNet trainer modulep
+"""
+import sys
+import numpy as np
+import mxnet as mx
+from mxnet import gluon, autograd, nd
+from tqdm import trange
+
+from models import WaveNet
+from utils import decode_mu_law
+from data_loader import load_wav, data_generation, data_generation_sample
+# pylint: disable=invalid-name, too-many-arguments, too-many-instance-attributes, no-member, no-self-use
+# set gpu count
+def setting_ctx(use_gpu):
+    """
+    Description : setting cpu/gpu
+    """
+    if eval(use_gpu):
+        ctx = mx.gpu()
+    else:
+        ctx = mx.cpu()
+    return ctx
+
+class Train():
+    """
+    Description : Trainer for WaveNet
+    """
+    def __init__(self, config):
+        ##setting hyper-parameters
+        self.batch_size = config.batch_size
+        self.epoches = config.epoches
+        self.mu = config.mu
+        self.n_residue = config.n_residue
+        self.n_skip = config.n_skip
+        self.dilation_depth = config.dilation_depth
+        self.n_repeat = config.n_repeat
+        self.seq_size = config.seq_size
+        self.use_gpu = config.use_gpu
+        self.ctx = setting_ctx(self.use_gpu)
+        self.build_model()
+
+    def build_model(self):
+        """
+        Description : module for building network
+        """
+        self.net = WaveNet(mu=self.mu, n_residue=self.n_residue, n_skip=self.n_skip,\
+         dilation_depth=self.dilation_depth, n_repeat=self.n_repeat)
+        #parameter initialization
+        self.net.collect_params().initialize(ctx=self.ctx)
+        #set optimizer
+        self.trainer = gluon.Trainer(self.net.collect_params(), optimizer='adam',\
+        optimizer_params={'learning_rate':0.01})
+        self.loss_fn = gluon.loss.SoftmaxCrossEntropyLoss()
+
+    def save_model(self, epoch, current_loss):
+        """
+        Description : module for saving network
+        """
+        filename = 'models/best_perf_epoch_'+str(epoch)+"_loss_"+str(current_loss)
+        self.net.save_params(filename)
+
+    def train(self):
+        """
+        Description : module for running train
+        """
+        fs, data = load_wav('parametric-2.wav')
 
 Review comment:
   why is this wavefile hardcoded?

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