does branch mechanism has not been implemented yet？

[ymsdu2004]

Traceback (most recent call last): File "main_with_runtime.py", line 579, in <module> main() File "main_with_runtime.py", line 129, in main module = importlib.import_module(args.module) File "/opt/conda/lib/python3.6/importlib/__init__.py", line 126, in import_module return _bootstrap._gcd_import(name[level:], package, level) File "<frozen importlib._bootstrap>", line 994, in _gcd_import File "<frozen importlib._bootstrap>", line 971, in _find_and_load File "<frozen importlib._bootstrap>", line 955, in _find_and_load_unlocked File "<frozen importlib._bootstrap>", line 665, in _load_unlocked File "<frozen importlib._bootstrap_external>", line 678, in exec_module File "<frozen importlib._bootstrap>", line 219, in _call_with_frames_removed File "/home/admin/pipedream/runtime/image_classification/models/inceptionv3/gpus=2/__init__.py", line 1, in <module> from .inceptionv3 import Inceptionv3Partitioned File "/home/admin/pipedream/runtime/image_classification/models/inceptionv3/gpus=2/inceptionv3.py", line 2, in <module> from .stage0 import Stage0 File "/home/admin/pipedream/runtime/image_classification/models/inceptionv3/gpus=2/stage0.py", line 24 self.layer19 = torch.nn.Branch 3

here is generated stages's code， it seems not legal python code：

class Stage0(torch.nn.Module): def __init__(self): super(Stage0, self).__init__() self.layer2 = torch.nn.Conv2d(3, 32, kernel_size=(3, 3), stride=(2, 2), bias=False) self.layer3 = torch.nn.BatchNorm2d(32, eps=0.001, momentum=0.1, affine=True, track_running_stats=True) self.layer4 = torch.nn.ReLU(inplace=True) self.layer5 = torch.nn.Conv2d(32, 32, kernel_size=(3, 3), stride=(1, 1), bias=False) self.layer6 = torch.nn.BatchNorm2d(32, eps=0.001, momentum=0.1, affine=True, track_running_stats=True) self.layer7 = torch.nn.ReLU(inplace=True) self.layer8 = torch.nn.Conv2d(32, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False) self.layer9 = torch.nn.BatchNorm2d(64, eps=0.001, momentum=0.1, affine=True, track_running_stats=True) self.layer10 = torch.nn.ReLU(inplace=True) self.layer11 = torch.nn.MaxPool2d(kernel_size=3, stride=2, padding=0, dilation=1, ceil_mode=False) self.layer12 = torch.nn.Conv2d(64, 80, kernel_size=(1, 1), stride=(1, 1), bias=False) self.layer13 = torch.nn.BatchNorm2d(80, eps=0.001, momentum=0.1, affine=True, track_running_stats=True) self.layer14 = torch.nn.ReLU(inplace=True) self.layer15 = torch.nn.Conv2d(80, 192, kernel_size=(3, 3), stride=(1, 1), bias=False) self.layer16 = torch.nn.BatchNorm2d(192, eps=0.001, momentum=0.1, affine=True, track_running_stats=True) self.layer17 = torch.nn.ReLU(inplace=True) self.layer18 = torch.nn.MaxPool2d(kernel_size=3, stride=2, padding=0, dilation=1, ceil_mode=False) self.layer19 = torch.nn.Branch 3 self.layer20 = torch.nn.Branch 2 self.layer21 = torch.nn.Branch 1 self.layer22 = torch.nn.Branch 0 self.layer24 = torch.nn.Branch 7 self.layer25 = torch.nn.Branch 6 self.layer26 = torch.nn.Branch 5 self.layer27 = torch.nn.Branch 4 self.layer29 = torch.nn.Branch 9 self.layer30 = torch.nn.Branch 8 self.layer31 = torch.nn.Branch 11 self.layer32 = torch.nn.Branch 10 self.layer34 = torch.nn.MaxPool2d(kernel_size=3, stride=2, padding=0, dilation=1, ceil_mode=False) self.layer35 = torch.nn.Branch 13 self.layer36 = torch.nn.Branch 12

[deepakn94]

It seems that your profile has a module called Branch that PipeDream's code generator doesn't know how to code generate. Things should work if you put some logic in convert_graph_to_model.py to handle this.