Bug with 2 convolution layers

[mkskeller]

When modifying the mpc_autograd_cnn example to have two convolutional layers as in the attached patch, I get the following error:

Traceback (most recent call last):
  File "/usr/lib/python3.8/multiprocessing/process.py", line 315, in _bootstrap
    self.run()
  File "/usr/lib/python3.8/multiprocessing/process.py", line 108, in run
    self._target(*self._args, **self._kwargs)
  File "~/CrypTen/examples/multiprocess_launcher.py", line 64, in _run_process
    run_process_fn(fn_args)
  File "~/CrypTen/examples/mpc_autograd_cnn/launcher.py", line 92, in _run_experiment
    run_mpc_autograd_cnn(
  File "~/CrypTen/examples/mpc_autograd_cnn/mpc_autograd_cnn.py", line 63, in run_mpc_autograd_cnn
    model = crypten.nn.from_pytorch(model_plaintext, dummy_input)
  File "~/CrypTen/crypten/nn/onnx_converter.py", line 45, in from_pytorch
    f = _from_pytorch_to_bytes(pytorch_model, dummy_input)
  File "~/CrypTen/crypten/nn/onnx_converter.py", line 106, in _from_pytorch_to_bytes
    _export_pytorch_model(f, pytorch_model, dummy_input)
  File "~/CrypTen/crypten/nn/onnx_converter.py", line 131, in _export_pytorch_model
    torch.onnx.export(pytorch_model, dummy_input, f, **kwargs)
  File "/usr/local/lib/python3.8/dist-packages/torch/onnx/__init__.py", line 271, in export
    return utils.export(model, args, f, export_params, verbose, training,
  File "/usr/local/lib/python3.8/dist-packages/torch/onnx/utils.py", line 88, in export
    _export(model, args, f, export_params, verbose, training, input_names, output_names,
  File "/usr/local/lib/python3.8/dist-packages/torch/onnx/utils.py", line 694, in _export
    _model_to_graph(model, args, verbose, input_names,
  File "/usr/local/lib/python3.8/dist-packages/torch/onnx/utils.py", line 457, in _model_to_graph
    graph, params, torch_out, module = _create_jit_graph(model, args,
  File "/usr/local/lib/python3.8/dist-packages/torch/onnx/utils.py", line 420, in _create_jit_graph
    graph, torch_out = _trace_and_get_graph_from_model(model, args)
  File "/usr/local/lib/python3.8/dist-packages/torch/onnx/utils.py", line 380, in _trace_and_get_graph_from_model
    torch.jit._get_trace_graph(model, args, strict=False, _force_outplace=False, _return_inputs_states=True)
  File "/usr/local/lib/python3.8/dist-packages/torch/jit/_trace.py", line 1139, in _get_trace_graph
    outs = ONNXTracedModule(f, strict, _force_outplace, return_inputs, _return_inputs_states)(*args, **kwargs)
  File "/usr/local/lib/python3.8/dist-packages/torch/nn/modules/module.py", line 889, in _call_impl
    result = self.forward(*input, **kwargs)
  File "/usr/local/lib/python3.8/dist-packages/torch/jit/_trace.py", line 125, in forward
    graph, out = torch._C._create_graph_by_tracing(
  File "/usr/local/lib/python3.8/dist-packages/torch/jit/_trace.py", line 116, in wrapper
    outs.append(self.inner(*trace_inputs))
  File "/usr/local/lib/python3.8/dist-packages/torch/nn/modules/module.py", line 887, in _call_impl
    result = self._slow_forward(*input, **kwargs)
  File "/usr/local/lib/python3.8/dist-packages/torch/nn/modules/module.py", line 860, in _slow_forward
    result = self.forward(*input, **kwargs)
  File "~/CrypTen/examples/mpc_autograd_cnn/mpc_autograd_cnn.py", line 177, in forward
    out = self.conv2(x)
  File "/usr/local/lib/python3.8/dist-packages/torch/nn/modules/module.py", line 887, in _call_impl
    result = self._slow_forward(*input, **kwargs)
  File "/usr/local/lib/python3.8/dist-packages/torch/nn/modules/module.py", line 860, in _slow_forward
    result = self.forward(*input, **kwargs)
  File "/usr/local/lib/python3.8/dist-packages/torch/nn/modules/conv.py", line 399, in forward
    return self._conv_forward(input, self.weight, self.bias)
  File "/usr/local/lib/python3.8/dist-packages/torch/nn/modules/conv.py", line 395, in _conv_forward
    return F.conv2d(input, weight, bias, self.stride,
RuntimeError: Given groups=1, weight of size [16, 16, 3, 3], expected input[1, 1, 28, 28] to have 16 channels, but got 1 channels instead

Is that a bug in CrypTen?

2conv.txt

[mkskeller]

There was mistake in the code.