I followed this previous thread 1 to measure how much memory is being allocated for the input tensor to my CNN. After applying the formula tensor.element_size() * tensor.nelement() I discovered that each example allocates 1.18 Mb. The dimension of this tensor is (batch_size, num_images, input_height, input_width, n_channels) = [1, 6, 128, 128, 3] and dtype is float32. These 6 images have a disk size from 4 to 7 Kb at most. It is normal that such an input tensor needs to allocates so much memory? Thx