simple-math / mathrandom-progressive.py
fblgit's picture
Update mathrandom-progressive.py
c5614cb verified
import random
import json
import operator
import math
num_samples = [20000, 50000, 230000, 500000]
min_values = [-9.99, -19.99, -99.99, -99.99]
max_values = [9.99, 19.99, 99.99, 99.99]
vals_floats = ["%.2f", "%.3f", "%.3f", "%.4f"]
result_floats = ["%.2f", "%.3f", "%.4f", "%.4f"]
seed = 42
random.seed(seed)
# Binary operations
binary_operations = {
'+': operator.add,
'-': operator.sub,
'*': operator.mul,
'/': operator.truediv,
#'**': operator.pow, # it makes tons of troubles, but if u wanna contribute with a functional fix (L)
'%': operator.mod
}
# Safe division to avoid division by zero
def safe_division(numerator, denominator):
return numerator if denominator == 0 else numerator / denominator
# Unary operations
def safe_sqrt(x):
return math.sqrt(x) if x >= 0 else 0
def safe_log(x):
return math.log(x) if x > 0 else 0
unary_operations = {
'sqrt': safe_sqrt,
'sin': math.sin,
'cos': math.cos,
'log': safe_log
}
def format_result(result, format_spec):
if isinstance(result, complex):
real_part = format_spec % result.real
imag_part = format_spec % result.imag
return f"{real_part} + {imag_part}j"
else:
return format_spec % result
def safe_modulo(numerator, denominator):
return 0 if denominator == 0 else numerator % denominator
def safe_power(base, exponent):
if base == 0 and exponent < 0:
return 0 # or some other value that signifies an undefined operation
else:
return base ** exponent
def generate_sub_expression(min_value, max_value, val_float):
num1 = float(val_float % random.uniform(min_value, max_value))
num2 = float(val_float % random.uniform(min_value, max_value))
operation = random.choice(list(binary_operations.keys()))
if operation == '/':
result = safe_division(num1, num2)
elif operation == '%':
result = safe_modulo(num1, num2)
else:
result = binary_operations[operation](num1, num2)
expression = f"({num1} {operation} {num2})"
return expression, result
def generate_expression(num_samples, min_value, max_value, val_float, result_float):
data = []
for _ in range(num_samples):
sub_ops_count = random.randint(0, 2) # Number of sub-operations (0, 1, or 2), the code is not tailored for more cases, but feel free to improve it.
sub_expressions = [generate_sub_expression(min_value, max_value, val_float) for _ in range(sub_ops_count)]
# Main operation
main_num1 = float(val_float % random.uniform(min_value, max_value))
main_num2 = float(val_float % random.uniform(min_value, max_value))
main_operation = random.choice(list(binary_operations.keys()))
# Embed sub-expressions into main expression
if sub_expressions:
if len(sub_expressions) == 1:
sub_expr, sub_result = sub_expressions[0]
if random.choice([True, False]):
main_expression = f"{sub_expr} {main_operation} {main_num2}"
if main_operation == '/':
main_result = safe_division(sub_result, main_num2)
elif main_operation == '%':
main_result = safe_modulo(sub_result, main_num2)
else:
main_result = binary_operations[main_operation](sub_result, main_num2)
else:
main_expression = f"{main_num1} {main_operation} {sub_expr}"
if main_operation == '/':
main_result = safe_division(main_num1, sub_result)
elif main_operation == '%':
main_result = safe_modulo(main_num1, sub_result)
else:
main_result = binary_operations[main_operation](main_num1, sub_result)
else:
sub_expr1, sub_result1 = sub_expressions[0]
sub_expr2, sub_result2 = sub_expressions[1]
main_expression = f"{sub_expr1} {main_operation} {sub_expr2}"
if main_operation == '/':
main_result = safe_division(sub_result1, sub_result2)
elif main_operation == '%':
main_result = safe_modulo(sub_result1, sub_result2)
else:
main_result = binary_operations[main_operation](sub_result1, sub_result2)
else:
main_expression = f"{main_num1} {main_operation} {main_num2}"
if main_operation == '/':
main_result = safe_division(main_num1, main_num2)
elif main_operation == '%':
main_result = safe_modulo(main_num1, main_num2)
else:
main_result = binary_operations[main_operation](main_num1, main_num2)
output = format_result(main_result, result_float)
data.append({'instruction': main_expression, 'output': output})
return data
# DPO (Follows Ultrabinarized Format)
def make_prompt(expression, output):
prompt = {
'prompt': 'What is the result of the following expression?',
'chosen': [],
'rejected': [],
'messages': []
}
prompt['chosen'].append({'content': prompt['prompt'] + '\n' + expression, 'role': 'user'})
prompt['chosen'].append({'content': output, 'role': 'assistant'})
prompt['rejected'].append({'content': prompt['prompt'] + '\n' + expression, 'role': 'user'})
prompt['rejected'].append({'content': output[0:2], 'role': 'assistant'})
prompt['messages'].append({'content': prompt['prompt'] + '\n' + expression, 'role': 'user'})
prompt['messages'].append({'content': output, 'role': 'assistant'})
return prompt
# Generate and write data for each set of parameters
for idx, sample_count in enumerate(num_samples):
data = generate_expression(sample_count, min_values[idx], max_values[idx], vals_floats[idx], result_floats[idx])
dpo_data = [make_prompt(elem['instruction'], elem['output']) for elem in data]
out_file = f'arithmetic-float-complex_{idx}.json'
with open(out_file, 'w') as f:
json.dump(data, f)
out_file = f'arithmetic-float-complex_DPO_{idx}.json'
with open(out_file, 'w') as f:
json.dump(dpo_data, f)