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"""Vanilla Neural Network for simple tests.
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Authors
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* Elena Rastorgueva 2020
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"""
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import paddle
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from paddlespeech.s2t.models.wav2vec2.modules import containers
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from paddlespeech.s2t.models.wav2vec2.modules import linear
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class VanillaNN(containers.Sequential):
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"""A simple vanilla Deep Neural Network.
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Arguments
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---------
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activation : paddle class
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A class used for constructing the activation layers.
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dnn_blocks : int
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The number of linear neural blocks to include.
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dnn_neurons : int
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The number of neurons in the linear layers.
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Example
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-------
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>>> inputs = paddle.rand([10, 120, 60])
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>>> model = VanillaNN(input_shape=inputs.shape)
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>>> outputs = model(inputs)
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>>> outputs.shape
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paddle.shape([10, 120, 512])
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"""
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def __init__(
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self,
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input_shape,
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activation=paddle.nn.LeakyReLU,
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dnn_blocks=2,
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dnn_neurons=512, ):
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super().__init__(input_shape=input_shape)
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for block_index in range(dnn_blocks):
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self.append(
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linear.Linear,
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n_neurons=dnn_neurons,
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bias=True,
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layer_name="linear", )
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self.append(activation(), layer_name="act")
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