mindspore.common.initializer

Initializer for cell parameters.

• class mindspore.common.initializer.Initializer(**kwargs)[source]

• The base class of the initializer.

  • Parameters

  • kwargs (dict) – Keyword arguments for Initializer.

  • Returns

  • Array, assigned array.

• mindspore.common.initializer.initializer(init, shape=None, dtype=mindspore.float32)[source]

• Create and initialize a tensor.

  • Parameters

  • • init (Union__[Tensor, str, Initializer, numbers.Number]) – Initialize value.

    • shape (Union__[tuple, list, int]) – A list of integers, a tuple of integers or an integer as the shape ofoutput. Default: None.

    • dtype (mindspore.dtype) – The type of data in initialized tensor. Default: mstype.float32.

  • Returns

  • Tensor, initialized tensor.

Examples

Copy>>> tensor = initializer('ones', [1, 2, 3], mstype.float32)

• class mindspore.common.initializer.TruncatedNormal(sigma=0.01)[source]

• Initialize a truncated normal distribution which is a bounded normal distribution within N(low, high).

  • Parameters

  • sigma (float) – The sigma of the array. Default: 0.01.

  • Returns

  • Array, truncated normal array.

• class mindspore.common.initializer.Normal(sigma=0.01)[source]

• Initialize a normal array, and obtain values N(0, sigma) from the uniform distributionto fill the input tensor.

  • Parameters

  • sigma (float) – The sigma of the array. Default: 0.01.

  • Returns

  • Array, normal array.

• class mindspore.common.initializer.Uniform(scale=0.07)[source]

• Initialize a uniform array, and obtain values U(-scale, scale) from the uniform distributionto fill the input tensor.

  • Parameters

  • scale (float) – The scale of the array. Default: 0.07.

  • Returns

  • Array, uniform array.

• class mindspore.common.initializer.HeUniform(**kwargs)[source]
• Initialize the array with He kaiming uniform algorithm, and from a uniform distribution collect samples withinU[-boundary, boundary] where

where

is the number ofinput units in the weight tensor.

• Parameters

• arr (Array) – The array to be assigned.

• Returns

• Array, assigned array.

• class mindspore.common.initializer.XavierUniform(gain=1)[source]
• Initialize the array with xavier uniform algorithm, and from a uniform distribution collect samples withinU[-boundary, boundary] where

.

• Parameters

• gain (Array) – The array to be assigned. Default: 1.

• Returns

• Array, assigned array.

• class mindspore.common.initializer.One(**kwargs)[source]

• Initialize the array to one.

  • Parameters

  • arr (Array) – The array to be assigned.

  • Returns

  • Array, assigned array.

• class mindspore.common.initializer.Zero(**kwargs)[source]

• Initialize the array to zero.

  • Parameters

  • arr (Array) – The array to be assigned.

  • Returns

  • Array, assigned array.