Get Model Summary with `torchsummary` pip Package
I am trying to get a good summary of my deep learning model like Keras summary function (can be found in here).
For that, what I have found is torch-summary pip package (details can be found here) is the best package I have found from this question.
My pytorch model is like this-
class DeepLearningModel(Module):
    # define model elements
    def __init__(self, n_inputs=34):
        super(DeepLearningModel, self).__init__()
        # input to first hidden layer
        self.hidden1 = Linear(n_inputs, 10)
        kaiming_uniform_(self.hidden1.weight, nonlinearity='relu')
        self.act1 = ReLU()
        # second hidden layer
        self.hidden2 = Linear(10, 8)
        kaiming_uniform_(self.hidden2.weight, nonlinearity='relu')
        self.act2 = ReLU()
        # third hidden layer and output
        self.hidden3 = Linear(8, 1)
        xavier_uniform_(self.hidden3.weight)
        self.act3 = Sigmoid()

    # forward propagate input
    def forward(self, X):
        # input to the first hidden layer
        X = self.hidden1(X)
        X = self.act1(X)
         # second hidden layer
        X = self.hidden2(X)
        X = self.act2(X)
        # third hidden layer and output
        X = self.hidden3(X)
        X = self.act3(X)
        return X

And to view the model's summary with the package, I am using this-
model_stats = summary(my_model, input_size=(1, 34, 8))

But for that, I am finding this error-
  Message=mat1 and mat2 shapes cannot be multiplied (68x8 and 34x10)
  Source=D:\Education\0. Research\1. Computer Science Knowledge Graph\Code\Terms Extractor\TermExtractor\BinaryClassifier\DeepLearningModel.py
  StackTrace:
  File &quot;D:\Education\0. Research\1. Computer Science Knowledge Graph\Code\Terms Extractor\TermExtractor\BinaryClassifier\DeepLearningModel.py&quot;, line 25, in forward (Current frame)
    X = self.hidden1(X)
  File &quot;D:\Education\0. Research\1. Computer Science Knowledge Graph\Code\Terms Extractor\TermExtractor\BinaryClassifier\DeepLearningClassifier.py&quot;, line 170, in printModel
    model_stats = summary(self.model, (1, 34, 8))
  File &quot;D:\Education\0. Research\1. Computer Science Knowledge Graph\Code\Terms Extractor\TermExtractor\BinaryClassifier\main-caller.py&quot;, line 11, in &lt;module&gt;
    model.printModel()


So, I am not sure what values should I put in the input_size parameter. Can anyone please help me find the issue or find my actual input shape for the model for getting a summary?

Linear expects the number of channels on the last axis of the input to be in_features.
model_stats = summary(my_model, input_size=(1, 8, 34))

