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""" |
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Paper: "UTRNet: High-Resolution Urdu Text Recognition In Printed Documents" presented at ICDAR 2023 |
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Authors: Abdur Rahman, Arjun Ghosh, Chetan Arora |
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GitHub Repository: https://github.com/abdur75648/UTRNet-High-Resolution-Urdu-Text-Recognition |
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Project Website: https://abdur75648.github.io/UTRNet/ |
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Copyright (c) 2023-present: This work is licensed under the Creative Commons Attribution-NonCommercial |
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4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/) |
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""" |
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import torch.nn as nn |
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import torch |
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import numpy as np |
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class dropout_layer(nn.Module): |
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def __init__(self,device): |
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super(dropout_layer, self).__init__() |
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self.device = device |
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def forward(self, input): |
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nums = (np.random.rand(input.shape[1]) > 0.2).astype (int) |
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dummy_array_output = torch.from_numpy(nums).to(self.device) |
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dummy_array_output_t = torch.reshape(dummy_array_output, (input.shape[1], 1)).to(self.device) |
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dummy_array_output_f = dummy_array_output_t.repeat(input.shape[0], 1,input.shape[2]).to(self.device) |
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output = input*dummy_array_output_f |
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return output |
