| import re | |
| # Read the file | |
| with open('./mlir/self_attn_with_consts_linalg_dialect.mlir', 'r') as f: | |
| content = f.read() | |
| # Pattern to match tensor.expand_shape without output_shape | |
| pattern = r'tensor\.expand_shape\s+([^[]+)\s+(\[\[.*?\]\])\s*:\s*([^)]+)\s+into\s+(tensor<[^>]+>)' | |
| def add_output_shape(match): | |
| var, indices, input_type, output_type = match.groups() | |
| # Extract dimensions from output tensor type | |
| dims_match = re.search(r'tensor<([^>]+)>', output_type) | |
| if dims_match: | |
| dims_str = dims_match.group(1) | |
| # Extract just the dimension numbers (ignore 'xf32' etc.) | |
| dims = re.findall(r'\d+', dims_str.split('x')[:-1]) # Exclude the type part | |
| if dims: | |
| output_shape = '[' + ', '.join(dims) + ']' | |
| return f'tensor.expand_shape {var} {indices} output_shape {output_shape} : {input_type} into {output_type}' | |
| return match.group(0) # Return original if we can't parse | |
| # Apply the fix | |
| fixed_content = re.sub(pattern, add_output_shape, content, flags=re.MULTILINE) | |
| # Write back | |
| with open('./mlir/self_attn_with_consts_linalg_dialect.mlir', 'w') as f: | |
| f.write(fixed_content) | |
| print("Fixed tensor.expand_shape syntax") | |