Migrate Gemma3ImagePixelInputs to TensorSchema

[bbeckca]

Purpose

This PR migrates Gemma3ImagePixelInputs from a TypedDict-based definition to a structured TensorSchema model with runtime shape validation. This brings it in line with recent changes to Phi3VImagePixelInputs, and is part of a broader effort to improve input contract enforcement and debug-ability across multi-modal models.

Test Plan

Confirm validation works via standalone tests in tests/standalone_test/test_tensor_schema.py and rely on CI to check integration.

Test Result

(venv) benjibeck@Benjis-MBP vllm % python3 -m pytest tests/standalone_tests/test_tensor_schema.py -v --log-cli-level=DEBUG
========================================= test session starts =========================================
platform darwin -- Python 3.9.6, pytest-8.4.1, pluggy-1.6.0 -- /Users/benjibeck/Projects/vllm/venv/bin/python3
cachedir: .pytest_cache
rootdir: /Users/benjibeck/Projects/vllm
configfile: pyproject.toml
plugins: anyio-4.9.0
collected 14 items                                                                                    

tests/standalone_tests/test_tensor_schema.py::test_tensor_schema_valid_tensor PASSED            [  7%]
tests/standalone_tests/test_tensor_schema.py::test_tensor_schema_optional_fields PASSED         [ 14%]
tests/standalone_tests/test_tensor_schema.py::test_tensor_schema_constant_dim_failure PASSED    [ 21%]
tests/standalone_tests/test_tensor_schema.py::test_tensor_schema_symbolic_dim_mismatch PASSED   [ 28%]
tests/standalone_tests/test_tensor_schema.py::test_tensor_schema_list_tensor_valid PASSED       [ 35%]
tests/standalone_tests/test_tensor_schema.py::test_tensor_schema_variable_patch_counts_valid PASSED [ 42%]
tests/standalone_tests/test_tensor_schema.py::test_tensor_schema_tuple_tensor_valid PASSED      [ 50%]
tests/standalone_tests/test_tensor_schema.py::test_tensor_schema_inconsistent_shapes_in_list PASSED [ 57%]
tests/standalone_tests/test_tensor_schema.py::test_tensor_schema_empty_list PASSED              [ 64%]
tests/standalone_tests/test_tensor_schema.py::test_tensor_schema_validation_disabled_skips_shape_check PASSED [ 71%]
tests/standalone_tests/test_tensor_schema.py::test_tensor_schema_with_valid_resolve_binding_dims PASSED [ 78%]
tests/standalone_tests/test_tensor_schema.py::test_tensor_schema_with_invalid_resolve_binding_dims PASSED [ 85%]
tests/standalone_tests/test_tensor_schema.py::test_tensor_schema_with_list_of_symbolic_dim PASSED [ 92%]
tests/standalone_tests/test_tensor_schema.py::test_tensor_schema_with_list_of_symbolic_dim_mismatch_in_length PASSED [100%]

[github-actions]

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[gemini-code-assist]

Code Review

This pull request successfully migrates Gemma3ImagePixelInputs to use TensorSchema for improved input validation, which is a great enhancement for robustness and clarity. The changes align well with similar patterns in the codebase. I've identified one potential issue where a missing None check for num_crops could lead to a runtime error, and I've provided a suggestion to address it.

[gemini-code-assist]

The previous implementation had an isinstance check that would implicitly fail if num_crops was None. With the removal of this check, if pixel_values is provided but num_crops is not, num_crops will be None, leading to a crash inside flatten_bn with a potentially unclear error message. It's safer to add an explicit assertion before this line to ensure num_crops is provided whenever pixel_values is present.

        assert num_crops is not None, \
            "'num_crops' must be provided when 'pixel_values' is present."

        image_size = self.config.vision_config.image_size