The torch.tan ()
function provides support for the torch function in PyTorch. It expects input in radians, and output is in the range [-∞, ∞]. Input type — tensor, and if the input contains more than one element, the element-wise tangent is calculated.
Syntax : torch.tan (x, out = None)
Parameters : x : Input tensor name (optional): Output tensor
Return type : A tensor with the same type as that of x.
Code # 1:
# PyTorch library import
import
torch
# Constant tensor of size 6
a
=
torch.FloatTensor ([
1.0
,
-
0.5
,
3.4
,
-
2.1
,
0.0
,
-
6.5
])
print
(a)
# Apply the tanning function and
# save the result to & # 39; b & # 39;
b
=
torch.tan (a)
print
(b)
Exit :
1.0000 -0.5000 3.4000 -2.1000 0.0000 -6.5000 [torch.FloatTensor of size 6] 1.5574 -0.5463 0.2643 1.7098 0.0000 -0.2203 [torch.FloatTensor of size 6] Code # 2: Rendering
# Import PyTorch library
import
torch
# Import NumPy library
import
numpy as np
# Import matplotlib.pylot function
import
matplotlib.pyplot as plt
# Vector size 15 with values from -1 to 1
a
=
np.linspace (
-
1
,
1
,
15
)
# Applying a tangent function and
# save the result to & # 39; b & # 39;
b
=
torch.tan (torch.FloatTensor (a))
print
(b)
# Plot
plt.plot (a, b.numpy ( ), color
=
’red’
, marker
=
"o"
)
plt.title (
"torch.tan"
)
plt.xlabel (
"X"
)
plt.ylabel (
"Y"
)
plt.show ()
Output:
-1.5574 -1.1549 -0.8670 -0.6430 -0.4569 -0.2938 -0.1438 0.0000 0.1438 0.2938 0.4569 0.6430 0.8670 1.1549 1.5574 [torch.FloatTensor of size 15]
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