isclose¶
- paddle. isclose ( x, y, rtol=1e-05, atol=1e-08, equal_nan=False, name=None ) [source]
- 
         This operator checks if all \(x\) and \(y\) satisfy the condition: \[\left| x - y \right| \leq atol + rtol \times \left| y \right|\]elementwise, for all elements of \(x\) and \(y\). The behaviour of this operator is analogous to \(numpy.isclose\), namely that it returns \(True\) if two tensors are elementwise equal within a tolerance. - Parameters
- 
           - x (Tensor) – The input tensor, it’s data type should be float32, float64. 
- y (Tensor) – The input tensor, it’s data type should be float32, float64. 
- rtol (rtoltype, optional) – The relative tolerance. Default: \(1e-5\) . 
- atol (atoltype, optional) – The absolute tolerance. Default: \(1e-8\) . 
- equal_nan (equalnantype, optional) – If \(True\) , then two \(NaNs\) will be compared as equal. Default: \(False\) . 
- name (str, optional) – Name for the operation. For more information, please refer to Name. Default: None. 
 
- Returns
- 
           The output tensor, it’s data type is bool. 
- Return type
- 
           Tensor 
 Examples import paddle x = paddle.to_tensor([10000., 1e-07]) y = paddle.to_tensor([10000.1, 1e-08]) result1 = paddle.isclose(x, y, rtol=1e-05, atol=1e-08, equal_nan=False, name="ignore_nan") # [True, False] result2 = paddle.isclose(x, y, rtol=1e-05, atol=1e-08, equal_nan=True, name="equal_nan") # [True, False] x = paddle.to_tensor([1.0, float('nan')]) y = paddle.to_tensor([1.0, float('nan')]) result1 = paddle.isclose(x, y, rtol=1e-05, atol=1e-08, equal_nan=False, name="ignore_nan") # [True, False] result2 = paddle.isclose(x, y, rtol=1e-05, atol=1e-08, equal_nan=True, name="equal_nan") # [True, True] 
