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1051 lines
29 KiB
JSON
1051 lines
29 KiB
JSON
[
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{
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"name": "input_layer",
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"description": "Represents an input of the model",
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"attributes": [
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{
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"name": "original_names",
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"type": "string[]",
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"description": "Name of this layer in the original framework, such as Pytorch or Tensorflow",
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"visible": false
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}
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]
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},
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{
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"name": "output_layer",
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"description": "Represents an output of the model",
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"attributes": [
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{
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"name": "original_names",
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"type": "string[]",
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|
"description": "Name of this layer in the original framework, such as Pytorch or Tensorflow",
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"visible": false
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}]
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},
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{
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"name": "postprocess",
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"description": "Represents a whole post-processing function of some meta-architecture",
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"attributes": [
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{
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"name": "original_names",
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|
"type": "string[]",
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|
"description": "Name of this layer in the original framework, such as Pytorch or Tensorflow",
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"visible": false
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},
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{
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"name": "max_proposals_per_class",
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"type": "int64",
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"description": "Maximum number of proposals per class",
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"visible": false
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|
},
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{
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"name": "iou_th",
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"type": "float32",
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"visible": false,
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"description": "Intersection over union overlap threshold, used in the NMS iterative elimination process where potential duplicates of detected items are ignored"
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},
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{
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"name": "meta_arch",
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"type": "string",
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"visible": false,
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"description": "Postprocessing meta-architecture name"
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},
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{
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|
"name": "max_total_output_proposals",
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"type": "int64",
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"visible": false,
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"description": "Maximum number of bounding box proposals"
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},
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{
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"name": "postprocess_type",
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"type": "string",
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"visible": false,
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"description": "Postprocessing type name"
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}
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]
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},
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{
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"name": "conv",
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"category": "Layer",
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"description": "Convolution layer",
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|
"attributes": [
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{
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"name": "original_names",
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|
"type": "string[]",
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|
"description": "Name of this layer in the original framework, such as Pytorch or Tensorflow",
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|
"visible": false
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|
},
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|
{
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|
"name": "kernel_shape",
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"type": "int64[]",
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|
"label": "kernel",
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"description": "Shape of the kernel in Tensorflow convention (kernel height, kernel width, features in, features out)",
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"visible": true
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},
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{
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"name": "strides",
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|
"type": "int64[]",
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"description": "Stride along each axis (batch, height, width, features)"
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|
},
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|
{
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|
"name": "dilations",
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"type": "int64[]",
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"description": "Dilation value along each axis (batch, height, width, features)"
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},
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|
{
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"name": "padding",
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"type": "string",
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"description": "Padding mode, either VALID, SAME (symmetric, Caffe-like), SAME_TENSORFLOW, or DECONV"
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|
},
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{
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"name": "groups",
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|
"type": "int64",
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"description": "Number of groups input channels and output channels are divided into"
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|
},
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{
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|
"name": "batch_norm",
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"type": "boolean",
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|
"description": "Whether batch normalization is folded into the layer"
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|
},
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{
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|
"name": "elementwise_add",
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|
"type": "boolean",
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|
"description": "Whether elementwise addition is folded into the layer",
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"visible": false
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|
},
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{
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|
"name": "activation",
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|
"type": "string",
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"description": "Activation function name",
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"visible": false
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},
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{
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"name": "pre_layer_batch_norm",
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"type": "boolean",
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"description": "Whether batch normalization is folded into the layer, before the operation itself",
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"visible": false
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},
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{
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"name": "transpose_output_width_features",
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"type": "boolean",
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"description": "Whether to transpose the width and the features axes of the layer's output tensor",
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"visible": false
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},
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{
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"name": "spatial_flatten_output",
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"type": "boolean",
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"description": "Whether to flatten the layer's output to one row",
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"visible": false
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}
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]
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},
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{
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"name": "relu",
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"category": "Activation"
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},
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{
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"name": "delta",
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"category": "Activation"
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},
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{
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"name": "activation",
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"category": "Activation",
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"description": "Activation function",
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"attributes": [
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{
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"name": "original_names",
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"type": "string[]",
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"description": "Name of this layer in the original framework, such as Pytorch or Tensorflow",
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"visible": false
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},
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{
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"name": "batch_norm",
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"type": "boolean",
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"description": "Whether batch normalization is folded into the layer",
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"visible": false
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},
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{
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"name": "elementwise_add",
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"type": "boolean",
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"description": "Whether elementwise addition is folded into the layer",
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"visible": false
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},
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{
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"name": "activation",
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"type": "string",
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"description": "Activation function name",
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"visible": false
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}
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]
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},
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{
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"name": "argmax",
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"description": "Argmax layer",
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"attributes": [
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{
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"name": "original_names",
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"type": "string[]",
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"description": "Name of this layer in the original framework, such as Pytorch or Tensorflow",
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"visible": false
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}]
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},
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{
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"name": "avgpool",
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"category": "Pool",
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|
"description": "Average pooling layer",
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"attributes": [
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{
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|
"name": "original_names",
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"type": "string[]",
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|
"description": "Name of this layer in the original framework, such as Pytorch or Tensorflow",
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"visible": false
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},
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{
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"name": "kernel_shape",
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"type": "int64[]",
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"label": "kernel",
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"description": "Shape of the kernel in Tensorflow convention (kernel height, kernel width, features in, features out)",
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"visible": true
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},
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{
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|
"name": "strides",
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"type": "int64[]",
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"description": "Stride along each axis (batch, height, width, features)",
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"visible": false
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},
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{
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"name": "padding",
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"type": "string",
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"description": "Padding mode, either VALID, SAME (symmetric, Caffe-like), SAME_TENSORFLOW, or DECONV",
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"visible": false
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|
},
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{
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"name": "activation",
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"type": "string",
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"description": "Activation function name",
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"visible": false
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}
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]
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},
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{
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"name": "batch_norm",
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"category": "Normalization",
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"description": "Batch normalization layer",
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|
"attributes": [
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{
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|
"name": "original_names",
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"type": "string[]",
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"description": "Name of this layer in the original framework, such as Pytorch or Tensorflow",
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"visible": false
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|
},
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{
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|
"name": "elementwise_add",
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|
"type": "boolean",
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|
"description": "Whether elementwise addition is folded into the layer",
|
|
"visible": false
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|
},
|
|
{
|
|
"name": "activation",
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|
"type": "string",
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|
"description": "Activation function name",
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"visible": false
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}
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]
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},
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{
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"name": "bbox_decoder",
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"description": "Bounding box decoding layer",
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"attributes": [
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{
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"name": "original_names",
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"type": "string[]",
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|
"description": "Name of this layer in the original framework, such as Pytorch or Tensorflow",
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"visible": false
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}
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]
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},
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{
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"name": "deconv",
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"category": "Layer",
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"description": "Deconvolution (transposed convolution) layer",
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|
"attributes": [
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{
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"name": "original_names",
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|
"type": "string[]",
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|
"description": "Name of this layer in the original framework, such as Pytorch or Tensorflow",
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"visible": false
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},
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{
|
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"name": "kernel_shape",
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"type": "int64[]",
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"label": "kernel",
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|
"description": "Shape of the kernel in Tensorflow convention (kernel height, kernel width, features in, features out)",
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"visible": true
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|
},
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|
{
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|
"name": "strides",
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|
"type": "int64[]",
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|
"description": "Stride along each axis (batch, height, width, features)",
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|
"visible": false
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|
},
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|
{
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|
"name": "dilations",
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|
"type": "int64[]",
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"description": "Dilation value along each axis (batch, height, width, features)",
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"visible": false
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|
},
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|
{
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|
"name": "padding",
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|
"type": "string",
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|
"description": "Padding mode, either VALID, SAME (symmetric, Caffe-like), SAME_TENSORFLOW, or DECONV",
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|
"visible": false
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|
},
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{
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|
"name": "groups",
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|
"type": "int64",
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|
"description": "Number of groups input channels and output channels are divided into",
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|
"visible": false
|
|
},
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|
{
|
|
"name": "batch_norm",
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|
"type": "boolean",
|
|
"description": "Whether batch normalization is folded into the layer",
|
|
"visible": false
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|
},
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|
{
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|
"name": "elementwise_add",
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|
"type": "boolean",
|
|
"description": "Whether elementwise addition is folded into the layer",
|
|
"visible": false
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|
},
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|
{
|
|
"name": "activation",
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|
"type": "string",
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|
"description": "Activation function name",
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"visible": false
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}
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]
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},
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{
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"name": "dense",
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"category": "Layer",
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"description": "Dense (fully connected) layer",
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"attributes": [
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{
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|
"name": "original_names",
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|
"type": "string[]",
|
|
"description": "Name of this layer in the original framework, such as Pytorch or Tensorflow",
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|
"visible": false
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|
},
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|
{
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|
"name": "kernel_shape",
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|
"type": "int64[]",
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|
"label": "kernel",
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|
"description": "Shape of the kernel in Tensorflow convention (kernel height, kernel width, features in, features out)",
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|
"visible": true
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|
},
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|
{
|
|
"name": "batch_norm",
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"type": "boolean",
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|
"description": "Whether batch normalization is folded into the layer",
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|
"visible": false
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|
}
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]
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},
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{
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"name": "depth_to_space",
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|
"description": "Depth to space layer",
|
|
"attributes": [
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|
{
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|
"name": "original_names",
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|
"type": "string[]",
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|
"description": "Name of this layer in the original framework, such as Pytorch or Tensorflow",
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|
"visible": false
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|
},
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|
{
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|
"name": "block_sizes",
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|
"type": "int64[]",
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|
"description": "Block size along each spatial axis",
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|
"visible": false
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|
},
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|
{
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|
"name": "depth_to_space_type",
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"type": "string",
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"description": "Depth to space variant, either dcr (depth-column-row) or crd (column-row-depth)",
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"visible": false
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}
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]
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},
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{
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"name": "dw",
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"description": "Depthwise convolution layer",
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|
"attributes": [
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{
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"name": "original_names",
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|
"type": "string[]",
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|
"description": "Name of this layer in the original framework, such as Pytorch or Tensorflow",
|
|
"visible": false
|
|
},
|
|
{
|
|
"name": "kernel_shape",
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|
"type": "int64[]",
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|
"label": "kernel",
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|
"description": "Shape of the kernel in Tensorflow convention (kernel height, kernel width, features in, features out)",
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"visible": true
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|
},
|
|
{
|
|
"name": "strides",
|
|
"type": "int64[]",
|
|
"description": "Stride along each axis (batch, height, width, features)",
|
|
"visible": false
|
|
},
|
|
{
|
|
"name": "dilations",
|
|
"type": "int64[]",
|
|
"description": "Dilation value along each axis (batch, height, width, features)",
|
|
"visible": false
|
|
},
|
|
{
|
|
"name": "padding",
|
|
"type": "string",
|
|
"description": "Padding mode, either VALID, SAME (symmetric, Caffe-like), SAME_TENSORFLOW, or DECONV",
|
|
"visible": false
|
|
},
|
|
{
|
|
"name": "groups",
|
|
"type": "int64",
|
|
"description": "Number of groups input channels and output channels are divided into",
|
|
"visible": false
|
|
},
|
|
{
|
|
"name": "batch_norm",
|
|
"type": "boolean",
|
|
"description": "Whether batch normalization is folded into the layer",
|
|
"visible": false
|
|
},
|
|
{
|
|
"name": "elementwise_add",
|
|
"type": "boolean",
|
|
"description": "Whether elementwise addition is folded into the layer",
|
|
"visible": false
|
|
},
|
|
{
|
|
"name": "activation",
|
|
"type": "string",
|
|
"description": "Activation function name",
|
|
"visible": false
|
|
},
|
|
{
|
|
"name": "transpose_output_width_features",
|
|
"type": "string",
|
|
"description": "Whether to transpose the width and the features axes of the layer's output tensor",
|
|
"visible": false
|
|
},
|
|
{
|
|
"name": "dynamic_weights",
|
|
"type": "boolean",
|
|
"description": "Whether the layer's weights are data driven",
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|
"visible": false
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|
}
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|
]
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|
},
|
|
{
|
|
"name": "external_pad",
|
|
"description": "Padding layer",
|
|
"attributes": [
|
|
{
|
|
"name": "original_names",
|
|
"type": "string[]",
|
|
"description": "Name of this layer in the original framework, such as Pytorch or Tensorflow",
|
|
"visible": false
|
|
},
|
|
{
|
|
"name": "external_pad_params",
|
|
"type": "int64[]",
|
|
"description": "Padding value in pixels in each edge (top, bottom, left, right)",
|
|
"visible": false
|
|
}
|
|
]
|
|
},
|
|
{
|
|
"name": "feature_interleave",
|
|
"description": "Feature interleave layer",
|
|
"attributes": [
|
|
{
|
|
"name": "original_names",
|
|
"type": "string[]",
|
|
"description": "Name of this layer in the original framework, such as Pytorch or Tensorflow",
|
|
"visible": false
|
|
}]
|
|
},
|
|
{
|
|
"name": "feature_multiplier",
|
|
"description": "Elementwise feature multiplication layer",
|
|
"attributes": [
|
|
{
|
|
"name": "original_names",
|
|
"type": "string[]",
|
|
"description": "Name of this layer in the original framework, such as Pytorch or Tensorflow",
|
|
"visible": false
|
|
},
|
|
{
|
|
"name": "feature_multiplier_type",
|
|
"type": "string",
|
|
"description": "Feature multiplier variant, either square (to multiply each value by itself), or user_specified",
|
|
"visible": false
|
|
}
|
|
]
|
|
},
|
|
{
|
|
"name": "feature_shuffle",
|
|
"description": "Feature shuffle layer",
|
|
"attributes": [
|
|
{
|
|
"name": "original_names",
|
|
"type": "string[]",
|
|
"description": "Name of this layer in the original framework, such as Pytorch or Tensorflow",
|
|
"visible": false
|
|
}]
|
|
},
|
|
{
|
|
"name": "format_conversion",
|
|
"description": "Reshapes the input tensor between different memory layouts",
|
|
"attributes": [
|
|
{
|
|
"name": "original_names",
|
|
"type": "string[]",
|
|
"description": "Name of this layer in the original framework, such as Pytorch or Tensorflow",
|
|
"visible": false
|
|
},
|
|
{
|
|
"name": "expand_spatial_sizes",
|
|
"type": "int64[]",
|
|
"description": "New output tensor dimensions after the reshape (height, width)",
|
|
"visible": false
|
|
},
|
|
{
|
|
"name": "conversion_type",
|
|
"type": "string",
|
|
"visible": false,
|
|
"description": "Format conversion variant"
|
|
}
|
|
]
|
|
},
|
|
{
|
|
"name": "global_avg_pool",
|
|
"category": "Pool",
|
|
"description": "Global average pooling layer",
|
|
"attributes": [
|
|
{
|
|
"name": "original_names",
|
|
"type": "string[]",
|
|
"description": "Name of this layer in the original framework, such as Pytorch or Tensorflow",
|
|
"visible": false
|
|
}]
|
|
},
|
|
{
|
|
"name": "maxpool",
|
|
"category": "Pool",
|
|
"description": "Maximum pooling layer",
|
|
"attributes": [
|
|
{
|
|
"name": "original_names",
|
|
"type": "string[]",
|
|
"description": "Name of this layer in the original framework, such as Pytorch or Tensorflow",
|
|
"visible": false
|
|
},
|
|
{
|
|
"name": "kernel_shape",
|
|
"type": "int64[]",
|
|
"label": "kernel",
|
|
"description": "Shape of the kernel in Tensorflow convention (kernel height, kernel width, features in, features out)",
|
|
"visible": true
|
|
},
|
|
{
|
|
"name": "strides",
|
|
"type": "int64[]",
|
|
"description": "Stride along each axis (batch, height, width, features)",
|
|
"visible": false
|
|
},
|
|
{
|
|
"name": "padding",
|
|
"type": "string",
|
|
"description": "Padding mode, either VALID, SAME (symmetric, Caffe-like), SAME_TENSORFLOW, or DECONV",
|
|
"visible": false
|
|
},
|
|
{
|
|
"name": "activation",
|
|
"type": "string",
|
|
"description": "Activation function name",
|
|
"visible": false
|
|
}
|
|
]
|
|
},
|
|
{
|
|
"name": "nms",
|
|
"description": "Non-maximum suppression layer",
|
|
"attributes": [
|
|
{
|
|
"name": "original_names",
|
|
"type": "string[]",
|
|
"description": "Name of this layer in the original framework, such as Pytorch or Tensorflow",
|
|
"visible": false
|
|
},
|
|
{
|
|
"name": "scores_threshold",
|
|
"type": "float32",
|
|
"description": "Confidence threshold for NMS filtering",
|
|
"visible": false
|
|
},
|
|
{
|
|
"name": "iou_threshold",
|
|
"type": "float32",
|
|
"description": "Intersection over union overlap threshold, used in the NMS iterative elimination process where potential duplicates of detected items are ignored",
|
|
"visible": false
|
|
},
|
|
{
|
|
"name": "classes",
|
|
"type": "int64",
|
|
"description": "Number of NMS classes",
|
|
"visible": false
|
|
},
|
|
{
|
|
"name": "max_output_size",
|
|
"type": "int64",
|
|
"description": "Maximum number of proposals per class",
|
|
"visible": false
|
|
}
|
|
]
|
|
},
|
|
{
|
|
"name": "normalization",
|
|
"category": "Normalization",
|
|
"description": "Normalization layer",
|
|
"attributes": [
|
|
{
|
|
"name": "original_names",
|
|
"type": "string[]",
|
|
"description": "Name of this layer in the original framework, such as Pytorch or Tensorflow",
|
|
"visible": false
|
|
},
|
|
{
|
|
"name": "elementwise_add",
|
|
"type": "boolean",
|
|
"description": "Whether elementwise addition is folded into the layer",
|
|
"visible": false
|
|
},
|
|
{
|
|
"name": "activation",
|
|
"type": "string",
|
|
"description": "Activation function name",
|
|
"visible": false
|
|
}
|
|
]
|
|
},
|
|
{
|
|
"name": "proposal_generator",
|
|
"description": "Proposal generator layer",
|
|
"attributes": [
|
|
{
|
|
"name": "original_names",
|
|
"type": "string[]",
|
|
"description": "Name of this layer in the original framework, such as Pytorch or Tensorflow",
|
|
"visible": false
|
|
}]
|
|
},
|
|
{
|
|
"name": "reduce_l2",
|
|
"description": "Reduce layer",
|
|
"attributes": [
|
|
{
|
|
"name": "original_names",
|
|
"type": "string[]",
|
|
"description": "Name of this layer in the original framework, such as Pytorch or Tensorflow",
|
|
"visible": false
|
|
}]
|
|
},
|
|
{
|
|
"name": "reduce_max",
|
|
"description": "Reduce Max layer",
|
|
"attributes": [
|
|
{
|
|
"name": "original_names",
|
|
"type": "string[]",
|
|
"description": "Name of this layer in the original framework, such as Pytorch or Tensorflow",
|
|
"visible": false
|
|
},
|
|
{
|
|
"name": "groups",
|
|
"type": "int64",
|
|
"description": "Number of groups input channels and output channels are divided into",
|
|
"visible": false
|
|
}
|
|
]
|
|
},
|
|
{
|
|
"name": "reduce_sum",
|
|
"description": "Reduce Sum layer",
|
|
"attributes": [
|
|
{
|
|
"name": "original_names",
|
|
"type": "string[]",
|
|
"description": "Name of this layer in the original framework, such as Pytorch or Tensorflow",
|
|
"visible": false
|
|
},
|
|
{
|
|
"name": "groups",
|
|
"type": "int64",
|
|
"description": "Number of groups input channels and output channels are divided into",
|
|
"visible": false
|
|
},
|
|
{
|
|
"name": "activation",
|
|
"type": "string",
|
|
"description": "Activation function name",
|
|
"visible": false
|
|
},
|
|
{
|
|
"name": "reduce_axes",
|
|
"type": "int64[]",
|
|
"description": "List of axes to reduce",
|
|
"visible": false
|
|
}
|
|
]
|
|
},
|
|
{
|
|
"name": "resize",
|
|
"category": "Tensor",
|
|
"description": "Resize layer",
|
|
"attributes": [
|
|
{
|
|
"name": "original_names",
|
|
"type": "string[]",
|
|
"description": "Name of this layer in the original framework, such as Pytorch or Tensorflow",
|
|
"visible": false
|
|
},
|
|
{
|
|
"name": "resize_h_ratio_list",
|
|
"type": "float32[]",
|
|
"visible": true
|
|
},
|
|
{
|
|
"name": "resize_w_ratio_list",
|
|
"type": "float32[]",
|
|
"visible": true
|
|
},
|
|
{
|
|
"name": "resize_f_ratio_list",
|
|
"type": "float32[]",
|
|
"visible": true
|
|
},
|
|
{
|
|
"name": "method",
|
|
"type": "string",
|
|
"description": "Resize method, either bilinear or nearest_neighbor",
|
|
"visible": false
|
|
},
|
|
{
|
|
"name": "resize_bilinear_pixels_mode",
|
|
"type": "string",
|
|
"description": "Bilinear resize variant, either half_pixels, align_corners, or disabled (where both align_corners and half_pixels are false)",
|
|
"visible": false
|
|
}
|
|
]
|
|
},
|
|
{
|
|
"name": "shortcut",
|
|
"description": "Shortcut layer",
|
|
"attributes": [
|
|
{
|
|
"name": "original_names",
|
|
"type": "string[]",
|
|
"description": "Name of this layer in the original framework, such as Pytorch or Tensorflow",
|
|
"visible": false
|
|
}]
|
|
},
|
|
{
|
|
"name": "slice",
|
|
"description": "Slice layer",
|
|
"attributes": [
|
|
{
|
|
"name": "original_names",
|
|
"type": "string[]",
|
|
"description": "Name of this layer in the original framework, such as Pytorch or Tensorflow",
|
|
"visible": false
|
|
},
|
|
{
|
|
"name": "height_slice",
|
|
"type": "int64[]",
|
|
"visible": false,
|
|
"description": "Slice in the height axis (start, stop, step)"
|
|
},
|
|
{
|
|
"name": "width_slice",
|
|
"type": "int64[]",
|
|
"visible": false,
|
|
"description": "Slice in the width axis (start, stop, step)"
|
|
},
|
|
{
|
|
"name": "features_slice",
|
|
"type": "int64[]",
|
|
"visible": false,
|
|
"description": "Slice in the features axis (start, stop, step)"
|
|
}
|
|
]
|
|
},
|
|
{
|
|
"name": "softmax",
|
|
"category": "Activation",
|
|
"description": "Softmax layer",
|
|
"attributes": [
|
|
{
|
|
"name": "original_names",
|
|
"type": "string[]",
|
|
"description": "Name of this layer in the original framework, such as Pytorch or Tensorflow",
|
|
"visible": false
|
|
},
|
|
{
|
|
"name": "groups",
|
|
"type": "int64",
|
|
"description": "Number of groups input channels and output channels are divided into",
|
|
"visible": false
|
|
}
|
|
]
|
|
},
|
|
{
|
|
"name": "space_to_depth",
|
|
"description": "Space to depth layer",
|
|
"attributes": [
|
|
{
|
|
"name": "original_names",
|
|
"type": "string[]",
|
|
"description": "Name of this layer in the original framework, such as Pytorch or Tensorflow",
|
|
"visible": false
|
|
},
|
|
{
|
|
"name": "block_sizes",
|
|
"type": "int64[]",
|
|
"description": "Block size along each spatial axis",
|
|
"visible": false
|
|
},
|
|
{
|
|
"name": "space_to_depth_type",
|
|
"type": "string",
|
|
"description": "Space to depth variant, either classic_dcr (depth-column-row) classic_crd (column-row-depth), serial (used by Transformers patchify function), or focus (Yolov5-like)",
|
|
"visible": false
|
|
},
|
|
{
|
|
"name": "spatial_flatten_output",
|
|
"type": "boolean",
|
|
"description": "Whether to flatten the layer's output to one row",
|
|
"visible": false
|
|
}
|
|
]
|
|
},
|
|
{
|
|
"name": "output_mux",
|
|
"description": "Output muxer layer",
|
|
"attributes": [
|
|
{
|
|
"name": "original_names",
|
|
"type": "string[]",
|
|
"description": "Name of this layer in the original framework, such as Pytorch or Tensorflow",
|
|
"visible": false
|
|
}]
|
|
},
|
|
{
|
|
"name": "concat",
|
|
"category": "Tensor",
|
|
"description": "Concatenation layer",
|
|
"attributes": [
|
|
{
|
|
"name": "original_names",
|
|
"type": "string[]",
|
|
"description": "Name of this layer in the original framework, such as Pytorch or Tensorflow",
|
|
"visible": false
|
|
},
|
|
{
|
|
"name": "concat_axis",
|
|
"type": "int64",
|
|
"description": "Axis to concatenate along, either features or spatial_w (which means the width axis)",
|
|
"visible": false
|
|
},
|
|
{
|
|
"name": "spatial_w_concat",
|
|
"type": "boolean",
|
|
"description": "Whether the concat operation is in the width dimension",
|
|
"visible": false
|
|
}
|
|
]
|
|
},
|
|
{
|
|
"name": "matmul",
|
|
"description": "Matrix multiplication layer",
|
|
"attributes": [
|
|
{
|
|
"name": "original_names",
|
|
"type": "string[]",
|
|
"description": "Name of this layer in the original framework, such as Pytorch or Tensorflow",
|
|
"visible": false
|
|
},
|
|
{
|
|
"name": "kernel_shape",
|
|
"type": "int64[]",
|
|
"label": "kernel",
|
|
"description": "Shape of the kernel in Tensorflow convention (kernel height, kernel width, features in, features out)",
|
|
"visible": true
|
|
},
|
|
{
|
|
"name": "dynamic_weights",
|
|
"type": "boolean",
|
|
"description": "Whether the layer's weights are data driven",
|
|
"visible": false
|
|
},
|
|
{
|
|
"name": "transpose_matmul_input",
|
|
"type": "boolean",
|
|
"description": "Whether to transpose the width and the features axes of the layer's second input tensor",
|
|
"visible": false
|
|
}
|
|
]
|
|
},
|
|
{
|
|
"name": "ew_add",
|
|
"description": "Elementwise addition layer",
|
|
"attributes": [
|
|
{
|
|
"name": "original_names",
|
|
"type": "string[]",
|
|
"description": "Name of this layer in the original framework, such as Pytorch or Tensorflow",
|
|
"visible": false
|
|
},
|
|
{
|
|
"name": "activation",
|
|
"type": "string",
|
|
"description": "Activation function name",
|
|
"visible": false
|
|
}
|
|
]
|
|
},
|
|
{
|
|
"name": "ew_div",
|
|
"description": "Elementwise division layer",
|
|
"attributes": [
|
|
{
|
|
"name": "original_names",
|
|
"type": "string[]",
|
|
"description": "Name of this layer in the original framework, such as Pytorch or Tensorflow",
|
|
"visible": false
|
|
},
|
|
{
|
|
"name": "activation",
|
|
"type": "string",
|
|
"description": "Activation function name",
|
|
"visible": false
|
|
}
|
|
]
|
|
},
|
|
{
|
|
"name": "ew_mult",
|
|
"description": "Elementwise multiplication layer",
|
|
"attributes": [
|
|
{
|
|
"name": "original_names",
|
|
"type": "string[]",
|
|
"description": "Name of this layer in the original framework, such as Pytorch or Tensorflow",
|
|
"visible": false
|
|
},
|
|
{
|
|
"name": "activation",
|
|
"type": "string",
|
|
"description": "Activation function name",
|
|
"visible": false
|
|
}
|
|
]
|
|
},
|
|
{
|
|
"name": "ew_sub",
|
|
"description": "Elementwise subtraction layer",
|
|
"attributes": [
|
|
{
|
|
"name": "original_names",
|
|
"type": "string[]",
|
|
"description": "Name of this layer in the original framework, such as Pytorch or Tensorflow",
|
|
"visible": false
|
|
},
|
|
{
|
|
"name": "activation",
|
|
"type": "string",
|
|
"description": "Activation function name",
|
|
"visible": false
|
|
}
|
|
]
|
|
},
|
|
{
|
|
"name": "demux",
|
|
"description": "Demuxer layer",
|
|
"attributes": [
|
|
{
|
|
"name": "original_names",
|
|
"type": "string[]",
|
|
"description": "Name of this layer in the original framework, such as Pytorch or Tensorflow",
|
|
"visible": false
|
|
}]
|
|
},
|
|
{
|
|
"name": "row_splitter",
|
|
"description": "Splits the input tensor along the height axis",
|
|
"attributes": [
|
|
{
|
|
"name": "original_names",
|
|
"type": "string[]",
|
|
"description": "Name of this layer in the original framework, such as Pytorch or Tensorflow",
|
|
"visible": false
|
|
}]
|
|
},
|
|
{
|
|
"name": "feature_splitter",
|
|
"description": "Splits the input tensor along the features axis",
|
|
"attributes": [
|
|
{
|
|
"name": "original_names",
|
|
"type": "string[]",
|
|
"description": "Name of this layer in the original framework, such as Pytorch or Tensorflow",
|
|
"visible": false
|
|
}]
|
|
},
|
|
{
|
|
"name": "const_input",
|
|
"category": "Constant",
|
|
"description": "Constant input",
|
|
"attributes": [
|
|
{
|
|
"name": "original_names",
|
|
"type": "string[]",
|
|
"description": "Name of this layer in the original framework, such as Pytorch or Tensorflow",
|
|
"visible": false
|
|
}]
|
|
},
|
|
{
|
|
"name": "inv_pos",
|
|
"category": "Activation"
|
|
},
|
|
{
|
|
"name": "exp",
|
|
"category": "Activation"
|
|
},
|
|
{
|
|
"name": "silu",
|
|
"category": "Activation"
|
|
},
|
|
{
|
|
"name": "leaky",
|
|
"category": "Activation"
|
|
},
|
|
{
|
|
"name": "layer_normalization",
|
|
"category": "Normalization"
|
|
}
|
|
]
|
|
|