Validate algorithmic operations carefully

Mathematical and logical operations require careful validation to ensure correctness. Common issues include:

1. Operator precedence in complex conditions
2. Incorrect scaling/normalization calculations
3. Type mismatches in comparisons
4. Edge case handling

Example of a problematic implementation:

def _is_fp8_w8a8_sm90_or_sm100(weight_quant, input_quant):
    return (self._check_scheme_supported(90) or
            self._check_scheme_supported(100) and
            self._is_fp8_w8a8(weight_quant, input_quant))

Corrected version with proper operator precedence:

def _is_fp8_w8a8_sm90_or_sm100(weight_quant, input_quant):
    return ((self._check_scheme_supported(90) or
             self._check_scheme_supported(100)) and
            self._is_fp8_w8a8(weight_quant, input_quant))

Key validation practices:

• Use parentheses to make operator precedence explicit
• Validate numerical operations with edge cases (zero, negative, overflow)
• Ensure type consistency in comparisons
• Add assertions or validation checks for critical assumptions
• Test with boundary conditions and extreme values