Add 1 more model and update script (#1527)

Signed-off-by: Tom Wildenhain <[email protected]>

Author: TomWildenhain-Microsoft

tests/cobalt_group_c_perf_testing_models.yaml

@@ -90,11 +90,10 @@ cord-19-swivel-128d:
   converted_model: "D:/co_tfhubmodels_c/cord-19-swivel-128d/model.onnx"
   model_type: saved_model
   large_model: false
-  run_tf_frozen: false
-  use_custom_ops: true
-  input_get: get_sentences
+  input_get: get_ramp
   inputs:
     "sentences:0": [1]
+    "256:0": [1, 512]
   outputs:
     - Identity:0
   rtol: 0.05
@@ -912,6 +911,7 @@ unet-industrial-class_10:
     - "UNet_v1/sigmoid:0"
   rtol: 0.05
   atol: 0.0005
+  ptol: 1.0
   tag: ""
   signature_def: "default"
 
@@ -1337,6 +1337,31 @@ on_device_vision-classifier-landmarks_classifier_africa_V1:
   tag: ""
   signature_def: "default"
 
+tn_bert:
+  disabled: true
+  skip_conversion: true
+  model: "D:/co_tfhubmodels_c/tn_bert"
+  converted_model: "D:/co_tfhubmodels_c/tn_bert/model.onnx"
+  model_type: saved_model
+  large_model: false
+  input_get: get_small_rand_int32
+  inputs:
+    "input_word_ids:0": [1, 512]
+    "input_type_ids:0":
+      shape: [1, 512]
+      input_get: get_zeros_then_ones
+    "input_mask:0":
+      shape: [1, 512]
+      input_get: get_ones_int32
+  outputs:
+    - Identity:0
+    - Identity_1:0
+    - Identity_2:0
+  rtol: 0.05
+  atol: 0.0005
+  tag: "serve"
+  signature_def: "serving_default"
+
 german-tacotron2:
   disabled: true
   skip_conversion: true

tests/run_pretrained_models.py

@@ -419,19 +419,20 @@ def run_tflite():
                 interpreter.invoke()
                 result = [interpreter.get_tensor(output['index']) for output in output_details]
                 return result
-            tf_results = run_tflite()
-            if self.perf:
-                logger.info("Running TFLite perf")
-                n = 0
-                start = time.time()
-                stop = start + PERF_TIME
-                while time.time() < stop:
-                    for _ in range(PERF_STEP):
-                        _ = run_tflite()
-                    n += PERF_STEP
-                self.tf_runtime = 1000 * (time.time() - start) / n
-                logger.info("TFLite perf {:.2f}ms/inference, n={}".format(self.tf_runtime, n))
-            logger.info("TFLite OK")
+            if not self.skip_tensorflow:
+                tf_results = run_tflite()
+                if self.perf:
+                    logger.info("Running TFLite perf")
+                    n = 0
+                    start = time.time()
+                    stop = start + PERF_TIME
+                    while time.time() < stop:
+                        for _ in range(PERF_STEP):
+                            _ = run_tflite()
+                        n += PERF_STEP
+                    self.tf_runtime = 1000 * (time.time() - start) / n
+                    logger.info("TFLite perf {:.2f}ms/inference, n={}".format(self.tf_runtime, n))
+                logger.info("TFLite OK")
 
         if not self.run_tf_frozen:
             inputs = {}