Document feedback

Question document fragment

When a question document fragment contains a formula, it is displayed as a space.

Submission type

issue

It's a little complicated...

I'd like to ask someone.

Please select the submission type

Problem type

Specifications and Common Mistakes

- Specifications and Common Mistakes:

- Misspellings or punctuation mistakes,incorrect formulas, abnormal display.

- Incorrect links, empty cells, or wrong formats.

- Chinese characters in English context.

- Minor inconsistencies between the UI and descriptions.

- Low writing fluency that does not affect understanding.

- Incorrect version numbers, including software package names and version numbers on the UI.

Usability

- Usability:

- Incorrect or missing key steps.

- Missing main function descriptions, keyword explanation, necessary prerequisites, or precautions.

- Ambiguous descriptions, unclear reference, or contradictory context.

- Unclear logic, such as missing classifications, items, and steps.

Correctness

- Correctness:

- Technical principles, function descriptions, supported platforms, parameter types, or exceptions inconsistent with that of software implementation.

- Incorrect schematic or architecture diagrams.

- Incorrect commands or command parameters.

- Incorrect code.

- Commands inconsistent with the functions.

- Wrong screenshots.

- Sample code running error, or running results inconsistent with the expectation.

Risk Warnings

- Risk Warnings:

- Lack of risk warnings for operations that may damage the system or important data.

Content Compliance

- Content Compliance:

- Contents that may violate applicable laws and regulations or geo-cultural context-sensitive words and expressions.

- Copyright infringement.

Please select the type of question

Problem description

Describe the bug so that we can quickly locate the problem.

Submit

Document feedback

mindspore.nn.WarmUpLR

class mindspore.nn.WarmUpLR(learning_rate, warmup_steps)

Gets learning rate warming up.

For current step, the formula of computing warmup learning rate is:

$$warmup\mathrm{\_}learning\mathrm{\_}rate=learning\mathrm{\_}rate\ast tmp\mathrm{\_}step/warmup\mathrm{\_}steps$$

Where

$$tmp\mathrm{\_}step=min(current\mathrm{\_}step,warmup\mathrm{\_}steps)$$

Parameters

• learning_rate (float) – The initial value of learning rate. The value of learning_rate must be greater than 0.

• warmup_steps (int) – The warm up steps of learning rate. The value of warmup_steps must be greater than or equal to 1.

Inputs:

• global_step (Tensor) - The current step number. Shape is $()$.

Outputs:

Tensor. The learning rate value for the current step with shape $()$.

Raises

• TypeError – If learning_rate is not a float.

• TypeError – If warmup_steps is not an int.

• ValueError – If warmup_steps is less than 1.

• ValueError – If learning_rate is less than or equal to 0.

Supported Platforms:

Ascend GPU CPU

Examples

>>> import mindspore
>>> from mindspore import Tensor, nn
>>>
>>> learning_rate = 0.1
>>> warmup_steps = 2
>>> global_step = Tensor(2, mindspore.int32)
>>> warmup_lr = nn.WarmUpLR(learning_rate, warmup_steps)
>>> lr = warmup_lr(global_step)
>>> net = nn.Dense(2, 3)
>>> optim = nn.SGD(net.trainable_params(), learning_rate=lr)