From a7b68379a5d4952c82f1df77f6f583ae166aa9b5 Mon Sep 17 00:00:00 2001
From: NAUD Maxence <maxence.naud@cea.fr>
Date: Thu, 3 Apr 2025 12:10:59 +0000
Subject: [PATCH] add: function to get inference time and output of some
GraphView
---
aidge_backend_cuda/__init__.py | 2 +-
aidge_backend_cuda/benchmark.py | 47 +++++++++++++++++++++++++++++++++
2 files changed, 48 insertions(+), 1 deletion(-)
create mode 100644 aidge_backend_cuda/benchmark.py
diff --git a/aidge_backend_cuda/__init__.py b/aidge_backend_cuda/__init__.py
index 7b57dd6..889bf00 100644
--- a/aidge_backend_cuda/__init__.py
+++ b/aidge_backend_cuda/__init__.py
@@ -1,2 +1,2 @@
from aidge_backend_cuda.aidge_backend_cuda import * # import so generated by PyBind
-
+from . import benchmark
diff --git a/aidge_backend_cuda/benchmark.py b/aidge_backend_cuda/benchmark.py
new file mode 100644
index 0000000..a163c09
--- /dev/null
+++ b/aidge_backend_cuda/benchmark.py
@@ -0,0 +1,47 @@
+import time
+
+import numpy as np
+
+import aidge_core
+import aidge_backend_cuda
+
+def measure_inference_time(model: aidge_core.GraphView, input_data: list[str, np.ndarray], nb_warmup: int = 10, nb_iterations: int = 50) -> list[float]:
+ # update model and inputs backend
+ model.set_backend("cuda")
+ ordered_inputs = [aidge_core.Tensor(i[1]) for i in input_data]
+ for ordered_input in ordered_inputs:
+ ordered_input.set_backend("cuda")
+
+ scheduler = aidge_core.SequentialScheduler(model)
+ scheduler.generate_scheduling()
+
+ timings = []
+ # Warm-up runs.
+ for i in range(nb_warmup + nb_iterations):
+ if i < nb_warmup:
+ scheduler.forward(forward_dims=False, data=ordered_inputs)
+ else:
+ start = time.process_time()
+ scheduler.forward(forward_dims=False, data=ordered_inputs)
+ end = time.process_time()
+ timings.append((end - start))
+ return timings
+
+def compute_output(model: aidge_core.GraphView, input_data: list[str, np.ndarray]) -> list[np.ndarray]:
+ # update model and inputs backend
+ model.set_backend("cuda", device = 1)
+ ordered_inputs = [aidge_core.Tensor(i[1]) for i in input_data]
+ for ordered_input in ordered_inputs:
+ ordered_input.set_backend("cuda", device = 1)
+
+ scheduler = aidge_core.SequentialScheduler(model)
+ scheduler.generate_scheduling()
+
+ scheduler.forward(forward_dims=False, data=ordered_inputs)
+ outs = []
+ for pair in model.get_ordered_outputs():
+ t = pair[0].get_operator().get_output(pair[1])
+ t.set_backend("cpu")
+ outs.append(t)
+
+ return [np.array(out) for out in outs]
\ No newline at end of file
--
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