!22988 [bug][Ascend] fix accuracy loss of yolov3_resnet18 post training quantization

Merge pull request !22988 from chenzhuo/master

model_zoo/official/cv/yolov3_resnet18/ascend310_quant_infer/post_quant.py

@@ -21,6 +21,7 @@ from amct_mindspore.quantize_tool import create_quant_config
 from amct_mindspore.quantize_tool import quantize_model
 from amct_mindspore.quantize_tool import save_model
 import mindspore as ms
+import mindspore.ops as ops
 from mindspore import context, Tensor
 from mindspore.train.serialization import load_checkpoint, load_param_into_net
 
@@ -47,8 +48,17 @@ def quant_yolov3_resnet(network, dataset, input_data):
     calibration_network.set_train(False)
 
     # step4: perform the evaluation of network to do activation calibration
+    concat = ops.Concat()
+    index = 0
+    image_data = []
     for data in dataset.create_dict_iterator(num_epochs=1):
-        _ = calibration_network(data["image"], data["image_shape"])
+        index += 1
+        if index == 1:
+            image_data = data["image"]
+        else:
+            image_data = concat((image_data, data["image"]))
+        if index == dataset.get_dataset_size():
+            _ = calibration_network(image_data, data["image_shape"])
 
     # step5: export the air file
     save_model("results/yolov3_resnet_quant", calibration_network, *input_data)
@@ -87,7 +97,7 @@ def export_yolov3_resnet():
         else:
             print("image_dir or anno_path not exits")
     datasets = create_yolo_dataset(mindrecord_file, is_training=False)
-    ds = datasets.take(1)
+    ds = datasets.take(16)
     quant_yolov3_resnet(eval_net, ds, inputs)