Question

Tensorflow图形转换页面https://github.com/tensorflow/tensorflow/blob/master/tensorflow/tools/graph_transforms/README.md显示了如何使用strip_unused_nodes。但是，如何知道我的模型在strip_unused_nodes(type=X, shape="y0,y1,y3,3")中正确的X和Y值？

在我的MobileNetV2模型上summarize_graph的输出：

Found 1 possible inputs: (name=image_tensor, type=uint8(4), shape=[?,?,?,3]) 
No variables spotted.
Found 4 possible outputs: (name=detection_boxes, op=Identity) (name=detection_scores, op=Identity) (name=detection_classes, op=Identity) (name=num_detections, op=Identity) 
Found 3457096 (3.46M) const parameters, 0 (0) variable parameters, and 623 control_edges
Op types used: 1707 Const, 525 Identity, 277 Mul, 194 Add, 170 Reshape, 147 GatherV2, 133 Sub, 117 Minimum, 98 Slice, 92 Maximum, 77 ConcatV2, 77 Cast, 64 Rsqrt, 60 StridedSlice, 59 Relu6, 55 Conv2D, 54 Pack, 52 Greater, 49 Shape, 46 Split, 46 Where, 45 ExpandDims, 40 Fill, 37 Tile, 33 RealDiv, 33 DepthwiseConv2dNative, 30 Range, 29 Switch, 27 Unpack, 26 Enter, 25 Squeeze, 25 ZerosLike, 23 NonMaxSuppressionV2, 14 Merge, 12 BiasAdd, 12 FusedBatchNorm, 11 TensorArrayV3, 8 NextIteration, 6 TensorArrayWriteV3, 6 TensorArraySizeV3, 6 Sqrt, 6 Exit, 6 TensorArrayGatherV3, 5 TensorArrayScatterV3, 5 TensorArrayReadV3, 3 Rank, 3 Equal, 3 Transpose, 3 Assert, 2 Exp, 2 Less, 2 LoopCond, 1 All, 1 TopKV2, 1 Size, 1 Sigmoid, 1 ResizeBilinear, 1 Placeholder
To use with tensorflow/tools/benchmark:benchmark_model try these arguments:
bazel run tensorflow/tools/benchmark:benchmark_model -- --graph=/home/ubuntu/model-optimization/frozen_inference_graph.pb --show_flops --input_layer=image_tensor --input_layer_type=uint8 --input_layer_shape=-1,-1,-1,3 --output_layer=detection_boxes,detection_scores,detection_classes,num_detections

Answer 1

我相信您应该复制输入层的暗淡，可以在模型的.ascii文件中找到

strip_unused_nodes的正确参数

1 个答案: