PyTorch torch.result_type Function
Pytorch torch Reference Manual
torch.result_typeis a function in PyTorch used to determine the result type of an operation. It accepts tensors or scalars as input and returns the data type that should be used after performing the relevant operation.
Function Definition
torch.result_type(tensor, scalar)
Parameter Description
tensor: input tensor or data typescalar: scalar value or another tensor
Usage Example
Example
import torch
# Create tensors of different types
a = torch.tensor([1, 2, 3], dtype=torch.float32)
b = torch.tensor([4, 5, 6], dtype=torch.float64)
# Get the result type
result_dtype = torch.result_type(a, b)
print("Result type of float32 and float64:", result_dtype)
# Using a scalar
c = torch.tensor([1, 2, 3], dtype=torch.int32)
result_dtype2 = torch.result_type(c, 1.5)
print("Result type of int32 and 1.5:", result_dtype2)
# Create tensors of different types
a = torch.tensor([1, 2, 3], dtype=torch.float32)
b = torch.tensor([4, 5, 6], dtype=torch.float64)
# Get the result type
result_dtype = torch.result_type(a, b)
print("Result type of float32 and float64:", result_dtype)
# Using a scalar
c = torch.tensor([1, 2, 3], dtype=torch.int32)
result_dtype2 = torch.result_type(c, 1.5)
print("Result type of int32 and 1.5:", result_dtype2)
The output result is:
float32 和 float64 的结果类型: torch.float64 int32 和 1.5 的结果类型: torch.float32
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