| 1 | # SPDX-License-Identifier: Apache-2.0 |
| 2 | # SPDX-FileCopyrightText: Copyright contributors to the vLLM project |
| 3 | """Model inspection utilities for vLLM.""" |
| 4 | |
| 5 | import torch.nn as nn |
| 6 | |
| 7 | |
| 8 | def _get_module_info(module: nn.Module) -> str: |
| 9 | """Get info string for a module.""" |
| 10 | class_name = type(module).__name__ |
| 11 | parts = [] |
| 12 | |
| 13 | # Add quant_method if present |
| 14 | quant_method = getattr(module, "quant_method", None) |
| 15 | if quant_method is not None: |
| 16 | quant_name = type(quant_method).__name__ |
| 17 | # For CompressedTensors, show the underlying scheme instead |
| 18 | scheme = getattr(module, "scheme", None) |
| 19 | if scheme is not None: |
| 20 | quant_name = type(scheme).__name__ |
| 21 | # Skip unquantized methods |
| 22 | if "Unquantized" not in quant_name: |
| 23 | parts.append(f"quant={quant_name}") |
| 24 | |
| 25 | # If module has extra_repr, use it |
| 26 | if hasattr(module, "extra_repr"): |
| 27 | parts.append(module.extra_repr().replace("\n", "")) |
| 28 | |
| 29 | if parts: |
| 30 | return f"{class_name}({', '.join(parts)})" |
| 31 | |
| 32 | # For unknown modules, use the default PyTorch repr |
| 33 | return str(module) |
| 34 | |
| 35 | |
| 36 | def _get_child_signature(child: nn.Module) -> str: |
| 37 | """Get a signature for a child module to detect duplicates.""" |
| 38 | lines = [] |
| 39 | for name, submodule in child.named_modules(): |
| 40 | lines.append(f"{name}:{_get_module_info(submodule)}") |
| 41 | return "\n".join(lines) |
| 42 | |
| 43 | |
| 44 | def _format_index_ranges(indices: list[int]) -> str: |
| 45 | """Format indices into range notation (e.g., [0,1,2,4,5,6] -> '0-2, 4-6').""" |
| 46 | indices = sorted(indices) |
| 47 | ranges = [] |
| 48 | start = end = indices[0] |
| 49 | |
| 50 | for idx in indices[1:]: |
| 51 | if idx == end + 1: |
| 52 | end = idx |
| 53 | else: |
| 54 | ranges.append(str(start) if start == end else f"{start}-{end}") |
| 55 | start = end = idx |
| 56 | |
| 57 | ranges.append(str(start) if start == end else f"{start}-{end}") |
| 58 | return ", ".join(ranges) |
| 59 | |
| 60 | |
| 61 | def _format_module_tree( |
| 62 | module: nn.Module, |
| 63 | name: str = "", |
| 64 | indent: int = 0, |
| 65 | ) -> list[str]: |
| 66 | """Format a module tree with indentation, grouping identical layers. |
| 67 | |
| 68 | Produces output like: |
| 69 | (layers): ModuleList( |
| 70 | (0-27, 29-47): 47 x LlamaDecoderLayer( |
| 71 | ... |
| 72 | ) |
| 73 | (28, 48): 2 x DifferentDecoderLayer( |
| 74 | ... |
| 75 | ) |
| 76 | ) |
| 77 | """ |
| 78 | lines = [] |
| 79 | prefix = " " * indent |
| 80 | children = list(module.named_children()) |
| 81 | |
| 82 | # Leaf node - just output the module info |
| 83 | if not children: |
| 84 | info = _get_module_info(module) |
| 85 | lines.append(f"{prefix}({name}): {info}" if name else f"{prefix}{info}") |
| 86 | return lines |
| 87 | |
| 88 | # Non-leaf node - output opening line and recurse into children |
| 89 | info = _get_module_info(module) |
| 90 | lines.append(f"{prefix}({name}): {info}(" if name else f"{prefix}{info}(") |
| 91 | |
| 92 | # Separate numbered children (e.g., "0", "1") from named ones (e.g., "norm") |
| 93 | numbered: list[tuple[int, nn.Module]] = [] |
| 94 | non_numbered: list[tuple[str, nn.Module]] = [] |
| 95 | for child_name, child_module in children: |
| 96 | try: |
| 97 | numbered.append((int(child_name), child_module)) |
| 98 | except ValueError: |
| 99 | non_numbered.append((child_name, child_module)) |
| 100 | |
| 101 | # Group numbered children by structure signature to collapse identical layers |
| 102 | # e.g., layers 0-27 and 29-47 with same structure become "(0-27, 29-47): 47 x" |
| 103 | if numbered: |
| 104 | sig_to_group: dict[str, list[tuple[int, nn.Module]]] = {} |
| 105 | for idx, child_module in numbered: |
| 106 | sig = _get_child_signature(child_module) |
| 107 | sig_to_group.setdefault(sig, []).append((idx, child_module)) |
| 108 | |
| 109 | # Output groups sorted by first index |
| 110 | for group in sorted(sig_to_group.values(), key=lambda g: g[0][0]): |
| 111 | indices = [idx for idx, _ in group] |
| 112 | representative = group[0][1] |
| 113 | child_lines = _format_module_tree(representative, "", indent + 1) |
| 114 | first_line = child_lines[0].lstrip() |
| 115 | child_prefix = " " * (indent + 1) |
| 116 | |
| 117 | if len(indices) > 1: |
| 118 | range_str = _format_index_ranges(indices) |
| 119 | child_lines[0] = ( |
| 120 | f"{child_prefix}({range_str}): {len(indices)} x {first_line}" |
| 121 | ) |
| 122 | else: |
| 123 | child_lines[0] = f"{child_prefix}({indices[0]}): {first_line}" |
| 124 | lines.extend(child_lines) |
| 125 | |
| 126 | # Output non-numbered children (e.g., "embed_tokens", "norm") |
| 127 | for child_name, child_module in non_numbered: |
| 128 | lines.extend(_format_module_tree(child_module, child_name, indent + 1)) |
| 129 | |
| 130 | lines.append(f"{prefix})") |
| 131 | return lines |
| 132 | |
| 133 | |
| 134 | def format_model_inspection(model: nn.Module) -> str: |
| 135 | """Format a model into a transformers-style hierarchical string.""" |
| 136 | return "\n".join(_format_module_tree(model)) |