{
  "desc_dataset_files": {
    "shape-384-10-10-1-384-1-0": {
      "name": "MobileNet_0.75_160 Conv2d_7 input 10x10x384 filter 1x1x384 stride 1 pad 0"
    }, 
    "shape-48-40-40-1-96-1-0": {
      "name": "MobileNet_0.75_160 Conv2d_2 input 40x40x48 filter 1x1x96 stride 1 pad 0"
    }, 
    "shape-768-1-1-1-1001-1-0": {
      "name": "MobileNet_0.75_160 Logits_Conv2d_1c_1x1 input 1x1x768 filter 1x1x1001 stride 1 pad 0"
    }, 
    "shape-192-10-10-1-384-1-0": {
      "name": "MobileNet_0.75_160 Conv2d_6 input 10x10x192 filter 1x1x384 stride 1 pad 0"
    }, 
    "shape-3-160-160-3-24-2-0": {
      "name": "MobileNet_0.75_160 Conv2d_0 input 160x160x3 filter 3x3x24 stride 2 pad 0"
    }, 
    "shape-384-5-5-1-768-1-0": {
      "name": "MobileNet_0.75_160 Conv2d_12 input 5x5x384 filter 1x1x768 stride 1 pad 0"
    }, 
    "shape-192-20-20-1-192-1-0": {
      "name": "MobileNet_0.75_160 Conv2d_5 input 20x20x192 filter 1x1x192 stride 1 pad 0"
    }, 
    "shape-96-40-40-1-96-1-0": {
      "name": "MobileNet_0.75_160 Conv2d_3 input 40x40x96 filter 1x1x96 stride 1 pad 0"
    }, 
    "shape-96-20-20-1-192-1-0": {
      "name": "MobileNet_0.75_160 Conv2d_4 input 20x20x96 filter 1x1x192 stride 1 pad 0"
    }, 
    "shape-768-5-5-1-768-1-0": {
      "name": "MobileNet_0.75_160 Conv2d_13 input 5x5x768 filter 1x1x768 stride 1 pad 0"
    }, 
    "shape-24-80-80-1-48-1-0": {
      "name": "MobileNet_0.75_160 Conv2d_1 input 80x80x24 filter 1x1x48 stride 1 pad 0"
    }
  }, 
  "dataset_files": [
    "shape-3-160-160-3-24-2-0", 
    "shape-24-80-80-1-48-1-0", 
    "shape-48-40-40-1-96-1-0", 
    "shape-96-40-40-1-96-1-0", 
    "shape-96-20-20-1-192-1-0", 
    "shape-192-20-20-1-192-1-0", 
    "shape-192-10-10-1-384-1-0", 
    "shape-384-10-10-1-384-1-0", 
    "shape-384-5-5-1-768-1-0", 
    "shape-768-5-5-1-768-1-0", 
    "shape-768-1-1-1-1001-1-0"
  ], 
  "tags": [
    "dataset", 
    "nntest", 
    "tensor-conv", 
    "tensor-conv-mobilenets", 
    "conv", 
    "convolution", 
    "mobilenets", 
    "mobilenets-v1", 
    "mobilenets-v1-0.75-160"
  ]
}