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import numpy as np
from pytorch_grad_cam.base_cam import BaseCAM
class RandomCAM(BaseCAM):
def __init__(self, model, target_layers, use_cuda=False,
reshape_transform=None):
super(
RandomCAM,
self).__init__(
model,
target_layers,
use_cuda,
reshape_transform)
def get_cam_weights(self,
input_tensor,
target_layer,
target_category,
activations,
grads):
return np.random.uniform(-1, 1, size=(grads.shape[0], grads.shape[1]))
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