When I print batch , I get:
batch
[tensor([[[-0.0579,  0.0439,  0.0658,  …, -0.0565,  0.0413, -0.0023]],
     [[ 0.9421,  0.8119,  0.6808,  ...,  0.0039,  0.0252,  0.0431]],

     [[ 0.7007,  0.5435,  0.2290,  ..., -0.1226,  0.0346, -0.0850]],

     ...,

     [[ 0.9834,  0.4084,  0.5638,  ...,  0.0261, -0.0626,  0.0173]],

     [[ 0.8450,  1.0068,  0.9290,  ..., -0.0277,  0.0607,  0.0565]],

     [[ 1.0653,  0.6558,  0.4438,  ...,  0.0670,  0.1114, -0.0131]]]),

tensor([2, 3, 1, 1, 2, 3, 2, 4, 3, 1, 0, 2, 3, 0, 1, 2, 4, 2, 1, 2, 4, 1, 2, 0, 3, 1, 4, 2, 1, 4, 2, 3])]
Also on removing .text part:
from torchviz import make_dot
make_dot(m1(batch), params=dict(list(m1.named_parameters()))).render(“cnn_torchviz”, format=“png”)
I GET ERROR:
TypeError                                 Traceback (most recent call last)
 in 
1 from torchviz import make_dot
2
----> 3 make_dot(m1(batch), params=dict(list(m1.named_parameters()))).render(“cnn_torchviz”, format=“png”)
/opt/conda/lib/python3.7/site-packages/torch/nn/modules/module.py in _call_impl(self, *input, **kwargs)
725             result = self._slow_forward(*input, **kwargs)
726         else:
 → 727             result = self.forward(*input, **kwargs)
728         for hook in itertools.chain(
729                 _global_forward_hooks.values(),
 in forward(self, input)
36         #input = input.unsqueeze(1)
37         #input = input.unsqueeze(0)
—> 38         x = self.conv1(input)
39         x = self.conv2(x)
40         x = self.conv3(x)
/opt/conda/lib/python3.7/site-packages/torch/nn/modules/module.py in _call_impl(self, *input, **kwargs)
725             result = self._slow_forward(*input, **kwargs)
726         else:
 → 727             result = self.forward(*input, **kwargs)
728         for hook in itertools.chain(
729                 _global_forward_hooks.values(),
 in forward(self, input)
52         #print(“INPUT SHAPE SKIP”)
53         #print(input.shape)
—> 54         conv1 = self.conv_1(input)
55         x = self.normalization_1(conv1)
56         x = self.swish_1(x)
/opt/conda/lib/python3.7/site-packages/torch/nn/modules/module.py in _call_impl(self, *input, **kwargs)
725             result = self._slow_forward(*input, **kwargs)
726         else:
 → 727             result = self.forward(*input, **kwargs)
728         for hook in itertools.chain(
729                 _global_forward_hooks.values(),
/opt/conda/lib/python3.7/site-packages/torch/nn/modules/conv.py in forward(self, input)
257                             _single(0), self.dilation, self.groups)
258         return F.conv1d(input, self.weight, self.bias, self.stride,
 → 259                         self.padding, self.dilation, self.groups)
260
261
TypeError: conv1d(): argument ‘input’ (position 1) must be Tensor, not list