mindspore.ops.max

mindspore.ops.max(input, axis=None, keepdims=False, *, initial=None, where=None)[source]

Calculates the maximum value along with the given axis for the input tensor. It returns the maximum values and indices.

Note

  • In auto_parallel and semi_auto_parallel mode, the first output index can not be used.

  • When axis is None, keepdims and subsequent parameters have no effect. At the same time, the index is fixed to return 0.

Warning

  • If there are multiple maximum values, the index of the first maximum value is used.

  • The value range of “axis” is [-dims, dims - 1]. “dims” is the dimension length of “input”.

Also see: mindspore.ops.ArgMaxWithValue.

Parameters

  • input (Tensor) – The input tensor, can be any dimension. Complex tensor is not supported for now.

  • axis (int) – The dimension to reduce. Default: 0.

  • keepdims (bool) – Whether to reduce dimension, if true, the output will keep same dimension with the input, the output will reduce dimension if false. Default: False.

Keyword Arguments

  • initial (scalar, optional) – The minimum value of an output element. Must be present to allow computation on empty slice. Default: None.

  • where (Tensor[bool], optional) – A Tensor indicating whether you need to replace the primitive value in ‘input’ with the initial value. If True, do not replace, if False, replace. The ‘where’ position is False and the corresponding ‘initial’ value must be provided. Default value: None, which indicates True by default.

Returns

tuple (Tensor), tuple of 2 tensors, containing the corresponding index and the maximum value of the input tensor.

  • values (Tensor) - The maximum value of input tensor, with the same shape as index, and same dtype as x.

  • index (Tensor) - The index for the maximum value of the input tensor, with dtype int32. If keepdims is true, the shape of output tensors is \((input_1, input_2, ..., input_{axis-1}, 1, input_{axis+1}, ..., input_N)\) . Otherwise, the shape is \((input_1, input_2, ..., input_{axis-1}, input_{axis+1}, ..., input_N)\) .

Raises
Supported Platforms:

Ascend GPU CPU

Examples

>>> x = Tensor(np.array([0.0, 0.4, 0.6, 0.7, 0.1]), mindspore.float32)
>>> output, index,  = ops.max(x, keepdims=True)
>>> print(output, index)
0.7 0