nn_utils_clip_grad_norm_: Clips gradient norm of an iterable of parameters.
In torch: Tensors and Neural Networks with 'GPU' Acceleration
View source: R/nn-utils-clip-grad.R
nn_utils_clip_grad_norm_ R Documentation
Clips gradient norm of an iterable of parameters.
Description
The norm is computed over all gradients together, as if they were
concatenated into a single vector. Gradients are modified in-place.
Usage
nn_utils_clip_grad_norm_(parameters, max_norm, norm_type = 2)
Arguments
parameters
(IterableTensor or Tensor): an iterable of Tensors or a
single Tensor that will have gradients normalized
max_norm
(float or int): max norm of the gradients
norm_type
(float or int): type of the used p-norm. Can be Inf for
infinity norm.
Value
Total norm of the parameters (viewed as a single vector).
torch documentation built on May 29, 2024, 9:54 a.m.
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View source: R/nn-utils-clip-grad.R
| nn_utils_clip_grad_norm_ | R Documentation |
Clips gradient norm of an iterable of parameters.
Description
The norm is computed over all gradients together, as if they were concatenated into a single vector. Gradients are modified in-place.
Usage
nn_utils_clip_grad_norm_(parameters, max_norm, norm_type = 2)
Arguments
parameters |
(IterableTensor or Tensor): an iterable of Tensors or a single Tensor that will have gradients normalized |
max_norm |
(float or int): max norm of the gradients |
norm_type |
(float or int): type of the used p-norm. Can be |
Value
Total norm of the parameters (viewed as a single vector).
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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