class_docstr: Simple nn.Module to flatten each tensor of a batch of tensors.
class_docstr_tok: ["Simple","nn.Module","to","flatten","each","tensor","of","a","batch","of","tensors","."]
code: def forward(self, x):
      batch_size = x.shape[0]
      return x.view(batch_size, -1)
  
imports: from avalanche.benchmarks.utils import _make_taskaware_classification_dataset
  from avalanche.models.dynamic_modules import MultiTaskModule, DynamicModule
  import torch.nn
  from torch.nn.parallel import DistributedDataParallel
  from collections import OrderedDict
  from avalanche.benchmarks.scenarios import CLExperience
label_desc: Use image node_id 2 for calling the Flatten obj's underlying member method code with example usage: obj.forward(x) and returns: x