- paddle. argmin ( x, axis=None, keepdim=False, dtype='int64', name=None )
Computes the indices of the min elements of the input tensor’s element along the provided axis.
x (Tensor) – An input N-D Tensor with type float32, float64, int16, int32, int64, uint8.
axis (int, optional) – Axis to compute indices along. The effective range is [-R, R), where R is x.ndim. when axis < 0, it works the same way as axis + R. Default is None, the input x will be into the flatten tensor, and selecting the min value index.
keepdim (bool, optional) – Whether to keep the given axis in output. If it is True, the dimensions will be same as input x and with size one in the axis. Otherwise the output dimentions is one fewer than x since the axis is squeezed. Default is False.
dtype (str, optional) – Data type of the output tensor which can be int32, int64. The default value is ‘int64’, and it will return the int64 indices.
name (str, optional) – For details, please refer to Name. Generally, no setting is required. Default: None.
Tensor, return the tensor of int32 if set
dtypeis int32, otherwise return the tensor of int64.
import paddle x = paddle.to_tensor([[5,8,9,5], [0,0,1,7], [6,9,2,4]]) out1 = paddle.argmin(x) print(out1) # 4 out2 = paddle.argmin(x, axis=0) print(out2) # [1, 1, 1, 2] out3 = paddle.argmin(x, axis=-1) print(out3) # [0, 0, 2] out4 = paddle.argmin(x, axis=0, keepdim=True) print(out4) # [[1, 1, 1, 2]]