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import streamlit as st
import random
from tensorflow.keras.preprocessing.text import Tokenizer
from tensorflow.keras.preprocessing.sequence import pad_sequences
st.title("Addition Equation Generator")
# Sidebar for user input
num_samples = st.sidebar.number_input("Number of Samples", min_value=100, max_value=100000, value=5000)
max_num = st.sidebar.slider("Maximum Number for Addition", min_value=10, max_value=100, value=99)
# Function to generate addition data
def generate_addition_data(num_samples, max_num, stop_token=';'):
input_equations = []
answers = []
for _ in range(num_samples):
a = random.randint(0, max_num)
b = random.randint(0, max_num)
input_eq = f"{a} + {b} ="
answer = str(a + b) + stop_token
input_equations.append(input_eq)
answers.append(answer)
return input_equations, answers
# Button to generate and process data
if st.button('Generate and Process Data'):
input_equations, answers = generate_addition_data(num_samples, max_num)
# Display some sample data
st.write("Sample Generated Data:")
for i in range(min(5, len(input_equations))):
st.write(f"Input Equation: {input_equations[i]}")
st.write(f"Answer: {answers[i]}")
# Tokenization
tokenizer = Tokenizer(char_level=True)
tokenizer.fit_on_texts(input_equations + answers)
input_sequences = tokenizer.texts_to_sequences(input_equations)
answer_sequences = tokenizer.texts_to_sequences(answers)
# Padding sequences
max_len = max(max([len(seq) for seq in input_sequences]), max([len(seq) for seq in answer_sequences]))
input_sequences_padded = pad_sequences(input_sequences, maxlen=max_len, padding='post')
answer_sequences_padded = pad_sequences(answer_sequences, maxlen=max_len, padding='post')
# Display tokenization and padding results
st.write("Tokenization and Padding Results:")
for i in range(min(5, len(input_equations))):
st.write(f"Input Equation: {input_equations[i]}")
st.write(f"Tokenized Input Sequence: {input_sequences[i]}")
st.write(f"Padded Input Sequence: {input_sequences_padded[i]}")
st.write(f"Answer: {answers[i]}")
st.write(f"Tokenized Answer Sequence: {answer_sequences[i]}")
st.write(f"Padded Answer Sequence: {answer_sequences_padded[i]}")
# Instruction to run the app
st.write("Run the app with `streamlit run <script_name>.py` in your terminal.")
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