julien-c's picture
julien-c HF staff
Add mobilenet files
8766451 verified
raw
history blame
139 kB
{
"modelTopology": {
"node": [
{
"attr": {
"dtype": { "type": "DT_FLOAT" },
"value": {
"tensor": {
"dtype": "DT_FLOAT",
"tensorShape": { "dim": [{ "size": "80" }] }
}
}
},
"name": "module_apply_default/MobilenetV2/expanded_conv_15/project/BatchNorm/FusedBatchNorm/Offset",
"op": "Const"
},
{
"attr": {
"dtype": { "type": "DT_FLOAT" },
"value": {
"tensor": {
"dtype": "DT_FLOAT",
"tensorShape": {
"dim": [
{ "size": "1" },
{ "size": "1" },
{ "size": "80" },
{ "size": "480" }
]
}
}
}
},
"name": "module_apply_default/MobilenetV2/expanded_conv_15/expand/Conv2D/merged_input",
"op": "Const"
},
{
"attr": {
"dtype": { "type": "DT_FLOAT" },
"value": {
"tensor": {
"dtype": "DT_FLOAT",
"tensorShape": { "dim": [{ "size": "480" }] }
}
}
},
"name": "module_apply_default/MobilenetV2/expanded_conv_15/expand/BatchNorm/FusedBatchNorm/Offset",
"op": "Const"
},
{
"attr": {
"dtype": { "type": "DT_FLOAT" },
"value": {
"tensor": {
"dtype": "DT_FLOAT",
"tensorShape": {
"dim": [
{ "size": "3" },
{ "size": "3" },
{ "size": "480" },
{ "size": "1" }
]
}
}
}
},
"name": "module/MobilenetV2/expanded_conv_15/depthwise/depthwise_weights",
"op": "Const"
},
{
"attr": {
"dtype": { "type": "DT_FLOAT" },
"value": {
"tensor": {
"dtype": "DT_FLOAT",
"tensorShape": { "dim": [{ "size": "480" }] }
}
}
},
"name": "module_apply_default/MobilenetV2/expanded_conv_15/depthwise/BatchNorm/FusedBatchNorm/Scaled",
"op": "Const"
},
{
"attr": {
"dtype": { "type": "DT_FLOAT" },
"value": {
"tensor": {
"dtype": "DT_FLOAT",
"tensorShape": { "dim": [{ "size": "480" }] }
}
}
},
"name": "module_apply_default/MobilenetV2/expanded_conv_15/depthwise/BatchNorm/FusedBatchNorm/Offset",
"op": "Const"
},
{
"attr": {
"dtype": { "type": "DT_FLOAT" },
"value": {
"tensor": {
"dtype": "DT_FLOAT",
"tensorShape": {
"dim": [
{ "size": "1" },
{ "size": "1" },
{ "size": "480" },
{ "size": "80" }
]
}
}
}
},
"name": "module_apply_default/MobilenetV2/expanded_conv_15/project/Conv2D/merged_input",
"op": "Const"
},
{
"attr": {
"dtype": { "type": "DT_FLOAT" },
"value": {
"tensor": {
"dtype": "DT_FLOAT",
"tensorShape": { "dim": [{ "size": "80" }] }
}
}
},
"name": "module_apply_default/MobilenetV2/expanded_conv_14/project/BatchNorm/FusedBatchNorm/Offset",
"op": "Const"
},
{
"attr": {
"dtype": { "type": "DT_FLOAT" },
"value": {
"tensor": {
"dtype": "DT_FLOAT",
"tensorShape": {
"dim": [
{ "size": "1" },
{ "size": "1" },
{ "size": "80" },
{ "size": "480" }
]
}
}
}
},
"name": "module_apply_default/MobilenetV2/expanded_conv_14/expand/Conv2D/merged_input",
"op": "Const"
},
{
"attr": {
"dtype": { "type": "DT_FLOAT" },
"value": {
"tensor": {
"dtype": "DT_FLOAT",
"tensorShape": { "dim": [{ "size": "480" }] }
}
}
},
"name": "module_apply_default/MobilenetV2/expanded_conv_14/expand/BatchNorm/FusedBatchNorm/Offset",
"op": "Const"
},
{
"attr": {
"dtype": { "type": "DT_FLOAT" },
"value": {
"tensor": {
"dtype": "DT_FLOAT",
"tensorShape": {
"dim": [
{ "size": "3" },
{ "size": "3" },
{ "size": "480" },
{ "size": "1" }
]
}
}
}
},
"name": "module/MobilenetV2/expanded_conv_14/depthwise/depthwise_weights",
"op": "Const"
},
{
"attr": {
"dtype": { "type": "DT_FLOAT" },
"value": {
"tensor": {
"dtype": "DT_FLOAT",
"tensorShape": { "dim": [{ "size": "480" }] }
}
}
},
"name": "module_apply_default/MobilenetV2/expanded_conv_14/depthwise/BatchNorm/FusedBatchNorm/Scaled",
"op": "Const"
},
{
"attr": {
"dtype": { "type": "DT_FLOAT" },
"value": {
"tensor": {
"dtype": "DT_FLOAT",
"tensorShape": { "dim": [{ "size": "480" }] }
}
}
},
"name": "module_apply_default/MobilenetV2/expanded_conv_14/depthwise/BatchNorm/FusedBatchNorm/Offset",
"op": "Const"
},
{
"attr": {
"dtype": { "type": "DT_FLOAT" },
"value": {
"tensor": {
"dtype": "DT_FLOAT",
"tensorShape": {
"dim": [
{ "size": "1" },
{ "size": "1" },
{ "size": "480" },
{ "size": "80" }
]
}
}
}
},
"name": "module_apply_default/MobilenetV2/expanded_conv_14/project/Conv2D/merged_input",
"op": "Const"
},
{
"attr": {
"dtype": { "type": "DT_FLOAT" },
"value": {
"tensor": {
"dtype": "DT_FLOAT",
"tensorShape": { "dim": [{ "size": "48" }] }
}
}
},
"name": "module_apply_default/MobilenetV2/expanded_conv_12/project/BatchNorm/FusedBatchNorm/Offset",
"op": "Const"
},
{
"attr": {
"dtype": { "type": "DT_FLOAT" },
"value": {
"tensor": {
"dtype": "DT_FLOAT",
"tensorShape": {
"dim": [
{ "size": "1" },
{ "size": "1" },
{ "size": "48" },
{ "size": "288" }
]
}
}
}
},
"name": "module_apply_default/MobilenetV2/expanded_conv_12/expand/Conv2D/merged_input",
"op": "Const"
},
{
"attr": {
"dtype": { "type": "DT_FLOAT" },
"value": {
"tensor": {
"dtype": "DT_FLOAT",
"tensorShape": { "dim": [{ "size": "288" }] }
}
}
},
"name": "module_apply_default/MobilenetV2/expanded_conv_12/expand/BatchNorm/FusedBatchNorm/Offset",
"op": "Const"
},
{
"attr": {
"dtype": { "type": "DT_FLOAT" },
"value": {
"tensor": {
"dtype": "DT_FLOAT",
"tensorShape": {
"dim": [
{ "size": "3" },
{ "size": "3" },
{ "size": "288" },
{ "size": "1" }
]
}
}
}
},
"name": "module/MobilenetV2/expanded_conv_12/depthwise/depthwise_weights",
"op": "Const"
},
{
"attr": {
"dtype": { "type": "DT_FLOAT" },
"value": {
"tensor": {
"dtype": "DT_FLOAT",
"tensorShape": { "dim": [{ "size": "288" }] }
}
}
},
"name": "module_apply_default/MobilenetV2/expanded_conv_12/depthwise/BatchNorm/FusedBatchNorm/Scaled",
"op": "Const"
},
{
"attr": {
"dtype": { "type": "DT_FLOAT" },
"value": {
"tensor": {
"dtype": "DT_FLOAT",
"tensorShape": { "dim": [{ "size": "288" }] }
}
}
},
"name": "module_apply_default/MobilenetV2/expanded_conv_12/depthwise/BatchNorm/FusedBatchNorm/Offset",
"op": "Const"
},
{
"attr": {
"dtype": { "type": "DT_FLOAT" },
"value": {
"tensor": {
"dtype": "DT_FLOAT",
"tensorShape": {
"dim": [
{ "size": "1" },
{ "size": "1" },
{ "size": "288" },
{ "size": "48" }
]
}
}
}
},
"name": "module_apply_default/MobilenetV2/expanded_conv_12/project/Conv2D/merged_input",
"op": "Const"
},
{
"attr": {
"dtype": { "type": "DT_FLOAT" },
"value": {
"tensor": {
"dtype": "DT_FLOAT",
"tensorShape": { "dim": [{ "size": "48" }] }
}
}
},
"name": "module_apply_default/MobilenetV2/expanded_conv_11/project/BatchNorm/FusedBatchNorm/Offset",
"op": "Const"
},
{
"attr": {
"dtype": { "type": "DT_FLOAT" },
"value": {
"tensor": {
"dtype": "DT_FLOAT",
"tensorShape": {
"dim": [
{ "size": "1" },
{ "size": "1" },
{ "size": "48" },
{ "size": "288" }
]
}
}
}
},
"name": "module_apply_default/MobilenetV2/expanded_conv_11/expand/Conv2D/merged_input",
"op": "Const"
},
{
"attr": {
"dtype": { "type": "DT_FLOAT" },
"value": {
"tensor": {
"dtype": "DT_FLOAT",
"tensorShape": { "dim": [{ "size": "288" }] }
}
}
},
"name": "module_apply_default/MobilenetV2/expanded_conv_11/expand/BatchNorm/FusedBatchNorm/Offset",
"op": "Const"
},
{
"attr": {
"dtype": { "type": "DT_FLOAT" },
"value": {
"tensor": {
"dtype": "DT_FLOAT",
"tensorShape": {
"dim": [
{ "size": "3" },
{ "size": "3" },
{ "size": "288" },
{ "size": "1" }
]
}
}
}
},
"name": "module/MobilenetV2/expanded_conv_11/depthwise/depthwise_weights",
"op": "Const"
},
{
"attr": {
"dtype": { "type": "DT_FLOAT" },
"value": {
"tensor": {
"dtype": "DT_FLOAT",
"tensorShape": { "dim": [{ "size": "288" }] }
}
}
},
"name": "module_apply_default/MobilenetV2/expanded_conv_11/depthwise/BatchNorm/FusedBatchNorm/Scaled",
"op": "Const"
},
{
"attr": {
"dtype": { "type": "DT_FLOAT" },
"value": {
"tensor": {
"dtype": "DT_FLOAT",
"tensorShape": { "dim": [{ "size": "288" }] }
}
}
},
"name": "module_apply_default/MobilenetV2/expanded_conv_11/depthwise/BatchNorm/FusedBatchNorm/Offset",
"op": "Const"
},
{
"attr": {
"dtype": { "type": "DT_FLOAT" },
"value": {
"tensor": {
"dtype": "DT_FLOAT",
"tensorShape": {
"dim": [
{ "size": "1" },
{ "size": "1" },
{ "size": "288" },
{ "size": "48" }
]
}
}
}
},
"name": "module_apply_default/MobilenetV2/expanded_conv_11/project/Conv2D/merged_input",
"op": "Const"
},
{
"attr": {
"dtype": { "type": "DT_FLOAT" },
"value": {
"tensor": {
"dtype": "DT_FLOAT",
"tensorShape": { "dim": [{ "size": "32" }] }
}
}
},
"name": "module_apply_default/MobilenetV2/expanded_conv_9/project/BatchNorm/FusedBatchNorm/Offset",
"op": "Const"
},
{
"attr": {
"dtype": { "type": "DT_FLOAT" },
"value": {
"tensor": {
"dtype": "DT_FLOAT",
"tensorShape": {
"dim": [
{ "size": "1" },
{ "size": "1" },
{ "size": "32" },
{ "size": "192" }
]
}
}
}
},
"name": "module_apply_default/MobilenetV2/expanded_conv_9/expand/Conv2D/merged_input",
"op": "Const"
},
{
"attr": {
"dtype": { "type": "DT_FLOAT" },
"value": {
"tensor": {
"dtype": "DT_FLOAT",
"tensorShape": { "dim": [{ "size": "192" }] }
}
}
},
"name": "module_apply_default/MobilenetV2/expanded_conv_9/expand/BatchNorm/FusedBatchNorm/Offset",
"op": "Const"
},
{
"attr": {
"dtype": { "type": "DT_FLOAT" },
"value": {
"tensor": {
"dtype": "DT_FLOAT",
"tensorShape": {
"dim": [
{ "size": "3" },
{ "size": "3" },
{ "size": "192" },
{ "size": "1" }
]
}
}
}
},
"name": "module/MobilenetV2/expanded_conv_9/depthwise/depthwise_weights",
"op": "Const"
},
{
"attr": {
"dtype": { "type": "DT_FLOAT" },
"value": {
"tensor": {
"dtype": "DT_FLOAT",
"tensorShape": { "dim": [{ "size": "192" }] }
}
}
},
"name": "module_apply_default/MobilenetV2/expanded_conv_9/depthwise/BatchNorm/FusedBatchNorm/Scaled",
"op": "Const"
},
{
"attr": {
"dtype": { "type": "DT_FLOAT" },
"value": {
"tensor": {
"dtype": "DT_FLOAT",
"tensorShape": { "dim": [{ "size": "192" }] }
}
}
},
"name": "module_apply_default/MobilenetV2/expanded_conv_9/depthwise/BatchNorm/FusedBatchNorm/Offset",
"op": "Const"
},
{
"attr": {
"dtype": { "type": "DT_FLOAT" },
"value": {
"tensor": {
"dtype": "DT_FLOAT",
"tensorShape": {
"dim": [
{ "size": "1" },
{ "size": "1" },
{ "size": "192" },
{ "size": "32" }
]
}
}
}
},
"name": "module_apply_default/MobilenetV2/expanded_conv_9/project/Conv2D/merged_input",
"op": "Const"
},
{
"attr": {
"dtype": { "type": "DT_FLOAT" },
"value": {
"tensor": {
"dtype": "DT_FLOAT",
"tensorShape": { "dim": [{ "size": "32" }] }
}
}
},
"name": "module_apply_default/MobilenetV2/expanded_conv_8/project/BatchNorm/FusedBatchNorm/Offset",
"op": "Const"
},
{
"attr": {
"dtype": { "type": "DT_FLOAT" },
"value": {
"tensor": {
"dtype": "DT_FLOAT",
"tensorShape": {
"dim": [
{ "size": "1" },
{ "size": "1" },
{ "size": "32" },
{ "size": "192" }
]
}
}
}
},
"name": "module_apply_default/MobilenetV2/expanded_conv_8/expand/Conv2D/merged_input",
"op": "Const"
},
{
"attr": {
"dtype": { "type": "DT_FLOAT" },
"value": {
"tensor": {
"dtype": "DT_FLOAT",
"tensorShape": { "dim": [{ "size": "192" }] }
}
}
},
"name": "module_apply_default/MobilenetV2/expanded_conv_8/expand/BatchNorm/FusedBatchNorm/Offset",
"op": "Const"
},
{
"attr": {
"dtype": { "type": "DT_FLOAT" },
"value": {
"tensor": {
"dtype": "DT_FLOAT",
"tensorShape": {
"dim": [
{ "size": "3" },
{ "size": "3" },
{ "size": "192" },
{ "size": "1" }
]
}
}
}
},
"name": "module/MobilenetV2/expanded_conv_8/depthwise/depthwise_weights",
"op": "Const"
},
{
"attr": {
"dtype": { "type": "DT_FLOAT" },
"value": {
"tensor": {
"dtype": "DT_FLOAT",
"tensorShape": { "dim": [{ "size": "192" }] }
}
}
},
"name": "module_apply_default/MobilenetV2/expanded_conv_8/depthwise/BatchNorm/FusedBatchNorm/Scaled",
"op": "Const"
},
{
"attr": {
"dtype": { "type": "DT_FLOAT" },
"value": {
"tensor": {
"dtype": "DT_FLOAT",
"tensorShape": { "dim": [{ "size": "192" }] }
}
}
},
"name": "module_apply_default/MobilenetV2/expanded_conv_8/depthwise/BatchNorm/FusedBatchNorm/Offset",
"op": "Const"
},
{
"attr": {
"dtype": { "type": "DT_FLOAT" },
"value": {
"tensor": {
"dtype": "DT_FLOAT",
"tensorShape": {
"dim": [
{ "size": "1" },
{ "size": "1" },
{ "size": "192" },
{ "size": "32" }
]
}
}
}
},
"name": "module_apply_default/MobilenetV2/expanded_conv_8/project/Conv2D/merged_input",
"op": "Const"
},
{
"attr": {
"dtype": { "type": "DT_FLOAT" },
"value": {
"tensor": {
"dtype": "DT_FLOAT",
"tensorShape": { "dim": [{ "size": "32" }] }
}
}
},
"name": "module_apply_default/MobilenetV2/expanded_conv_7/project/BatchNorm/FusedBatchNorm/Offset",
"op": "Const"
},
{
"attr": {
"dtype": { "type": "DT_FLOAT" },
"value": {
"tensor": {
"dtype": "DT_FLOAT",
"tensorShape": {
"dim": [
{ "size": "1" },
{ "size": "1" },
{ "size": "32" },
{ "size": "192" }
]
}
}
}
},
"name": "module_apply_default/MobilenetV2/expanded_conv_7/expand/Conv2D/merged_input",
"op": "Const"
},
{
"attr": {
"dtype": { "type": "DT_FLOAT" },
"value": {
"tensor": {
"dtype": "DT_FLOAT",
"tensorShape": { "dim": [{ "size": "192" }] }
}
}
},
"name": "module_apply_default/MobilenetV2/expanded_conv_7/expand/BatchNorm/FusedBatchNorm/Offset",
"op": "Const"
},
{
"attr": {
"dtype": { "type": "DT_FLOAT" },
"value": {
"tensor": {
"dtype": "DT_FLOAT",
"tensorShape": {
"dim": [
{ "size": "3" },
{ "size": "3" },
{ "size": "192" },
{ "size": "1" }
]
}
}
}
},
"name": "module/MobilenetV2/expanded_conv_7/depthwise/depthwise_weights",
"op": "Const"
},
{
"attr": {
"dtype": { "type": "DT_FLOAT" },
"value": {
"tensor": {
"dtype": "DT_FLOAT",
"tensorShape": { "dim": [{ "size": "192" }] }
}
}
},
"name": "module_apply_default/MobilenetV2/expanded_conv_7/depthwise/BatchNorm/FusedBatchNorm/Scaled",
"op": "Const"
},
{
"attr": {
"dtype": { "type": "DT_FLOAT" },
"value": {
"tensor": {
"dtype": "DT_FLOAT",
"tensorShape": { "dim": [{ "size": "192" }] }
}
}
},
"name": "module_apply_default/MobilenetV2/expanded_conv_7/depthwise/BatchNorm/FusedBatchNorm/Offset",
"op": "Const"
},
{
"attr": {
"dtype": { "type": "DT_FLOAT" },
"value": {
"tensor": {
"dtype": "DT_FLOAT",
"tensorShape": {
"dim": [
{ "size": "1" },
{ "size": "1" },
{ "size": "192" },
{ "size": "32" }
]
}
}
}
},
"name": "module_apply_default/MobilenetV2/expanded_conv_7/project/Conv2D/merged_input",
"op": "Const"
},
{
"attr": {
"dtype": { "type": "DT_FLOAT" },
"value": {
"tensor": {
"dtype": "DT_FLOAT",
"tensorShape": { "dim": [{ "size": "16" }] }
}
}
},
"name": "module_apply_default/MobilenetV2/expanded_conv_5/project/BatchNorm/FusedBatchNorm/Offset",
"op": "Const"
},
{
"attr": {
"dtype": { "type": "DT_FLOAT" },
"value": {
"tensor": {
"dtype": "DT_FLOAT",
"tensorShape": {
"dim": [
{ "size": "1" },
{ "size": "1" },
{ "size": "16" },
{ "size": "96" }
]
}
}
}
},
"name": "module_apply_default/MobilenetV2/expanded_conv_5/expand/Conv2D/merged_input",
"op": "Const"
},
{
"attr": {
"dtype": { "type": "DT_FLOAT" },
"value": {
"tensor": {
"dtype": "DT_FLOAT",
"tensorShape": { "dim": [{ "size": "96" }] }
}
}
},
"name": "module_apply_default/MobilenetV2/expanded_conv_5/expand/BatchNorm/FusedBatchNorm/Offset",
"op": "Const"
},
{
"attr": {
"dtype": { "type": "DT_FLOAT" },
"value": {
"tensor": {
"dtype": "DT_FLOAT",
"tensorShape": {
"dim": [
{ "size": "3" },
{ "size": "3" },
{ "size": "96" },
{ "size": "1" }
]
}
}
}
},
"name": "module/MobilenetV2/expanded_conv_5/depthwise/depthwise_weights",
"op": "Const"
},
{
"attr": {
"dtype": { "type": "DT_FLOAT" },
"value": {
"tensor": {
"dtype": "DT_FLOAT",
"tensorShape": { "dim": [{ "size": "96" }] }
}
}
},
"name": "module_apply_default/MobilenetV2/expanded_conv_5/depthwise/BatchNorm/FusedBatchNorm/Scaled",
"op": "Const"
},
{
"attr": {
"dtype": { "type": "DT_FLOAT" },
"value": {
"tensor": {
"dtype": "DT_FLOAT",
"tensorShape": { "dim": [{ "size": "96" }] }
}
}
},
"name": "module_apply_default/MobilenetV2/expanded_conv_5/depthwise/BatchNorm/FusedBatchNorm/Offset",
"op": "Const"
},
{
"attr": {
"dtype": { "type": "DT_FLOAT" },
"value": {
"tensor": {
"dtype": "DT_FLOAT",
"tensorShape": {
"dim": [
{ "size": "1" },
{ "size": "1" },
{ "size": "96" },
{ "size": "16" }
]
}
}
}
},
"name": "module_apply_default/MobilenetV2/expanded_conv_5/project/Conv2D/merged_input",
"op": "Const"
},
{
"attr": {
"dtype": { "type": "DT_FLOAT" },
"value": {
"tensor": {
"dtype": "DT_FLOAT",
"tensorShape": { "dim": [{ "size": "16" }] }
}
}
},
"name": "module_apply_default/MobilenetV2/expanded_conv_4/project/BatchNorm/FusedBatchNorm/Offset",
"op": "Const"
},
{
"attr": {
"dtype": { "type": "DT_FLOAT" },
"value": {
"tensor": {
"dtype": "DT_FLOAT",
"tensorShape": {
"dim": [
{ "size": "1" },
{ "size": "1" },
{ "size": "16" },
{ "size": "96" }
]
}
}
}
},
"name": "module_apply_default/MobilenetV2/expanded_conv_4/expand/Conv2D/merged_input",
"op": "Const"
},
{
"attr": {
"dtype": { "type": "DT_FLOAT" },
"value": {
"tensor": {
"dtype": "DT_FLOAT",
"tensorShape": { "dim": [{ "size": "96" }] }
}
}
},
"name": "module_apply_default/MobilenetV2/expanded_conv_4/expand/BatchNorm/FusedBatchNorm/Offset",
"op": "Const"
},
{
"attr": {
"dtype": { "type": "DT_FLOAT" },
"value": {
"tensor": {
"dtype": "DT_FLOAT",
"tensorShape": {
"dim": [
{ "size": "3" },
{ "size": "3" },
{ "size": "96" },
{ "size": "1" }
]
}
}
}
},
"name": "module/MobilenetV2/expanded_conv_4/depthwise/depthwise_weights",
"op": "Const"
},
{
"attr": {
"dtype": { "type": "DT_FLOAT" },
"value": {
"tensor": {
"dtype": "DT_FLOAT",
"tensorShape": { "dim": [{ "size": "96" }] }
}
}
},
"name": "module_apply_default/MobilenetV2/expanded_conv_4/depthwise/BatchNorm/FusedBatchNorm/Scaled",
"op": "Const"
},
{
"attr": {
"dtype": { "type": "DT_FLOAT" },
"value": {
"tensor": {
"dtype": "DT_FLOAT",
"tensorShape": { "dim": [{ "size": "96" }] }
}
}
},
"name": "module_apply_default/MobilenetV2/expanded_conv_4/depthwise/BatchNorm/FusedBatchNorm/Offset",
"op": "Const"
},
{
"attr": {
"dtype": { "type": "DT_FLOAT" },
"value": {
"tensor": {
"dtype": "DT_FLOAT",
"tensorShape": {
"dim": [
{ "size": "1" },
{ "size": "1" },
{ "size": "96" },
{ "size": "16" }
]
}
}
}
},
"name": "module_apply_default/MobilenetV2/expanded_conv_4/project/Conv2D/merged_input",
"op": "Const"
},
{
"attr": {
"dtype": { "type": "DT_FLOAT" },
"value": {
"tensor": {
"dtype": "DT_FLOAT",
"tensorShape": { "dim": [{ "size": "16" }] }
}
}
},
"name": "module_apply_default/MobilenetV2/expanded_conv_2/project/BatchNorm/FusedBatchNorm/Offset",
"op": "Const"
},
{
"attr": {
"dtype": { "type": "DT_FLOAT" },
"value": {
"tensor": {
"dtype": "DT_FLOAT",
"tensorShape": {
"dim": [
{ "size": "1" },
{ "size": "1" },
{ "size": "16" },
{ "size": "96" }
]
}
}
}
},
"name": "module_apply_default/MobilenetV2/expanded_conv_2/expand/Conv2D/merged_input",
"op": "Const"
},
{
"attr": {
"dtype": { "type": "DT_FLOAT" },
"value": {
"tensor": {
"dtype": "DT_FLOAT",
"tensorShape": { "dim": [{ "size": "96" }] }
}
}
},
"name": "module_apply_default/MobilenetV2/expanded_conv_2/expand/BatchNorm/FusedBatchNorm/Offset",
"op": "Const"
},
{
"attr": {
"dtype": { "type": "DT_FLOAT" },
"value": {
"tensor": {
"dtype": "DT_FLOAT",
"tensorShape": {
"dim": [
{ "size": "3" },
{ "size": "3" },
{ "size": "96" },
{ "size": "1" }
]
}
}
}
},
"name": "module/MobilenetV2/expanded_conv_2/depthwise/depthwise_weights",
"op": "Const"
},
{
"attr": {
"dtype": { "type": "DT_FLOAT" },
"value": {
"tensor": {
"dtype": "DT_FLOAT",
"tensorShape": { "dim": [{ "size": "96" }] }
}
}
},
"name": "module_apply_default/MobilenetV2/expanded_conv_2/depthwise/BatchNorm/FusedBatchNorm/Scaled",
"op": "Const"
},
{
"attr": {
"dtype": { "type": "DT_FLOAT" },
"value": {
"tensor": {
"dtype": "DT_FLOAT",
"tensorShape": { "dim": [{ "size": "96" }] }
}
}
},
"name": "module_apply_default/MobilenetV2/expanded_conv_2/depthwise/BatchNorm/FusedBatchNorm/Offset",
"op": "Const"
},
{
"attr": {
"dtype": { "type": "DT_FLOAT" },
"value": {
"tensor": {
"dtype": "DT_FLOAT",
"tensorShape": {
"dim": [
{ "size": "1" },
{ "size": "1" },
{ "size": "96" },
{ "size": "16" }
]
}
}
}
},
"name": "module_apply_default/MobilenetV2/expanded_conv_2/project/Conv2D/merged_input",
"op": "Const"
},
{
"attr": {
"dtype": { "type": "DT_FLOAT" },
"shape": {
"shape": {
"dim": [
{ "size": "-1" },
{ "size": "224" },
{ "size": "224" },
{ "size": "3" }
]
}
}
},
"name": "images",
"op": "Placeholder"
},
{
"attr": {
"dtype": { "type": "DT_FLOAT" },
"value": { "tensor": { "dtype": "DT_FLOAT", "tensorShape": {} } }
},
"name": "module_apply_default/hub_input/Mul/y",
"op": "Const"
},
{
"attr": {
"dtype": { "type": "DT_FLOAT" },
"value": { "tensor": { "dtype": "DT_FLOAT", "tensorShape": {} } }
},
"name": "module_apply_default/hub_input/Sub/y",
"op": "Const"
},
{
"attr": {
"dtype": { "type": "DT_FLOAT" },
"value": {
"tensor": {
"dtype": "DT_FLOAT",
"tensorShape": {
"dim": [
{ "size": "3" },
{ "size": "3" },
{ "size": "3" },
{ "size": "16" }
]
}
}
}
},
"name": "module_apply_default/MobilenetV2/Conv/Conv2D/merged_input",
"op": "Const"
},
{
"attr": {
"dtype": { "type": "DT_FLOAT" },
"value": {
"tensor": {
"dtype": "DT_FLOAT",
"tensorShape": { "dim": [{ "size": "16" }] }
}
}
},
"name": "module_apply_default/MobilenetV2/Conv/BatchNorm/FusedBatchNorm/Offset",
"op": "Const"
},
{
"attr": {
"dtype": { "type": "DT_FLOAT" },
"value": {
"tensor": {
"dtype": "DT_FLOAT",
"tensorShape": {
"dim": [
{ "size": "3" },
{ "size": "3" },
{ "size": "16" },
{ "size": "1" }
]
}
}
}
},
"name": "module/MobilenetV2/expanded_conv/depthwise/depthwise_weights",
"op": "Const"
},
{
"attr": {
"dtype": { "type": "DT_FLOAT" },
"value": {
"tensor": {
"dtype": "DT_FLOAT",
"tensorShape": { "dim": [{ "size": "16" }] }
}
}
},
"name": "module_apply_default/MobilenetV2/expanded_conv/depthwise/BatchNorm/FusedBatchNorm/Scaled",
"op": "Const"
},
{
"attr": {
"dtype": { "type": "DT_FLOAT" },
"value": {
"tensor": {
"dtype": "DT_FLOAT",
"tensorShape": { "dim": [{ "size": "16" }] }
}
}
},
"name": "module_apply_default/MobilenetV2/expanded_conv/depthwise/BatchNorm/FusedBatchNorm/Offset",
"op": "Const"
},
{
"attr": {
"dtype": { "type": "DT_FLOAT" },
"value": {
"tensor": {
"dtype": "DT_FLOAT",
"tensorShape": {
"dim": [
{ "size": "1" },
{ "size": "1" },
{ "size": "16" },
{ "size": "8" }
]
}
}
}
},
"name": "module_apply_default/MobilenetV2/expanded_conv/project/Conv2D/merged_input",
"op": "Const"
},
{
"attr": {
"dtype": { "type": "DT_FLOAT" },
"value": {
"tensor": {
"dtype": "DT_FLOAT",
"tensorShape": { "dim": [{ "size": "8" }] }
}
}
},
"name": "module_apply_default/MobilenetV2/expanded_conv/project/BatchNorm/FusedBatchNorm/Offset",
"op": "Const"
},
{
"attr": {
"dtype": { "type": "DT_FLOAT" },
"value": {
"tensor": {
"dtype": "DT_FLOAT",
"tensorShape": {
"dim": [
{ "size": "1" },
{ "size": "1" },
{ "size": "8" },
{ "size": "48" }
]
}
}
}
},
"name": "module_apply_default/MobilenetV2/expanded_conv_1/expand/Conv2D/merged_input",
"op": "Const"
},
{
"attr": {
"dtype": { "type": "DT_FLOAT" },
"value": {
"tensor": {
"dtype": "DT_FLOAT",
"tensorShape": { "dim": [{ "size": "48" }] }
}
}
},
"name": "module_apply_default/MobilenetV2/expanded_conv_1/expand/BatchNorm/FusedBatchNorm/Offset",
"op": "Const"
},
{
"attr": {
"dtype": { "type": "DT_FLOAT" },
"value": {
"tensor": {
"dtype": "DT_FLOAT",
"tensorShape": {
"dim": [
{ "size": "3" },
{ "size": "3" },
{ "size": "48" },
{ "size": "1" }
]
}
}
}
},
"name": "module/MobilenetV2/expanded_conv_1/depthwise/depthwise_weights",
"op": "Const"
},
{
"attr": {
"dtype": { "type": "DT_FLOAT" },
"value": {
"tensor": {
"dtype": "DT_FLOAT",
"tensorShape": { "dim": [{ "size": "48" }] }
}
}
},
"name": "module_apply_default/MobilenetV2/expanded_conv_1/depthwise/BatchNorm/FusedBatchNorm/Scaled",
"op": "Const"
},
{
"attr": {
"dtype": { "type": "DT_FLOAT" },
"value": {
"tensor": {
"dtype": "DT_FLOAT",
"tensorShape": { "dim": [{ "size": "48" }] }
}
}
},
"name": "module_apply_default/MobilenetV2/expanded_conv_1/depthwise/BatchNorm/FusedBatchNorm/Offset",
"op": "Const"
},
{
"attr": {
"dtype": { "type": "DT_FLOAT" },
"value": {
"tensor": {
"dtype": "DT_FLOAT",
"tensorShape": {
"dim": [
{ "size": "1" },
{ "size": "1" },
{ "size": "48" },
{ "size": "16" }
]
}
}
}
},
"name": "module_apply_default/MobilenetV2/expanded_conv_1/project/Conv2D/merged_input",
"op": "Const"
},
{
"attr": {
"dtype": { "type": "DT_FLOAT" },
"value": {
"tensor": {
"dtype": "DT_FLOAT",
"tensorShape": { "dim": [{ "size": "16" }] }
}
}
},
"name": "module_apply_default/MobilenetV2/expanded_conv_1/project/BatchNorm/FusedBatchNorm/Offset",
"op": "Const"
},
{
"attr": {
"dtype": { "type": "DT_FLOAT" },
"value": {
"tensor": {
"dtype": "DT_FLOAT",
"tensorShape": {
"dim": [
{ "size": "1" },
{ "size": "1" },
{ "size": "16" },
{ "size": "96" }
]
}
}
}
},
"name": "module_apply_default/MobilenetV2/expanded_conv_3/expand/Conv2D/merged_input",
"op": "Const"
},
{
"attr": {
"dtype": { "type": "DT_FLOAT" },
"value": {
"tensor": {
"dtype": "DT_FLOAT",
"tensorShape": { "dim": [{ "size": "96" }] }
}
}
},
"name": "module_apply_default/MobilenetV2/expanded_conv_3/expand/BatchNorm/FusedBatchNorm/Offset",
"op": "Const"
},
{
"attr": {
"dtype": { "type": "DT_FLOAT" },
"value": {
"tensor": {
"dtype": "DT_FLOAT",
"tensorShape": {
"dim": [
{ "size": "3" },
{ "size": "3" },
{ "size": "96" },
{ "size": "1" }
]
}
}
}
},
"name": "module/MobilenetV2/expanded_conv_3/depthwise/depthwise_weights",
"op": "Const"
},
{
"attr": {
"dtype": { "type": "DT_FLOAT" },
"value": {
"tensor": {
"dtype": "DT_FLOAT",
"tensorShape": { "dim": [{ "size": "96" }] }
}
}
},
"name": "module_apply_default/MobilenetV2/expanded_conv_3/depthwise/BatchNorm/FusedBatchNorm/Scaled",
"op": "Const"
},
{
"attr": {
"dtype": { "type": "DT_FLOAT" },
"value": {
"tensor": {
"dtype": "DT_FLOAT",
"tensorShape": { "dim": [{ "size": "96" }] }
}
}
},
"name": "module_apply_default/MobilenetV2/expanded_conv_3/depthwise/BatchNorm/FusedBatchNorm/Offset",
"op": "Const"
},
{
"attr": {
"dtype": { "type": "DT_FLOAT" },
"value": {
"tensor": {
"dtype": "DT_FLOAT",
"tensorShape": {
"dim": [
{ "size": "1" },
{ "size": "1" },
{ "size": "96" },
{ "size": "16" }
]
}
}
}
},
"name": "module_apply_default/MobilenetV2/expanded_conv_3/project/Conv2D/merged_input",
"op": "Const"
},
{
"attr": {
"dtype": { "type": "DT_FLOAT" },
"value": {
"tensor": {
"dtype": "DT_FLOAT",
"tensorShape": { "dim": [{ "size": "16" }] }
}
}
},
"name": "module_apply_default/MobilenetV2/expanded_conv_3/project/BatchNorm/FusedBatchNorm/Offset",
"op": "Const"
},
{
"attr": {
"dtype": { "type": "DT_FLOAT" },
"value": {
"tensor": {
"dtype": "DT_FLOAT",
"tensorShape": {
"dim": [
{ "size": "1" },
{ "size": "1" },
{ "size": "16" },
{ "size": "96" }
]
}
}
}
},
"name": "module_apply_default/MobilenetV2/expanded_conv_6/expand/Conv2D/merged_input",
"op": "Const"
},
{
"attr": {
"dtype": { "type": "DT_FLOAT" },
"value": {
"tensor": {
"dtype": "DT_FLOAT",
"tensorShape": { "dim": [{ "size": "96" }] }
}
}
},
"name": "module_apply_default/MobilenetV2/expanded_conv_6/expand/BatchNorm/FusedBatchNorm/Offset",
"op": "Const"
},
{
"attr": {
"dtype": { "type": "DT_FLOAT" },
"value": {
"tensor": {
"dtype": "DT_FLOAT",
"tensorShape": {
"dim": [
{ "size": "3" },
{ "size": "3" },
{ "size": "96" },
{ "size": "1" }
]
}
}
}
},
"name": "module/MobilenetV2/expanded_conv_6/depthwise/depthwise_weights",
"op": "Const"
},
{
"attr": {
"dtype": { "type": "DT_FLOAT" },
"value": {
"tensor": {
"dtype": "DT_FLOAT",
"tensorShape": { "dim": [{ "size": "96" }] }
}
}
},
"name": "module_apply_default/MobilenetV2/expanded_conv_6/depthwise/BatchNorm/FusedBatchNorm/Scaled",
"op": "Const"
},
{
"attr": {
"dtype": { "type": "DT_FLOAT" },
"value": {
"tensor": {
"dtype": "DT_FLOAT",
"tensorShape": { "dim": [{ "size": "96" }] }
}
}
},
"name": "module_apply_default/MobilenetV2/expanded_conv_6/depthwise/BatchNorm/FusedBatchNorm/Offset",
"op": "Const"
},
{
"attr": {
"dtype": { "type": "DT_FLOAT" },
"value": {
"tensor": {
"dtype": "DT_FLOAT",
"tensorShape": {
"dim": [
{ "size": "1" },
{ "size": "1" },
{ "size": "96" },
{ "size": "32" }
]
}
}
}
},
"name": "module_apply_default/MobilenetV2/expanded_conv_6/project/Conv2D/merged_input",
"op": "Const"
},
{
"attr": {
"dtype": { "type": "DT_FLOAT" },
"value": {
"tensor": {
"dtype": "DT_FLOAT",
"tensorShape": { "dim": [{ "size": "32" }] }
}
}
},
"name": "module_apply_default/MobilenetV2/expanded_conv_6/project/BatchNorm/FusedBatchNorm/Offset",
"op": "Const"
},
{
"attr": {
"dtype": { "type": "DT_FLOAT" },
"value": {
"tensor": {
"dtype": "DT_FLOAT",
"tensorShape": {
"dim": [
{ "size": "1" },
{ "size": "1" },
{ "size": "32" },
{ "size": "192" }
]
}
}
}
},
"name": "module_apply_default/MobilenetV2/expanded_conv_10/expand/Conv2D/merged_input",
"op": "Const"
},
{
"attr": {
"dtype": { "type": "DT_FLOAT" },
"value": {
"tensor": {
"dtype": "DT_FLOAT",
"tensorShape": { "dim": [{ "size": "192" }] }
}
}
},
"name": "module_apply_default/MobilenetV2/expanded_conv_10/expand/BatchNorm/FusedBatchNorm/Offset",
"op": "Const"
},
{
"attr": {
"dtype": { "type": "DT_FLOAT" },
"value": {
"tensor": {
"dtype": "DT_FLOAT",
"tensorShape": {
"dim": [
{ "size": "3" },
{ "size": "3" },
{ "size": "192" },
{ "size": "1" }
]
}
}
}
},
"name": "module/MobilenetV2/expanded_conv_10/depthwise/depthwise_weights",
"op": "Const"
},
{
"attr": {
"dtype": { "type": "DT_FLOAT" },
"value": {
"tensor": {
"dtype": "DT_FLOAT",
"tensorShape": { "dim": [{ "size": "192" }] }
}
}
},
"name": "module_apply_default/MobilenetV2/expanded_conv_10/depthwise/BatchNorm/FusedBatchNorm/Scaled",
"op": "Const"
},
{
"attr": {
"dtype": { "type": "DT_FLOAT" },
"value": {
"tensor": {
"dtype": "DT_FLOAT",
"tensorShape": { "dim": [{ "size": "192" }] }
}
}
},
"name": "module_apply_default/MobilenetV2/expanded_conv_10/depthwise/BatchNorm/FusedBatchNorm/Offset",
"op": "Const"
},
{
"attr": {
"dtype": { "type": "DT_FLOAT" },
"value": {
"tensor": {
"dtype": "DT_FLOAT",
"tensorShape": {
"dim": [
{ "size": "1" },
{ "size": "1" },
{ "size": "192" },
{ "size": "48" }
]
}
}
}
},
"name": "module_apply_default/MobilenetV2/expanded_conv_10/project/Conv2D/merged_input",
"op": "Const"
},
{
"attr": {
"dtype": { "type": "DT_FLOAT" },
"value": {
"tensor": {
"dtype": "DT_FLOAT",
"tensorShape": { "dim": [{ "size": "48" }] }
}
}
},
"name": "module_apply_default/MobilenetV2/expanded_conv_10/project/BatchNorm/FusedBatchNorm/Offset",
"op": "Const"
},
{
"attr": {
"dtype": { "type": "DT_FLOAT" },
"value": {
"tensor": {
"dtype": "DT_FLOAT",
"tensorShape": {
"dim": [
{ "size": "1" },
{ "size": "1" },
{ "size": "48" },
{ "size": "288" }
]
}
}
}
},
"name": "module_apply_default/MobilenetV2/expanded_conv_13/expand/Conv2D/merged_input",
"op": "Const"
},
{
"attr": {
"dtype": { "type": "DT_FLOAT" },
"value": {
"tensor": {
"dtype": "DT_FLOAT",
"tensorShape": { "dim": [{ "size": "288" }] }
}
}
},
"name": "module_apply_default/MobilenetV2/expanded_conv_13/expand/BatchNorm/FusedBatchNorm/Offset",
"op": "Const"
},
{
"attr": {
"dtype": { "type": "DT_FLOAT" },
"value": {
"tensor": {
"dtype": "DT_FLOAT",
"tensorShape": {
"dim": [
{ "size": "3" },
{ "size": "3" },
{ "size": "288" },
{ "size": "1" }
]
}
}
}
},
"name": "module/MobilenetV2/expanded_conv_13/depthwise/depthwise_weights",
"op": "Const"
},
{
"attr": {
"dtype": { "type": "DT_FLOAT" },
"value": {
"tensor": {
"dtype": "DT_FLOAT",
"tensorShape": { "dim": [{ "size": "288" }] }
}
}
},
"name": "module_apply_default/MobilenetV2/expanded_conv_13/depthwise/BatchNorm/FusedBatchNorm/Scaled",
"op": "Const"
},
{
"attr": {
"dtype": { "type": "DT_FLOAT" },
"value": {
"tensor": {
"dtype": "DT_FLOAT",
"tensorShape": { "dim": [{ "size": "288" }] }
}
}
},
"name": "module_apply_default/MobilenetV2/expanded_conv_13/depthwise/BatchNorm/FusedBatchNorm/Offset",
"op": "Const"
},
{
"attr": {
"dtype": { "type": "DT_FLOAT" },
"value": {
"tensor": {
"dtype": "DT_FLOAT",
"tensorShape": {
"dim": [
{ "size": "1" },
{ "size": "1" },
{ "size": "288" },
{ "size": "80" }
]
}
}
}
},
"name": "module_apply_default/MobilenetV2/expanded_conv_13/project/Conv2D/merged_input",
"op": "Const"
},
{
"attr": {
"dtype": { "type": "DT_FLOAT" },
"value": {
"tensor": {
"dtype": "DT_FLOAT",
"tensorShape": { "dim": [{ "size": "80" }] }
}
}
},
"name": "module_apply_default/MobilenetV2/expanded_conv_13/project/BatchNorm/FusedBatchNorm/Offset",
"op": "Const"
},
{
"attr": {
"dtype": { "type": "DT_FLOAT" },
"value": {
"tensor": {
"dtype": "DT_FLOAT",
"tensorShape": {
"dim": [
{ "size": "1" },
{ "size": "1" },
{ "size": "80" },
{ "size": "480" }
]
}
}
}
},
"name": "module_apply_default/MobilenetV2/expanded_conv_16/expand/Conv2D/merged_input",
"op": "Const"
},
{
"attr": {
"dtype": { "type": "DT_FLOAT" },
"value": {
"tensor": {
"dtype": "DT_FLOAT",
"tensorShape": { "dim": [{ "size": "480" }] }
}
}
},
"name": "module_apply_default/MobilenetV2/expanded_conv_16/expand/BatchNorm/FusedBatchNorm/Offset",
"op": "Const"
},
{
"attr": {
"dtype": { "type": "DT_FLOAT" },
"value": {
"tensor": {
"dtype": "DT_FLOAT",
"tensorShape": {
"dim": [
{ "size": "3" },
{ "size": "3" },
{ "size": "480" },
{ "size": "1" }
]
}
}
}
},
"name": "module/MobilenetV2/expanded_conv_16/depthwise/depthwise_weights",
"op": "Const"
},
{
"attr": {
"dtype": { "type": "DT_FLOAT" },
"value": {
"tensor": {
"dtype": "DT_FLOAT",
"tensorShape": { "dim": [{ "size": "480" }] }
}
}
},
"name": "module_apply_default/MobilenetV2/expanded_conv_16/depthwise/BatchNorm/FusedBatchNorm/Scaled",
"op": "Const"
},
{
"attr": {
"dtype": { "type": "DT_FLOAT" },
"value": {
"tensor": {
"dtype": "DT_FLOAT",
"tensorShape": { "dim": [{ "size": "480" }] }
}
}
},
"name": "module_apply_default/MobilenetV2/expanded_conv_16/depthwise/BatchNorm/FusedBatchNorm/Offset",
"op": "Const"
},
{
"attr": {
"dtype": { "type": "DT_FLOAT" },
"value": {
"tensor": {
"dtype": "DT_FLOAT",
"tensorShape": {
"dim": [
{ "size": "1" },
{ "size": "1" },
{ "size": "480" },
{ "size": "160" }
]
}
}
}
},
"name": "module_apply_default/MobilenetV2/expanded_conv_16/project/Conv2D/merged_input",
"op": "Const"
},
{
"attr": {
"dtype": { "type": "DT_FLOAT" },
"value": {
"tensor": {
"dtype": "DT_FLOAT",
"tensorShape": { "dim": [{ "size": "160" }] }
}
}
},
"name": "module_apply_default/MobilenetV2/expanded_conv_16/project/BatchNorm/FusedBatchNorm/Offset",
"op": "Const"
},
{
"attr": {
"dtype": { "type": "DT_FLOAT" },
"value": {
"tensor": {
"dtype": "DT_FLOAT",
"tensorShape": {
"dim": [
{ "size": "1" },
{ "size": "1" },
{ "size": "160" },
{ "size": "1280" }
]
}
}
}
},
"name": "module_apply_default/MobilenetV2/Conv_1/Conv2D/merged_input",
"op": "Const"
},
{
"attr": {
"dtype": { "type": "DT_FLOAT" },
"value": {
"tensor": {
"dtype": "DT_FLOAT",
"tensorShape": { "dim": [{ "size": "1280" }] }
}
}
},
"name": "module_apply_default/MobilenetV2/Conv_1/BatchNorm/FusedBatchNorm/Offset",
"op": "Const"
},
{
"attr": {
"dtype": { "type": "DT_FLOAT" },
"value": {
"tensor": {
"dtype": "DT_FLOAT",
"tensorShape": {
"dim": [
{ "size": "1" },
{ "size": "1" },
{ "size": "1280" },
{ "size": "1001" }
]
}
}
}
},
"name": "module/MobilenetV2/Logits/Conv2d_1c_1x1/weights",
"op": "Const"
},
{
"attr": {
"dtype": { "type": "DT_FLOAT" },
"value": {
"tensor": {
"dtype": "DT_FLOAT",
"tensorShape": { "dim": [{ "size": "1001" }] }
}
}
},
"name": "module/MobilenetV2/Logits/Conv2d_1c_1x1/biases",
"op": "Const"
},
{
"input": ["images", "module_apply_default/hub_input/Mul/y"],
"attr": { "T": { "type": "DT_FLOAT" } },
"name": "module_apply_default/hub_input/Mul",
"op": "Mul"
},
{
"input": [
"module_apply_default/hub_input/Mul",
"module_apply_default/hub_input/Sub/y"
],
"attr": { "T": { "type": "DT_FLOAT" } },
"name": "module_apply_default/hub_input/Sub",
"op": "Sub"
},
{
"input": [
"module_apply_default/hub_input/Sub",
"module_apply_default/MobilenetV2/Conv/Conv2D/merged_input"
],
"attr": {
"data_format": { "s": "TkhXQw==" },
"use_cudnn_on_gpu": { "b": true },
"padding": { "s": "U0FNRQ==" },
"strides": { "list": { "i": ["1", "2", "2", "1"] } },
"T": { "type": "DT_FLOAT" },
"dilations": { "list": { "i": ["1", "1", "1", "1"] } }
},
"name": "module_apply_default/MobilenetV2/Conv/BatchNorm/FusedBatchNorm/Mul",
"op": "Conv2D"
},
{
"input": [
"module_apply_default/MobilenetV2/Conv/BatchNorm/FusedBatchNorm/Mul",
"module_apply_default/MobilenetV2/Conv/BatchNorm/FusedBatchNorm/Offset"
],
"attr": { "T": { "type": "DT_FLOAT" } },
"name": "module_apply_default/MobilenetV2/Conv/BatchNorm/FusedBatchNorm",
"op": "Add"
},
{
"input": [
"module_apply_default/MobilenetV2/Conv/BatchNorm/FusedBatchNorm"
],
"attr": { "T": { "type": "DT_FLOAT" } },
"name": "module_apply_default/MobilenetV2/Conv/Relu6",
"op": "Relu6"
},
{
"input": [
"module_apply_default/MobilenetV2/Conv/Relu6",
"module/MobilenetV2/expanded_conv/depthwise/depthwise_weights"
],
"attr": {
"padding": { "s": "U0FNRQ==" },
"strides": { "list": { "i": ["1", "1", "1", "1"] } },
"dilations": { "list": { "i": ["1", "1", "1", "1"] } },
"data_format": { "s": "TkhXQw==" },
"T": { "type": "DT_FLOAT" }
},
"name": "module_apply_default/MobilenetV2/expanded_conv/depthwise/depthwise",
"op": "DepthwiseConv2dNative"
},
{
"input": [
"module_apply_default/MobilenetV2/expanded_conv/depthwise/depthwise",
"module_apply_default/MobilenetV2/expanded_conv/depthwise/BatchNorm/FusedBatchNorm/Scaled"
],
"attr": { "T": { "type": "DT_FLOAT" } },
"name": "module_apply_default/MobilenetV2/expanded_conv/depthwise/BatchNorm/FusedBatchNorm/Mul",
"op": "Mul"
},
{
"input": [
"module_apply_default/MobilenetV2/expanded_conv/depthwise/BatchNorm/FusedBatchNorm/Mul",
"module_apply_default/MobilenetV2/expanded_conv/depthwise/BatchNorm/FusedBatchNorm/Offset"
],
"attr": { "T": { "type": "DT_FLOAT" } },
"name": "module_apply_default/MobilenetV2/expanded_conv/depthwise/BatchNorm/FusedBatchNorm",
"op": "Add"
},
{
"input": [
"module_apply_default/MobilenetV2/expanded_conv/depthwise/BatchNorm/FusedBatchNorm"
],
"attr": { "T": { "type": "DT_FLOAT" } },
"name": "module_apply_default/MobilenetV2/expanded_conv/depthwise/Relu6",
"op": "Relu6"
},
{
"input": [
"module_apply_default/MobilenetV2/expanded_conv/depthwise/Relu6",
"module_apply_default/MobilenetV2/expanded_conv/project/Conv2D/merged_input"
],
"attr": {
"data_format": { "s": "TkhXQw==" },
"use_cudnn_on_gpu": { "b": true },
"padding": { "s": "U0FNRQ==" },
"strides": { "list": { "i": ["1", "1", "1", "1"] } },
"T": { "type": "DT_FLOAT" },
"dilations": { "list": { "i": ["1", "1", "1", "1"] } }
},
"name": "module_apply_default/MobilenetV2/expanded_conv/project/BatchNorm/FusedBatchNorm/Mul",
"op": "Conv2D"
},
{
"input": [
"module_apply_default/MobilenetV2/expanded_conv/project/BatchNorm/FusedBatchNorm/Mul",
"module_apply_default/MobilenetV2/expanded_conv/project/BatchNorm/FusedBatchNorm/Offset"
],
"attr": { "T": { "type": "DT_FLOAT" } },
"name": "module_apply_default/MobilenetV2/expanded_conv/project/BatchNorm/FusedBatchNorm",
"op": "Add"
},
{
"input": [
"module_apply_default/MobilenetV2/expanded_conv/project/BatchNorm/FusedBatchNorm",
"module_apply_default/MobilenetV2/expanded_conv_1/expand/Conv2D/merged_input"
],
"attr": {
"data_format": { "s": "TkhXQw==" },
"use_cudnn_on_gpu": { "b": true },
"padding": { "s": "U0FNRQ==" },
"strides": { "list": { "i": ["1", "1", "1", "1"] } },
"T": { "type": "DT_FLOAT" },
"dilations": { "list": { "i": ["1", "1", "1", "1"] } }
},
"name": "module_apply_default/MobilenetV2/expanded_conv_1/expand/BatchNorm/FusedBatchNorm/Mul",
"op": "Conv2D"
},
{
"input": [
"module_apply_default/MobilenetV2/expanded_conv_1/expand/BatchNorm/FusedBatchNorm/Mul",
"module_apply_default/MobilenetV2/expanded_conv_1/expand/BatchNorm/FusedBatchNorm/Offset"
],
"attr": { "T": { "type": "DT_FLOAT" } },
"name": "module_apply_default/MobilenetV2/expanded_conv_1/expand/BatchNorm/FusedBatchNorm",
"op": "Add"
},
{
"input": [
"module_apply_default/MobilenetV2/expanded_conv_1/expand/BatchNorm/FusedBatchNorm"
],
"attr": { "T": { "type": "DT_FLOAT" } },
"name": "module_apply_default/MobilenetV2/expanded_conv_1/expand/Relu6",
"op": "Relu6"
},
{
"input": [
"module_apply_default/MobilenetV2/expanded_conv_1/expand/Relu6",
"module/MobilenetV2/expanded_conv_1/depthwise/depthwise_weights"
],
"attr": {
"padding": { "s": "U0FNRQ==" },
"dilations": { "list": { "i": ["1", "1", "1", "1"] } },
"data_format": { "s": "TkhXQw==" },
"T": { "type": "DT_FLOAT" },
"strides": { "list": { "i": ["1", "2", "2", "1"] } }
},
"name": "module_apply_default/MobilenetV2/expanded_conv_1/depthwise/depthwise",
"op": "DepthwiseConv2dNative"
},
{
"input": [
"module_apply_default/MobilenetV2/expanded_conv_1/depthwise/depthwise",
"module_apply_default/MobilenetV2/expanded_conv_1/depthwise/BatchNorm/FusedBatchNorm/Scaled"
],
"attr": { "T": { "type": "DT_FLOAT" } },
"name": "module_apply_default/MobilenetV2/expanded_conv_1/depthwise/BatchNorm/FusedBatchNorm/Mul",
"op": "Mul"
},
{
"input": [
"module_apply_default/MobilenetV2/expanded_conv_1/depthwise/BatchNorm/FusedBatchNorm/Mul",
"module_apply_default/MobilenetV2/expanded_conv_1/depthwise/BatchNorm/FusedBatchNorm/Offset"
],
"attr": { "T": { "type": "DT_FLOAT" } },
"name": "module_apply_default/MobilenetV2/expanded_conv_1/depthwise/BatchNorm/FusedBatchNorm",
"op": "Add"
},
{
"input": [
"module_apply_default/MobilenetV2/expanded_conv_1/depthwise/BatchNorm/FusedBatchNorm"
],
"attr": { "T": { "type": "DT_FLOAT" } },
"name": "module_apply_default/MobilenetV2/expanded_conv_1/depthwise/Relu6",
"op": "Relu6"
},
{
"input": [
"module_apply_default/MobilenetV2/expanded_conv_1/depthwise/Relu6",
"module_apply_default/MobilenetV2/expanded_conv_1/project/Conv2D/merged_input"
],
"attr": {
"data_format": { "s": "TkhXQw==" },
"use_cudnn_on_gpu": { "b": true },
"padding": { "s": "U0FNRQ==" },
"strides": { "list": { "i": ["1", "1", "1", "1"] } },
"T": { "type": "DT_FLOAT" },
"dilations": { "list": { "i": ["1", "1", "1", "1"] } }
},
"name": "module_apply_default/MobilenetV2/expanded_conv_1/project/BatchNorm/FusedBatchNorm/Mul",
"op": "Conv2D"
},
{
"input": [
"module_apply_default/MobilenetV2/expanded_conv_1/project/BatchNorm/FusedBatchNorm/Mul",
"module_apply_default/MobilenetV2/expanded_conv_1/project/BatchNorm/FusedBatchNorm/Offset"
],
"attr": { "T": { "type": "DT_FLOAT" } },
"name": "module_apply_default/MobilenetV2/expanded_conv_1/project/BatchNorm/FusedBatchNorm",
"op": "Add"
},
{
"input": [
"module_apply_default/MobilenetV2/expanded_conv_1/project/BatchNorm/FusedBatchNorm",
"module_apply_default/MobilenetV2/expanded_conv_2/expand/Conv2D/merged_input"
],
"attr": {
"data_format": { "s": "TkhXQw==" },
"use_cudnn_on_gpu": { "b": true },
"padding": { "s": "U0FNRQ==" },
"strides": { "list": { "i": ["1", "1", "1", "1"] } },
"T": { "type": "DT_FLOAT" },
"dilations": { "list": { "i": ["1", "1", "1", "1"] } }
},
"name": "module_apply_default/MobilenetV2/expanded_conv_2/expand/BatchNorm/FusedBatchNorm/Mul",
"op": "Conv2D"
},
{
"input": [
"module_apply_default/MobilenetV2/expanded_conv_2/expand/BatchNorm/FusedBatchNorm/Mul",
"module_apply_default/MobilenetV2/expanded_conv_2/expand/BatchNorm/FusedBatchNorm/Offset"
],
"attr": { "T": { "type": "DT_FLOAT" } },
"name": "module_apply_default/MobilenetV2/expanded_conv_2/expand/BatchNorm/FusedBatchNorm",
"op": "Add"
},
{
"input": [
"module_apply_default/MobilenetV2/expanded_conv_2/expand/BatchNorm/FusedBatchNorm"
],
"attr": { "T": { "type": "DT_FLOAT" } },
"name": "module_apply_default/MobilenetV2/expanded_conv_2/expand/Relu6",
"op": "Relu6"
},
{
"input": [
"module_apply_default/MobilenetV2/expanded_conv_2/expand/Relu6",
"module/MobilenetV2/expanded_conv_2/depthwise/depthwise_weights"
],
"attr": {
"padding": { "s": "U0FNRQ==" },
"dilations": { "list": { "i": ["1", "1", "1", "1"] } },
"data_format": { "s": "TkhXQw==" },
"T": { "type": "DT_FLOAT" },
"strides": { "list": { "i": ["1", "1", "1", "1"] } }
},
"name": "module_apply_default/MobilenetV2/expanded_conv_2/depthwise/depthwise",
"op": "DepthwiseConv2dNative"
},
{
"input": [
"module_apply_default/MobilenetV2/expanded_conv_2/depthwise/depthwise",
"module_apply_default/MobilenetV2/expanded_conv_2/depthwise/BatchNorm/FusedBatchNorm/Scaled"
],
"attr": { "T": { "type": "DT_FLOAT" } },
"name": "module_apply_default/MobilenetV2/expanded_conv_2/depthwise/BatchNorm/FusedBatchNorm/Mul",
"op": "Mul"
},
{
"input": [
"module_apply_default/MobilenetV2/expanded_conv_2/depthwise/BatchNorm/FusedBatchNorm/Mul",
"module_apply_default/MobilenetV2/expanded_conv_2/depthwise/BatchNorm/FusedBatchNorm/Offset"
],
"attr": { "T": { "type": "DT_FLOAT" } },
"name": "module_apply_default/MobilenetV2/expanded_conv_2/depthwise/BatchNorm/FusedBatchNorm",
"op": "Add"
},
{
"input": [
"module_apply_default/MobilenetV2/expanded_conv_2/depthwise/BatchNorm/FusedBatchNorm"
],
"attr": { "T": { "type": "DT_FLOAT" } },
"name": "module_apply_default/MobilenetV2/expanded_conv_2/depthwise/Relu6",
"op": "Relu6"
},
{
"input": [
"module_apply_default/MobilenetV2/expanded_conv_2/depthwise/Relu6",
"module_apply_default/MobilenetV2/expanded_conv_2/project/Conv2D/merged_input"
],
"attr": {
"data_format": { "s": "TkhXQw==" },
"use_cudnn_on_gpu": { "b": true },
"padding": { "s": "U0FNRQ==" },
"strides": { "list": { "i": ["1", "1", "1", "1"] } },
"T": { "type": "DT_FLOAT" },
"dilations": { "list": { "i": ["1", "1", "1", "1"] } }
},
"name": "module_apply_default/MobilenetV2/expanded_conv_2/project/BatchNorm/FusedBatchNorm/Mul",
"op": "Conv2D"
},
{
"input": [
"module_apply_default/MobilenetV2/expanded_conv_2/project/BatchNorm/FusedBatchNorm/Mul",
"module_apply_default/MobilenetV2/expanded_conv_1/project/BatchNorm/FusedBatchNorm"
],
"attr": {
"_grappler:ArithmeticOptimizer:AddOpsRewriteStage": { "b": true },
"T": { "type": "DT_FLOAT" },
"N": { "i": "2" }
},
"name": "module_apply_default/MobilenetV2/expanded_conv_2/ArithmeticOptimizer/AddOpsRewrite_Leaf_1_add",
"op": "AddN"
},
{
"input": [
"module_apply_default/MobilenetV2/expanded_conv_2/project/BatchNorm/FusedBatchNorm/Offset",
"module_apply_default/MobilenetV2/expanded_conv_2/ArithmeticOptimizer/AddOpsRewrite_Leaf_1_add"
],
"attr": {
"_grappler:ArithmeticOptimizer:AddOpsRewriteStage": { "b": true },
"T": { "type": "DT_FLOAT" }
},
"name": "module_apply_default/MobilenetV2/expanded_conv_2/ArithmeticOptimizer/AddOpsRewrite_add",
"op": "Add"
},
{
"input": [
"module_apply_default/MobilenetV2/expanded_conv_2/ArithmeticOptimizer/AddOpsRewrite_add",
"module_apply_default/MobilenetV2/expanded_conv_3/expand/Conv2D/merged_input"
],
"attr": {
"data_format": { "s": "TkhXQw==" },
"use_cudnn_on_gpu": { "b": true },
"padding": { "s": "U0FNRQ==" },
"strides": { "list": { "i": ["1", "1", "1", "1"] } },
"T": { "type": "DT_FLOAT" },
"dilations": { "list": { "i": ["1", "1", "1", "1"] } }
},
"name": "module_apply_default/MobilenetV2/expanded_conv_3/expand/BatchNorm/FusedBatchNorm/Mul",
"op": "Conv2D"
},
{
"input": [
"module_apply_default/MobilenetV2/expanded_conv_3/expand/BatchNorm/FusedBatchNorm/Mul",
"module_apply_default/MobilenetV2/expanded_conv_3/expand/BatchNorm/FusedBatchNorm/Offset"
],
"attr": { "T": { "type": "DT_FLOAT" } },
"name": "module_apply_default/MobilenetV2/expanded_conv_3/expand/BatchNorm/FusedBatchNorm",
"op": "Add"
},
{
"input": [
"module_apply_default/MobilenetV2/expanded_conv_3/expand/BatchNorm/FusedBatchNorm"
],
"attr": { "T": { "type": "DT_FLOAT" } },
"name": "module_apply_default/MobilenetV2/expanded_conv_3/expand/Relu6",
"op": "Relu6"
},
{
"input": [
"module_apply_default/MobilenetV2/expanded_conv_3/expand/Relu6",
"module/MobilenetV2/expanded_conv_3/depthwise/depthwise_weights"
],
"attr": {
"dilations": { "list": { "i": ["1", "1", "1", "1"] } },
"strides": { "list": { "i": ["1", "2", "2", "1"] } },
"padding": { "s": "U0FNRQ==" },
"T": { "type": "DT_FLOAT" },
"data_format": { "s": "TkhXQw==" }
},
"name": "module_apply_default/MobilenetV2/expanded_conv_3/depthwise/depthwise",
"op": "DepthwiseConv2dNative"
},
{
"input": [
"module_apply_default/MobilenetV2/expanded_conv_3/depthwise/depthwise",
"module_apply_default/MobilenetV2/expanded_conv_3/depthwise/BatchNorm/FusedBatchNorm/Scaled"
],
"attr": { "T": { "type": "DT_FLOAT" } },
"name": "module_apply_default/MobilenetV2/expanded_conv_3/depthwise/BatchNorm/FusedBatchNorm/Mul",
"op": "Mul"
},
{
"input": [
"module_apply_default/MobilenetV2/expanded_conv_3/depthwise/BatchNorm/FusedBatchNorm/Mul",
"module_apply_default/MobilenetV2/expanded_conv_3/depthwise/BatchNorm/FusedBatchNorm/Offset"
],
"attr": { "T": { "type": "DT_FLOAT" } },
"name": "module_apply_default/MobilenetV2/expanded_conv_3/depthwise/BatchNorm/FusedBatchNorm",
"op": "Add"
},
{
"input": [
"module_apply_default/MobilenetV2/expanded_conv_3/depthwise/BatchNorm/FusedBatchNorm"
],
"attr": { "T": { "type": "DT_FLOAT" } },
"name": "module_apply_default/MobilenetV2/expanded_conv_3/depthwise/Relu6",
"op": "Relu6"
},
{
"input": [
"module_apply_default/MobilenetV2/expanded_conv_3/depthwise/Relu6",
"module_apply_default/MobilenetV2/expanded_conv_3/project/Conv2D/merged_input"
],
"attr": {
"data_format": { "s": "TkhXQw==" },
"use_cudnn_on_gpu": { "b": true },
"padding": { "s": "U0FNRQ==" },
"strides": { "list": { "i": ["1", "1", "1", "1"] } },
"T": { "type": "DT_FLOAT" },
"dilations": { "list": { "i": ["1", "1", "1", "1"] } }
},
"name": "module_apply_default/MobilenetV2/expanded_conv_3/project/BatchNorm/FusedBatchNorm/Mul",
"op": "Conv2D"
},
{
"input": [
"module_apply_default/MobilenetV2/expanded_conv_3/project/BatchNorm/FusedBatchNorm/Mul",
"module_apply_default/MobilenetV2/expanded_conv_3/project/BatchNorm/FusedBatchNorm/Offset"
],
"attr": { "T": { "type": "DT_FLOAT" } },
"name": "module_apply_default/MobilenetV2/expanded_conv_3/project/BatchNorm/FusedBatchNorm",
"op": "Add"
},
{
"input": [
"module_apply_default/MobilenetV2/expanded_conv_3/project/BatchNorm/FusedBatchNorm",
"module_apply_default/MobilenetV2/expanded_conv_4/expand/Conv2D/merged_input"
],
"attr": {
"data_format": { "s": "TkhXQw==" },
"use_cudnn_on_gpu": { "b": true },
"padding": { "s": "U0FNRQ==" },
"strides": { "list": { "i": ["1", "1", "1", "1"] } },
"T": { "type": "DT_FLOAT" },
"dilations": { "list": { "i": ["1", "1", "1", "1"] } }
},
"name": "module_apply_default/MobilenetV2/expanded_conv_4/expand/BatchNorm/FusedBatchNorm/Mul",
"op": "Conv2D"
},
{
"input": [
"module_apply_default/MobilenetV2/expanded_conv_4/expand/BatchNorm/FusedBatchNorm/Mul",
"module_apply_default/MobilenetV2/expanded_conv_4/expand/BatchNorm/FusedBatchNorm/Offset"
],
"attr": { "T": { "type": "DT_FLOAT" } },
"name": "module_apply_default/MobilenetV2/expanded_conv_4/expand/BatchNorm/FusedBatchNorm",
"op": "Add"
},
{
"input": [
"module_apply_default/MobilenetV2/expanded_conv_4/expand/BatchNorm/FusedBatchNorm"
],
"attr": { "T": { "type": "DT_FLOAT" } },
"name": "module_apply_default/MobilenetV2/expanded_conv_4/expand/Relu6",
"op": "Relu6"
},
{
"input": [
"module_apply_default/MobilenetV2/expanded_conv_4/expand/Relu6",
"module/MobilenetV2/expanded_conv_4/depthwise/depthwise_weights"
],
"attr": {
"padding": { "s": "U0FNRQ==" },
"strides": { "list": { "i": ["1", "1", "1", "1"] } },
"dilations": { "list": { "i": ["1", "1", "1", "1"] } },
"T": { "type": "DT_FLOAT" },
"data_format": { "s": "TkhXQw==" }
},
"name": "module_apply_default/MobilenetV2/expanded_conv_4/depthwise/depthwise",
"op": "DepthwiseConv2dNative"
},
{
"input": [
"module_apply_default/MobilenetV2/expanded_conv_4/depthwise/depthwise",
"module_apply_default/MobilenetV2/expanded_conv_4/depthwise/BatchNorm/FusedBatchNorm/Scaled"
],
"attr": { "T": { "type": "DT_FLOAT" } },
"name": "module_apply_default/MobilenetV2/expanded_conv_4/depthwise/BatchNorm/FusedBatchNorm/Mul",
"op": "Mul"
},
{
"input": [
"module_apply_default/MobilenetV2/expanded_conv_4/depthwise/BatchNorm/FusedBatchNorm/Mul",
"module_apply_default/MobilenetV2/expanded_conv_4/depthwise/BatchNorm/FusedBatchNorm/Offset"
],
"attr": { "T": { "type": "DT_FLOAT" } },
"name": "module_apply_default/MobilenetV2/expanded_conv_4/depthwise/BatchNorm/FusedBatchNorm",
"op": "Add"
},
{
"input": [
"module_apply_default/MobilenetV2/expanded_conv_4/depthwise/BatchNorm/FusedBatchNorm"
],
"attr": { "T": { "type": "DT_FLOAT" } },
"name": "module_apply_default/MobilenetV2/expanded_conv_4/depthwise/Relu6",
"op": "Relu6"
},
{
"input": [
"module_apply_default/MobilenetV2/expanded_conv_4/depthwise/Relu6",
"module_apply_default/MobilenetV2/expanded_conv_4/project/Conv2D/merged_input"
],
"attr": {
"data_format": { "s": "TkhXQw==" },
"use_cudnn_on_gpu": { "b": true },
"padding": { "s": "U0FNRQ==" },
"strides": { "list": { "i": ["1", "1", "1", "1"] } },
"T": { "type": "DT_FLOAT" },
"dilations": { "list": { "i": ["1", "1", "1", "1"] } }
},
"name": "module_apply_default/MobilenetV2/expanded_conv_4/project/BatchNorm/FusedBatchNorm/Mul",
"op": "Conv2D"
},
{
"input": [
"module_apply_default/MobilenetV2/expanded_conv_4/project/BatchNorm/FusedBatchNorm/Mul",
"module_apply_default/MobilenetV2/expanded_conv_3/project/BatchNorm/FusedBatchNorm"
],
"attr": {
"_grappler:ArithmeticOptimizer:AddOpsRewriteStage": { "b": true },
"T": { "type": "DT_FLOAT" },
"N": { "i": "2" }
},
"name": "module_apply_default/MobilenetV2/expanded_conv_4/ArithmeticOptimizer/AddOpsRewrite_Leaf_1_add",
"op": "AddN"
},
{
"input": [
"module_apply_default/MobilenetV2/expanded_conv_4/project/BatchNorm/FusedBatchNorm/Offset",
"module_apply_default/MobilenetV2/expanded_conv_4/ArithmeticOptimizer/AddOpsRewrite_Leaf_1_add"
],
"attr": {
"_grappler:ArithmeticOptimizer:AddOpsRewriteStage": { "b": true },
"T": { "type": "DT_FLOAT" }
},
"name": "module_apply_default/MobilenetV2/expanded_conv_4/ArithmeticOptimizer/AddOpsRewrite_add",
"op": "Add"
},
{
"input": [
"module_apply_default/MobilenetV2/expanded_conv_4/ArithmeticOptimizer/AddOpsRewrite_add",
"module_apply_default/MobilenetV2/expanded_conv_5/expand/Conv2D/merged_input"
],
"attr": {
"data_format": { "s": "TkhXQw==" },
"use_cudnn_on_gpu": { "b": true },
"padding": { "s": "U0FNRQ==" },
"strides": { "list": { "i": ["1", "1", "1", "1"] } },
"T": { "type": "DT_FLOAT" },
"dilations": { "list": { "i": ["1", "1", "1", "1"] } }
},
"name": "module_apply_default/MobilenetV2/expanded_conv_5/expand/BatchNorm/FusedBatchNorm/Mul",
"op": "Conv2D"
},
{
"input": [
"module_apply_default/MobilenetV2/expanded_conv_5/expand/BatchNorm/FusedBatchNorm/Mul",
"module_apply_default/MobilenetV2/expanded_conv_5/expand/BatchNorm/FusedBatchNorm/Offset"
],
"attr": { "T": { "type": "DT_FLOAT" } },
"name": "module_apply_default/MobilenetV2/expanded_conv_5/expand/BatchNorm/FusedBatchNorm",
"op": "Add"
},
{
"input": [
"module_apply_default/MobilenetV2/expanded_conv_5/expand/BatchNorm/FusedBatchNorm"
],
"attr": { "T": { "type": "DT_FLOAT" } },
"name": "module_apply_default/MobilenetV2/expanded_conv_5/expand/Relu6",
"op": "Relu6"
},
{
"input": [
"module_apply_default/MobilenetV2/expanded_conv_5/expand/Relu6",
"module/MobilenetV2/expanded_conv_5/depthwise/depthwise_weights"
],
"attr": {
"padding": { "s": "U0FNRQ==" },
"dilations": { "list": { "i": ["1", "1", "1", "1"] } },
"data_format": { "s": "TkhXQw==" },
"T": { "type": "DT_FLOAT" },
"strides": { "list": { "i": ["1", "1", "1", "1"] } }
},
"name": "module_apply_default/MobilenetV2/expanded_conv_5/depthwise/depthwise",
"op": "DepthwiseConv2dNative"
},
{
"input": [
"module_apply_default/MobilenetV2/expanded_conv_5/depthwise/depthwise",
"module_apply_default/MobilenetV2/expanded_conv_5/depthwise/BatchNorm/FusedBatchNorm/Scaled"
],
"attr": { "T": { "type": "DT_FLOAT" } },
"name": "module_apply_default/MobilenetV2/expanded_conv_5/depthwise/BatchNorm/FusedBatchNorm/Mul",
"op": "Mul"
},
{
"input": [
"module_apply_default/MobilenetV2/expanded_conv_5/depthwise/BatchNorm/FusedBatchNorm/Mul",
"module_apply_default/MobilenetV2/expanded_conv_5/depthwise/BatchNorm/FusedBatchNorm/Offset"
],
"attr": { "T": { "type": "DT_FLOAT" } },
"name": "module_apply_default/MobilenetV2/expanded_conv_5/depthwise/BatchNorm/FusedBatchNorm",
"op": "Add"
},
{
"input": [
"module_apply_default/MobilenetV2/expanded_conv_5/depthwise/BatchNorm/FusedBatchNorm"
],
"attr": { "T": { "type": "DT_FLOAT" } },
"name": "module_apply_default/MobilenetV2/expanded_conv_5/depthwise/Relu6",
"op": "Relu6"
},
{
"input": [
"module_apply_default/MobilenetV2/expanded_conv_5/depthwise/Relu6",
"module_apply_default/MobilenetV2/expanded_conv_5/project/Conv2D/merged_input"
],
"attr": {
"data_format": { "s": "TkhXQw==" },
"use_cudnn_on_gpu": { "b": true },
"padding": { "s": "U0FNRQ==" },
"strides": { "list": { "i": ["1", "1", "1", "1"] } },
"T": { "type": "DT_FLOAT" },
"dilations": { "list": { "i": ["1", "1", "1", "1"] } }
},
"name": "module_apply_default/MobilenetV2/expanded_conv_5/project/BatchNorm/FusedBatchNorm/Mul",
"op": "Conv2D"
},
{
"input": [
"module_apply_default/MobilenetV2/expanded_conv_5/project/BatchNorm/FusedBatchNorm/Mul",
"module_apply_default/MobilenetV2/expanded_conv_4/ArithmeticOptimizer/AddOpsRewrite_add"
],
"attr": {
"_grappler:ArithmeticOptimizer:AddOpsRewriteStage": { "b": true },
"T": { "type": "DT_FLOAT" },
"N": { "i": "2" }
},
"name": "module_apply_default/MobilenetV2/expanded_conv_5/ArithmeticOptimizer/AddOpsRewrite_Leaf_1_add",
"op": "AddN"
},
{
"input": [
"module_apply_default/MobilenetV2/expanded_conv_5/project/BatchNorm/FusedBatchNorm/Offset",
"module_apply_default/MobilenetV2/expanded_conv_5/ArithmeticOptimizer/AddOpsRewrite_Leaf_1_add"
],
"attr": {
"_grappler:ArithmeticOptimizer:AddOpsRewriteStage": { "b": true },
"T": { "type": "DT_FLOAT" }
},
"name": "module_apply_default/MobilenetV2/expanded_conv_5/ArithmeticOptimizer/AddOpsRewrite_add",
"op": "Add"
},
{
"input": [
"module_apply_default/MobilenetV2/expanded_conv_5/ArithmeticOptimizer/AddOpsRewrite_add",
"module_apply_default/MobilenetV2/expanded_conv_6/expand/Conv2D/merged_input"
],
"attr": {
"data_format": { "s": "TkhXQw==" },
"use_cudnn_on_gpu": { "b": true },
"padding": { "s": "U0FNRQ==" },
"strides": { "list": { "i": ["1", "1", "1", "1"] } },
"T": { "type": "DT_FLOAT" },
"dilations": { "list": { "i": ["1", "1", "1", "1"] } }
},
"name": "module_apply_default/MobilenetV2/expanded_conv_6/expand/BatchNorm/FusedBatchNorm/Mul",
"op": "Conv2D"
},
{
"input": [
"module_apply_default/MobilenetV2/expanded_conv_6/expand/BatchNorm/FusedBatchNorm/Mul",
"module_apply_default/MobilenetV2/expanded_conv_6/expand/BatchNorm/FusedBatchNorm/Offset"
],
"attr": { "T": { "type": "DT_FLOAT" } },
"name": "module_apply_default/MobilenetV2/expanded_conv_6/expand/BatchNorm/FusedBatchNorm",
"op": "Add"
},
{
"input": [
"module_apply_default/MobilenetV2/expanded_conv_6/expand/BatchNorm/FusedBatchNorm"
],
"attr": { "T": { "type": "DT_FLOAT" } },
"name": "module_apply_default/MobilenetV2/expanded_conv_6/expand/Relu6",
"op": "Relu6"
},
{
"input": [
"module_apply_default/MobilenetV2/expanded_conv_6/expand/Relu6",
"module/MobilenetV2/expanded_conv_6/depthwise/depthwise_weights"
],
"attr": {
"dilations": { "list": { "i": ["1", "1", "1", "1"] } },
"padding": { "s": "U0FNRQ==" },
"data_format": { "s": "TkhXQw==" },
"T": { "type": "DT_FLOAT" },
"strides": { "list": { "i": ["1", "2", "2", "1"] } }
},
"name": "module_apply_default/MobilenetV2/expanded_conv_6/depthwise/depthwise",
"op": "DepthwiseConv2dNative"
},
{
"input": [
"module_apply_default/MobilenetV2/expanded_conv_6/depthwise/depthwise",
"module_apply_default/MobilenetV2/expanded_conv_6/depthwise/BatchNorm/FusedBatchNorm/Scaled"
],
"attr": { "T": { "type": "DT_FLOAT" } },
"name": "module_apply_default/MobilenetV2/expanded_conv_6/depthwise/BatchNorm/FusedBatchNorm/Mul",
"op": "Mul"
},
{
"input": [
"module_apply_default/MobilenetV2/expanded_conv_6/depthwise/BatchNorm/FusedBatchNorm/Mul",
"module_apply_default/MobilenetV2/expanded_conv_6/depthwise/BatchNorm/FusedBatchNorm/Offset"
],
"attr": { "T": { "type": "DT_FLOAT" } },
"name": "module_apply_default/MobilenetV2/expanded_conv_6/depthwise/BatchNorm/FusedBatchNorm",
"op": "Add"
},
{
"input": [
"module_apply_default/MobilenetV2/expanded_conv_6/depthwise/BatchNorm/FusedBatchNorm"
],
"attr": { "T": { "type": "DT_FLOAT" } },
"name": "module_apply_default/MobilenetV2/expanded_conv_6/depthwise/Relu6",
"op": "Relu6"
},
{
"input": [
"module_apply_default/MobilenetV2/expanded_conv_6/depthwise/Relu6",
"module_apply_default/MobilenetV2/expanded_conv_6/project/Conv2D/merged_input"
],
"attr": {
"data_format": { "s": "TkhXQw==" },
"use_cudnn_on_gpu": { "b": true },
"padding": { "s": "U0FNRQ==" },
"strides": { "list": { "i": ["1", "1", "1", "1"] } },
"T": { "type": "DT_FLOAT" },
"dilations": { "list": { "i": ["1", "1", "1", "1"] } }
},
"name": "module_apply_default/MobilenetV2/expanded_conv_6/project/BatchNorm/FusedBatchNorm/Mul",
"op": "Conv2D"
},
{
"input": [
"module_apply_default/MobilenetV2/expanded_conv_6/project/BatchNorm/FusedBatchNorm/Mul",
"module_apply_default/MobilenetV2/expanded_conv_6/project/BatchNorm/FusedBatchNorm/Offset"
],
"attr": { "T": { "type": "DT_FLOAT" } },
"name": "module_apply_default/MobilenetV2/expanded_conv_6/project/BatchNorm/FusedBatchNorm",
"op": "Add"
},
{
"input": [
"module_apply_default/MobilenetV2/expanded_conv_6/project/BatchNorm/FusedBatchNorm",
"module_apply_default/MobilenetV2/expanded_conv_7/expand/Conv2D/merged_input"
],
"attr": {
"data_format": { "s": "TkhXQw==" },
"use_cudnn_on_gpu": { "b": true },
"padding": { "s": "U0FNRQ==" },
"strides": { "list": { "i": ["1", "1", "1", "1"] } },
"T": { "type": "DT_FLOAT" },
"dilations": { "list": { "i": ["1", "1", "1", "1"] } }
},
"name": "module_apply_default/MobilenetV2/expanded_conv_7/expand/BatchNorm/FusedBatchNorm/Mul",
"op": "Conv2D"
},
{
"input": [
"module_apply_default/MobilenetV2/expanded_conv_7/expand/BatchNorm/FusedBatchNorm/Mul",
"module_apply_default/MobilenetV2/expanded_conv_7/expand/BatchNorm/FusedBatchNorm/Offset"
],
"attr": { "T": { "type": "DT_FLOAT" } },
"name": "module_apply_default/MobilenetV2/expanded_conv_7/expand/BatchNorm/FusedBatchNorm",
"op": "Add"
},
{
"input": [
"module_apply_default/MobilenetV2/expanded_conv_7/expand/BatchNorm/FusedBatchNorm"
],
"attr": { "T": { "type": "DT_FLOAT" } },
"name": "module_apply_default/MobilenetV2/expanded_conv_7/expand/Relu6",
"op": "Relu6"
},
{
"input": [
"module_apply_default/MobilenetV2/expanded_conv_7/expand/Relu6",
"module/MobilenetV2/expanded_conv_7/depthwise/depthwise_weights"
],
"attr": {
"padding": { "s": "U0FNRQ==" },
"dilations": { "list": { "i": ["1", "1", "1", "1"] } },
"data_format": { "s": "TkhXQw==" },
"T": { "type": "DT_FLOAT" },
"strides": { "list": { "i": ["1", "1", "1", "1"] } }
},
"name": "module_apply_default/MobilenetV2/expanded_conv_7/depthwise/depthwise",
"op": "DepthwiseConv2dNative"
},
{
"input": [
"module_apply_default/MobilenetV2/expanded_conv_7/depthwise/depthwise",
"module_apply_default/MobilenetV2/expanded_conv_7/depthwise/BatchNorm/FusedBatchNorm/Scaled"
],
"attr": { "T": { "type": "DT_FLOAT" } },
"name": "module_apply_default/MobilenetV2/expanded_conv_7/depthwise/BatchNorm/FusedBatchNorm/Mul",
"op": "Mul"
},
{
"input": [
"module_apply_default/MobilenetV2/expanded_conv_7/depthwise/BatchNorm/FusedBatchNorm/Mul",
"module_apply_default/MobilenetV2/expanded_conv_7/depthwise/BatchNorm/FusedBatchNorm/Offset"
],
"attr": { "T": { "type": "DT_FLOAT" } },
"name": "module_apply_default/MobilenetV2/expanded_conv_7/depthwise/BatchNorm/FusedBatchNorm",
"op": "Add"
},
{
"input": [
"module_apply_default/MobilenetV2/expanded_conv_7/depthwise/BatchNorm/FusedBatchNorm"
],
"attr": { "T": { "type": "DT_FLOAT" } },
"name": "module_apply_default/MobilenetV2/expanded_conv_7/depthwise/Relu6",
"op": "Relu6"
},
{
"input": [
"module_apply_default/MobilenetV2/expanded_conv_7/depthwise/Relu6",
"module_apply_default/MobilenetV2/expanded_conv_7/project/Conv2D/merged_input"
],
"attr": {
"data_format": { "s": "TkhXQw==" },
"use_cudnn_on_gpu": { "b": true },
"padding": { "s": "U0FNRQ==" },
"strides": { "list": { "i": ["1", "1", "1", "1"] } },
"T": { "type": "DT_FLOAT" },
"dilations": { "list": { "i": ["1", "1", "1", "1"] } }
},
"name": "module_apply_default/MobilenetV2/expanded_conv_7/project/BatchNorm/FusedBatchNorm/Mul",
"op": "Conv2D"
},
{
"input": [
"module_apply_default/MobilenetV2/expanded_conv_7/project/BatchNorm/FusedBatchNorm/Mul",
"module_apply_default/MobilenetV2/expanded_conv_6/project/BatchNorm/FusedBatchNorm"
],
"attr": {
"_grappler:ArithmeticOptimizer:AddOpsRewriteStage": { "b": true },
"T": { "type": "DT_FLOAT" },
"N": { "i": "2" }
},
"name": "module_apply_default/MobilenetV2/expanded_conv_7/ArithmeticOptimizer/AddOpsRewrite_Leaf_1_add",
"op": "AddN"
},
{
"input": [
"module_apply_default/MobilenetV2/expanded_conv_7/project/BatchNorm/FusedBatchNorm/Offset",
"module_apply_default/MobilenetV2/expanded_conv_7/ArithmeticOptimizer/AddOpsRewrite_Leaf_1_add"
],
"attr": {
"_grappler:ArithmeticOptimizer:AddOpsRewriteStage": { "b": true },
"T": { "type": "DT_FLOAT" }
},
"name": "module_apply_default/MobilenetV2/expanded_conv_7/ArithmeticOptimizer/AddOpsRewrite_add",
"op": "Add"
},
{
"input": [
"module_apply_default/MobilenetV2/expanded_conv_7/ArithmeticOptimizer/AddOpsRewrite_add",
"module_apply_default/MobilenetV2/expanded_conv_8/expand/Conv2D/merged_input"
],
"attr": {
"data_format": { "s": "TkhXQw==" },
"use_cudnn_on_gpu": { "b": true },
"padding": { "s": "U0FNRQ==" },
"strides": { "list": { "i": ["1", "1", "1", "1"] } },
"T": { "type": "DT_FLOAT" },
"dilations": { "list": { "i": ["1", "1", "1", "1"] } }
},
"name": "module_apply_default/MobilenetV2/expanded_conv_8/expand/BatchNorm/FusedBatchNorm/Mul",
"op": "Conv2D"
},
{
"input": [
"module_apply_default/MobilenetV2/expanded_conv_8/expand/BatchNorm/FusedBatchNorm/Mul",
"module_apply_default/MobilenetV2/expanded_conv_8/expand/BatchNorm/FusedBatchNorm/Offset"
],
"attr": { "T": { "type": "DT_FLOAT" } },
"name": "module_apply_default/MobilenetV2/expanded_conv_8/expand/BatchNorm/FusedBatchNorm",
"op": "Add"
},
{
"input": [
"module_apply_default/MobilenetV2/expanded_conv_8/expand/BatchNorm/FusedBatchNorm"
],
"attr": { "T": { "type": "DT_FLOAT" } },
"name": "module_apply_default/MobilenetV2/expanded_conv_8/expand/Relu6",
"op": "Relu6"
},
{
"input": [
"module_apply_default/MobilenetV2/expanded_conv_8/expand/Relu6",
"module/MobilenetV2/expanded_conv_8/depthwise/depthwise_weights"
],
"attr": {
"dilations": { "list": { "i": ["1", "1", "1", "1"] } },
"strides": { "list": { "i": ["1", "1", "1", "1"] } },
"padding": { "s": "U0FNRQ==" },
"data_format": { "s": "TkhXQw==" },
"T": { "type": "DT_FLOAT" }
},
"name": "module_apply_default/MobilenetV2/expanded_conv_8/depthwise/depthwise",
"op": "DepthwiseConv2dNative"
},
{
"input": [
"module_apply_default/MobilenetV2/expanded_conv_8/depthwise/depthwise",
"module_apply_default/MobilenetV2/expanded_conv_8/depthwise/BatchNorm/FusedBatchNorm/Scaled"
],
"attr": { "T": { "type": "DT_FLOAT" } },
"name": "module_apply_default/MobilenetV2/expanded_conv_8/depthwise/BatchNorm/FusedBatchNorm/Mul",
"op": "Mul"
},
{
"input": [
"module_apply_default/MobilenetV2/expanded_conv_8/depthwise/BatchNorm/FusedBatchNorm/Mul",
"module_apply_default/MobilenetV2/expanded_conv_8/depthwise/BatchNorm/FusedBatchNorm/Offset"
],
"attr": { "T": { "type": "DT_FLOAT" } },
"name": "module_apply_default/MobilenetV2/expanded_conv_8/depthwise/BatchNorm/FusedBatchNorm",
"op": "Add"
},
{
"input": [
"module_apply_default/MobilenetV2/expanded_conv_8/depthwise/BatchNorm/FusedBatchNorm"
],
"attr": { "T": { "type": "DT_FLOAT" } },
"name": "module_apply_default/MobilenetV2/expanded_conv_8/depthwise/Relu6",
"op": "Relu6"
},
{
"input": [
"module_apply_default/MobilenetV2/expanded_conv_8/depthwise/Relu6",
"module_apply_default/MobilenetV2/expanded_conv_8/project/Conv2D/merged_input"
],
"attr": {
"data_format": { "s": "TkhXQw==" },
"use_cudnn_on_gpu": { "b": true },
"padding": { "s": "U0FNRQ==" },
"strides": { "list": { "i": ["1", "1", "1", "1"] } },
"T": { "type": "DT_FLOAT" },
"dilations": { "list": { "i": ["1", "1", "1", "1"] } }
},
"name": "module_apply_default/MobilenetV2/expanded_conv_8/project/BatchNorm/FusedBatchNorm/Mul",
"op": "Conv2D"
},
{
"input": [
"module_apply_default/MobilenetV2/expanded_conv_8/project/BatchNorm/FusedBatchNorm/Mul",
"module_apply_default/MobilenetV2/expanded_conv_7/ArithmeticOptimizer/AddOpsRewrite_add"
],
"attr": {
"_grappler:ArithmeticOptimizer:AddOpsRewriteStage": { "b": true },
"T": { "type": "DT_FLOAT" },
"N": { "i": "2" }
},
"name": "module_apply_default/MobilenetV2/expanded_conv_8/ArithmeticOptimizer/AddOpsRewrite_Leaf_1_add",
"op": "AddN"
},
{
"input": [
"module_apply_default/MobilenetV2/expanded_conv_8/project/BatchNorm/FusedBatchNorm/Offset",
"module_apply_default/MobilenetV2/expanded_conv_8/ArithmeticOptimizer/AddOpsRewrite_Leaf_1_add"
],
"attr": {
"_grappler:ArithmeticOptimizer:AddOpsRewriteStage": { "b": true },
"T": { "type": "DT_FLOAT" }
},
"name": "module_apply_default/MobilenetV2/expanded_conv_8/ArithmeticOptimizer/AddOpsRewrite_add",
"op": "Add"
},
{
"input": [
"module_apply_default/MobilenetV2/expanded_conv_8/ArithmeticOptimizer/AddOpsRewrite_add",
"module_apply_default/MobilenetV2/expanded_conv_9/expand/Conv2D/merged_input"
],
"attr": {
"data_format": { "s": "TkhXQw==" },
"use_cudnn_on_gpu": { "b": true },
"padding": { "s": "U0FNRQ==" },
"strides": { "list": { "i": ["1", "1", "1", "1"] } },
"T": { "type": "DT_FLOAT" },
"dilations": { "list": { "i": ["1", "1", "1", "1"] } }
},
"name": "module_apply_default/MobilenetV2/expanded_conv_9/expand/BatchNorm/FusedBatchNorm/Mul",
"op": "Conv2D"
},
{
"input": [
"module_apply_default/MobilenetV2/expanded_conv_9/expand/BatchNorm/FusedBatchNorm/Mul",
"module_apply_default/MobilenetV2/expanded_conv_9/expand/BatchNorm/FusedBatchNorm/Offset"
],
"attr": { "T": { "type": "DT_FLOAT" } },
"name": "module_apply_default/MobilenetV2/expanded_conv_9/expand/BatchNorm/FusedBatchNorm",
"op": "Add"
},
{
"input": [
"module_apply_default/MobilenetV2/expanded_conv_9/expand/BatchNorm/FusedBatchNorm"
],
"attr": { "T": { "type": "DT_FLOAT" } },
"name": "module_apply_default/MobilenetV2/expanded_conv_9/expand/Relu6",
"op": "Relu6"
},
{
"input": [
"module_apply_default/MobilenetV2/expanded_conv_9/expand/Relu6",
"module/MobilenetV2/expanded_conv_9/depthwise/depthwise_weights"
],
"attr": {
"dilations": { "list": { "i": ["1", "1", "1", "1"] } },
"strides": { "list": { "i": ["1", "1", "1", "1"] } },
"padding": { "s": "U0FNRQ==" },
"T": { "type": "DT_FLOAT" },
"data_format": { "s": "TkhXQw==" }
},
"name": "module_apply_default/MobilenetV2/expanded_conv_9/depthwise/depthwise",
"op": "DepthwiseConv2dNative"
},
{
"input": [
"module_apply_default/MobilenetV2/expanded_conv_9/depthwise/depthwise",
"module_apply_default/MobilenetV2/expanded_conv_9/depthwise/BatchNorm/FusedBatchNorm/Scaled"
],
"attr": { "T": { "type": "DT_FLOAT" } },
"name": "module_apply_default/MobilenetV2/expanded_conv_9/depthwise/BatchNorm/FusedBatchNorm/Mul",
"op": "Mul"
},
{
"input": [
"module_apply_default/MobilenetV2/expanded_conv_9/depthwise/BatchNorm/FusedBatchNorm/Mul",
"module_apply_default/MobilenetV2/expanded_conv_9/depthwise/BatchNorm/FusedBatchNorm/Offset"
],
"attr": { "T": { "type": "DT_FLOAT" } },
"name": "module_apply_default/MobilenetV2/expanded_conv_9/depthwise/BatchNorm/FusedBatchNorm",
"op": "Add"
},
{
"input": [
"module_apply_default/MobilenetV2/expanded_conv_9/depthwise/BatchNorm/FusedBatchNorm"
],
"attr": { "T": { "type": "DT_FLOAT" } },
"name": "module_apply_default/MobilenetV2/expanded_conv_9/depthwise/Relu6",
"op": "Relu6"
},
{
"input": [
"module_apply_default/MobilenetV2/expanded_conv_9/depthwise/Relu6",
"module_apply_default/MobilenetV2/expanded_conv_9/project/Conv2D/merged_input"
],
"attr": {
"data_format": { "s": "TkhXQw==" },
"use_cudnn_on_gpu": { "b": true },
"padding": { "s": "U0FNRQ==" },
"strides": { "list": { "i": ["1", "1", "1", "1"] } },
"T": { "type": "DT_FLOAT" },
"dilations": { "list": { "i": ["1", "1", "1", "1"] } }
},
"name": "module_apply_default/MobilenetV2/expanded_conv_9/project/BatchNorm/FusedBatchNorm/Mul",
"op": "Conv2D"
},
{
"input": [
"module_apply_default/MobilenetV2/expanded_conv_9/project/BatchNorm/FusedBatchNorm/Mul",
"module_apply_default/MobilenetV2/expanded_conv_8/ArithmeticOptimizer/AddOpsRewrite_add"
],
"attr": {
"_grappler:ArithmeticOptimizer:AddOpsRewriteStage": { "b": true },
"T": { "type": "DT_FLOAT" },
"N": { "i": "2" }
},
"name": "module_apply_default/MobilenetV2/expanded_conv_9/ArithmeticOptimizer/AddOpsRewrite_Leaf_1_add",
"op": "AddN"
},
{
"input": [
"module_apply_default/MobilenetV2/expanded_conv_9/project/BatchNorm/FusedBatchNorm/Offset",
"module_apply_default/MobilenetV2/expanded_conv_9/ArithmeticOptimizer/AddOpsRewrite_Leaf_1_add"
],
"attr": {
"_grappler:ArithmeticOptimizer:AddOpsRewriteStage": { "b": true },
"T": { "type": "DT_FLOAT" }
},
"name": "module_apply_default/MobilenetV2/expanded_conv_9/ArithmeticOptimizer/AddOpsRewrite_add",
"op": "Add"
},
{
"input": [
"module_apply_default/MobilenetV2/expanded_conv_9/ArithmeticOptimizer/AddOpsRewrite_add",
"module_apply_default/MobilenetV2/expanded_conv_10/expand/Conv2D/merged_input"
],
"attr": {
"data_format": { "s": "TkhXQw==" },
"use_cudnn_on_gpu": { "b": true },
"padding": { "s": "U0FNRQ==" },
"strides": { "list": { "i": ["1", "1", "1", "1"] } },
"T": { "type": "DT_FLOAT" },
"dilations": { "list": { "i": ["1", "1", "1", "1"] } }
},
"name": "module_apply_default/MobilenetV2/expanded_conv_10/expand/BatchNorm/FusedBatchNorm/Mul",
"op": "Conv2D"
},
{
"input": [
"module_apply_default/MobilenetV2/expanded_conv_10/expand/BatchNorm/FusedBatchNorm/Mul",
"module_apply_default/MobilenetV2/expanded_conv_10/expand/BatchNorm/FusedBatchNorm/Offset"
],
"attr": { "T": { "type": "DT_FLOAT" } },
"name": "module_apply_default/MobilenetV2/expanded_conv_10/expand/BatchNorm/FusedBatchNorm",
"op": "Add"
},
{
"input": [
"module_apply_default/MobilenetV2/expanded_conv_10/expand/BatchNorm/FusedBatchNorm"
],
"attr": { "T": { "type": "DT_FLOAT" } },
"name": "module_apply_default/MobilenetV2/expanded_conv_10/expand/Relu6",
"op": "Relu6"
},
{
"input": [
"module_apply_default/MobilenetV2/expanded_conv_10/expand/Relu6",
"module/MobilenetV2/expanded_conv_10/depthwise/depthwise_weights"
],
"attr": {
"dilations": { "list": { "i": ["1", "1", "1", "1"] } },
"padding": { "s": "U0FNRQ==" },
"strides": { "list": { "i": ["1", "1", "1", "1"] } },
"T": { "type": "DT_FLOAT" },
"data_format": { "s": "TkhXQw==" }
},
"name": "module_apply_default/MobilenetV2/expanded_conv_10/depthwise/depthwise",
"op": "DepthwiseConv2dNative"
},
{
"input": [
"module_apply_default/MobilenetV2/expanded_conv_10/depthwise/depthwise",
"module_apply_default/MobilenetV2/expanded_conv_10/depthwise/BatchNorm/FusedBatchNorm/Scaled"
],
"attr": { "T": { "type": "DT_FLOAT" } },
"name": "module_apply_default/MobilenetV2/expanded_conv_10/depthwise/BatchNorm/FusedBatchNorm/Mul",
"op": "Mul"
},
{
"input": [
"module_apply_default/MobilenetV2/expanded_conv_10/depthwise/BatchNorm/FusedBatchNorm/Mul",
"module_apply_default/MobilenetV2/expanded_conv_10/depthwise/BatchNorm/FusedBatchNorm/Offset"
],
"attr": { "T": { "type": "DT_FLOAT" } },
"name": "module_apply_default/MobilenetV2/expanded_conv_10/depthwise/BatchNorm/FusedBatchNorm",
"op": "Add"
},
{
"input": [
"module_apply_default/MobilenetV2/expanded_conv_10/depthwise/BatchNorm/FusedBatchNorm"
],
"attr": { "T": { "type": "DT_FLOAT" } },
"name": "module_apply_default/MobilenetV2/expanded_conv_10/depthwise/Relu6",
"op": "Relu6"
},
{
"input": [
"module_apply_default/MobilenetV2/expanded_conv_10/depthwise/Relu6",
"module_apply_default/MobilenetV2/expanded_conv_10/project/Conv2D/merged_input"
],
"attr": {
"data_format": { "s": "TkhXQw==" },
"use_cudnn_on_gpu": { "b": true },
"padding": { "s": "U0FNRQ==" },
"strides": { "list": { "i": ["1", "1", "1", "1"] } },
"T": { "type": "DT_FLOAT" },
"dilations": { "list": { "i": ["1", "1", "1", "1"] } }
},
"name": "module_apply_default/MobilenetV2/expanded_conv_10/project/BatchNorm/FusedBatchNorm/Mul",
"op": "Conv2D"
},
{
"input": [
"module_apply_default/MobilenetV2/expanded_conv_10/project/BatchNorm/FusedBatchNorm/Mul",
"module_apply_default/MobilenetV2/expanded_conv_10/project/BatchNorm/FusedBatchNorm/Offset"
],
"attr": { "T": { "type": "DT_FLOAT" } },
"name": "module_apply_default/MobilenetV2/expanded_conv_10/project/BatchNorm/FusedBatchNorm",
"op": "Add"
},
{
"input": [
"module_apply_default/MobilenetV2/expanded_conv_10/project/BatchNorm/FusedBatchNorm",
"module_apply_default/MobilenetV2/expanded_conv_11/expand/Conv2D/merged_input"
],
"attr": {
"data_format": { "s": "TkhXQw==" },
"use_cudnn_on_gpu": { "b": true },
"padding": { "s": "U0FNRQ==" },
"strides": { "list": { "i": ["1", "1", "1", "1"] } },
"T": { "type": "DT_FLOAT" },
"dilations": { "list": { "i": ["1", "1", "1", "1"] } }
},
"name": "module_apply_default/MobilenetV2/expanded_conv_11/expand/BatchNorm/FusedBatchNorm/Mul",
"op": "Conv2D"
},
{
"input": [
"module_apply_default/MobilenetV2/expanded_conv_11/expand/BatchNorm/FusedBatchNorm/Mul",
"module_apply_default/MobilenetV2/expanded_conv_11/expand/BatchNorm/FusedBatchNorm/Offset"
],
"attr": { "T": { "type": "DT_FLOAT" } },
"name": "module_apply_default/MobilenetV2/expanded_conv_11/expand/BatchNorm/FusedBatchNorm",
"op": "Add"
},
{
"input": [
"module_apply_default/MobilenetV2/expanded_conv_11/expand/BatchNorm/FusedBatchNorm"
],
"attr": { "T": { "type": "DT_FLOAT" } },
"name": "module_apply_default/MobilenetV2/expanded_conv_11/expand/Relu6",
"op": "Relu6"
},
{
"input": [
"module_apply_default/MobilenetV2/expanded_conv_11/expand/Relu6",
"module/MobilenetV2/expanded_conv_11/depthwise/depthwise_weights"
],
"attr": {
"padding": { "s": "U0FNRQ==" },
"dilations": { "list": { "i": ["1", "1", "1", "1"] } },
"data_format": { "s": "TkhXQw==" },
"T": { "type": "DT_FLOAT" },
"strides": { "list": { "i": ["1", "1", "1", "1"] } }
},
"name": "module_apply_default/MobilenetV2/expanded_conv_11/depthwise/depthwise",
"op": "DepthwiseConv2dNative"
},
{
"input": [
"module_apply_default/MobilenetV2/expanded_conv_11/depthwise/depthwise",
"module_apply_default/MobilenetV2/expanded_conv_11/depthwise/BatchNorm/FusedBatchNorm/Scaled"
],
"attr": { "T": { "type": "DT_FLOAT" } },
"name": "module_apply_default/MobilenetV2/expanded_conv_11/depthwise/BatchNorm/FusedBatchNorm/Mul",
"op": "Mul"
},
{
"input": [
"module_apply_default/MobilenetV2/expanded_conv_11/depthwise/BatchNorm/FusedBatchNorm/Mul",
"module_apply_default/MobilenetV2/expanded_conv_11/depthwise/BatchNorm/FusedBatchNorm/Offset"
],
"attr": { "T": { "type": "DT_FLOAT" } },
"name": "module_apply_default/MobilenetV2/expanded_conv_11/depthwise/BatchNorm/FusedBatchNorm",
"op": "Add"
},
{
"input": [
"module_apply_default/MobilenetV2/expanded_conv_11/depthwise/BatchNorm/FusedBatchNorm"
],
"attr": { "T": { "type": "DT_FLOAT" } },
"name": "module_apply_default/MobilenetV2/expanded_conv_11/depthwise/Relu6",
"op": "Relu6"
},
{
"input": [
"module_apply_default/MobilenetV2/expanded_conv_11/depthwise/Relu6",
"module_apply_default/MobilenetV2/expanded_conv_11/project/Conv2D/merged_input"
],
"attr": {
"data_format": { "s": "TkhXQw==" },
"use_cudnn_on_gpu": { "b": true },
"padding": { "s": "U0FNRQ==" },
"strides": { "list": { "i": ["1", "1", "1", "1"] } },
"T": { "type": "DT_FLOAT" },
"dilations": { "list": { "i": ["1", "1", "1", "1"] } }
},
"name": "module_apply_default/MobilenetV2/expanded_conv_11/project/BatchNorm/FusedBatchNorm/Mul",
"op": "Conv2D"
},
{
"input": [
"module_apply_default/MobilenetV2/expanded_conv_11/project/BatchNorm/FusedBatchNorm/Mul",
"module_apply_default/MobilenetV2/expanded_conv_10/project/BatchNorm/FusedBatchNorm"
],
"attr": {
"_grappler:ArithmeticOptimizer:AddOpsRewriteStage": { "b": true },
"T": { "type": "DT_FLOAT" },
"N": { "i": "2" }
},
"name": "module_apply_default/MobilenetV2/expanded_conv_11/ArithmeticOptimizer/AddOpsRewrite_Leaf_1_add",
"op": "AddN"
},
{
"input": [
"module_apply_default/MobilenetV2/expanded_conv_11/project/BatchNorm/FusedBatchNorm/Offset",
"module_apply_default/MobilenetV2/expanded_conv_11/ArithmeticOptimizer/AddOpsRewrite_Leaf_1_add"
],
"attr": {
"_grappler:ArithmeticOptimizer:AddOpsRewriteStage": { "b": true },
"T": { "type": "DT_FLOAT" }
},
"name": "module_apply_default/MobilenetV2/expanded_conv_11/ArithmeticOptimizer/AddOpsRewrite_add",
"op": "Add"
},
{
"input": [
"module_apply_default/MobilenetV2/expanded_conv_11/ArithmeticOptimizer/AddOpsRewrite_add",
"module_apply_default/MobilenetV2/expanded_conv_12/expand/Conv2D/merged_input"
],
"attr": {
"data_format": { "s": "TkhXQw==" },
"use_cudnn_on_gpu": { "b": true },
"padding": { "s": "U0FNRQ==" },
"strides": { "list": { "i": ["1", "1", "1", "1"] } },
"T": { "type": "DT_FLOAT" },
"dilations": { "list": { "i": ["1", "1", "1", "1"] } }
},
"name": "module_apply_default/MobilenetV2/expanded_conv_12/expand/BatchNorm/FusedBatchNorm/Mul",
"op": "Conv2D"
},
{
"input": [
"module_apply_default/MobilenetV2/expanded_conv_12/expand/BatchNorm/FusedBatchNorm/Mul",
"module_apply_default/MobilenetV2/expanded_conv_12/expand/BatchNorm/FusedBatchNorm/Offset"
],
"attr": { "T": { "type": "DT_FLOAT" } },
"name": "module_apply_default/MobilenetV2/expanded_conv_12/expand/BatchNorm/FusedBatchNorm",
"op": "Add"
},
{
"input": [
"module_apply_default/MobilenetV2/expanded_conv_12/expand/BatchNorm/FusedBatchNorm"
],
"attr": { "T": { "type": "DT_FLOAT" } },
"name": "module_apply_default/MobilenetV2/expanded_conv_12/expand/Relu6",
"op": "Relu6"
},
{
"input": [
"module_apply_default/MobilenetV2/expanded_conv_12/expand/Relu6",
"module/MobilenetV2/expanded_conv_12/depthwise/depthwise_weights"
],
"attr": {
"dilations": { "list": { "i": ["1", "1", "1", "1"] } },
"padding": { "s": "U0FNRQ==" },
"strides": { "list": { "i": ["1", "1", "1", "1"] } },
"T": { "type": "DT_FLOAT" },
"data_format": { "s": "TkhXQw==" }
},
"name": "module_apply_default/MobilenetV2/expanded_conv_12/depthwise/depthwise",
"op": "DepthwiseConv2dNative"
},
{
"input": [
"module_apply_default/MobilenetV2/expanded_conv_12/depthwise/depthwise",
"module_apply_default/MobilenetV2/expanded_conv_12/depthwise/BatchNorm/FusedBatchNorm/Scaled"
],
"attr": { "T": { "type": "DT_FLOAT" } },
"name": "module_apply_default/MobilenetV2/expanded_conv_12/depthwise/BatchNorm/FusedBatchNorm/Mul",
"op": "Mul"
},
{
"input": [
"module_apply_default/MobilenetV2/expanded_conv_12/depthwise/BatchNorm/FusedBatchNorm/Mul",
"module_apply_default/MobilenetV2/expanded_conv_12/depthwise/BatchNorm/FusedBatchNorm/Offset"
],
"attr": { "T": { "type": "DT_FLOAT" } },
"name": "module_apply_default/MobilenetV2/expanded_conv_12/depthwise/BatchNorm/FusedBatchNorm",
"op": "Add"
},
{
"input": [
"module_apply_default/MobilenetV2/expanded_conv_12/depthwise/BatchNorm/FusedBatchNorm"
],
"attr": { "T": { "type": "DT_FLOAT" } },
"name": "module_apply_default/MobilenetV2/expanded_conv_12/depthwise/Relu6",
"op": "Relu6"
},
{
"input": [
"module_apply_default/MobilenetV2/expanded_conv_12/depthwise/Relu6",
"module_apply_default/MobilenetV2/expanded_conv_12/project/Conv2D/merged_input"
],
"attr": {
"data_format": { "s": "TkhXQw==" },
"use_cudnn_on_gpu": { "b": true },
"padding": { "s": "U0FNRQ==" },
"strides": { "list": { "i": ["1", "1", "1", "1"] } },
"T": { "type": "DT_FLOAT" },
"dilations": { "list": { "i": ["1", "1", "1", "1"] } }
},
"name": "module_apply_default/MobilenetV2/expanded_conv_12/project/BatchNorm/FusedBatchNorm/Mul",
"op": "Conv2D"
},
{
"input": [
"module_apply_default/MobilenetV2/expanded_conv_12/project/BatchNorm/FusedBatchNorm/Mul",
"module_apply_default/MobilenetV2/expanded_conv_11/ArithmeticOptimizer/AddOpsRewrite_add"
],
"attr": {
"_grappler:ArithmeticOptimizer:AddOpsRewriteStage": { "b": true },
"T": { "type": "DT_FLOAT" },
"N": { "i": "2" }
},
"name": "module_apply_default/MobilenetV2/expanded_conv_12/ArithmeticOptimizer/AddOpsRewrite_Leaf_1_add",
"op": "AddN"
},
{
"input": [
"module_apply_default/MobilenetV2/expanded_conv_12/project/BatchNorm/FusedBatchNorm/Offset",
"module_apply_default/MobilenetV2/expanded_conv_12/ArithmeticOptimizer/AddOpsRewrite_Leaf_1_add"
],
"attr": {
"_grappler:ArithmeticOptimizer:AddOpsRewriteStage": { "b": true },
"T": { "type": "DT_FLOAT" }
},
"name": "module_apply_default/MobilenetV2/expanded_conv_12/ArithmeticOptimizer/AddOpsRewrite_add",
"op": "Add"
},
{
"input": [
"module_apply_default/MobilenetV2/expanded_conv_12/ArithmeticOptimizer/AddOpsRewrite_add",
"module_apply_default/MobilenetV2/expanded_conv_13/expand/Conv2D/merged_input"
],
"attr": {
"data_format": { "s": "TkhXQw==" },
"use_cudnn_on_gpu": { "b": true },
"padding": { "s": "U0FNRQ==" },
"strides": { "list": { "i": ["1", "1", "1", "1"] } },
"T": { "type": "DT_FLOAT" },
"dilations": { "list": { "i": ["1", "1", "1", "1"] } }
},
"name": "module_apply_default/MobilenetV2/expanded_conv_13/expand/BatchNorm/FusedBatchNorm/Mul",
"op": "Conv2D"
},
{
"input": [
"module_apply_default/MobilenetV2/expanded_conv_13/expand/BatchNorm/FusedBatchNorm/Mul",
"module_apply_default/MobilenetV2/expanded_conv_13/expand/BatchNorm/FusedBatchNorm/Offset"
],
"attr": { "T": { "type": "DT_FLOAT" } },
"name": "module_apply_default/MobilenetV2/expanded_conv_13/expand/BatchNorm/FusedBatchNorm",
"op": "Add"
},
{
"input": [
"module_apply_default/MobilenetV2/expanded_conv_13/expand/BatchNorm/FusedBatchNorm"
],
"attr": { "T": { "type": "DT_FLOAT" } },
"name": "module_apply_default/MobilenetV2/expanded_conv_13/expand/Relu6",
"op": "Relu6"
},
{
"input": [
"module_apply_default/MobilenetV2/expanded_conv_13/expand/Relu6",
"module/MobilenetV2/expanded_conv_13/depthwise/depthwise_weights"
],
"attr": {
"padding": { "s": "U0FNRQ==" },
"dilations": { "list": { "i": ["1", "1", "1", "1"] } },
"strides": { "list": { "i": ["1", "2", "2", "1"] } },
"T": { "type": "DT_FLOAT" },
"data_format": { "s": "TkhXQw==" }
},
"name": "module_apply_default/MobilenetV2/expanded_conv_13/depthwise/depthwise",
"op": "DepthwiseConv2dNative"
},
{
"input": [
"module_apply_default/MobilenetV2/expanded_conv_13/depthwise/depthwise",
"module_apply_default/MobilenetV2/expanded_conv_13/depthwise/BatchNorm/FusedBatchNorm/Scaled"
],
"attr": { "T": { "type": "DT_FLOAT" } },
"name": "module_apply_default/MobilenetV2/expanded_conv_13/depthwise/BatchNorm/FusedBatchNorm/Mul",
"op": "Mul"
},
{
"input": [
"module_apply_default/MobilenetV2/expanded_conv_13/depthwise/BatchNorm/FusedBatchNorm/Mul",
"module_apply_default/MobilenetV2/expanded_conv_13/depthwise/BatchNorm/FusedBatchNorm/Offset"
],
"attr": { "T": { "type": "DT_FLOAT" } },
"name": "module_apply_default/MobilenetV2/expanded_conv_13/depthwise/BatchNorm/FusedBatchNorm",
"op": "Add"
},
{
"input": [
"module_apply_default/MobilenetV2/expanded_conv_13/depthwise/BatchNorm/FusedBatchNorm"
],
"attr": { "T": { "type": "DT_FLOAT" } },
"name": "module_apply_default/MobilenetV2/expanded_conv_13/depthwise/Relu6",
"op": "Relu6"
},
{
"input": [
"module_apply_default/MobilenetV2/expanded_conv_13/depthwise/Relu6",
"module_apply_default/MobilenetV2/expanded_conv_13/project/Conv2D/merged_input"
],
"attr": {
"data_format": { "s": "TkhXQw==" },
"use_cudnn_on_gpu": { "b": true },
"padding": { "s": "U0FNRQ==" },
"strides": { "list": { "i": ["1", "1", "1", "1"] } },
"T": { "type": "DT_FLOAT" },
"dilations": { "list": { "i": ["1", "1", "1", "1"] } }
},
"name": "module_apply_default/MobilenetV2/expanded_conv_13/project/BatchNorm/FusedBatchNorm/Mul",
"op": "Conv2D"
},
{
"input": [
"module_apply_default/MobilenetV2/expanded_conv_13/project/BatchNorm/FusedBatchNorm/Mul",
"module_apply_default/MobilenetV2/expanded_conv_13/project/BatchNorm/FusedBatchNorm/Offset"
],
"attr": { "T": { "type": "DT_FLOAT" } },
"name": "module_apply_default/MobilenetV2/expanded_conv_13/project/BatchNorm/FusedBatchNorm",
"op": "Add"
},
{
"input": [
"module_apply_default/MobilenetV2/expanded_conv_13/project/BatchNorm/FusedBatchNorm",
"module_apply_default/MobilenetV2/expanded_conv_14/expand/Conv2D/merged_input"
],
"attr": {
"data_format": { "s": "TkhXQw==" },
"use_cudnn_on_gpu": { "b": true },
"padding": { "s": "U0FNRQ==" },
"strides": { "list": { "i": ["1", "1", "1", "1"] } },
"T": { "type": "DT_FLOAT" },
"dilations": { "list": { "i": ["1", "1", "1", "1"] } }
},
"name": "module_apply_default/MobilenetV2/expanded_conv_14/expand/BatchNorm/FusedBatchNorm/Mul",
"op": "Conv2D"
},
{
"input": [
"module_apply_default/MobilenetV2/expanded_conv_14/expand/BatchNorm/FusedBatchNorm/Mul",
"module_apply_default/MobilenetV2/expanded_conv_14/expand/BatchNorm/FusedBatchNorm/Offset"
],
"attr": { "T": { "type": "DT_FLOAT" } },
"name": "module_apply_default/MobilenetV2/expanded_conv_14/expand/BatchNorm/FusedBatchNorm",
"op": "Add"
},
{
"input": [
"module_apply_default/MobilenetV2/expanded_conv_14/expand/BatchNorm/FusedBatchNorm"
],
"attr": { "T": { "type": "DT_FLOAT" } },
"name": "module_apply_default/MobilenetV2/expanded_conv_14/expand/Relu6",
"op": "Relu6"
},
{
"input": [
"module_apply_default/MobilenetV2/expanded_conv_14/expand/Relu6",
"module/MobilenetV2/expanded_conv_14/depthwise/depthwise_weights"
],
"attr": {
"dilations": { "list": { "i": ["1", "1", "1", "1"] } },
"padding": { "s": "U0FNRQ==" },
"data_format": { "s": "TkhXQw==" },
"T": { "type": "DT_FLOAT" },
"strides": { "list": { "i": ["1", "1", "1", "1"] } }
},
"name": "module_apply_default/MobilenetV2/expanded_conv_14/depthwise/depthwise",
"op": "DepthwiseConv2dNative"
},
{
"input": [
"module_apply_default/MobilenetV2/expanded_conv_14/depthwise/depthwise",
"module_apply_default/MobilenetV2/expanded_conv_14/depthwise/BatchNorm/FusedBatchNorm/Scaled"
],
"attr": { "T": { "type": "DT_FLOAT" } },
"name": "module_apply_default/MobilenetV2/expanded_conv_14/depthwise/BatchNorm/FusedBatchNorm/Mul",
"op": "Mul"
},
{
"input": [
"module_apply_default/MobilenetV2/expanded_conv_14/depthwise/BatchNorm/FusedBatchNorm/Mul",
"module_apply_default/MobilenetV2/expanded_conv_14/depthwise/BatchNorm/FusedBatchNorm/Offset"
],
"attr": { "T": { "type": "DT_FLOAT" } },
"name": "module_apply_default/MobilenetV2/expanded_conv_14/depthwise/BatchNorm/FusedBatchNorm",
"op": "Add"
},
{
"input": [
"module_apply_default/MobilenetV2/expanded_conv_14/depthwise/BatchNorm/FusedBatchNorm"
],
"attr": { "T": { "type": "DT_FLOAT" } },
"name": "module_apply_default/MobilenetV2/expanded_conv_14/depthwise/Relu6",
"op": "Relu6"
},
{
"input": [
"module_apply_default/MobilenetV2/expanded_conv_14/depthwise/Relu6",
"module_apply_default/MobilenetV2/expanded_conv_14/project/Conv2D/merged_input"
],
"attr": {
"data_format": { "s": "TkhXQw==" },
"use_cudnn_on_gpu": { "b": true },
"padding": { "s": "U0FNRQ==" },
"strides": { "list": { "i": ["1", "1", "1", "1"] } },
"T": { "type": "DT_FLOAT" },
"dilations": { "list": { "i": ["1", "1", "1", "1"] } }
},
"name": "module_apply_default/MobilenetV2/expanded_conv_14/project/BatchNorm/FusedBatchNorm/Mul",
"op": "Conv2D"
},
{
"input": [
"module_apply_default/MobilenetV2/expanded_conv_14/project/BatchNorm/FusedBatchNorm/Mul",
"module_apply_default/MobilenetV2/expanded_conv_13/project/BatchNorm/FusedBatchNorm"
],
"attr": {
"_grappler:ArithmeticOptimizer:AddOpsRewriteStage": { "b": true },
"T": { "type": "DT_FLOAT" },
"N": { "i": "2" }
},
"name": "module_apply_default/MobilenetV2/expanded_conv_14/ArithmeticOptimizer/AddOpsRewrite_Leaf_1_add",
"op": "AddN"
},
{
"input": [
"module_apply_default/MobilenetV2/expanded_conv_14/project/BatchNorm/FusedBatchNorm/Offset",
"module_apply_default/MobilenetV2/expanded_conv_14/ArithmeticOptimizer/AddOpsRewrite_Leaf_1_add"
],
"attr": {
"_grappler:ArithmeticOptimizer:AddOpsRewriteStage": { "b": true },
"T": { "type": "DT_FLOAT" }
},
"name": "module_apply_default/MobilenetV2/expanded_conv_14/ArithmeticOptimizer/AddOpsRewrite_add",
"op": "Add"
},
{
"input": [
"module_apply_default/MobilenetV2/expanded_conv_14/ArithmeticOptimizer/AddOpsRewrite_add",
"module_apply_default/MobilenetV2/expanded_conv_15/expand/Conv2D/merged_input"
],
"attr": {
"data_format": { "s": "TkhXQw==" },
"use_cudnn_on_gpu": { "b": true },
"padding": { "s": "U0FNRQ==" },
"strides": { "list": { "i": ["1", "1", "1", "1"] } },
"T": { "type": "DT_FLOAT" },
"dilations": { "list": { "i": ["1", "1", "1", "1"] } }
},
"name": "module_apply_default/MobilenetV2/expanded_conv_15/expand/BatchNorm/FusedBatchNorm/Mul",
"op": "Conv2D"
},
{
"input": [
"module_apply_default/MobilenetV2/expanded_conv_15/expand/BatchNorm/FusedBatchNorm/Mul",
"module_apply_default/MobilenetV2/expanded_conv_15/expand/BatchNorm/FusedBatchNorm/Offset"
],
"attr": { "T": { "type": "DT_FLOAT" } },
"name": "module_apply_default/MobilenetV2/expanded_conv_15/expand/BatchNorm/FusedBatchNorm",
"op": "Add"
},
{
"input": [
"module_apply_default/MobilenetV2/expanded_conv_15/expand/BatchNorm/FusedBatchNorm"
],
"attr": { "T": { "type": "DT_FLOAT" } },
"name": "module_apply_default/MobilenetV2/expanded_conv_15/expand/Relu6",
"op": "Relu6"
},
{
"input": [
"module_apply_default/MobilenetV2/expanded_conv_15/expand/Relu6",
"module/MobilenetV2/expanded_conv_15/depthwise/depthwise_weights"
],
"attr": {
"dilations": { "list": { "i": ["1", "1", "1", "1"] } },
"strides": { "list": { "i": ["1", "1", "1", "1"] } },
"padding": { "s": "U0FNRQ==" },
"T": { "type": "DT_FLOAT" },
"data_format": { "s": "TkhXQw==" }
},
"name": "module_apply_default/MobilenetV2/expanded_conv_15/depthwise/depthwise",
"op": "DepthwiseConv2dNative"
},
{
"input": [
"module_apply_default/MobilenetV2/expanded_conv_15/depthwise/depthwise",
"module_apply_default/MobilenetV2/expanded_conv_15/depthwise/BatchNorm/FusedBatchNorm/Scaled"
],
"attr": { "T": { "type": "DT_FLOAT" } },
"name": "module_apply_default/MobilenetV2/expanded_conv_15/depthwise/BatchNorm/FusedBatchNorm/Mul",
"op": "Mul"
},
{
"input": [
"module_apply_default/MobilenetV2/expanded_conv_15/depthwise/BatchNorm/FusedBatchNorm/Mul",
"module_apply_default/MobilenetV2/expanded_conv_15/depthwise/BatchNorm/FusedBatchNorm/Offset"
],
"attr": { "T": { "type": "DT_FLOAT" } },
"name": "module_apply_default/MobilenetV2/expanded_conv_15/depthwise/BatchNorm/FusedBatchNorm",
"op": "Add"
},
{
"input": [
"module_apply_default/MobilenetV2/expanded_conv_15/depthwise/BatchNorm/FusedBatchNorm"
],
"attr": { "T": { "type": "DT_FLOAT" } },
"name": "module_apply_default/MobilenetV2/expanded_conv_15/depthwise/Relu6",
"op": "Relu6"
},
{
"input": [
"module_apply_default/MobilenetV2/expanded_conv_15/depthwise/Relu6",
"module_apply_default/MobilenetV2/expanded_conv_15/project/Conv2D/merged_input"
],
"attr": {
"data_format": { "s": "TkhXQw==" },
"use_cudnn_on_gpu": { "b": true },
"padding": { "s": "U0FNRQ==" },
"strides": { "list": { "i": ["1", "1", "1", "1"] } },
"T": { "type": "DT_FLOAT" },
"dilations": { "list": { "i": ["1", "1", "1", "1"] } }
},
"name": "module_apply_default/MobilenetV2/expanded_conv_15/project/BatchNorm/FusedBatchNorm/Mul",
"op": "Conv2D"
},
{
"input": [
"module_apply_default/MobilenetV2/expanded_conv_15/project/BatchNorm/FusedBatchNorm/Mul",
"module_apply_default/MobilenetV2/expanded_conv_14/ArithmeticOptimizer/AddOpsRewrite_add"
],
"attr": {
"_grappler:ArithmeticOptimizer:AddOpsRewriteStage": { "b": true },
"T": { "type": "DT_FLOAT" },
"N": { "i": "2" }
},
"name": "module_apply_default/MobilenetV2/expanded_conv_15/ArithmeticOptimizer/AddOpsRewrite_Leaf_1_add",
"op": "AddN"
},
{
"input": [
"module_apply_default/MobilenetV2/expanded_conv_15/project/BatchNorm/FusedBatchNorm/Offset",
"module_apply_default/MobilenetV2/expanded_conv_15/ArithmeticOptimizer/AddOpsRewrite_Leaf_1_add"
],
"attr": {
"_grappler:ArithmeticOptimizer:AddOpsRewriteStage": { "b": true },
"T": { "type": "DT_FLOAT" }
},
"name": "module_apply_default/MobilenetV2/expanded_conv_15/ArithmeticOptimizer/AddOpsRewrite_add",
"op": "Add"
},
{
"input": [
"module_apply_default/MobilenetV2/expanded_conv_15/ArithmeticOptimizer/AddOpsRewrite_add",
"module_apply_default/MobilenetV2/expanded_conv_16/expand/Conv2D/merged_input"
],
"attr": {
"data_format": { "s": "TkhXQw==" },
"use_cudnn_on_gpu": { "b": true },
"padding": { "s": "U0FNRQ==" },
"strides": { "list": { "i": ["1", "1", "1", "1"] } },
"T": { "type": "DT_FLOAT" },
"dilations": { "list": { "i": ["1", "1", "1", "1"] } }
},
"name": "module_apply_default/MobilenetV2/expanded_conv_16/expand/BatchNorm/FusedBatchNorm/Mul",
"op": "Conv2D"
},
{
"input": [
"module_apply_default/MobilenetV2/expanded_conv_16/expand/BatchNorm/FusedBatchNorm/Mul",
"module_apply_default/MobilenetV2/expanded_conv_16/expand/BatchNorm/FusedBatchNorm/Offset"
],
"attr": { "T": { "type": "DT_FLOAT" } },
"name": "module_apply_default/MobilenetV2/expanded_conv_16/expand/BatchNorm/FusedBatchNorm",
"op": "Add"
},
{
"input": [
"module_apply_default/MobilenetV2/expanded_conv_16/expand/BatchNorm/FusedBatchNorm"
],
"attr": { "T": { "type": "DT_FLOAT" } },
"name": "module_apply_default/MobilenetV2/expanded_conv_16/expand/Relu6",
"op": "Relu6"
},
{
"input": [
"module_apply_default/MobilenetV2/expanded_conv_16/expand/Relu6",
"module/MobilenetV2/expanded_conv_16/depthwise/depthwise_weights"
],
"attr": {
"dilations": { "list": { "i": ["1", "1", "1", "1"] } },
"strides": { "list": { "i": ["1", "1", "1", "1"] } },
"padding": { "s": "U0FNRQ==" },
"data_format": { "s": "TkhXQw==" },
"T": { "type": "DT_FLOAT" }
},
"name": "module_apply_default/MobilenetV2/expanded_conv_16/depthwise/depthwise",
"op": "DepthwiseConv2dNative"
},
{
"input": [
"module_apply_default/MobilenetV2/expanded_conv_16/depthwise/depthwise",
"module_apply_default/MobilenetV2/expanded_conv_16/depthwise/BatchNorm/FusedBatchNorm/Scaled"
],
"attr": { "T": { "type": "DT_FLOAT" } },
"name": "module_apply_default/MobilenetV2/expanded_conv_16/depthwise/BatchNorm/FusedBatchNorm/Mul",
"op": "Mul"
},
{
"input": [
"module_apply_default/MobilenetV2/expanded_conv_16/depthwise/BatchNorm/FusedBatchNorm/Mul",
"module_apply_default/MobilenetV2/expanded_conv_16/depthwise/BatchNorm/FusedBatchNorm/Offset"
],
"attr": { "T": { "type": "DT_FLOAT" } },
"name": "module_apply_default/MobilenetV2/expanded_conv_16/depthwise/BatchNorm/FusedBatchNorm",
"op": "Add"
},
{
"input": [
"module_apply_default/MobilenetV2/expanded_conv_16/depthwise/BatchNorm/FusedBatchNorm"
],
"attr": { "T": { "type": "DT_FLOAT" } },
"name": "module_apply_default/MobilenetV2/expanded_conv_16/depthwise/Relu6",
"op": "Relu6"
},
{
"input": [
"module_apply_default/MobilenetV2/expanded_conv_16/depthwise/Relu6",
"module_apply_default/MobilenetV2/expanded_conv_16/project/Conv2D/merged_input"
],
"attr": {
"data_format": { "s": "TkhXQw==" },
"use_cudnn_on_gpu": { "b": true },
"padding": { "s": "U0FNRQ==" },
"strides": { "list": { "i": ["1", "1", "1", "1"] } },
"T": { "type": "DT_FLOAT" },
"dilations": { "list": { "i": ["1", "1", "1", "1"] } }
},
"name": "module_apply_default/MobilenetV2/expanded_conv_16/project/BatchNorm/FusedBatchNorm/Mul",
"op": "Conv2D"
},
{
"input": [
"module_apply_default/MobilenetV2/expanded_conv_16/project/BatchNorm/FusedBatchNorm/Mul",
"module_apply_default/MobilenetV2/expanded_conv_16/project/BatchNorm/FusedBatchNorm/Offset"
],
"attr": { "T": { "type": "DT_FLOAT" } },
"name": "module_apply_default/MobilenetV2/expanded_conv_16/project/BatchNorm/FusedBatchNorm",
"op": "Add"
},
{
"input": [
"module_apply_default/MobilenetV2/expanded_conv_16/project/BatchNorm/FusedBatchNorm",
"module_apply_default/MobilenetV2/Conv_1/Conv2D/merged_input"
],
"attr": {
"data_format": { "s": "TkhXQw==" },
"use_cudnn_on_gpu": { "b": true },
"padding": { "s": "U0FNRQ==" },
"strides": { "list": { "i": ["1", "1", "1", "1"] } },
"T": { "type": "DT_FLOAT" },
"dilations": { "list": { "i": ["1", "1", "1", "1"] } }
},
"name": "module_apply_default/MobilenetV2/Conv_1/BatchNorm/FusedBatchNorm/Mul",
"op": "Conv2D"
},
{
"input": [
"module_apply_default/MobilenetV2/Conv_1/BatchNorm/FusedBatchNorm/Mul",
"module_apply_default/MobilenetV2/Conv_1/BatchNorm/FusedBatchNorm/Offset"
],
"attr": { "T": { "type": "DT_FLOAT" } },
"name": "module_apply_default/MobilenetV2/Conv_1/BatchNorm/FusedBatchNorm",
"op": "Add"
},
{
"input": [
"module_apply_default/MobilenetV2/Conv_1/BatchNorm/FusedBatchNorm"
],
"attr": { "T": { "type": "DT_FLOAT" } },
"name": "module_apply_default/MobilenetV2/Conv_1/Relu6",
"op": "Relu6"
},
{
"input": ["module_apply_default/MobilenetV2/Conv_1/Relu6"],
"attr": {
"padding": { "s": "VkFMSUQ=" },
"strides": { "list": { "i": ["1", "1", "1", "1"] } },
"data_format": { "s": "TkhXQw==" },
"ksize": { "list": { "i": ["1", "7", "7", "1"] } },
"T": { "type": "DT_FLOAT" }
},
"name": "module_apply_default/MobilenetV2/Logits/AvgPool",
"op": "AvgPool"
},
{
"input": [
"module_apply_default/MobilenetV2/Logits/AvgPool",
"module/MobilenetV2/Logits/Conv2d_1c_1x1/weights"
],
"attr": {
"data_format": { "s": "TkhXQw==" },
"use_cudnn_on_gpu": { "b": true },
"padding": { "s": "U0FNRQ==" },
"strides": { "list": { "i": ["1", "1", "1", "1"] } },
"T": { "type": "DT_FLOAT" },
"dilations": { "list": { "i": ["1", "1", "1", "1"] } }
},
"name": "module_apply_default/MobilenetV2/Logits/Conv2d_1c_1x1/Conv2D",
"op": "Conv2D"
},
{
"input": [
"module_apply_default/MobilenetV2/Logits/Conv2d_1c_1x1/Conv2D",
"module/MobilenetV2/Logits/Conv2d_1c_1x1/biases"
],
"attr": {
"T": { "type": "DT_FLOAT" },
"data_format": { "s": "TkhXQw==" }
},
"name": "module_apply_default/MobilenetV2/Logits/Conv2d_1c_1x1/BiasAdd",
"op": "BiasAdd"
},
{
"input": [
"module_apply_default/MobilenetV2/Logits/Conv2d_1c_1x1/BiasAdd"
],
"attr": {
"squeeze_dims": { "list": { "i": ["1", "2"] } },
"T": { "type": "DT_FLOAT" }
},
"name": "module_apply_default/MobilenetV2/Logits/Squeeze",
"op": "Squeeze"
},
{
"input": ["module_apply_default/MobilenetV2/Logits/Squeeze"],
"attr": { "T": { "type": "DT_FLOAT" } },
"name": "module_apply_default/MobilenetV2/Logits/output",
"op": "Identity"
}
],
"library": {},
"versions": {}
},
"weightsManifest": [
{
"paths": ["group1-shard1of2", "group1-shard2of2"],
"weights": [
{
"dtype": "float32",
"shape": [80],
"name": "module_apply_default/MobilenetV2/expanded_conv_15/project/BatchNorm/FusedBatchNorm/Offset"
},
{
"dtype": "float32",
"shape": [1, 1, 80, 480],
"name": "module_apply_default/MobilenetV2/expanded_conv_15/expand/Conv2D/merged_input"
},
{
"dtype": "float32",
"shape": [480],
"name": "module_apply_default/MobilenetV2/expanded_conv_15/expand/BatchNorm/FusedBatchNorm/Offset"
},
{
"dtype": "float32",
"shape": [3, 3, 480, 1],
"name": "module/MobilenetV2/expanded_conv_15/depthwise/depthwise_weights"
},
{
"dtype": "float32",
"shape": [480],
"name": "module_apply_default/MobilenetV2/expanded_conv_15/depthwise/BatchNorm/FusedBatchNorm/Scaled"
},
{
"dtype": "float32",
"shape": [480],
"name": "module_apply_default/MobilenetV2/expanded_conv_15/depthwise/BatchNorm/FusedBatchNorm/Offset"
},
{
"dtype": "float32",
"shape": [1, 1, 480, 80],
"name": "module_apply_default/MobilenetV2/expanded_conv_15/project/Conv2D/merged_input"
},
{
"dtype": "float32",
"shape": [80],
"name": "module_apply_default/MobilenetV2/expanded_conv_14/project/BatchNorm/FusedBatchNorm/Offset"
},
{
"dtype": "float32",
"shape": [1, 1, 80, 480],
"name": "module_apply_default/MobilenetV2/expanded_conv_14/expand/Conv2D/merged_input"
},
{
"dtype": "float32",
"shape": [480],
"name": "module_apply_default/MobilenetV2/expanded_conv_14/expand/BatchNorm/FusedBatchNorm/Offset"
},
{
"dtype": "float32",
"shape": [3, 3, 480, 1],
"name": "module/MobilenetV2/expanded_conv_14/depthwise/depthwise_weights"
},
{
"dtype": "float32",
"shape": [480],
"name": "module_apply_default/MobilenetV2/expanded_conv_14/depthwise/BatchNorm/FusedBatchNorm/Scaled"
},
{
"dtype": "float32",
"shape": [480],
"name": "module_apply_default/MobilenetV2/expanded_conv_14/depthwise/BatchNorm/FusedBatchNorm/Offset"
},
{
"dtype": "float32",
"shape": [1, 1, 480, 80],
"name": "module_apply_default/MobilenetV2/expanded_conv_14/project/Conv2D/merged_input"
},
{
"dtype": "float32",
"shape": [48],
"name": "module_apply_default/MobilenetV2/expanded_conv_12/project/BatchNorm/FusedBatchNorm/Offset"
},
{
"dtype": "float32",
"shape": [1, 1, 48, 288],
"name": "module_apply_default/MobilenetV2/expanded_conv_12/expand/Conv2D/merged_input"
},
{
"dtype": "float32",
"shape": [288],
"name": "module_apply_default/MobilenetV2/expanded_conv_12/expand/BatchNorm/FusedBatchNorm/Offset"
},
{
"dtype": "float32",
"shape": [3, 3, 288, 1],
"name": "module/MobilenetV2/expanded_conv_12/depthwise/depthwise_weights"
},
{
"dtype": "float32",
"shape": [288],
"name": "module_apply_default/MobilenetV2/expanded_conv_12/depthwise/BatchNorm/FusedBatchNorm/Scaled"
},
{
"dtype": "float32",
"shape": [288],
"name": "module_apply_default/MobilenetV2/expanded_conv_12/depthwise/BatchNorm/FusedBatchNorm/Offset"
},
{
"dtype": "float32",
"shape": [1, 1, 288, 48],
"name": "module_apply_default/MobilenetV2/expanded_conv_12/project/Conv2D/merged_input"
},
{
"dtype": "float32",
"shape": [48],
"name": "module_apply_default/MobilenetV2/expanded_conv_11/project/BatchNorm/FusedBatchNorm/Offset"
},
{
"dtype": "float32",
"shape": [1, 1, 48, 288],
"name": "module_apply_default/MobilenetV2/expanded_conv_11/expand/Conv2D/merged_input"
},
{
"dtype": "float32",
"shape": [288],
"name": "module_apply_default/MobilenetV2/expanded_conv_11/expand/BatchNorm/FusedBatchNorm/Offset"
},
{
"dtype": "float32",
"shape": [3, 3, 288, 1],
"name": "module/MobilenetV2/expanded_conv_11/depthwise/depthwise_weights"
},
{
"dtype": "float32",
"shape": [288],
"name": "module_apply_default/MobilenetV2/expanded_conv_11/depthwise/BatchNorm/FusedBatchNorm/Scaled"
},
{
"dtype": "float32",
"shape": [288],
"name": "module_apply_default/MobilenetV2/expanded_conv_11/depthwise/BatchNorm/FusedBatchNorm/Offset"
},
{
"dtype": "float32",
"shape": [1, 1, 288, 48],
"name": "module_apply_default/MobilenetV2/expanded_conv_11/project/Conv2D/merged_input"
},
{
"dtype": "float32",
"shape": [32],
"name": "module_apply_default/MobilenetV2/expanded_conv_9/project/BatchNorm/FusedBatchNorm/Offset"
},
{
"dtype": "float32",
"shape": [1, 1, 32, 192],
"name": "module_apply_default/MobilenetV2/expanded_conv_9/expand/Conv2D/merged_input"
},
{
"dtype": "float32",
"shape": [192],
"name": "module_apply_default/MobilenetV2/expanded_conv_9/expand/BatchNorm/FusedBatchNorm/Offset"
},
{
"dtype": "float32",
"shape": [3, 3, 192, 1],
"name": "module/MobilenetV2/expanded_conv_9/depthwise/depthwise_weights"
},
{
"dtype": "float32",
"shape": [192],
"name": "module_apply_default/MobilenetV2/expanded_conv_9/depthwise/BatchNorm/FusedBatchNorm/Scaled"
},
{
"dtype": "float32",
"shape": [192],
"name": "module_apply_default/MobilenetV2/expanded_conv_9/depthwise/BatchNorm/FusedBatchNorm/Offset"
},
{
"dtype": "float32",
"shape": [1, 1, 192, 32],
"name": "module_apply_default/MobilenetV2/expanded_conv_9/project/Conv2D/merged_input"
},
{
"dtype": "float32",
"shape": [32],
"name": "module_apply_default/MobilenetV2/expanded_conv_8/project/BatchNorm/FusedBatchNorm/Offset"
},
{
"dtype": "float32",
"shape": [1, 1, 32, 192],
"name": "module_apply_default/MobilenetV2/expanded_conv_8/expand/Conv2D/merged_input"
},
{
"dtype": "float32",
"shape": [192],
"name": "module_apply_default/MobilenetV2/expanded_conv_8/expand/BatchNorm/FusedBatchNorm/Offset"
},
{
"dtype": "float32",
"shape": [3, 3, 192, 1],
"name": "module/MobilenetV2/expanded_conv_8/depthwise/depthwise_weights"
},
{
"dtype": "float32",
"shape": [192],
"name": "module_apply_default/MobilenetV2/expanded_conv_8/depthwise/BatchNorm/FusedBatchNorm/Scaled"
},
{
"dtype": "float32",
"shape": [192],
"name": "module_apply_default/MobilenetV2/expanded_conv_8/depthwise/BatchNorm/FusedBatchNorm/Offset"
},
{
"dtype": "float32",
"shape": [1, 1, 192, 32],
"name": "module_apply_default/MobilenetV2/expanded_conv_8/project/Conv2D/merged_input"
},
{
"dtype": "float32",
"shape": [32],
"name": "module_apply_default/MobilenetV2/expanded_conv_7/project/BatchNorm/FusedBatchNorm/Offset"
},
{
"dtype": "float32",
"shape": [1, 1, 32, 192],
"name": "module_apply_default/MobilenetV2/expanded_conv_7/expand/Conv2D/merged_input"
},
{
"dtype": "float32",
"shape": [192],
"name": "module_apply_default/MobilenetV2/expanded_conv_7/expand/BatchNorm/FusedBatchNorm/Offset"
},
{
"dtype": "float32",
"shape": [3, 3, 192, 1],
"name": "module/MobilenetV2/expanded_conv_7/depthwise/depthwise_weights"
},
{
"dtype": "float32",
"shape": [192],
"name": "module_apply_default/MobilenetV2/expanded_conv_7/depthwise/BatchNorm/FusedBatchNorm/Scaled"
},
{
"dtype": "float32",
"shape": [192],
"name": "module_apply_default/MobilenetV2/expanded_conv_7/depthwise/BatchNorm/FusedBatchNorm/Offset"
},
{
"dtype": "float32",
"shape": [1, 1, 192, 32],
"name": "module_apply_default/MobilenetV2/expanded_conv_7/project/Conv2D/merged_input"
},
{
"dtype": "float32",
"shape": [16],
"name": "module_apply_default/MobilenetV2/expanded_conv_5/project/BatchNorm/FusedBatchNorm/Offset"
},
{
"dtype": "float32",
"shape": [1, 1, 16, 96],
"name": "module_apply_default/MobilenetV2/expanded_conv_5/expand/Conv2D/merged_input"
},
{
"dtype": "float32",
"shape": [96],
"name": "module_apply_default/MobilenetV2/expanded_conv_5/expand/BatchNorm/FusedBatchNorm/Offset"
},
{
"dtype": "float32",
"shape": [3, 3, 96, 1],
"name": "module/MobilenetV2/expanded_conv_5/depthwise/depthwise_weights"
},
{
"dtype": "float32",
"shape": [96],
"name": "module_apply_default/MobilenetV2/expanded_conv_5/depthwise/BatchNorm/FusedBatchNorm/Scaled"
},
{
"dtype": "float32",
"shape": [96],
"name": "module_apply_default/MobilenetV2/expanded_conv_5/depthwise/BatchNorm/FusedBatchNorm/Offset"
},
{
"dtype": "float32",
"shape": [1, 1, 96, 16],
"name": "module_apply_default/MobilenetV2/expanded_conv_5/project/Conv2D/merged_input"
},
{
"dtype": "float32",
"shape": [16],
"name": "module_apply_default/MobilenetV2/expanded_conv_4/project/BatchNorm/FusedBatchNorm/Offset"
},
{
"dtype": "float32",
"shape": [1, 1, 16, 96],
"name": "module_apply_default/MobilenetV2/expanded_conv_4/expand/Conv2D/merged_input"
},
{
"dtype": "float32",
"shape": [96],
"name": "module_apply_default/MobilenetV2/expanded_conv_4/expand/BatchNorm/FusedBatchNorm/Offset"
},
{
"dtype": "float32",
"shape": [3, 3, 96, 1],
"name": "module/MobilenetV2/expanded_conv_4/depthwise/depthwise_weights"
},
{
"dtype": "float32",
"shape": [96],
"name": "module_apply_default/MobilenetV2/expanded_conv_4/depthwise/BatchNorm/FusedBatchNorm/Scaled"
},
{
"dtype": "float32",
"shape": [96],
"name": "module_apply_default/MobilenetV2/expanded_conv_4/depthwise/BatchNorm/FusedBatchNorm/Offset"
},
{
"dtype": "float32",
"shape": [1, 1, 96, 16],
"name": "module_apply_default/MobilenetV2/expanded_conv_4/project/Conv2D/merged_input"
},
{
"dtype": "float32",
"shape": [16],
"name": "module_apply_default/MobilenetV2/expanded_conv_2/project/BatchNorm/FusedBatchNorm/Offset"
},
{
"dtype": "float32",
"shape": [1, 1, 16, 96],
"name": "module_apply_default/MobilenetV2/expanded_conv_2/expand/Conv2D/merged_input"
},
{
"dtype": "float32",
"shape": [96],
"name": "module_apply_default/MobilenetV2/expanded_conv_2/expand/BatchNorm/FusedBatchNorm/Offset"
},
{
"dtype": "float32",
"shape": [3, 3, 96, 1],
"name": "module/MobilenetV2/expanded_conv_2/depthwise/depthwise_weights"
},
{
"dtype": "float32",
"shape": [96],
"name": "module_apply_default/MobilenetV2/expanded_conv_2/depthwise/BatchNorm/FusedBatchNorm/Scaled"
},
{
"dtype": "float32",
"shape": [96],
"name": "module_apply_default/MobilenetV2/expanded_conv_2/depthwise/BatchNorm/FusedBatchNorm/Offset"
},
{
"dtype": "float32",
"shape": [1, 1, 96, 16],
"name": "module_apply_default/MobilenetV2/expanded_conv_2/project/Conv2D/merged_input"
},
{
"dtype": "float32",
"shape": [],
"name": "module_apply_default/hub_input/Mul/y"
},
{
"dtype": "float32",
"shape": [],
"name": "module_apply_default/hub_input/Sub/y"
},
{
"dtype": "float32",
"shape": [3, 3, 3, 16],
"name": "module_apply_default/MobilenetV2/Conv/Conv2D/merged_input"
},
{
"dtype": "float32",
"shape": [16],
"name": "module_apply_default/MobilenetV2/Conv/BatchNorm/FusedBatchNorm/Offset"
},
{
"dtype": "float32",
"shape": [3, 3, 16, 1],
"name": "module/MobilenetV2/expanded_conv/depthwise/depthwise_weights"
},
{
"dtype": "float32",
"shape": [16],
"name": "module_apply_default/MobilenetV2/expanded_conv/depthwise/BatchNorm/FusedBatchNorm/Scaled"
},
{
"dtype": "float32",
"shape": [16],
"name": "module_apply_default/MobilenetV2/expanded_conv/depthwise/BatchNorm/FusedBatchNorm/Offset"
},
{
"dtype": "float32",
"shape": [1, 1, 16, 8],
"name": "module_apply_default/MobilenetV2/expanded_conv/project/Conv2D/merged_input"
},
{
"dtype": "float32",
"shape": [8],
"name": "module_apply_default/MobilenetV2/expanded_conv/project/BatchNorm/FusedBatchNorm/Offset"
},
{
"dtype": "float32",
"shape": [1, 1, 8, 48],
"name": "module_apply_default/MobilenetV2/expanded_conv_1/expand/Conv2D/merged_input"
},
{
"dtype": "float32",
"shape": [48],
"name": "module_apply_default/MobilenetV2/expanded_conv_1/expand/BatchNorm/FusedBatchNorm/Offset"
},
{
"dtype": "float32",
"shape": [3, 3, 48, 1],
"name": "module/MobilenetV2/expanded_conv_1/depthwise/depthwise_weights"
},
{
"dtype": "float32",
"shape": [48],
"name": "module_apply_default/MobilenetV2/expanded_conv_1/depthwise/BatchNorm/FusedBatchNorm/Scaled"
},
{
"dtype": "float32",
"shape": [48],
"name": "module_apply_default/MobilenetV2/expanded_conv_1/depthwise/BatchNorm/FusedBatchNorm/Offset"
},
{
"dtype": "float32",
"shape": [1, 1, 48, 16],
"name": "module_apply_default/MobilenetV2/expanded_conv_1/project/Conv2D/merged_input"
},
{
"dtype": "float32",
"shape": [16],
"name": "module_apply_default/MobilenetV2/expanded_conv_1/project/BatchNorm/FusedBatchNorm/Offset"
},
{
"dtype": "float32",
"shape": [1, 1, 16, 96],
"name": "module_apply_default/MobilenetV2/expanded_conv_3/expand/Conv2D/merged_input"
},
{
"dtype": "float32",
"shape": [96],
"name": "module_apply_default/MobilenetV2/expanded_conv_3/expand/BatchNorm/FusedBatchNorm/Offset"
},
{
"dtype": "float32",
"shape": [3, 3, 96, 1],
"name": "module/MobilenetV2/expanded_conv_3/depthwise/depthwise_weights"
},
{
"dtype": "float32",
"shape": [96],
"name": "module_apply_default/MobilenetV2/expanded_conv_3/depthwise/BatchNorm/FusedBatchNorm/Scaled"
},
{
"dtype": "float32",
"shape": [96],
"name": "module_apply_default/MobilenetV2/expanded_conv_3/depthwise/BatchNorm/FusedBatchNorm/Offset"
},
{
"dtype": "float32",
"shape": [1, 1, 96, 16],
"name": "module_apply_default/MobilenetV2/expanded_conv_3/project/Conv2D/merged_input"
},
{
"dtype": "float32",
"shape": [16],
"name": "module_apply_default/MobilenetV2/expanded_conv_3/project/BatchNorm/FusedBatchNorm/Offset"
},
{
"dtype": "float32",
"shape": [1, 1, 16, 96],
"name": "module_apply_default/MobilenetV2/expanded_conv_6/expand/Conv2D/merged_input"
},
{
"dtype": "float32",
"shape": [96],
"name": "module_apply_default/MobilenetV2/expanded_conv_6/expand/BatchNorm/FusedBatchNorm/Offset"
},
{
"dtype": "float32",
"shape": [3, 3, 96, 1],
"name": "module/MobilenetV2/expanded_conv_6/depthwise/depthwise_weights"
},
{
"dtype": "float32",
"shape": [96],
"name": "module_apply_default/MobilenetV2/expanded_conv_6/depthwise/BatchNorm/FusedBatchNorm/Scaled"
},
{
"dtype": "float32",
"shape": [96],
"name": "module_apply_default/MobilenetV2/expanded_conv_6/depthwise/BatchNorm/FusedBatchNorm/Offset"
},
{
"dtype": "float32",
"shape": [1, 1, 96, 32],
"name": "module_apply_default/MobilenetV2/expanded_conv_6/project/Conv2D/merged_input"
},
{
"dtype": "float32",
"shape": [32],
"name": "module_apply_default/MobilenetV2/expanded_conv_6/project/BatchNorm/FusedBatchNorm/Offset"
},
{
"dtype": "float32",
"shape": [1, 1, 32, 192],
"name": "module_apply_default/MobilenetV2/expanded_conv_10/expand/Conv2D/merged_input"
},
{
"dtype": "float32",
"shape": [192],
"name": "module_apply_default/MobilenetV2/expanded_conv_10/expand/BatchNorm/FusedBatchNorm/Offset"
},
{
"dtype": "float32",
"shape": [3, 3, 192, 1],
"name": "module/MobilenetV2/expanded_conv_10/depthwise/depthwise_weights"
},
{
"dtype": "float32",
"shape": [192],
"name": "module_apply_default/MobilenetV2/expanded_conv_10/depthwise/BatchNorm/FusedBatchNorm/Scaled"
},
{
"dtype": "float32",
"shape": [192],
"name": "module_apply_default/MobilenetV2/expanded_conv_10/depthwise/BatchNorm/FusedBatchNorm/Offset"
},
{
"dtype": "float32",
"shape": [1, 1, 192, 48],
"name": "module_apply_default/MobilenetV2/expanded_conv_10/project/Conv2D/merged_input"
},
{
"dtype": "float32",
"shape": [48],
"name": "module_apply_default/MobilenetV2/expanded_conv_10/project/BatchNorm/FusedBatchNorm/Offset"
},
{
"dtype": "float32",
"shape": [1, 1, 48, 288],
"name": "module_apply_default/MobilenetV2/expanded_conv_13/expand/Conv2D/merged_input"
},
{
"dtype": "float32",
"shape": [288],
"name": "module_apply_default/MobilenetV2/expanded_conv_13/expand/BatchNorm/FusedBatchNorm/Offset"
},
{
"dtype": "float32",
"shape": [3, 3, 288, 1],
"name": "module/MobilenetV2/expanded_conv_13/depthwise/depthwise_weights"
},
{
"dtype": "float32",
"shape": [288],
"name": "module_apply_default/MobilenetV2/expanded_conv_13/depthwise/BatchNorm/FusedBatchNorm/Scaled"
},
{
"dtype": "float32",
"shape": [288],
"name": "module_apply_default/MobilenetV2/expanded_conv_13/depthwise/BatchNorm/FusedBatchNorm/Offset"
},
{
"dtype": "float32",
"shape": [1, 1, 288, 80],
"name": "module_apply_default/MobilenetV2/expanded_conv_13/project/Conv2D/merged_input"
},
{
"dtype": "float32",
"shape": [80],
"name": "module_apply_default/MobilenetV2/expanded_conv_13/project/BatchNorm/FusedBatchNorm/Offset"
},
{
"dtype": "float32",
"shape": [1, 1, 80, 480],
"name": "module_apply_default/MobilenetV2/expanded_conv_16/expand/Conv2D/merged_input"
},
{
"dtype": "float32",
"shape": [480],
"name": "module_apply_default/MobilenetV2/expanded_conv_16/expand/BatchNorm/FusedBatchNorm/Offset"
},
{
"dtype": "float32",
"shape": [3, 3, 480, 1],
"name": "module/MobilenetV2/expanded_conv_16/depthwise/depthwise_weights"
},
{
"dtype": "float32",
"shape": [480],
"name": "module_apply_default/MobilenetV2/expanded_conv_16/depthwise/BatchNorm/FusedBatchNorm/Scaled"
},
{
"dtype": "float32",
"shape": [480],
"name": "module_apply_default/MobilenetV2/expanded_conv_16/depthwise/BatchNorm/FusedBatchNorm/Offset"
},
{
"dtype": "float32",
"shape": [1, 1, 480, 160],
"name": "module_apply_default/MobilenetV2/expanded_conv_16/project/Conv2D/merged_input"
},
{
"dtype": "float32",
"shape": [160],
"name": "module_apply_default/MobilenetV2/expanded_conv_16/project/BatchNorm/FusedBatchNorm/Offset"
},
{
"dtype": "float32",
"shape": [1, 1, 160, 1280],
"name": "module_apply_default/MobilenetV2/Conv_1/Conv2D/merged_input"
},
{
"dtype": "float32",
"shape": [1280],
"name": "module_apply_default/MobilenetV2/Conv_1/BatchNorm/FusedBatchNorm/Offset"
},
{
"dtype": "float32",
"shape": [1, 1, 1280, 1001],
"name": "module/MobilenetV2/Logits/Conv2d_1c_1x1/weights"
},
{
"dtype": "float32",
"shape": [1001],
"name": "module/MobilenetV2/Logits/Conv2d_1c_1x1/biases"
}
]
}
]
}