message: Removed numbers from text
diff: "\n",
  "Pseudo-code:\n",
  "\n",
  - " 1. *score = FC(tanh(FC(EO) + FC(H)))*\n",
  - " 2. *attention weights = softmax(score, axis = 1)*. Softmax by default is applied on the last axis but here we want to apply it on the *1st axis*, since the shape of score is *(batch_size, max_length, hidden_size)*. Max_length is the length of our input. Since we are trying to assign a weight to each input, softmax should be applied on that axis.\n",
  - " 3. *context vector = sum(attention weights * EO, axis = 1)*. Same reason as above for choosing axis as 1.\n",
  - " 4. *embedding output = The input to the decoder X is passed through an embedding layer.*\n",
  - " 5. *merged vector = concat(embedding output, context vector)*\n",
  - " 6. *This merged vector is then given to the GRU*\n",
  + " * score = FC(tanh(FC(EO) + FC(H)))*\n",
  + " * attention weights = softmax(score, axis = 1)*. Softmax by default is applied on the last axis but here we want to apply it on the *1st axis*, since the shape of score is *(batch_size, max_length, hidden_size)*. Max_length is the length of our input. Since we are trying to assign a weight to each input, softmax should be applied on that axis.\n",
  + " * context vector = sum(attention weights * EO, axis = 1)*. Same reason as above for choosing axis as 1.\n",
  + " * embedding output = The input to the decoder X is passed through an embedding layer.*\n",
  + " * merged vector = concat(embedding output, context vector)*\n",
  + " * This merged vector is then given to the GRU*\n",
  " \n",
  "The shapes of all the vectors at each step have been specified in the comments in the code.\n",
  " \n",
  