class_docstr: Block that aggregations the operations in a residual block.
  
  Attributes:
    out_dim: Integer, number of filter in the convolution.
    norm_type: Object type of the norm to use.
    skip: Boolean, apply convolution in the skip connection.
    kernel_size: Integer, convolution kernel size.
    stride: Integer, stride used in the convolution.
    padding: String, padding type used in the convolution.
    name: String, name of the block.
class_docstr_tok: ["Block","that","aggregations","the","operations","in","a","residual","block",".","Attributes",":","out_dim",":","Integer",",","number","of","filter","in","the","convolution",".","norm_type",":","Object","type","of","the","norm","to","use",".","skip",":","Boolean",",","apply","convolution","in","the","skip","connection",".","kernel_size",":","Integer",",","convolution","kernel","size",".","stride",":","Integer",",","stride","used","in","the","convolution",".","padding",":","String",",","padding","type","used","in","the","convolution",".","name",":","String",",","name","of","the","block","."]
code: def call(self, inputs, **kwargs):
      x = self.conv_block(inputs)
      x = self.conv(x)
      x = self.norm(x)
      x_skip = self.skip(inputs)
      x = self.relu(x + x_skip)
      return x
  
file_path: graphics/tensorflow_graphics/projects/points_to_3Dobjects/networks/custom_blocks.py
imports: import tensorflow
label_desc: Use image node_id 2 for calling the ResidualBlock obj's underlying member method code with example usage: obj.call(inputs) and returns: x