test: Update L0_io to work with only 2 GPUs instead of requiring 4 GP…

…Us (#7947)

qa/L0_io/gen_libtorch_model.py

@@ -0,0 +1,90 @@
+#!/usr/bin/python
+# Copyright 2025, NVIDIA CORPORATION & AFFILIATES. All rights reserved.
+#
+# Redistribution and use in source and binary forms, with or without
+# modification, are permitted provided that the following conditions
+# are met:
+#  * Redistributions of source code must retain the above copyright
+#    notice, this list of conditions and the following disclaimer.
+#  * Redistributions in binary form must reproduce the above copyright
+#    notice, this list of conditions and the following disclaimer in the
+#    documentation and/or other materials provided with the distribution.
+#  * Neither the name of NVIDIA CORPORATION nor the names of its
+#    contributors may be used to endorse or promote products derived
+#    from this software without specific prior written permission.
+#
+# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS ``AS IS'' AND ANY
+# EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
+# IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR
+# PURPOSE ARE DISCLAIMED.  IN NO EVENT SHALL THE COPYRIGHT OWNER OR
+# CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL,
+# EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,
+# PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR
+# PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY
+# OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
+# (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
+# OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
+
+import torch
+import torch.nn as nn
+
+
+class SumModule(nn.Module):
+    def __init__(self, device):
+        super(SumModule, self).__init__()
+        self.device = device
+
+    def forward(self, INPUT0, INPUT1):
+        INPUT0 = INPUT0.to(self.device)
+        INPUT1 = INPUT1.to(self.device)
+        print(
+            "SumModule - INPUT0 device: {}, INPUT1 device: {}\n".format(
+                INPUT0.device, INPUT1.device
+            )
+        )
+        return INPUT0 + INPUT1
+
+
+class DiffModule(nn.Module):
+    def __init__(self, device):
+        super(DiffModule, self).__init__()
+        self.device = device
+
+    def forward(self, INPUT0, INPUT1):
+        INPUT0 = INPUT0.to(self.device)
+        INPUT1 = INPUT1.to(self.device)
+        print(
+            "DiffModule - INPUT0 device: {}, INPUT1 device: {}\n".format(
+                INPUT0.device, INPUT1.device
+            )
+        )
+        return INPUT0 - INPUT1
+
+
+class TestModel(nn.Module):
+    def __init__(self, device0, device1):
+        super(TestModel, self).__init__()
+        self.device0 = device0
+        self.device1 = device1
+
+        self.layer1 = SumModule(self.device0)
+        self.layer2 = DiffModule(self.device1)
+
+    def forward(self, INPUT0, INPUT1):
+        op0 = self.layer1(INPUT0, INPUT1)
+        op1 = self.layer2(INPUT0, INPUT1)
+        return op0, op1
+
+
+if torch.cuda.device_count() < 2:
+    print("Need at least 2 GPUs to run this test")
+    exit(1)
+
+devices = [("cuda:1", "cuda:0"), ("cpu", "cuda:1")]
+model_names = ["libtorch_multi_gpu", "libtorch_multi_device"]
+
+for device_pair, model_name in zip(devices, model_names):
+    model = TestModel(device_pair[0], device_pair[1])
+    model_path = "models/" + model_name + "/1/model.pt"
+    scripted_model = torch.jit.script(model)
+    scripted_model.save(model_path)

qa/L0_io/test.sh

@@ -1,5 +1,5 @@
 #!/bin/bash
-# Copyright 2019-2024, NVIDIA CORPORATION & AFFILIATES. All rights reserved.
+# Copyright 2019-2025, NVIDIA CORPORATION & AFFILIATES. All rights reserved.
 #
 # Redistribution and use in source and binary forms, with or without
 # modification, are permitted provided that the following conditions
@@ -38,7 +38,8 @@ if [ ! -z "$TEST_REPO_ARCH" ]; then
     REPO_VERSION=${REPO_VERSION}_${TEST_REPO_ARCH}
 fi
 
-export CUDA_VISIBLE_DEVICES=0,1,2,3
+# This test requires at least 2 GPUs to test h2d and d2d transfer combinations
+export CUDA_VISIBLE_DEVICES=0,1
 
 IO_TEST_UTIL=./memory_alloc
 CLIENT_LOG="./client.log"
@@ -147,7 +148,6 @@ cp -r $ENSEMBLEDIR/nop_TYPE_FP32_-1 $MODELSDIR/. && \
 
 # prepare libtorch multi-device and multi-gpu models
 cp -r ../L0_libtorch_instance_group_kind_model/models/libtorch_multi_device $MODELSDIR/.
-cp ../L0_libtorch_instance_group_kind_model/gen_models.py ./gen_libtorch_model.py
 mkdir -p $MODELSDIR/libtorch_multi_device/1
 mkdir -p $MODELSDIR/libtorch_multi_gpu/1
 cp $MODELSDIR/libtorch_multi_device/config.pbtxt $MODELSDIR/libtorch_multi_gpu/.