torch.utils.bottleneck

import torch
from torch.utils.bottleneck import bottleneck

model = YourModelDefinition()
inputs = torch.randn(batch_size, input_shape)

with bottleneck(mode='full'):
    outputs = model(inputs)
    loss = loss_function(outputs)
    loss.backward()

bottleneck.show_bottlenecks()

• bottleneck.show_bottlenecks() display a report highlighting the most time-consuming operations in your PyTorch code