From 48371618a5b33778897cfed1e554d4c90cde882c Mon Sep 17 00:00:00 2001
From: cmoineau <cyril.moineau@cea.fr>
Date: Fri, 13 Sep 2024 14:04:36 +0000
Subject: [PATCH] Fix gnuplot issue
---
aidge_core/mem_info.py | 26 +++++++++++---------------
1 file changed, 11 insertions(+), 15 deletions(-)
diff --git a/aidge_core/mem_info.py b/aidge_core/mem_info.py
index 720208580..1f2f48dd6 100644
--- a/aidge_core/mem_info.py
+++ b/aidge_core/mem_info.py
@@ -42,7 +42,6 @@ def compute_default_mem_info(scheduler: aidge_core.Scheduler) -> Tuple[int, List
def generate_optimized_memory_info(scheduler: aidge_core.Scheduler, stats_folder: Path, wrapping: bool = False) -> Tuple[int, List[dict]]:
-
# The forward dims has to done outside the function
# Also supposed the generation of the scheduler has been performed outside
# Otherwise decomment the following line
@@ -55,18 +54,16 @@ def generate_optimized_memory_info(scheduler: aidge_core.Scheduler, stats_folder
# List of nodes which are connected at the input of the graph (None if input is not connected)
nodes_at_input = [n[0] for n in scheduler.graph_view().inputs()]
# Use gnuplot to generate the log
- try:
- os.makedirs(str(stats_folder / "graph"), exist_ok=True)
- mem_manager.log("memory_info")
- os.chmod("memory_info_plot.gnu", 0o777)
- os.system("./memory_info_plot.gnu")
- shutil.move("memory_info", str(stats_folder / "graph" / "memory_info"))
- shutil.move("memory_info_plot.png", str(
- stats_folder / "graph" / "memory_info_plot.png"))
- os.remove("memory_info_plot.gnu")
- except:
- print("Please install gnuplot if you want memory plot from MemoryManager.")
-
+ if isinstance(stats_folder, str):
+ stats_folder = Path(stats_folder)
+ os.makedirs(str(Path(stats_folder) / "graph"), exist_ok=True)
+ mem_manager.log("memory_info")
+ os.chmod("memory_info_plot.gnu", 0o777)
+ os.system("./memory_info_plot.gnu")
+ shutil.move("memory_info", str(Path(stats_folder) / "graph" / "memory_info"))
+ shutil.move("memory_info_plot.png", str(
+ Path(stats_folder) / "graph" / "memory_info_plot.png"))
+ os.remove("memory_info_plot.gnu")
# In the export, we currently use an unified memory buffer whose size
# is determined by the memory peak usage
mem_size = mem_manager.get_peak_usage()
@@ -86,7 +83,6 @@ def generate_optimized_memory_info(scheduler: aidge_core.Scheduler, stats_folder
if len(tensor.dims()) < 3:
raise RuntimeError(
f"Input producer dimensions must be with [:, channel, height, width] but got {tensor.dims()} instead")
-
# TODO : use get_chan get_height and get_width function !
node_mem_info.append({
"size": tensor.dims()[-3], # Should be nb_channels
@@ -108,7 +104,7 @@ def generate_optimized_memory_info(scheduler: aidge_core.Scheduler, stats_folder
plane = mem_planes[node][out_id]
node_mem_info.append({
"size": plane.size,
- "offset": plane.offset,
+ "offset": plane.get_contiguous_offset(),
"stride": plane.stride,
"length": plane.length,
"count": plane.count,
--
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