PyTorch is an open-source machine learning library developed by Facebook. It is used for deep neural network and natural language processing purposes.
The function torch.asin() provides support for the inverse sine function in PyTorch. It expects the input to be in the range [-1, 1] and gives the output in radian form. It returns nan if the input does not lie in the range [-1, 1]. The input type is tensor and if the input contains more than one element, element-wise inverse sine is computed.
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Syntax: torch.asin(x, out=None)
Parameters:Â
x: Input tensorÂ
name (optional): Output tensor
Return type: A tensor with the same type as that of x.Â
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Code #1:Â
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Python3
# Importing the PyTorch libraryimport torchÂ
# A constant tensor of size 6a = torch.FloatTensor([1.0, -0.5, 3.4, 0.2, 0.0, -2])print(a)Â
# Applying the inverse sin function and# storing the result in 'b'b = torch.asin(a)print(b) |
Output:Â
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tensor([ 1.0000, -0.5000, 3.4000, 0.2000, 0.0000, -2.0000]) tensor([ 1.5708, -0.5236, nan, 0.2014, 0.0000, nan])
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Code #2: VisualizationÂ
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Python3
# Importing the PyTorch libraryimport torchÂ
# Importing the NumPy libraryimport numpy as npÂ
# Importing the matplotlib.pyplot functionimport matplotlib.pyplot as pltÂ
# A vector of size 15 with values from -1 to 1a = np.linspace(-1, 1, 15)Â
# Applying the inverse sine function and# storing the result in 'b'b = torch.asin(torch.FloatTensor(a))Â
print(b)Â
# Plottingplt.plot(a, b.numpy(), color = 'red', marker = "o") plt.title("torch.asin") plt.xlabel("X") plt.ylabel("Y") Â
plt.show() |
Output:Â
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tensor([-1.5708, -1.0297, -0.7956, -0.6082, -0.4429, -0.2898, -0.1433, 0.0000,
0.1433, 0.2898, 0.4429, 0.6082, 0.7956, 1.0297, 1.5708])
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