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@ -268,10 +268,10 @@ class XavierUniform(Initializer):
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Initialize the array with xavier uniform algorithm, and from a uniform distribution collect samples within
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U[-boundary, boundary] The boundary is defined as :
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math:`boundary = gain * \sqrt{\frac{6}{n_{in} + n_{out}}}`.
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where :math:`boundary = gain * \sqrt{\frac{6}{n_{in} + n_{out}}}`.
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math:`n_{in}` is the number of input units in the weight tensor.
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math:`n_{out}` is the number of output units in the weight tensor.
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where :math:`n_{in}` is the number of input units in the weight tensor.
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where :math:`n_{out}` is the number of output units in the weight tensor.
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Args:
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gain (Array): The array to be assigned. Default: 1.
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@ -298,9 +298,9 @@ class HeUniform(Initializer):
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Initialize the array with He kaiming uniform algorithm, and from a uniform distribution collect samples within
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U[-boundary, boundary] The boundary is defined as :
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math:`boundary = \sqrt{\frac{6}{n_{in}}}`
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where :math:`boundary = \sqrt{\frac{6}{n_{in}}}`.
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math:`n_{in}` is the number of input units in the weight tensor.
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where :math:`n_{in}` is the number of input units in the weight tensor.
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Args:
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arr (Array): The array to be assigned.
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