debug and rewrite this code so as to geerate normal image instead of rgb "import numpy as np

import torch

import matplotlib.pyplot as plt

def generate$\_$and$\_$visualize$\_$image$\_$from$\_$text$($model$,$ max$\_$caption$\_$length, vocabulary, device$=$'cpu'$)$:

# Take input text from the user

input$\_$text $=$ input$("$Enter a description to generate an image: $")$

print$("$Input Text:", input$\_$text$)$

# Tokenize the input text

input$\_$tokens $=$ input$\_$text.split$()$

print$("$Input Tokens:", input$\_$tokens$)$

# Convert tokens to indices using vocabulary

input$\_$indices $=[$vocabulary$.$get$($token$,$ vocabulary$[\text{'}\text{'}])$ for token in input$\_$tokens$]$

print$("$Input Indices:", input$\_$indices$)$

# Pad the indices to match the max caption length

padded$\_$indices $=$ input$\_$indices$[$:max$\_$caption$\_$length$]+[$vocabulary$[\text{'}\text{'}]]*($max$\_$caption$\_$length $-$ len$($input$\_$indices$))$

# Convert indices to tensor

input$\_$tensor $=$ torch.tensor$($padded$\_$indices, dtype$=$torch.long, device$=$device$).$unsqueeze$(0)$

# Generate image from the input text

with torch.no$\_$grad$()$:

model.eval$()$

generated$\_$image $=$ model$($input$\_$tensor$)$

# Convert the generated image tensor to numpy array

generated$\_$image$\_$np $=$ generated$\_$image.cpu$().$numpy$()$

print$("$Generated image tensor size:", generated$\_$image$\_$np$.$size$)$

# Ensure the generated image tensor has the correct dimensions for visualization

if generated$\_$image$\_$np$.$ndim $==2$:

# If the tensor is flattened, reshape it into a $3$D format

num$\_$pixels $=$ generated$\_$image$\_$np$.$size

channels $=3$

height, width $=64,64$ # Assuming RGB channels

if num$\_$pixels $==$ channels $*$ height $*$ width:

generated$\_$image$\_$np $=$ generated$\_$image$\_$np$.$reshape$(($channels$,$ height, width$))$

else:

print$("$Generated image tensor has unexpected size. Unable to reshape."$)$

return

elif generated$\_$image$\_$np$.$ndim $==3$:

# If the tensor already has $3$ dimensions, transpose it to $($height$,$ width, channels$)$ format

generated$\_$image$\_$np $=$ np$.$transpose$($generated$\_$image$\_$np$,(1,2,0))$

# Visualize the generated image

plt$.$imshow$($generated$\_$image$\_$np$)$

plt$.$axis$(\text{'}$off$\text{'})$

plt$.$show$()$

# Example usage

generate$\_$and$\_$visualize$\_$image$\_$from$\_$text$($model$,$ max$\_$caption$\_$length, vocabulary, device$)"$ it gives "Generated image tensor size: $6000$

Generated image tensor has unexpected size. Unable to reshape."