Repository: pytorch
Issue: Jit fail with TracingCheckError with tracing model with layers created after init.
Labels: oncall: jit

## 🐛 Bug

Jit fail with TracingCheckError with tracing model with layers created after init.

## To Reproduce

``` python
import torch
from torch import nn

class InputDepthAdapter(nn.Module):
    def __init__(self, channels):
        super().__init__()

        self.channels = channels

        self.reshape_conv_dict = nn.ModuleDict()

        self.inputs_list = None

    def adopt_depth(self, input):
        input_depth = input.shape[1]
        input_depth_name = str(input_depth)
        
        if input_depth_name not in self.reshape_conv_dict:
            reshape_conv = nn.Conv2d(
                                    input_depth,
                                    self.channels,
                                    kernel_size=1,
                                    stride=1,
                                    padding=0,
                                    )
            reshape_conv.to(input.device)
            self.reshape_conv_dict[input_depth_name] = reshape_conv
        
        reshape_conv = self.reshape_conv_dict[input_depth_name]
        return reshape_conv(input)

    def forward(self, input):
        input = self.adopt_depth(input)
        return input
    
model = InputDepthAdapter(10)
dummy_input1 = torch.randn(1, 3, 10, 10)

model(dummy_input1);
torch.jit.trace(model, dummy_input1)
```
```
TracingCheckError                         Traceback (most recent call last)
<ipython-input-7-25d3e20ac58b> in <module>()
     38 
     39 model(dummy_input1);
---> 40 torch.jit.trace(model, dummy_input1)

/opt/conda/lib/python3.6/site-packages/torch/jit/__init__.py in trace(func, example_inputs, optimize, check_trace, check_inputs, check_tolerance, _force_outplace)
    641             _check_trace(check_inputs, func, executor_options, module, check_tolerance, _force_outplace)
    642         else:
--> 643             _check_trace([example_inputs], func, executor_options, module, check_tolerance, _force_outplace)
    644 
    645     return module

/opt/conda/lib/python3.6/site-packages/torch/autograd/grad_mode.py in decorate_no_grad(*args, **kwargs)
     41         def decorate_no_grad(*args, **kwargs):
     42             with self:
---> 43                 return func(*args, **kwargs)
     44         return decorate_no_grad
     45 

/opt/conda/lib/python3.6/site-packages/torch/jit/__init__.py in _check_trace(check_inputs, func, executor_options, module, check_tolerance, force_outplace)
    543         diag_info = graph_diagnostic_info()
    544         if any(info is not None for info in diag_info):
--> 545             raise TracingCheckError(*diag_info)
    546 
    547 

TracingCheckError: Tracing failed sanity checks!
ERROR: Graphs differed across invocations!
	Graph diff:
		  graph(%input : Tensor
		        %1 : Tensor
		+       %2 : Tensor
		+       %3 : Tensor
		-       %2 : Tensor) {
		?        ^
		+       %4 : Tensor) {
		?        ^
		-   %tensor.2 : Tensor = prim::Constant[value=<Tensor>](), scope: InputDepthAdapter
		-   %4 : float = prim::Constant[value=-0.57735](), scope: InputDepthAdapter
		-   %5 : float = prim::Constant[value=0.57735](), scope: InputDepthAdapter
		?        ^^^^                         ^^^^^^^
		+   %5 : int = prim::Constant[value=1](), scope: InputDepthAdapter/Conv2d
		?        ^^                         ^                             +++++++
		-   %6 : Generator = prim::NoneGenerator(), scope: InputDepthAdapter
		-   %tensor.3 : Tensor = aten::uniform_(%tensor.2, %4, %5, %6), scope: InputDepthAdapter
		-   %tensor : Tensor = prim::Constant[value= 0.2530  0.3104 -0.2102  0.5556 -0.0427  0.4699  0.1543  0.2224 -0.5463 -0.4535 [ CPUFloatType{10} ]](), scope: InputDepthAdapter
		+   %6 : int = prim::Constant[value=1](), scope: InputDepthAdapter/Conv2d
		+   %7 : int[] = prim::ListConstruct(%5, %6), scope: InputDepthAdapter/Conv2d
		+   %8 : int = prim::Constant[value=0](), scope: InputDepthAdapter/Conv2d
		-   %9 : float = prim::Constant[value=-0.57735](), scope: InputDepthAdapter
		?        ^^^^                         - ------
		+   %9 : int = prim::Constant[value=0](), scope: InputDepthAdapter/Conv2d
		?        ^^                                                       +++++++
		+   %10 : int[] = prim::ListConstruct(%8, %9), scope: InputDepthAdapter/Conv2d
		-   %10 : float = prim::Constant[value=0.57735](), scope: InputDepthAdapter
		-   %11 : Generator = prim::NoneGenerator(), scope: InputDepthAdapter
		-   %12 : Tensor = aten::uniform_(%tensor, %9, %10, %11), scope: InputDepthAdapter
		-   %13 : int = prim::Constant[value=1](), scope: InputDepthAdapter/Conv2d
		?     ^
		+   %11 : int = prim::Constant[value=1](), scope: InputDepthAdapter/Conv2d
		?     ^
		-   %14 : int = prim::Constant[value=1](), scope: InputDepthAdapter/Conv2d
		?     ^
		+   %12 : int = prim::Constant[value=1](), scope: InputDepthAdapter/Conv2d
		?     ^
		-   %15 : int[] = prim::ListConstruct(%13, %14), scope: InputDepthAdapter/Conv2d
		?     ^                                 ^    ^
		+   %13 : int[] = prim::ListConstruct(%11, %12), scope: InputDepthAdapter/Conv2d
		?     ^                                 ^    ^
		+   %14 : bool = prim::Constant[value=0](), scope: InputDepthAdapter/Conv2d
		+   %15 : int = prim::Constant[value=0](), scope: InputDepthAdapter/Conv2d
		    %16 : int = prim::Constant[value=0](), scope: InputDepthAdapter/Conv2d
		-   %17 : int = prim::Constant[value=0](), scope: InputDepthAdapter/Conv2d
		-   %18 : int[] = prim::ListConstruct(%16, %17), scope: InputDepthAdapter/Conv2d
		?     ^                                 ^    ^
		+   %17 : int[] = prim::ListConstruct(%15, %16), scope: InputDepthAdapter/Conv2d
		?     ^                                 ^    ^
		-   %19 : int = prim::Constant[value=1](), scope: InputDepthAdapter/Conv2d
		?     ^
		+   %18 : int = prim::Constant[value=1](), scope: InputDepthAdapter/Conv2d
		?     ^
		-   %20 : int = prim::Constant[value=1](), scope: InputDepthAdapter/Conv2d
		?    ^^   ^^^                        ^
		+   %19 : bool = prim::Constant[value=0](), scope: InputDepthAdapter/Conv2d
		?    ^^   ^^^^                        ^
		-   %21 : int[] = prim::ListConstruct(%19, %20), scope: InputDepthAdapter/Conv2d
		-   %22 : bool = prim::Constant[value=0](), scope: InputDepthAdapter/Conv2d
		?     ^
		+   %20 : bool = prim::Constant[value=0](), scope: InputDepthAdapter/Conv2d
		?     ^
		-   %23 : int = prim::Constant[value=0](), scope: InputDepthAdapter/Conv2d
		-   %24 : int = prim::Constant[value=0](), scope: InputDepthAdapter/Conv2d
		-   %25 : int[] = prim::ListConstruct(%23, %24), scope: InputDepthAdapter/Conv2d
		-   %26 : int = prim::Constant[value=1](), scope: InputDepthAdapter/Conv2d
		-   %27 : bool = prim::Constant[value=0](), scope: InputDepthAdapter/Conv2d
		-   %28 : bool = prim::Constant[value=0](), scope: InputDepthAdapter/Conv2d
		-   %29 : bool = prim::Constant[value=1](), scope: InputDepthAdapter/Conv2d
		?     ^
		+   %21 : bool = prim::Constant[value=1](), scope: InputDepthAdapter/Conv2d
		?     ^
		-   %30 : Tensor = aten::_convolution(%input, %tensor.3, %12, %15, %18, %21, %22, %25, %26, %27, %28, %29), scope: InputDepthAdapter/Conv2d
		+   %22 : Tensor = aten::_convolution(%input, %3, %4, %7, %10, %13, %14, %17, %18, %19, %20, %21), scope: InputDepthAdapter/Conv2d
		-   return (%30);
		?            ^^
		+   return (%22);
		?            ^^
		  }
	First diverging operator:
	Node diff:
		- %tensor.2 : Tensor = prim::Constant[value=<Tensor>](), scope: InputDepthAdapter
		+ %5 : int = prim::Constant[value=1](), scope: InputDepthAdapter/Conv2d
	Trace source location:
		/opt/conda/lib/python3.6/site-packages/torch/nn/init.py(187): _calculate_fan_in_and_fan_out
		/opt/conda/lib/python3.6/site-packages/torch/nn/init.py(257): _calculate_correct_fan
		/opt/conda/lib/python3.6/site-packages/torch/nn/init.py(288): kaiming_uniform_
		/opt/conda/lib/python3.6/site-packages/torch/nn/modules/conv.py(47): reset_parameters
		/opt/conda/lib/python3.6/site-packages/torch/nn/modules/conv.py(43): __init__
		/opt/conda/lib/python3.6/site-packages/torch/nn/modules/conv.py(315): __init__
		<ipython-input-7-25d3e20ac58b>(24): adopt_depth
		<ipython-input-7-25d3e20ac58b>(33): forward
		/opt/conda/lib/python3.6/site-packages/torch/nn/modules/module.py(477): _slow_forward
		/opt/conda/lib/python3.6/site-packages/torch/nn/modules/module.py(487): __call__
		/opt/conda/lib/python3.6/site-packages/torch/jit/__init__.py(636): trace
		<ipython-input-7-25d3e20ac58b>(40): <module>
		/opt/conda/lib/python3.6/site-packages/IPython/core/interactiveshell.py(2963): run_code
		/opt/conda/lib/python3.6/site-packages/IPython/core/interactiveshell.py(2909): run_ast_nodes
		/opt/conda/lib/python3.6/site-packages/IPython/core/interactiveshell.py(2785): _run_cell
		/opt/conda/lib/python3.6/site-packages/IPython/core/interactiveshell.py(2662): run_cell
		/opt/conda/lib/python3.6/site-packages/ipykernel/zmqshell.py(537): run_cell
		/opt/conda/lib/python3.6/site-packages/ipykernel/ipkernel.py(208): do_execute
		/opt/conda/lib/python3.6/site-packages/ipykernel/kernelbase.py(399): execute_request
		/opt/conda/lib/python3.6/site-packages/ipykernel/kernelbase.py(233): dispatch_shell
		/opt/conda/lib/python3.6/site-packages/ipykernel/kernelbase.py(283): dispatcher
		/opt/conda/lib/python3.6/site-packages/tornado/stack_context.py(276): null_wrapper
		/opt/conda/lib/python3.6/site-packages/zmq/eventloop/zmqstream.py(432): _run_callback
		/opt/conda/lib/python3.6/site-packages/zmq/eventloop/zmqstream.py(480): _handle_recv
		/opt/conda/lib/python3.6/site-packages/zmq/eventloop/zmqstream.py(450): _handle_events
		/opt/conda/lib/python3.6/site-packages/tornado/stack_context.py(276): null_wrapper
		/opt/conda/lib/python3.6/site-packages/tornado/platform/asyncio.py(117): _handle_events
		/opt/conda/lib/python3.6/asyncio/events.py(145): _run
		/opt/conda/lib/python3.6/asyncio/base_events.py(1432): _run_once
		/opt/conda/lib/python3.6/asyncio/base_events.py(422): run_forever
		/opt/conda/lib/python3.6/site-packages/tornado/platform/asyncio.py(127): start
		/opt/conda/lib/python3.6/site-packages/ipykernel/kernelapp.py(486): start
		/opt/conda/lib/python3.6/site-packages/traitlets/config/application.py(658): launch_instance
		/opt/conda/lib/python3.6/site-packages/ipykernel_launcher.py(16): <module>
		/opt/conda/lib/python3.6/runpy.py(85): _run_code
		/opt/conda/lib/python3.6/runpy.py(193): _run_module_as_main
	Check source location:
		/opt/conda/lib/python3.6/site-packages/torch/nn/modules/conv.py(320): forward
		/opt/conda/lib/python3.6/site-packages/torch/nn/modules/module.py(477): _slow_forward
		/opt/conda/lib/python3.6/site-packages/torch/nn/modules/module.py(487): __call__
		<ipython-input-7-25d3e20ac58b>(30): adopt_depth
		<ipython-input-7-25d3e20ac58b>(33): forward
		/opt/conda/lib/python3.6/site-packages/torch/nn/modules/module.py(477): _slow_forward
		/opt/conda/lib/python3.6/site-packages/torch/nn/modules/module.py(487): __call__
		/opt/conda/lib/python3.6/site-packages/torch/jit/__init__.py(636): trace
		/opt/conda/lib/python3.6/site-packages/torch/jit/__init__.py(436): _check_trace
		/opt/conda/lib/python3.6/site-packages/torch/autograd/grad_mode.py(43): decorate_no_grad
		/opt/conda/lib/python3.6/site-packages/torch/jit/__init__.py(643): trace
		<ipython-input-7-25d3e20ac58b>(40): <module>
		/opt/conda/lib/python3.6/site-packages/IPython/core/interactiveshell.py(2963): run_code
		/opt/conda/lib/python3.6/site-packages/IPython/core/interactiveshell.py(2909): run_ast_nodes
		/opt/conda/lib/python3.6/site-packages/IPython/core/interactiveshell.py(2785): _run_cell
		/opt/conda/lib/python3.6/site-packages/IPython/core/interactiveshell.py(2662): run_cell
		/opt/conda/lib/python3.6/site-packages/ipykernel/zmqshell.py(537): run_cell
		/opt/conda/lib/python3.6/site-packages/ipykernel/ipkernel.py(208): do_execute
		/opt/conda/lib/python3.6/site-packages/ipykernel/kernelbase.py(399): execute_request
		/opt/conda/lib/python3.6/site-packages/ipykernel/kernelbase.py(233): dispatch_shell
		/opt/conda/lib/python3.6/site-packages/ipykernel/kernelbase.py(283): dispatcher
		/opt/conda/lib/python3.6/site-packages/tornado/stack_context.py(276): null_wrapper
		/opt/conda/lib/python3.6/site-packages/zmq/eventloop/zmqstream.py(432): _run_callback
		/opt/conda/lib/python3.6/site-packages/zmq/eventloop/zmqstream.py(480): _handle_recv
		/opt/conda/lib/python3.6/site-packages/zmq/eventloop/zmqstream.py(450): _handle_events
		/opt/conda/lib/python3.6/site-packages/tornado/stack_context.py(276): null_wrapper
		/opt/conda/lib/python3.6/site-packages/tornado/platform/asyncio.py(117): _handle_events
		/opt/conda/lib/python3.6/asyncio/events.py(145): _run
		/opt/conda/lib/python3.6/asyncio/base_events.py(1432): _run_once
		/opt/conda/lib/python3.6/asyncio/base_events.py(422): run_forever
		/opt/conda/lib/python3.6/site-packages/tornado/platform/asyncio.py(127): start
		/opt/conda/lib/python3.6/site-packages/ipykernel/kernelapp.py(486): start
		/opt/conda/lib/python3.6/site-packages/traitlets/config/application.py(658): launch_instance
		/opt/conda/lib/python3.6/site-packages/ipykernel_launcher.py(16): <module>
		/opt/conda/lib/python3.6/runpy.py(85): _run_code
		/opt/conda/lib/python3.6/runpy.py(193): _run_module_as_main

```
## Expected behavior

<!-- A clear and concise description of what you expected to happen. -->

## Environment

Please copy and paste the output from our
[environment collection script](https://raw.githubusercontent.com/pytorch/pytorch/master/torch/utils/collect_env.py)
(or fill out the checklist below manually).

You can get the script and run it with:
```
wget https://raw.githubusercontent.com/pytorch/pytorch/master/torch/utils/collect_env.py
# For security purposes, please check the contents of collect_env.py before running it.
python collect_env.py
```
PyTorch version: 1.0.1.post2
Is debug build: No
CUDA used to build PyTorch: 9.0.176

OS: Ubuntu 16.04.4 LTS
GCC version: (Ubuntu 5.4.0-6ubuntu1~16.04.10) 5.4.0 20160609
CMake version: version 3.11.1

Python version: 3.6
Is CUDA available: Yes
CUDA runtime version: 9.0.176
GPU models and configuration: 
GPU 0: GeForce GTX 1080
GPU 1: GeForce GTX 1080
GPU 2: GeForce GTX 1080
GPU 3: GeForce GTX 1080
GPU 4: GeForce GTX 1080
GPU 5: GeForce GTX 1080
GPU 6: GeForce GTX 1080
GPU 7: GeForce GTX 1080

Nvidia driver version: 410.78
cuDNN version: /usr/lib/x86_64-linux-gnu/libcudnn.so.7.1.4

Versions of relevant libraries:
[pip] numpy==1.14.3
[pip] numpydoc==0.8.0
[pip] torch==1.0.1.post2
[pip] torchvision==0.2.2.post3
[conda] blas                      1.0                         mkl  
[conda] magma-cuda90              2.5.0                         1    pytorch
[conda] mkl                       2018.0.2                      1  
[conda] mkl-include               2019.3                      199  
[conda] mkl-service               1.1.2            py36h17a0993_4  
[conda] mkl_fft                   1.0.1            py36h3010b51_0  
[conda] mkl_random                1.0.1            py36h629b387_0  
[conda] mkldnn                    0.13.0                        0    mingfeima
[conda] torch                     1.0.1.post2              pypi_0    pypi
[conda] torchvision               0.2.2.post3              pypi_0    pypi

## Code with setting layers to attributes doesn't work either.
```python
import torch
from torch import nn

class InputDepthAdapter(nn.Module):
    def __init__(self, channels):
        super().__init__()

        self.channels = channels

        #self.reshape_conv_dict = nn.ModuleDict()

        self.inputs_list = None

    def adopt_depth(self, input):
        input_depth = input.shape[1]
        input_depth_name = str(input_depth)
        
        #if input_depth_name not in self.reshape_conv_dict:
        if not hasattr(self, input_depth_name):
            reshape_conv = nn.Conv2d(
                                    input_depth,
                                    self.channels,
                                    kernel_size=1,
                                    stride=1,
                                    padding=0,
                                    )
            reshape_conv.to(input.device)
            #self.reshape_conv_dict[input_depth_name] = reshape_conv
            setattr(self, input_depth_name, reshape_conv)
        
        reshape_conv = getattr(self, input_depth_name)
        return reshape_conv(input)

    def forward(self, input):
        input = self.adopt_depth(input)
        return input
    
model = InputDepthAdapter(10)
dummy_input1 = torch.randn(1, 3, 10, 10)

model(dummy_input1);
torch.jit.trace(model, dummy_input1)
```

```
TracingCheckError: Tracing failed sanity checks!
ERROR: Graphs differed across invocations!
	Graph diff:
		  graph(%input : Tensor
		        %1 : Tensor
		+       %2 : Tensor
		+       %3 : Tensor
		-       %2 : Tensor) {
		?        ^
		+       %4 : Tensor) {
		?        ^
		-   %tensor.2 : Tensor = prim::Constant[value=<Tensor>](), scope: InputDepthAdapter
		-   %4 : float = prim::Constant[value=-0.57735](), scope: InputDepthAdapter
		-   %5 : float = prim::Constant[value=0.57735](), scope: InputDepthAdapter
		?        ^^^^                         ^^^^^^^
		+   %5 : int = prim::Constant[value=1](), scope: InputDepthAdapter/Conv2d[tensor(3)]
		?        ^^                         ^                             ++++++++++++++++++
		-   %6 : Generator = prim::NoneGenerator(), scope: InputDepthAdapter
		-   %tensor.3 : Tensor = aten::uniform_(%tensor.2, %4, %5, %6), scope: InputDepthAdapter
		-   %tensor : Tensor = prim::Constant[value= 0.0085  0.1566  0.0217 -0.5607 -0.1521 -0.4864  0.0343  0.2710  0.1833  0.2357 [ CPUFloatType{10} ]](), scope: InputDepthAdapter
		+   %6 : int = prim::Constant[value=1](), scope: InputDepthAdapter/Conv2d[tensor(3)]
		+   %7 : int[] = prim::ListConstruct(%5, %6), scope: InputDepthAdapter/Conv2d[tensor(3)]
		+   %8 : int = prim::Constant[value=0](), scope: InputDepthAdapter/Conv2d[tensor(3)]
		-   %9 : float = prim::Constant[value=-0.57735](), scope: InputDepthAdapter
		?        ^^^^                         - ------
		+   %9 : int = prim::Constant[value=0](), scope: InputDepthAdapter/Conv2d[tensor(3)]
		?        ^^                                                       ++++++++++++++++++
		+   %10 : int[] = prim::ListConstruct(%8, %9), scope: InputDepthAdapter/Conv2d[tensor(3)]
		-   %10 : float = prim::Constant[value=0.57735](), scope: InputDepthAdapter
		-   %11 : Generator = prim::NoneGenerator(), scope: InputDepthAdapter
		-   %12 : Tensor = aten::uniform_(%tensor, %9, %10, %11), scope: InputDepthAdapter
		-   %13 : int = prim::Constant[value=1](), scope: InputDepthAdapter/Conv2d[tensor(3)]
		?     ^
		+   %11 : int = prim::Constant[value=1](), scope: InputDepthAdapter/Conv2d[tensor(3)]
		?     ^
		-   %14 : int = prim::Constant[value=1](), scope: InputDepthAdapter/Conv2d[tensor(3)]
		?     ^
		+   %12 : int = prim::Constant[value=1](), scope: InputDepthAdapter/Conv2d[tensor(3)]
		?     ^
		-   %15 : int[] = prim::ListConstruct(%13, %14), scope: InputDepthAdapter/Conv2d[tensor(3)]
		?     ^                                 ^    ^
		+   %13 : int[] = prim::ListConstruct(%11, %12), scope: InputDepthAdapter/Conv2d[tensor(3)]
		?     ^                                 ^    ^
		+   %14 : bool = prim::Constant[value=0](), scope: InputDepthAdapter/Conv2d[tensor(3)]
		+   %15 : int = prim::Constant[value=0](), scope: InputDepthAdapter/Conv2d[tensor(3)]
		    %16 : int = prim::Constant[value=0](), scope: InputDepthAdapter/Conv2d[tensor(3)]
		-   %17 : int = prim::Constant[value=0](), scope: InputDepthAdapter/Conv2d[tensor(3)]
		-   %18 : int[] = prim::ListConstruct(%16, %17), scope: InputDepthAdapter/Conv2d[tensor(3)]
		?     ^                                 ^    ^
		+   %17 : int[] = prim::ListConstruct(%15, %16), scope: InputDepthAdapter/Conv2d[tensor(3)]
		?     ^                                 ^    ^
		-   %19 : int = prim::Constant[value=1](), scope: InputDepthAdapter/Conv2d[tensor(3)]
		?     ^
		+   %18 : int = prim::Constant[value=1](), scope: InputDepthAdapter/Conv2d[tensor(3)]
		?     ^
		-   %20 : int = prim::Constant[value=1](), scope: InputDepthAdapter/Conv2d[tensor(3)]
		?    ^^   ^^^                        ^
		+   %19 : bool = prim::Constant[value=0](), scope: InputDepthAdapter/Conv2d[tensor(3)]
		?    ^^   ^^^^                        ^
		-   %21 : int[] = prim::ListConstruct(%19, %20), scope: InputDepthAdapter/Conv2d[tensor(3)]
		-   %22 : bool = prim::Constant[value=0](), scope: InputDepthAdapter/Conv2d[tensor(3)]
		?     ^
		+   %20 : bool = prim::Constant[value=0](), scope: InputDepthAdapter/Conv2d[tensor(3)]
		?     ^
		-   %23 : int = prim::Constant[value=0](), scope: InputDepthAdapter/Conv2d[tensor(3)]
		-   %24 : int = prim::Constant[value=0](), scope: InputDepthAdapter/Conv2d[tensor(3)]
		-   %25 : int[] = prim::ListConstruct(%23, %24), scope: InputDepthAdapter/Conv2d[tensor(3)]
		-   %26 : int = prim::Constant[value=1](), scope: InputDepthAdapter/Conv2d[tensor(3)]
		-   %27 : bool = prim::Constant[value=0](), scope: InputDepthAdapter/Conv2d[tensor(3)]
		-   %28 : bool = prim::Constant[value=0](), scope: InputDepthAdapter/Conv2d[tensor(3)]
		-   %29 : bool = prim::Constant[value=1](), scope: InputDepthAdapter/Conv2d[tensor(3)]
		?     ^
		+   %21 : bool = prim::Constant[value=1](), scope: InputDepthAdapter/Conv2d[tensor(3)]
		?     ^
		-   %30 : Tensor = aten::_convolution(%input, %tensor.3, %12, %15, %18, %21, %22, %25, %26, %27, %28, %29), scope: InputDepthAdapter/Conv2d[tensor(3)]
		+   %22 : Tensor = aten::_convolution(%input, %3, %4, %7, %10, %13, %14, %17, %18, %19, %20, %21), scope: InputDepthAdapter/Conv2d[tensor(3)]
		-   return (%30);
		?            ^^
		+   return (%22);
		?            ^^
		  }
	First diverging operator:
	Node diff:
		- %tensor.2 : Tensor = prim::Constant[value=<Tensor>](), scope: InputDepthAdapter
		+ %5 : int = prim::Constant[value=1](), scope: InputDepthAdapter/Conv2d[tensor(3)]
	Trace source location:
		/opt/conda/lib/python3.6/site-packages/torch/nn/init.py(187): _calculate_fan_in_and_fan_out
		/opt/conda/lib/python3.6/site-packages/torch/nn/init.py(257): _calculate_correct_fan
		/opt/conda/lib/python3.6/site-packages/torch/nn/init.py(288): kaiming_uniform_
		/opt/conda/lib/python3.6/site-packages/torch/nn/modules/conv.py(47): reset_parameters
		/opt/conda/lib/python3.6/site-packages/torch/nn/modules/conv.py(43): __init__
		/opt/conda/lib/python3.6/site-packages/torch/nn/modules/conv.py(315): __init__
		<ipython-input-8-968b96d263cc>(25): adopt_depth
		<ipython-input-8-968b96d263cc>(35): forward
		/opt/conda/lib/python3.6/site-packages/torch/nn/modules/module.py(477): _slow_forward
		/opt/conda/lib/python3.6/site-packages/torch/nn/modules/module.py(487): __call__
		/opt/conda/lib/python3.6/site-packages/torch/jit/__init__.py(636): trace
		<ipython-input-8-968b96d263cc>(42): <module>
		/opt/conda/lib/python3.6/site-packages/IPython/core/interactiveshell.py(2963): run_code
		/opt/conda/lib/python3.6/site-packages/IPython/core/interactiveshell.py(2909): run_ast_nodes
		/opt/conda/lib/python3.6/site-packages/IPython/core/interactiveshell.py(2785): _run_cell
		/opt/conda/lib/python3.6/site-packages/IPython/core/interactiveshell.py(2662): run_cell
		/opt/conda/lib/python3.6/site-packages/ipykernel/zmqshell.py(537): run_cell
		/opt/conda/lib/python3.6/site-packages/ipykernel/ipkernel.py(208): do_execute
		/opt/conda/lib/python3.6/site-packages/ipykernel/kernelbase.py(399): execute_request
		/opt/conda/lib/python3.6/site-packages/ipykernel/kernelbase.py(233): dispatch_shell
		/opt/conda/lib/python3.6/site-packages/ipykernel/kernelbase.py(283): dispatcher
		/opt/conda/lib/python3.6/site-packages/tornado/stack_context.py(276): null_wrapper
		/opt/conda/lib/python3.6/site-packages/zmq/eventloop/zmqstream.py(432): _run_callback
		/opt/conda/lib/python3.6/site-packages/zmq/eventloop/zmqstream.py(480): _handle_recv
		/opt/conda/lib/python3.6/site-packages/zmq/eventloop/zmqstream.py(450): _handle_events
		/opt/conda/lib/python3.6/site-packages/tornado/stack_context.py(276): null_wrapper
		/opt/conda/lib/python3.6/site-packages/tornado/platform/asyncio.py(117): _handle_events
		/opt/conda/lib/python3.6/asyncio/events.py(145): _run
		/opt/conda/lib/python3.6/asyncio/base_events.py(1432): _run_once
		/opt/conda/lib/python3.6/asyncio/base_events.py(422): run_forever
		/opt/conda/lib/python3.6/site-packages/tornado/platform/asyncio.py(127): start
		/opt/conda/lib/python3.6/site-packages/ipykernel/kernelapp.py(486): start
		/opt/conda/lib/python3.6/site-packages/traitlets/config/application.py(658): launch_instance
		/opt/conda/lib/python3.6/site-packages/ipykernel_launcher.py(16): <module>
		/opt/conda/lib/python3.6/runpy.py(85): _run_code
		/opt/conda/lib/python3.6/runpy.py(193): _run_module_as_main
	Check source location:
		/opt/conda/lib/python3.6/site-packages/torch/nn/modules/conv.py(320): forward
		/opt/conda/lib/python3.6/site-packages/torch/nn/modules/module.py(477): _slow_forward
		/opt/conda/lib/python3.6/site-packages/torch/nn/modules/module.py(487): __call__
		<ipython-input-8-968b96d263cc>(32): adopt_depth
		<ipython-input-8-968b96d263cc>(35): forward
		/opt/conda/lib/python3.6/site-packages/torch/nn/modules/module.py(477): _slow_forward
		/opt/conda/lib/python3.6/site-packages/torch/nn/modules/module.py(487): __call__
		/opt/conda/lib/python3.6/site-packages/torch/jit/__init__.py(636): trace
		/opt/conda/lib/python3.6/site-packages/torch/jit/__init__.py(436): _check_trace
		/opt/conda/lib/python3.6/site-packages/torch/autograd/grad_mode.py(43): decorate_no_grad
		/opt/conda/lib/python3.6/site-packages/torch/jit/__init__.py(643): trace
		<ipython-input-8-968b96d263cc>(42): <module>
		/opt/conda/lib/python3.6/site-packages/IPython/core/interactiveshell.py(2963): run_code
		/opt/conda/lib/python3.6/site-packages/IPython/core/interactiveshell.py(2909): run_ast_nodes
		/opt/conda/lib/python3.6/site-packages/IPython/core/interactiveshell.py(2785): _run_cell
		/opt/conda/lib/python3.6/site-packages/IPython/core/interactiveshell.py(2662): run_cell
		/opt/conda/lib/python3.6/site-packages/ipykernel/zmqshell.py(537): run_cell
		/opt/conda/lib/python3.6/site-packages/ipykernel/ipkernel.py(208): do_execute
		/opt/conda/lib/python3.6/site-packages/ipykernel/kernelbase.py(399): execute_request
		/opt/conda/lib/python3.6/site-packages/ipykernel/kernelbase.py(233): dispatch_shell
		/opt/conda/lib/python3.6/site-packages/ipykernel/kernelbase.py(283): dispatcher
		/opt/conda/lib/python3.6/site-packages/tornado/stack_context.py(276): null_wrapper
		/opt/conda/lib/python3.6/site-packages/zmq/eventloop/zmqstream.py(432): _run_callback
		/opt/conda/lib/python3.6/site-packages/zmq/eventloop/zmqstream.py(480): _handle_recv
		/opt/conda/lib/python3.6/site-packages/zmq/eventloop/zmqstream.py(450): _handle_events
		/opt/conda/lib/python3.6/site-packages/tornado/stack_context.py(276): null_wrapper
		/opt/conda/lib/python3.6/site-packages/tornado/platform/asyncio.py(117): _handle_events
		/opt/conda/lib/python3.6/asyncio/events.py(145): _run
		/opt/conda/lib/python3.6/asyncio/base_events.py(1432): _run_once
		/opt/conda/lib/python3.6/asyncio/base_events.py(422): run_forever
		/opt/conda/lib/python3.6/site-packages/tornado/platform/asyncio.py(127): start
		/opt/conda/lib/python3.6/site-packages/ipykernel/kernelapp.py(486): start
		/opt/conda/lib/python3.6/site-packages/traitlets/config/application.py(658): launch_instance
		/opt/conda/lib/python3.6/site-packages/ipykernel_launcher.py(16): <module>
		/opt/conda/lib/python3.6/runpy.py(85): _run_code
		/opt/conda/lib/python3.6/runpy.py(193): _run_module_as_main

```