CODEWITHSUNDEEP
pytorch
user3668129
user3668129

Reputation: 4820

TypeError: ‘tuple’ object is not callable when using flatten layer

I Have the following model:

import torch
import torch.nn as nn
import torch.nn.functional as F

class MyModel(nn.Module):

def __init__(self, input_size, num_classes):
    super(MyModel, self).__init__()
    
    
    
    self.layer_1      = nn.Conv1d(1,   16,  3, bias=False, stride=2)
    self.activation_1 = F.relu       
    self.adap         = nn.AdaptiveAvgPool1d(1)
    self.flatten      = nn.Flatten          (),  
    
    self.layer_2      = torch.nn.Linear(2249, 500)
    self.activation_2 = F.relu
    self.layer_3      = torch.nn.Linear(500, 2)
   
    
    pass

def forward(self, x, labels=None):
    
    
    x = x.reshape(256, 1, -1)                        
    x = self.layer_1(x)     
    x = self.activation_1(x)            
    x = self.flatten(x)
    return x

When running torchinfo

model = MyModel(input_size=4500, num_classes=2)
torchinfo.summary(model, (256, 4500))

I’m Getting error:

Input In [101], in MyModel.forward(self, x, labels)
30 x = self.activation_1(x)
—> 31 x = self.flatten(x)
32 return x

TypeError: ‘tuple’ object is not callable
  1. What is wrong ?
  2. What do I need to change ?

Upvotes: 0

Views: 1089

Answers (1)

Ophir Yaniv
Ophir Yaniv

Reputation: 366

You have , at the end of the flatten line. please remove it

import torch
import torch.nn as nn
import torch.nn.functional as F

class MyModel(nn.Module):

    def __init__(self, input_size, num_classes):
        super(MyModel, self).__init__()

        self.layer_1      = nn.Conv1d(1,   16,  3, bias=False, stride=2)
        self.activation_1 = F.relu       
        self.adap         = nn.AdaptiveAvgPool1d(1)
        self.flatten      = nn.Flatten()  

        self.layer_2      = torch.nn.Linear(2249, 500)
        self.activation_2 = F.relu
        self.layer_3      = torch.nn.Linear(500, 2)


        pass

    def forward(self, x, labels=None):


        x = x.reshape(256, 1, -1)                        
        x = self.layer_1(x)     
        x = self.activation_1(x)            
        x = self.flatten(x)
        return x

Upvotes: 2

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