Review model changes in Canvas — reference
For the short walkthrough, see the user guide. This page keeps the detailed behavior and implementation notes.
Contents
Use Graph diff on an open native Python code diff, or Open PR in Canvas or the Command Palette. Paste the PR URL or choose a repository PR; TensorViz reads its revisions, discovers affected models, and opens the comparison without requiring a live model. See direct PR review for supported source providers, model selection, authentication, update handling, and limits.
Source Control's Graph diff uses the same Canvas: Changes compares the index with working files (including unsaved buffers); Staged Changes compares HEAD with the index. Graph diff against HEAD in the editor or Command Palette compares HEAD with working files. Its existing tensorviz.compareWithHead command ID is retained for keybindings. The retired ghost-comparison route and parser are removed; these actions neither open the old editor canvas nor create .tensorviz/views files.
For advanced local comparisons, open a model with Open as Graph, then select the Git comparison icon or run tensorViz: Review model changes.
- Working changes: HEAD versus current Python files, including unsaved buffers.
- Branch changes: the merge base of a chosen base branch and HEAD versus HEAD, for a checked-out pull request. Fetch refs first; this command only reads local Git.
- Two revisions: two local branches, tags, or commits.
Opening a local review from a captured model keeps the full graph on Canvas. Its nodes, connections, expansion and arrangement stay intact. The change navigator reports source edits, including constructor-default edits on the root. An edit is placed on a captured call only when its registered-path correspondence belongs to an exact reviewed source snapshot; unmatched changes focus the root and say Not located in this capture. The capture is reference context: its shapes and connections have not been re-executed, and no runtime Before/After is inferred. The toolbar shows the current change in a compact row, for example ffn_layer default: 'mlp' → 'swiglu'. It has no graph-type switch or capture explanation. A PR or another model without a matching local capture uses the source comparison below.
Source modifications on nodes and module frames have an amber outline and tinted header, including collapsed modules and the large-graph overview. The outline stays two screen pixels wide when zooming out; selecting the node retains its diff highlight. Connection-only changes use blue and say inputs changed; source plus connection changes say modified + inputs. The counts and navigator distinguish these cases, including model outputs. See input connection changes. Constructor default edits highlight the model root, not unproven internal calls. Errors keep their red outline. Closing review removes the highlights. When a reviewed declaration is absent from source lowering, its exact registered capture path can still highlight the individual module. Added declarations are green on an after-side capture, removed declarations red on a before-side capture, and modifications amber. All observed calls of a uniquely registered module are highlighted. The navigator lists each declaration separately; selecting a mapped call shows that change and opens its source span. No runtime topology is inferred. Without a matching capture, an omitted declaration remains in the navigator and focuses the model root. Unobserved or ambiguous calls are not guessed.
The native code diff stays in the editor and the graph stays in Canvas. Before, Diff, and After share tile positions. Diff shows green additions, dashed red removals, amber modifications, blue input changes, old → new parameter values, and replacements in one tile. Removed edges curve around inserted tiles. Previous/next visits each changed tile; source links open the correct revision and mapped line. Moving the cursor within a mapped code span focuses the corresponding tile. Collapsed modules retain a summary. Closing review restores the live graph and arrangement.
Review chrome takes two rows so the graph keeps the height. The page header shows Graph diff with the compared revisions (prefixed by the review title, when one exists) and holds the code diff, Refresh graph diff, and close actions. The toolbar row holds Before/Diff/After (source comparisons only), the previous/next stepper, the current change with a status-coloured dot, stale or PR-updated notices, the counts, and the coverage disclosures. Long change text truncates with the full text in its tooltip; narrow panels wrap the counts instead of adding fixed rows. A multi-model PR adds one row for its affected-model chooser.
Both code sides are immutable snapshots. Editing a working-tree snapshot's Python source marks review stale; Refresh graph diff reads the revisions again. Review never checks out branches, modifies the index, writes model source, or executes either revision. A capture made while opening the live model is not reused as evidence about these snapshots. Review projections are stateless (review_only) with a separate graph identity: they do not write to the project store or advance the live graph's revision.
Coverage and correspondence
This surface is available in native VS Code Canvas, and compares source projections of the selected model using the existing bounded multi-file AST projector. Reviews on an existing capture have a compact Graph diff footer; standalone source reviews say Source comparison · Not executed. Constructor sizes are parameters; runtime shapes are not fabricated. Source notes and truncation remain visible. Canonical execution-capture comparison is separate.
Coverage notes prioritize changed files and the selected model's known dependencies. Identical before/after notes appear once. Coverage limits and Other repository notes are neutral, collapsed disclosures; only one opens at a time, with bounded scrolling. Tab into the details and press Escape to close them and restore focus. Other notes concern discovery of other affected models. Optional external imports alone do not produce warnings; unresolved dynamic references and imports name the actual source line and reason. Review shares CodeLens's declaration-scoped module discovery, including Torch container subclasses and proven fallback aliases. Repository/source budget limits remain in the main coverage notes.
Named declarations match by qualified attribute identity and defining file. Anonymous statements can match an edited expression when the parser proves a unique local assignment in that method and exactly one projected operation for the statement. Reassigned names and statements with multiple operations do not receive this binding identity. Other statements require a unique exact source digest in the same file and parent scope. Generated ordinals, positional container entries, tensor shapes, and topology are not correspondence evidence. Unmatched named layers are reported added/removed only with complete projections; otherwise they say unresolved. Edges involving unresolved identities are not counted as confirmed additions or removals. Endpoint/port multisets preserve duplicate value uses. Line movement, canvas positions, and generated edge IDs are ignored.
Opaque Python cards name dotted calls in AST evaluation order, so F.normalize(x.float()) reads float → normalize. The changed tile and source link retain the exact expression. This is a source description, not a measured dtype or execution trace. Expressions with conditional evaluation and older graph files without order metadata use an unordered list instead of misleading arrows.
Source-proven Torch import aliases and equivalent positional/keyword constructor arguments compare by their meaning. Unsupported constructor expressions remain in the comparison, so a changed expression still produces a modification. Literal scalar +, -, *, and / operations retain their operand and its side. A numeric constructor attribute used by forward() is included only when source shows one unconditional assignment and no later write; mutable or dynamically assigned attributes are not inferred. Execution, shape inference, and export preserve these scalar operands. Dedicated parser, projection-identity, runtime, and export regressions cover these rules, including private capture-worker imports. Omitted literal Torch constructor defaults compare equally to explicit defaults. Default edits retain both values (for example, bias: true → false). RNN, GRU, and LSTM use their Torch base signature; unpacked arguments receive no assumed defaults, and unproven user constructors cannot borrow Torch defaults.
Repeated value uses survive parsing, node renaming, inheritance composition, and multi-file expansion. For example, layer(x) + layer(x) retains two incoming connections to the addition. Repeated generation of the same module bridge is still deduplicated; edge identities distinguish actual operand occurrences.
Direct, source-proven local instance helpers are expanded from forward, including nested helpers and transparent *args/**kwargs forwarding wrappers. Argument binding preserves literals, keywords and literal tuple/dictionary unpacking; tuple/dictionary returns route their selected producers. Inline Torch module calls such as nn.ReLU()(x) become individual operations with their actual source spans. Each helper call keeps its own local bindings and comparison context. Recursion, decorators, rebinding, generators, comprehensions, unknown argument expansion and the depth/work budget stay opaque. Source paths are not an execution trace.
Within the same proven call context, pure operation insertion/deletion is reported only when the unchanged operation sequence has a unique exact source embedding. This permits two identical new ReLUs around unchanged operations while refusing ambiguous repeated anchors, replacements and reordered sequences. Truncated snapshots cannot establish this proof.
An opaque self.helper(...) call retains the source bodies of reachable methods on the same class. Editing a reachable body marks the call as Helper implementation changed; unrelated methods are excluded. This records source changes without executing helpers or claiming that an opaque body is understood.
The enclosing if/else, while, and for conditions are retained on guarded layers and operations. A changed predicate marks the affected tile as Execution condition changed. This does not evaluate the predicate or resolve dynamic control flow; the comparison remains source-only.
Matrix products written with @, torch.matmul, or torch.bmm remain explicit operations. Attention stages connect through these operations instead of copying all previous ancestors into later edges. The four-stage regression checks two inputs per matrix product, bounded edge growth, and faithful code export.
Constructor defaults are compared separately from projected layers. A default such as DINOv2's ffn_layer changing from mlp to swiglu appears on the model root even when dynamic blocks cannot be expanded statically. A changed class body with no mapped layer change remains unresolved and links to the code diff; it does not produce a no-changes claim. Comments and docstrings are excluded from this class comparison. Incomplete projections say Comparison incomplete.
Review also retains direct self declarations from the initializer, including conditional expressions and factory calls omitted by graph lowering. Each has its own source digest and declaration span; branch/loop conditions participate in that digest, and repeated assignments remain ambiguous. Review responses retain all supplied source-file digests so a capture can be checked against the complete reviewed snapshot. Captured registered module paths remain available for matching even when no static layer card exists. Shared aliases do not prove a unique mapping.
This does not prove behavioral equivalence or represent every Python edit as a structural change. Dynamic construction, control flow, external code, and opaque containers retain the projector's limitations. Both revisions must contain the same selected file and class; whole-model additions/deletions and file/class renames require choosing a common target or inspecting the native code diff. For GitHub pull requests and selection among affected models, use Open PR.
Input connection changes
Inserting a layer in front of an unchanged operation changes what feeds that operation. It does not edit the operation's own expression. Review keeps those facts separate:
- inputs changed (blue): incoming connections changed; the matched node's projected source and parameters did not.
- modified (amber): the operation, expression, constructor arguments, execution condition, or local helper implementation changed.
- modified + inputs (amber): both changed.
A node with both kinds of change counts once as modified. Before and After clear these badges. Edges that touch an unresolved node are not confirmed connection changes. A captured overlay needs an exact source snapshot. It labels the source change and does not invent a new execution.
Source operation cards
Graph review and the live graph use the same layer cards. Source projection keeps reshape, view, permute, and source-proven interpolate calls, including nested chains. Only the tensor operand becomes a tensor connection. Shape and dtype reads stay scalar metadata. Unevaluated options such as self.interpolate_antialias are shown as source expressions and compared as parameters. They are not measured shapes. Export refuses symbolic source arguments rather than dropping them or inventing defaults.
An expression card is titled from the call that produces the statement's result. torch.where(...) reads Select by condition, with torch.where under the title. Nested calls that only prepare arguments are not drawn as a single chain. Unknown calls keep their method or function name.