Fairseq Random Sentence Generator

This function uses the Fairseq library's model and dictionary to generate a random sentence. First, it initializes the model, then it creates a random input sequence, uses the model to generate the output sequence, and finally converts the generated token sequence to a string.

Technology Stack : Fairseq, PyTorch, Dictionary

Code Type : Fairseq model random sentence generation

Code Difficulty : Intermediate

                
                    
import random
import torch
from fairseq.models import FairseqModel
from fairseq.data import Dictionary

def random_sentence_generator(model, dictionary, length=50):
    """
    Generates a random sentence using a Fairseq model and dictionary.
    """
    # Initialize the model
    model.eval()
    
    # Create a random tensor to represent a sequence
    random_input = torch.randint(0, dictionary.size(), (1, length))
    
    # Generate the output sequence
    with torch.no_grad():
        output_tokens = model.generate(random_input, sample=True)
    
    # Convert tokens to a string
    generated_sentence = dictionary.string(output_tokens[0], addEOS=False)
    
    return generated_sentence