onnxruntime

dce58e87 - Fix Cast node naming collisions and opset 10 Resize in float16 conversion (#27469)

Fix Cast node naming collisions and opset 10 Resize in float16 conversion (#27469) ## Summary - Fix Cast node naming collisions in `convert_float_to_float16` when nodes have empty names (common in PyTorch exports) - Fix `ALWAYS_FLOAT_INPUTS` for opset 10 Resize where scales at index 1 was unprotected - Add dedicated test suite for float16 conversion (`test_float16.py`, 8 tests) ## Motivation Fixes #14827 When `convert_float_to_float16` processes models with unnamed nodes (empty `node.name`, very common in PyTorch/TensorFlow-exported ONNX models), the generated Cast node names collide. For example, multiple Resize nodes all produce Cast nodes named `"_input_cast_2"` and output tensors named `"_input_cast_2"`, corrupting the graph with duplicate names. Additionally, the `ALWAYS_FLOAT_INPUTS` dict only protected Resize scales at index 2 (opset 11+ layout: `[X, roi, scales, sizes]`), but opset 10 Resize has scales at index 1 (`[X, scales]`), leaving it unprotected. ## Changes **`onnxruntime/python/tools/transformers/float16.py`** (11 lines changed): - Use unique tensor names (`input_name`/`output`) as the base for generated Cast node and output names, instead of potentially-empty `node.name` - Add index 1 to `ALWAYS_FLOAT_INPUTS["Resize"]` to protect opset 10 scales - Fix misleading comment ("change current node's input name" → "output name") **`onnxruntime/test/python/transformers/test_float16.py`** (new file, 8 tests): - `test_resize_opset11_cast_naming_unique` — multiple unnamed Resize nodes produce unique Cast names - `test_resize_opset11_scales_initializer_stays_fp32` — scales initializer preserved as float32 - `test_resize_opset10_scales_initializer_stays_fp32` — opset 10 scales protected at index 1 - `test_resize_opset10_multiple_unnamed_unique_names` — opset 10 naming uniqueness - `test_blocked_node_cast_naming_unique` — blocked op nodes (Upsample) also get unique Cast names - `test_resize_with_op_block_list` — Resize in op_block_list still produces unique names - `test_data_input_converted_to_fp16` — data tensor correctly converts to fp16 - `test_force_fp16_initializers` — force flag overrides protection ## Test Plan - All 8 new tests pass locally (`python -m unittest test_float16.TestFloat16Conversion -v`) - Existing `test_gpt2_past_fp16` test passes (no regression in existing float16 behavior) - `ruff check` passes on both files