mindspore.ops.dropout

mindspore.ops.dropout(x, p=0.5, seed0=0, seed1=0)[source]

During training, randomly zeroes some of the elements of the input tensor with probability p from a Bernoulli distribution. It plays the role of reducing neuron correlation and avoid overfitting.

Parameters

x (Tensor) – The input of Dropout, a Tensor of any shape with data type of float16 or float32.
p (float, optional) – The dropping rate, between 0 and 1, e.g. p = 0.1, means dropping out 10% of input units. Default: 0.5.
seed0 (int, optional) – seed0 value for random generating. Default: 0.
seed1 (int, optional) – seed1 value for random generating. Default: 0.

Returns

output (Tensor) - With the same shape and data type as x.
mask (Tensor) - With the same shape as x.

Raises

TypeError – If p is not a float.
TypeError – If seed0 or seed1 is not an int.
TypeError – If dtype of x is neither float16 nor float32.
TypeError – If x is not a Tensor.

Supported Platforms:: Ascend GPU CPU

Examples

>>> x = Tensor(((20, 16), (50, 50)), mindspore.float32)
>>> output, mask = ops.dropout(x, p=0.5)
>>> print(output.shape)
(2, 2)