Update the model to use the same add sub logic

Author: krishung5

qa/L0_libtorch_instance_group_kind_model/client.py

@@ -78,8 +78,8 @@ def test_infer(self):
         output0_data = results.as_numpy('OUTPUT__0')
         output1_data = results.as_numpy('OUTPUT__1')
 
-        expected_output_0 = input0_data + input0_data
-        expected_output_1 = input1_data + input1_data
+        expected_output_0 = input0_data + input1_data
+        expected_output_1 = input0_data - input1_data
 
         self.assertEqual(output0_data.shape, (1, 16))
         self.assertEqual(output1_data.shape, (1, 16))

qa/L0_libtorch_instance_group_kind_model/gen_models.py

@@ -30,36 +30,47 @@
 
 
 class SumModule(nn.Module):
-
     def __init__(self):
         super(SumModule, self).__init__()
 
-    def forward(self, x):
-        return torch.sum(x, dim=1)
+    def forward(self, INPUT0, INPUT1):
+        print('SumModule - INPUT0 device: {}, INPUT1 device: {}\n'.format(
+            INPUT0.device, INPUT1.device))
+        return INPUT0 + INPUT1
+
+class DiffModule(nn.Module):
+    def __init__(self):
+        super(DiffModule, self).__init__()
+
+    def forward(self, INPUT0, INPUT1):
+        print('DiffModule - INPUT0 device: {}, INPUT1 device: {}\n'.format(
+            INPUT0.device, INPUT1.device))
+        return INPUT0 - INPUT1
 
 
 class TestModel(nn.Module):
 
-    def __init__(self, device1, device2):
+    def __init__(self, device0, device1):
         super(TestModel, self).__init__()
+        self.device0 = device0
         self.device1 = device1
-        self.device2 = device2
-        self.layers1 = SumModule().to(self.device1)
-        self.layers2 = SumModule().to(self.device2)
+
+        self.layers1 = SumModule().to(self.device0)
+        self.layers2 = DiffModule().to(self.device1)
 
     def forward(self, INPUT0, INPUT1):
-        INPUT0 = INPUT0.to(self.device1)
-        INPUT1 = INPUT1.to(self.device2)
-        print('INPUT0 device: {}, INPUT1 device: {}\n'.format(
-            INPUT0.device, INPUT1.device))
+        INPUT0_0 = INPUT0.to(self.device0)
+        INPUT0_1 = INPUT0.to(self.device1)
+        INPUT1_0 = INPUT1.to(self.device0)
+        INPUT1_1 = INPUT1.to(self.device1)
 
-        op0 = self.layers1(torch.stack([INPUT0, INPUT0], dim=1))
-        op1 = self.layers2(torch.stack([INPUT1, INPUT1], dim=1))
+        op0 = self.layers1(INPUT0_0, INPUT1_0)
+        op1 = self.layers2(INPUT0_1, INPUT1_1)
         return op0, op1
 
 
 devices = [("cuda:2", "cuda:0"), ("cpu", "cuda:3")]
-model_names = ["libtorch_multi_gpu", "libtorch_multi_devices"]
+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])

qa/L0_libtorch_instance_group_kind_model/models/libtorch_multi_devices/config.pbtxt renamed to qa/L0_libtorch_instance_group_kind_model/models/libtorch_multi_device/config.pbtxt

@@ -24,7 +24,7 @@
 # (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
 # OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
 
-name: "libtorch_multi_devices"
+name: "libtorch_multi_device"
 platform: "pytorch_libtorch"
 max_batch_size: 8
 

qa/L0_libtorch_instance_group_kind_model/test.sh

@@ -57,11 +57,11 @@ RET=0
 
 rm -f *.log *.txt
 
-mkdir -p models/libtorch_multi_devices/1
+mkdir -p models/libtorch_multi_device/1
 mkdir -p models/libtorch_multi_gpu/1
-cp models/libtorch_multi_devices/config.pbtxt models/libtorch_multi_gpu/.
+cp models/libtorch_multi_device/config.pbtxt models/libtorch_multi_gpu/.
 (cd models/libtorch_multi_gpu && \
-    sed -i "s/name: \"libtorch_multi_devices\"/name: \"libtorch_multi_gpu\"/" config.pbtxt)
+    sed -i "s/name: \"libtorch_multi_device\"/name: \"libtorch_multi_gpu\"/" config.pbtxt)
 
 # Generate the models which are partioned across multiple devices
 set +e
@@ -82,8 +82,7 @@ fi
 
 set +e
 
-MESSAGE="INPUT0 device: cpu, INPUT1 device: cuda:3"
-export MODEL_NAME='libtorch_multi_devices'
+export MODEL_NAME='libtorch_multi_device'
 python3 $CLIENT_PY >> $CLIENT_LOG 2>&1 
 if [ $? -ne 0 ]; then
     echo -e "\n***\n*** Model $MODEL_NAME FAILED. \n***"
@@ -98,14 +97,17 @@ else
     fi
 fi
 
-if grep "$MESSAGE" $SERVER_LOG; then
-    echo -e "Found \"$MESSAGE\"" >> $CLIENT_LOG
-else
-    echo -e "Not found \"$MESSAGE\"" >> $CLIENT_LOG
-    RET=1
-fi
+MESSAGES=("SumModule - INPUT0 device: cpu, INPUT1 device: cpu"
+    "DiffModule - INPUT0 device: cuda:3, INPUT1 device: cuda:3")
+for MESSAGE in "${MESSAGES[@]}"; do
+    if grep -q "$MESSAGE" "$SERVER_LOG"; then
+        echo -e "Found \"$MESSAGE\"" >> "$CLIENT_LOG"
+    else
+        echo -e "Not found \"$MESSAGE\"" >> "$CLIENT_LOG"
+        RET=1
+    fi
+done
 
-MESSAGE="INPUT0 device: cuda:2, INPUT1 device: cuda:0"
 export MODEL_NAME='libtorch_multi_gpu'
 python3 $CLIENT_PY >> $CLIENT_LOG 2>&1 
 if [ $? -ne 0 ]; then
@@ -121,12 +123,16 @@ else
     fi
 fi
 
-if grep "$MESSAGE" $SERVER_LOG; then
-    echo -e "Found \"$MESSAGE\"" >> $CLIENT_LOG
-else
-    echo -e "Not found \"$MESSAGE\"" >> $CLIENT_LOG
-    RET=1
-fi
+MESSAGES=("SumModule - INPUT0 device: cuda:2, INPUT1 device: cuda:2"
+    "DiffModule - INPUT0 device: cuda:0, INPUT1 device: cuda:0")
+for MESSAGE in "${MESSAGES[@]}"; do
+    if grep -q "$MESSAGE" "$SERVER_LOG"; then
+        echo -e "Found \"$MESSAGE\"" >> "$CLIENT_LOG"
+    else
+        echo -e "Not found \"$MESSAGE\"" >> "$CLIENT_LOG"
+        RET=1
+    fi
+done
 
 set -e