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| Section | Weight | Objectives |
|---|---|---|
| Content Aggregation | - Asset overriding and reuse - Modular asset building - Instancing and scene assembly | |
| Data Modeling | - Built-in schemas and data organization - USD and Sdf data structures - Prims, properties, primvars, time samples | |
| Composition | 23% | - Composition arcs (LIVERPS) - Composition strategies and debugging - References, payloads, sublayers, variants |
| Data Exchange | - Data translation and conversion - Interoperability between tools - Import/export workflows | |
| Pipeline Development | - Version control integration - Workflow design and implementation - Collaborative pipeline setup | |
| Debugging and Troubleshooting | - Composition error resolution - Stage introspection - Performance and data quality optimization | |
| Visualization | - UsdGeom, UsdShade, UsdLux domains - Rendering and display workflows - Geometry, materials, cameras, lights | |
| Customizing USD | 6% | - Plugin development - File format extensions - Custom schemas |
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NEW QUESTION # 19
Another department at your company has provided layer1.usda that has a Sphere Gprim with animated timeValues that translate the sphere along the Y-axis:
#usda 1.0
(
endTimeCode = 60
startTimeCode = 1
)
def Xform "Asset"
{
def Sphere "Sphere"
{
double3 xformOp:translate.timeSamples = {
1: (0, 5.0, 0)
30: (0, -5.0, 0)
60: (0, 5.0, 0)
}
uniform token[] xformOpOrder = ["xformOp:translate"]
}
}
You've been given rootLayer.usda that references Sphere from layer1.usda as follows:
#usda 1.0
(
endTimeCode = 60
startTimeCode = 1
)
def Xform "World"
{
def Sphere "Sphere" (
prepend references = @./layer1.usda@ < /Asset/Sphere >
)
{
}
}
For testing purposes, you want to check what Sphere would look like if it was at (0, -5.0, 0) at timeCode = 45.
Which of the following changes in rootLayer.usda would place Sphere at -5.0 in the Y-axis at timeCode 45?
Note that it is okay if the position of Sphere at other timeCodes is changed. Choose two.
Answer: A,C
Explanation:
At timeCode 45, the referenced animation from layer1.usda interpolates between the samples at 30 and 60.
Since the Y values are -5.0 at frame 30 and 5.0 at frame 60, the interpolated local translate at frame 45 is 0.0.
Option A works because adding a parent transform on /World at frame 45 contributes an additional Y translation of -5.0; combined with the sphere's interpolated local value of 0.0, the resulting placement is Y =
-5.0.
Option C also works because a layer offset retimes animation across a reference. NVIDIA defines a layer offset as an adjustment to time values when composing layers through references, payloads, or sublayers, using offset and scale to retime animated data non-destructively. With offset = 15, the source sample at frame
30 is composed at frame 45, so the referenced sphere evaluates to Y = -5.0 at root time 45. Value resolution accounts for layer offsets and interpolation of time samples.
Option B only changes timeline metadata and does not retime or override the animation. Option D interpolates between -2.5 at frame 30 and -5.0 at frame 60, producing -3.75 at frame 45, not -5.0. This aligns with Composition # References, Layer Offsets, Time Samples, and Value Resolution .
NEW QUESTION # 20
When prioritizing ease of interchange and reducing dependencies between different applications in a pipeline, why might codeless schemas, schemas defined purely in .usda files, be preferred over codeful schemas, schemas with generated classes using usdGenSchema?
Answer: A
Explanation:
Codeless schemas are preferred when the pipeline goal is portability, easy distribution, and reduced application coupling. NVIDIA's Learn OpenUSD schema guidance states that schemas define data models and optional APIs for encoding and interchanging 3D and non-3D concepts, and notes a trend toward codeless schemas for easier distribution, with schemas becoming more focused on data modeling rather than behavior implementation.
Option A is correct because a codeless schema can be distributed as schema data and plugin metadata without requiring every consuming application to compile, link, or ship custom generated C++/Python schema classes. OpenUSD's schema-generation documentation identifies codeless schemas as schemas produced without corresponding C++ classes, where only generatedSchema.usda and plugInfo.json are essential for runtime registration.
Option B is incorrect because strongly typed convenience APIs are the advantage of codeful generated schemas. Option C is incorrect because fallback values are authored in schema definitions. Option D is incorrect because codeful and codeless schemas can both participate in schema registration and value interpretation. This aligns with Customizing USD # Schemas, API Schemas, Codeless Schemas, Schema Registry, Data Modeling for Interchange .
NEW QUESTION # 21
Why use Tf.MakeValidIdentifier for prim/material names?
Answer: B
Explanation:
It fixes invalid characters and leading digits.
NEW QUESTION # 22
What method allows skipping children during a PrimRange traversal?
Answer: D
Explanation:
Using prim.SkipChildren() (adjusted for this question) prevents traversal into a prim's children, useful when you only care about top-level nodes.
NEW QUESTION # 23
Which of the following statements about debugging complex LIVRPS scenarios are correct?
Answer: C
Explanation:
Option A is correct because local opinions are the strongest opinions in USD composition strength ordering.
NVIDIA's Learn OpenUSD strength-ordering guide describes LIVRPS, now also written as LIVERPS with relocates included, as the ordered set of composition operations used to determine which opinions win. The order is strongest to weakest: local , inherits, variant sets, relocates, references, payloads, and specializes.
When debugging an unexpected value, local opinions should be inspected first because a directly authored opinion in the local layer stack can override opinions arriving through other composition arcs. NVIDIA's tracing guidance also highlights how complex composition debugging becomes when many prims, properties, layers, and arcs contribute competing opinions.
Option B is false because specializes arcs are not unoverrideable; they are the weakest fallback-style opinions in the composition order. Option C is false because references are stronger than payloads in LIVRPS
/LIVERPS ordering, so checking payloads before references reverses the standard diagnostic priority. This aligns with Debugging and Troubleshooting # LIVERPS Strength Ordering, Local Opinions, References, Payloads, Specializes, and Composition Diagnostics .
NEW QUESTION # 24
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