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{
  "op": "ai.onnx.Compress",
  "cases": [
    {
      "name": "compress-axis0-f32-64k-by-4",
      "attrs": { "axis": 0 },
      "inputs": {
        "input": { "dtype": "float32", "shape": [65536, 4], "dist": "normal", "seed": 915, "scale": 1 },
        "condition": { "dtype": "bool", "shape": [65536], "dist": "linearMod", "mod": 2 }
      },
      "outputs": { "output": { "dtype": "float32", "shape": [32768, 4] } }
    },
    {
      "name": "compress-flatten-f32-1m",
      "preset": "smoke",
      "inputs": {
        "input": { "dtype": "float32", "shape": [1048576], "dist": "normal", "seed": 917, "scale": 1 },
        "condition": { "dtype": "bool", "shape": [1048576], "dist": "linearMod", "mod": 2 }
      },
      "outputs": { "output": { "dtype": "float32", "shape": [524288] } },
      "bench": {
        "primary": true,
        "metrics": [{ "type": "bandwidth", "value": "4 * numel(shapes.input) * 2 + 4 * numel(shapes.output)" }]
      }
    },
    {
      "name": "compress-flatten-f32-blockstarve-256k",
      "preset": "smoke",
      "inputs": {
        "input": { "dtype": "float32", "shape": [262144], "dist": "normal", "seed": 919, "scale": 1 },
        "condition": { "dtype": "bool", "shape": [262144], "dist": "linearMod", "mod": 2 }
      },
      "outputs": { "output": { "dtype": "float32", "shape": [131072] } },
      "bench": {
        "metrics": [{ "type": "bandwidth", "value": "4 * numel(shapes.input) * 2 + 4 * numel(shapes.output)" }]
      }
    },
    {
      "name": "compress-flatten-f32-singlelane-cliff-1024",
      "preset": "smoke",
      "inputs": {
        "input": { "dtype": "float32", "shape": [1024], "dist": "normal", "seed": 921, "scale": 1 },
        "condition": { "dtype": "bool", "shape": [1024], "dist": "linearMod", "mod": 2 }
      },
      "outputs": { "output": { "dtype": "float32", "shape": [512] } },
      "bench": {
        "metrics": [{ "type": "bandwidth", "value": "4 * numel(shapes.input) * 2 + 4 * numel(shapes.output)" }]
      }
    },
    {
      "name": "compress-flatten-f32-vit-token-prune-768-to384",
      "preset": "stress",
      "inputs": {
        "input": { "dtype": "float32", "shape": [768], "dist": "normal", "seed": 923, "scale": 1 },
        "condition": { "dtype": "bool", "shape": [768], "dist": "linearMod", "mod": 2 }
      },
      "outputs": { "output": { "dtype": "float32", "shape": [384] } },
      "bench": {
        "primary": true,
        "metrics": [{ "type": "bandwidth", "value": "4 * numel(shapes.input) * 2 + 4 * numel(shapes.output)" }]
      }
    },
    {
      "name": "compress-flatten-f32-parallel-healthy-2048",
      "preset": "smoke",
      "inputs": {
        "input": { "dtype": "float32", "shape": [2048], "dist": "normal", "seed": 922, "scale": 1 },
        "condition": { "dtype": "bool", "shape": [2048], "dist": "linearMod", "mod": 2 }
      },
      "outputs": { "output": { "dtype": "float32", "shape": [1024] } },
      "bench": {
        "metrics": [{ "type": "bandwidth", "value": "4 * numel(shapes.input) * 2 + 4 * numel(shapes.output)" }]
      }
    },
    {
      "name": "compress-axis0-f32-singlelane-serialcopy-512x2",
      "preset": "smoke",
      "attrs": { "axis": 0 },
      "inputs": {
        "input": { "dtype": "float32", "shape": [512, 2], "dist": "normal", "seed": 931, "scale": 1 },
        "condition": { "dtype": "bool", "shape": [512], "dist": "linearMod", "mod": 2 }
      },
      "outputs": { "output": { "dtype": "float32", "shape": [256, 2] } },
      "bench": { "metrics": [{ "type": "bandwidth", "value": "4 * numel(shapes.input) + 4 * numel(shapes.output)" }] }
    },
    {
      "name": "compress-flatten-f16-parallel-narrowstore-1m",
      "preset": "smoke",
      "inputs": {
        "input": { "dtype": "float16", "shape": [1048576], "dist": "normal", "seed": 941, "scale": 1 },
        "condition": { "dtype": "bool", "shape": [1048576], "dist": "linearMod", "mod": 2 }
      },
      "outputs": { "output": { "dtype": "float16", "shape": [524288] } },
      "bench": {
        "metrics": [
          {
            "type": "bandwidth",
            "value": "2 * numel(shapes.input) + 4 * numel(shapes.input) + 2 * numel(shapes.output)"
          }
        ]
      }
    }
  ]
}