mirror of https://github.com/llvm/torch-mlir
ef9e4c95f2
We do this by inroducing a TensorPlaceholder class, which can be used to specify dynamic sizes. Internally, we canonicalize all example inputs to TensorPlaceholder's. This commit also adds some basic testing, which was missing before. |
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dialects | ||
eager_mode | ||
__init__.py | ||
compiler_utils.py |