4.6. Utils
The utils
module contains utility functions for the ConFIG algorithm.
Network Utility Functions¤
conflictfree.utils.get_para_vector
¤
get_para_vector(network) -> torch.Tensor
Returns the parameter vector of the given network.
Parameters:
Name | Type | Description | Default |
---|---|---|---|
network |
Module
|
The network for which to compute the gradient vector. |
required |
Returns:
Type | Description |
---|---|
Tensor
|
torch.Tensor: The parameter vector of the network. |
Source code in conflictfree/utils.py
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conflictfree.utils.apply_para_vector
¤
apply_para_vector(
network: torch.nn.Module, para_vec: torch.Tensor
) -> None
Applies a parameter vector to the network's parameters.
Parameters:
Name | Type | Description | Default |
---|---|---|---|
network |
Module
|
The network to apply the parameter vector to. |
required |
para_vec |
Tensor
|
The parameter vector to apply. |
required |
Source code in conflictfree/utils.py
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|
conflictfree.utils.get_gradient_vector
¤
get_gradient_vector(network) -> torch.Tensor
Returns the gradient vector of the given network.
Parameters:
Name | Type | Description | Default |
---|---|---|---|
network |
Module
|
The network for which to compute the gradient vector. |
required |
Returns:
Type | Description |
---|---|
Tensor
|
torch.Tensor: The gradient vector of the network. |
Source code in conflictfree/utils.py
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conflictfree.utils.apply_gradient_vector
¤
apply_gradient_vector(
network: torch.nn.Module, grad_vec: torch.Tensor
) -> None
Applies a gradient vector to the network's parameters.
Parameters:
Name | Type | Description | Default |
---|---|---|---|
network |
Module
|
The network to apply the gradient vector to. |
required |
grad_vec |
Tensor
|
The gradient vector to apply. |
required |
Source code in conflictfree/utils.py
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|
Math Utility Functions¤
conflictfree.utils.get_cos_similarity
¤
get_cos_similarity(
vector1: torch.Tensor, vector2: torch.Tensor
) -> torch.Tensor
Calculates the cosine angle between two vectors.
Parameters:
Name | Type | Description | Default |
---|---|---|---|
vector1 |
Tensor
|
The first vector. |
required |
vector2 |
Tensor
|
The second vector. |
required |
Returns:
Type | Description |
---|---|
Tensor
|
torch.Tensor: The cosine angle between the two vectors. |
Source code in conflictfree/utils.py
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|
conflictfree.utils.unit_vector
¤
unit_vector(
vector: torch.Tensor, warn_zero=False
) -> torch.Tensor
Compute the unit vector of a given tensor.
Parameters:
Name | Type | Description | Default |
---|---|---|---|
vector |
Tensor
|
The input tensor. |
required |
warn_zero |
bool
|
Whether to print a warning when the input tensor is zero. default: False |
False
|
Returns:
Type | Description |
---|---|
Tensor
|
torch.Tensor: The unit vector of the input tensor. |
Source code in conflictfree/utils.py
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|
Conflict Utility Functions¤
conflictfree.utils.estimate_conflict
¤
estimate_conflict(gradients: torch.Tensor) -> torch.Tensor
Estimates the degree of conflict of gradients.
Parameters:
Name | Type | Description | Default |
---|---|---|---|
gradients |
Tensor
|
A tensor containing gradients. |
required |
Returns:
Type | Description |
---|---|
Tensor
|
torch.Tensor: A tensor consistent of the dot products between the sum of gradients and each sub-gradient. |
Source code in conflictfree/utils.py
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|
Slice Selector Classes¤
conflictfree.utils.OrderedSliceSelector
¤
Selects a slice of the source sequence in order. Usually used for selecting loss functions/gradients/losses in momentum-based method if you want to update more tha one gradient in a single iteration.
Source code in conflictfree/utils.py
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|
__init__
¤
__init__()
Source code in conflictfree/utils.py
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|
select
¤
select(
n: int, source_sequence: Sequence
) -> Tuple[Sequence, Union[float, Sequence]]
Selects a slice of the source sequence in order.
Parameters:
Name | Type | Description | Default |
---|---|---|---|
n |
int
|
The length of the target slice. |
required |
source_sequence |
Sequence
|
The source sequence to select from. |
required |
Returns:
Type | Description |
---|---|
Tuple[Sequence, Union[float, Sequence]]
|
Tuple[Sequence,Union[float,Sequence]]: A tuple containing the indexes of the selected slice and the selected slice. |
Source code in conflictfree/utils.py
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|
conflictfree.utils.RandomSliceSelector
¤
Selects a slice of the source sequence randomly. Usually used for selecting loss functions/gradients/losses in momentum-based method if you want to update more tha one gradient in a single iteration.
Source code in conflictfree/utils.py
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|
select
¤
select(
n: int, source_sequence: Sequence
) -> Tuple[Sequence, Union[float, Sequence]]
Selects a slice of the source sequence randomly.
Parameters:
Name | Type | Description | Default |
---|---|---|---|
n |
int
|
The length of the target slice. |
required |
source_sequence |
Sequence
|
The source sequence to select from. |
required |
Returns:
Type | Description |
---|---|
Tuple[Sequence, Union[float, Sequence]]
|
Tuple[Sequence,Union[float,Sequence]]: A tuple containing the indexes of the selected slice and the selected slice. |
Source code in conflictfree/utils.py
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|
Others¤
conflictfree.utils.has_zero
¤
has_zero(lists: Sequence) -> bool
Check if any element in the list is zero.
Parameters:
Name | Type | Description | Default |
---|---|---|---|
lists |
Sequence
|
A list of elements. |
required |
Returns:
Name | Type | Description |
---|---|---|
bool |
bool
|
True if any element is zero, False otherwise. |
Source code in conflictfree/utils.py
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|