run benchmarks

README.md

@@ -22,7 +22,7 @@ pip install deepinv[benchmarks]
 and then run on python:
 
 ```python
-from deepinv.benchmarks import run_benchmark
+from deepinv_bench import run_benchmark
 my_solver = lambda y, physics: ...  # your solver here
 results = run_benchmark(my_solver, "benchmark_name")
 ```

pyproject.toml

@@ -0,0 +1,12 @@
+[build-system]
+requires = ["setuptools>=61.0.0"]
+build-backend = "setuptools.build_meta"
+
+[project]
+name = "deepinv_bench"
+version = "0.0.1"
+dependencies = [
+    "torch",
+    "deepinv",
+    "benchopt"
+]

run.py

@@ -0,0 +1,23 @@
+import deepinv as dinv
+import torch
+import benchopt
+
+def run_benchmark(model : dinv.models.Reconstructor | torch.nn.Module, benchmark_name : str):
+    r"""
+    Run a benchmark on a given model.
+
+
+    :param dinv.models.Reconstructor | torch.nn.Module model:
+    :param str benchmark_name: Name of the benchmark to run.
+    :return: dict with benchmark results, including metrics and runtime.
+    """
+
+    # TODO: how can we do this with benchopt?
+
+    return results
+
+
+if __name__ == "__main__":
+    solver = dinv.models.RAM()
+    results = run_benchmark(solver, "div2k_gaussian_deblurring")
+    print(results)