@@ -203,7 +203,7 @@ def __init__(
203203 # Add no validation models
204204 self .options_ .append (
205205 PerfAnalyzerScenario .ModelOption (
206- "resnet_v1_50_def " , 32 , (1 , 4 , 1 ), queue_latency_range_us
206+ "resnet_v1_50 " , 32 , (1 , 4 , 1 ), queue_latency_range_us
207207 )
208208 )
209209 for trial in sequence_trials :
@@ -334,7 +334,7 @@ def run(self, client_metadata):
334334class ResNetScenario (Scenario ):
335335 def __init__ (self , name , batch_size = 32 , verbose = False , out_stream = sys .stdout ):
336336 super ().__init__ (name , [], verbose , out_stream )
337- self .model_name_ = "resnet_v1_50_def "
337+ self .model_name_ = "resnet_v1_50 "
338338 self .batch_size_ = batch_size
339339
340340 img = self .preprocess ("../images/vulture.jpeg" )
@@ -353,7 +353,7 @@ def preprocess(self, filename):
353353 return scaled
354354
355355 def postprocess (self , results ):
356- output_array = results .as_numpy ("resnet_v1_50/predictions/Softmax" )
356+ output_array = results .as_numpy ("resnet_v1_50/predictions/Softmax:0 " )
357357 if len (output_array ) != self .batch_size_ :
358358 raise Exception (
359359 "expected {} results, got {}" .format (
@@ -377,12 +377,12 @@ def postprocess(self, results):
377377 def run (self , client_metadata ):
378378 triton_client = client_metadata [0 ]
379379
380- inputs = [grpcclient .InferInput ("input" , self .image_data_ .shape , "FP32" )]
380+ inputs = [grpcclient .InferInput ("input:0 " , self .image_data_ .shape , "FP32" )]
381381 inputs [0 ].set_data_from_numpy (self .image_data_ )
382382
383383 outputs = [
384384 grpcclient .InferRequestedOutput (
385- "resnet_v1_50/predictions/Softmax" , class_count = 1
385+ "resnet_v1_50/predictions/Softmax:0 " , class_count = 1
386386 )
387387 ]
388388 res = triton_client .infer (self .model_name_ , inputs , outputs = outputs )
0 commit comments