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@ -1386,7 +1386,7 @@ def min(input, dim=None, keep_dim=False, out=None, name=None):
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return out
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def log1p(x, out=None, name=None):
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def log1p(x, name=None):
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"""
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:alias_main: paddle.log1p
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:alias: paddle.log1p,paddle.tensor.log1p,paddle.tensor.math.log1p
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@ -1396,9 +1396,6 @@ def log1p(x, out=None, name=None):
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Out = \\ln(x+1)
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Args:
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x (Variable): Input LoDTensor or Tensor. Must be one of the following types: float32, float64.
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out(Variable, optional): Optional output which can be any created
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Variable that meets the requirements to store the result of operation.
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if out is None, a new Varibale will be create to store the result.
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name(str, optional): The default value is None. Normally there is no need for
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user to set this property. For more information, please refer to :ref:`api_guide_Name`
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Returns:
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@ -1427,11 +1424,11 @@ def log1p(x, out=None, name=None):
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inputs = {'X': [x]}
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helper = LayerHelper('log1p', **locals())
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dtype = helper.input_dtype(input_param_name='x')
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if out is None:
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out = helper.create_variable_for_type_inference(dtype)
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out = helper.create_variable_for_type_inference(dtype)
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helper.append_op(type="log1p", inputs={"X": x}, outputs={"Out": out})
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return out
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def addcmul(input, tensor1, tensor2, value=1.0, out=None, name=None):
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"""
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:alias_main: paddle.addcmul
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