memory

Functions

`garbage_collection_cuda`	Garbage collection Torch (CUDA) memory.
`get_model_size_mb`	Calculates the size of a Module in megabytes.
`is_cuda_out_of_memory`	rtype `bool`
`is_cudnn_snafu`	rtype `bool`
`is_oom_error`	rtype `bool`
`is_out_of_cpu_memory`	rtype `bool`
`recursive_detach`	Detach all tensors in in_dict.

Utilities related to memory.

pytorch_lightning.utilities.memory.garbage_collection_cuda()[source]

Garbage collection Torch (CUDA) memory.

Return type: None

pytorch_lightning.utilities.memory.get_model_size_mb(model)[source]

Calculates the size of a Module in megabytes.

The computation includes everything in the state_dict(), i.e., by default the parameters and buffers.

Return type: float
Returns: Number of megabytes in the parameters of the input module.

pytorch_lightning.utilities.memory.recursive_detach(in_dict, to_cpu=False)[source]

Detach all tensors in in_dict.

May operate recursively if some of the values in in_dict are dictionaries which contain instances of Tensor. Other types in in_dict are not affected by this utility function.

Parameters

in_dict (Any) – Dictionary with tensors to detach
to_cpu (bool) – Whether to move tensor to cpu

Returns

Dictionary with detached tensors

Return type

out_dict