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Description
❓ Question
Since only part of the ops support dynamic shapes, and some are not. What's the criteria to decide if an op supports dynamic shape or not?
For some existing ops, which are not marked as supports_dynamic_shapes=True, can I write a converter that wraps the existing converter, and mark my own converter with high priority? Is this the recommended way?
or should I just turn on assume_dynamic_shape_support, which seems to be a flag globally for all converters ?
What you have already tried
Environment
Build information about Torch-TensorRT can be found by turning on debug messages
- PyTorch Version (e.g., 1.0): 2.4.1
- CPU Architecture: x86_64
- OS (e.g., Linux): linux
- How you installed PyTorch (
conda,pip,libtorch, source): pip - Build command you used (if compiling from source):
- Are you using local sources or building from archives:
- Python version: 3.11.9
- CUDA version: 12.1
- GPU models and configuration: Nvidia L4
- Any other relevant information: