Specify input layout (i.e. NHWC) explicitly in tests

Due to a change in the behavior of the upstream [`SetBlob`]( https://github.com/openvinotoolkit/openvino/pull/2402/files#diff-0ec2c2a8d308ceb06e9f0d16319099aa1bb461c49a19e51c5267ced413f25f77R278-R280), `infer_request.set_blob` would fail with a `GeneralError`. In tracking this down, it appears that the blob validation expects the "blocking descriptions" to match. In these tests, we import NHWC tensors so we must now explicitly set this as the input layout.

Author: abrown

crates/openvino/tests/classify-alexnet.rs

@@ -11,7 +11,7 @@ use util::{Prediction, Predictions};
 #[test]
 fn classify_alexnet() {
     let mut core = Core::new(None).unwrap();
-    let network = core
+    let mut network = core
         .read_network_from_file(
             &Fixture::graph().to_string_lossy(),
             &Fixture::weights().to_string_lossy(),
@@ -20,6 +20,7 @@ fn classify_alexnet() {
 
     let input_name = &network.get_input_name(0).unwrap();
     assert_eq!(input_name, "data");
+    network.set_input_layout(input_name, Layout::NHWC).unwrap();
     let output_name = &network.get_output_name(0).unwrap();
     assert_eq!(output_name, "prob");
 

crates/openvino/tests/classify-inception.rs

@@ -11,7 +11,7 @@ use util::{Prediction, Predictions};
 #[test]
 fn classify_inception() {
     let mut core = Core::new(None).unwrap();
-    let network = core
+    let mut network = core
         .read_network_from_file(
             &Fixture::graph().to_string_lossy(),
             &Fixture::weights().to_string_lossy(),
@@ -20,6 +20,7 @@ fn classify_inception() {
 
     let input_name = &network.get_input_name(0).unwrap();
     assert_eq!(input_name, "input");
+    network.set_input_layout(input_name, Layout::NHWC).unwrap();
     let output_name = &network.get_output_name(0).unwrap();
     assert_eq!(output_name, "InceptionV3/Predictions/Softmax");
 

crates/openvino/tests/classify-mobilenet.rs

@@ -12,7 +12,7 @@ use util::{Prediction, Predictions};
 #[test]
 fn classify_mobilenet() {
     let mut core = Core::new(None).unwrap();
-    let network = core
+    let mut network = core
         .read_network_from_file(
             &Fixture::graph().to_string_lossy(),
             &Fixture::weights().to_string_lossy(),
@@ -21,6 +21,7 @@ fn classify_mobilenet() {
 
     let input_name = &network.get_input_name(0).unwrap();
     assert_eq!(input_name, "input");
+    network.set_input_layout(input_name, Layout::NHWC).unwrap();
     let output_name = &network.get_output_name(0).unwrap();
     assert_eq!(output_name, "MobilenetV2/Predictions/Reshape_1");