ONNX models with exact inference contracts

Small, validated ONNX graphs paired with named JSON inputs and expected tensor outputs. Use them to test runtime loading, dtype and shape handling, broadcasting, dynamic batches, reduction behavior, and numeric tolerances without downloading a production-sized model.

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ONNX Inference Contract - Static Identity Model

A one-node identity graph with a fixed 1x4 float tensor, useful as the smallest loader and inference smoke test. The matching JSON input and expected output make the model immediately usable in a CI inference assertion.

File: ONNX · Model Inference
Use case: Model inference testingModel evaluation+1· Conversion set

ONNX Inference Contract - Static Identity Input

The named float32 input tensor payload for the Static Identity model, with explicit shapes and JSON values for runner-independent test setup.

File: JSON · Model Inference
Use case: Model inference testingModel evaluation+1· Conversion set

ONNX Inference Contract - Static Identity Expected Output

The reference-evaluator output for the Static Identity model and supplied input, including shape, dtype, exact values and a 1e-6 tolerance.

File: JSON · Model Inference
Use case: Model inference testingModel evaluation+1· Conversion set

ONNX Inference Contract - Affine MatMul plus Add Model

A two-node affine transform with fixed weights and bias, exercising initializers, MatMul dimensions and Add broadcasting. The matching JSON input and expected output make the model immediately usable in a CI inference assertion.

File: ONNX · Model Inference
Use case: Model inference testingModel evaluation+1· Conversion set

ONNX Inference Contract - Affine MatMul plus Add Input

The named float32 input tensor payload for the Affine MatMul plus Add model, with explicit shapes and JSON values for runner-independent test setup.

File: JSON · Model Inference
Use case: Model inference testingModel evaluation+1· Conversion set

ONNX Inference Contract - Affine MatMul plus Add Expected Output

The reference-evaluator output for the Affine MatMul plus Add model and supplied input, including shape, dtype, exact values and a 1e-6 tolerance.

File: JSON · Model Inference
Use case: Model inference testingModel evaluation+1· Conversion set

ONNX Inference Contract - Two-Input Broadcast Add Model

A two-input Add graph where a length-two bias broadcasts across a 2x2 matrix, checking input binding and broadcasting rules. The matching JSON input and expected output make the model immediately usable in a CI inference assertion.

File: ONNX · Model Inference
Use case: Model inference testingModel evaluation+1· Conversion set

ONNX Inference Contract - Two-Input Broadcast Add Input

The named float32 input tensor payload for the Two-Input Broadcast Add model, with explicit shapes and JSON values for runner-independent test setup.

File: JSON · Model Inference
Use case: Model inference testingModel evaluation+1· Conversion set

ONNX Inference Contract - Two-Input Broadcast Add Expected Output

The reference-evaluator output for the Two-Input Broadcast Add model and supplied input, including shape, dtype, exact values and a 1e-6 tolerance.

File: JSON · Model Inference
Use case: Model inference testingModel evaluation+1· Conversion set

ONNX Inference Contract - Dynamic-Batch ReduceSum Model

A ReduceSum graph with a symbolic batch dimension and fixed feature width, for dynamic-shape import and batch-output tests. The matching JSON input and expected output make the model immediately usable in a CI inference assertion.