Version up

Author: sovrasov

README.md

@@ -44,7 +44,7 @@ Experimental support:
 
 - This backend doesn't take into account some of the `torch.nn.functional.*` and `tensor.*` operations. Therefore unsupported operations are
 not contributing to the final complexity estimation. See `ptflops/pytorch_ops.py:FUNCTIONAL_MAPPING,TENSOR_OPS_MAPPING` to check supported ops.
-Sometimes considering functional style conflicts with hooks for `nn.Module` (for instance, custom ones). In that case, counting with these ops can be disabled by
+Sometimes functional-level hooks conflict with hooks for `nn.Module` (for instance, custom ones). In that case, counting with these ops can be disabled by
 passing `backend_specific_config={"count_functional" : False}`.
 - `ptflops` launches a given model on a random tensor and estimates amount of computations during inference. Complicated models can have several inputs, some of them could be optional. To construct non-trivial input one can use the `input_constructor` argument of the `get_model_complexity_info`. `input_constructor` is a function that takes the input spatial resolution as a tuple and returns a dict with named input arguments of the model. Next, this dict would be passed to the model as a keyword arguments.
 - `verbose` parameter allows to get information about modules that don't contribute to the final numbers.

pyproject.toml

@@ -4,11 +4,11 @@ build-backend = "setuptools.build_meta"
 
 [project]
 name = "ptflops"
-version = "0.7.4"
+version = "0.7.5"
 dependencies = [
   "torch>=2.0",
 ]
-requires-python = ">=3.8"
+requires-python = ">=3.9"
 authors = [
   {name = "Vladislav Sovrasov", email = "sovrasov.vlad@gmail.com"},
 ]
@@ -21,7 +21,7 @@ license = {file = "LICENSE"}
 keywords = ["pytorch", "cnn", "transformer"]
 classifiers = [
   "License :: OSI Approved :: MIT License",
-  "Programming Language :: Python :: 3.8"
+  "Programming Language :: Python :: 3.9"
 ]
 
 [project.optional-dependencies]