mshr-h commented on code in PR #18429:
URL: https://github.com/apache/tvm/pull/18429#discussion_r2513619153
##########
python/tvm/relax/frontend/torch/exported_program_translator.py:
##########
@@ -1149,14 +1170,22 @@ def from_exported_program(
from torch import fx # type: ignore
# Create input variables.
- parameter_buffer_constant_vars, user_input_vars =
self.create_input_vars(exported_program)
+ (
+ parameter_buffer_constant_vars,
+ user_input_vars,
+ range_constraints,
+ ) = self.create_input_vars(exported_program)
inputs_vars = user_input_vars.copy()
inputs_vars.update(parameter_buffer_constant_vars)
# Initialize the block builder with a function and a dataflow block.
self.block_builder = relax.BlockBuilder()
func_name = "main"
func_attrs = {"num_input": len(user_input_vars)} if
keep_params_as_input else None
+ if range_constraints:
+ if func_attrs is None:
+ func_attrs = {}
+ func_attrs["shape_var_constraints"] = range_constraints
Review Comment:
Please use `tir_var_upper_bound` to annotate upper bound.
I grepped the tvm code base and I found that there's no lower bound
annotation. So I don't think we need to keep it at the moment. If we have a
real use case for it, it's fine to keep it in the Relax module.
https://github.com/apache/tvm/blob/main/src/relax/transform/static_plan_block_memory.cc#L62-L66
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