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torch.div#

torch.div(input,other,*,rounding_mode=None,out=None)→Tensor#

Divides each element of the inputinput by the corresponding element ofother.

outi=inputiotheri\text{out}_i = \frac{\text{input}_i}{\text{other}_i}

Note

By default, this performs a “true” division like Python 3.See therounding_mode argument for floor division.

Supportsbroadcasting to a common shape,type promotion, and integer, float, and complex inputs.Always promotes integer types to the default scalar type.

Parameters

  • input (Tensor) – the dividend

  • other (Tensor orNumber) – the divisor

Keyword Arguments

  • rounding_mode (str,optional) –

    Type of rounding applied to the result:

    • None - default behavior. Performs no rounding and, if bothinput andother are integer types, promotes the inputs to the default scalar type.Equivalent to true division in Python (the/ operator) and NumPy’snp.true_divide.

    • "trunc" - rounds the results of the division towards zero.Equivalent to C-style integer division.

    • "floor" - rounds the results of the division down.Equivalent to floor division in Python (the// operator) and NumPy’snp.floor_divide.

  • out (Tensor,optional) – the output tensor.

Examples:

>>>x=torch.tensor([0.3810,1.2774,-0.2972,-0.3719,0.4637])>>>torch.div(x,0.5)tensor([ 0.7620,  2.5548, -0.5944, -0.7438,  0.9274])>>>a=torch.tensor([[-0.3711,-1.9353,-0.4605,-0.2917],...[0.1815,-1.0111,0.9805,-1.5923],...[0.1062,1.4581,0.7759,-1.2344],...[-0.1830,-0.0313,1.1908,-1.4757]])>>>b=torch.tensor([0.8032,0.2930,-0.8113,-0.2308])>>>torch.div(a,b)tensor([[-0.4620, -6.6051,  0.5676,  1.2639],        [ 0.2260, -3.4509, -1.2086,  6.8990],        [ 0.1322,  4.9764, -0.9564,  5.3484],        [-0.2278, -0.1068, -1.4678,  6.3938]])>>>torch.div(a,b,rounding_mode='trunc')tensor([[-0., -6.,  0.,  1.],        [ 0., -3., -1.,  6.],        [ 0.,  4., -0.,  5.],        [-0., -0., -1.,  6.]])>>>torch.div(a,b,rounding_mode='floor')tensor([[-1., -7.,  0.,  1.],        [ 0., -4., -2.,  6.],        [ 0.,  4., -1.,  5.],        [-1., -1., -2.,  6.]])