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{
  "cases": [
    {
      "name": "vector_23",
      "inputs": {
        "x": { "dtype": "float32", "shape": [23], "data": { "kind": "fillFloat32", "sinStep": 0.29, "cosStep": 0.17 } }
      },
      "outputs": { "y": { "dtype": "float32", "shape": [23], "tolerance": 0.000001 } }
    },
    {
      "name": "f32_extreme_and_non_finite",
      "inputs": {
        "x": {
          "dtype": "float32",
          "shape": [11],
          "data": {
            "kind": "values",
            "values": [-1000.0, -100.0, -20.0, 0.0, 0.0, 20.0, 100.0, 1000.0, "-Infinity", "Infinity", "NaN"]
          }
        }
      },
      "outputs": { "y": { "dtype": "float32", "shape": [11], "tolerance": 0.000001, "allowNaN": true } }
    },
    {
      "name": "rank0_scalar",
      "inputs": { "x": { "dtype": "float32", "shape": [], "data": { "kind": "values", "values": [-2.0] } } },
      "outputs": { "y": { "dtype": "float32", "shape": [], "tolerance": 0.000001 } }
    },
    {
      "name": "near_overflow_thresholds",
      "inputs": {
        "x": {
          "dtype": "float32",
          "shape": [6],
          "data": { "kind": "values", "values": [-88.0, -80.0, -40.0, 40.0, 80.0, 88.0] }
        }
      },
      "outputs": { "y": { "dtype": "float32", "shape": [6], "tolerance": 0.000001 } }
    },
    {
      "name": "ort_activation_extremes",
      "provenance": {
        "source": "onnxruntime/test/providers/cpu/activation/activation_op_test.cc",
        "test": "ActivationOpTest.Sigmoid",
        "notes": "ORT shared activation vector with infinities, float max, min, and subnormal values."
      },
      "inputs": {
        "x": {
          "dtype": "float32",
          "shape": [13],
          "data": {
            "kind": "values",
            "values": [-1.0, 0.0, 1.0, 100.0, -100.0, 1000.0, -1000.0, 1.1754943508222875e-38, 1.1754943508222876e-39, -1.1754943508222876e-39, 3.4028234663852886e+38, -3.4028234663852886e+38, "Infinity"]
          }
        }
      },
      "outputs": { "y": { "dtype": "float32", "shape": [13], "tolerance": 0.000001 } }
    },
    {
      "name": "ort_fp16_activation_extremes",
      "provenance": {
        "source": "onnxruntime/test/providers/cpu/activation/activation_op_test.cc",
        "test": "ActivationOpTest.Sigmoid_fp16"
      },
      "inputs": {
        "x": {
          "dtype": "float16",
          "shape": [13],
          "data": {
            "kind": "values",
            "values": [-1.0, 0.0, 1.0, 100.0, -100.0, 1000.0, -1000.0, 1.1754943508222875e-38, 1.1754943508222876e-39, -1.1754943508222876e-39, 3.4028234663852886e+38, -3.4028234663852886e+38, "Infinity"]
          }
        }
      },
      "outputs": { "y": { "dtype": "float16", "shape": [13], "tolerance": 0.001 } }
    },
    {
      "name": "onnx_backend_example",
      "provenance": { "source": "cmake/external/onnx/onnx/backend/test/data/node/test_sigmoid_example" },
      "inputs": { "x": { "dtype": "float32", "shape": [3], "data": { "kind": "values", "values": [-1.0, 0.0, 1.0] } } },
      "outputs": { "y": { "dtype": "float32", "shape": [3], "tolerance": 0.000001 } }
    },
    {
      "name": "onnx_backend_sigmoid",
      "provenance": { "source": "cmake/external/onnx/onnx/backend/test/data/node/test_sigmoid" },
      "inputs": {
        "x": {
          "dtype": "float32",
          "shape": [3, 4, 5],
          "data": {
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            "values": [1.764052391052246, 0.40015721321105957, 0.978738009929657, 2.2408931255340576, 1.8675580024719238, -0.9772778749465942, 0.9500884413719177, -0.15135720372200012, -0.10321885347366333, 0.4105985164642334, 0.14404356479644775, 1.4542734622955322, 0.7610377073287964, 0.12167501449584961, 0.44386324286460876, 0.3336743414402008, 1.4940791130065918, -0.2051582634449005, 0.3130677044391632, -0.8540957570075989, -2.5529897212982178, 0.653618574142456, 0.8644362092018127, -0.7421650290489197, 2.269754648208618, -1.4543657302856445, 0.04575851559638977, -0.18718385696411133, 1.5327792167663574, 1.4693588018417358, 0.154947429895401, 0.37816253304481506, -0.8877857327461243, -1.980796456336975, -0.34791216254234314, 0.15634897351264954, 1.2302906513214111, 1.202379822731018, -0.38732680678367615, -0.302302747964859, -1.0485529899597168, -1.420017957687378, -1.7062702178955078, 1.950775384902954, -0.5096521973609924, -0.4380742907524109, -1.2527953386306763, 0.7774903774261475, -1.6138978004455566, -0.21274028718471527, -0.8954665660858154, 0.38690251111984253, -0.5108051300048828, -1.18063223361969, -0.02818222902715206, 0.4283318817615509, 0.06651721894741058, 0.30247190594673157, -0.6343221068382263, -0.3627411723136902]
          }
        }
      },
      "outputs": { "y": { "dtype": "float32", "shape": [3, 4, 5], "tolerance": 0.00001 } }
    },
    {
      "name": "onnx_backend_sigmoid_example",
      "provenance": { "source": "cmake/external/onnx/onnx/backend/test/data/node/test_sigmoid_example" },
      "inputs": { "x": { "dtype": "float32", "shape": [3], "data": { "kind": "values", "values": [-1.0, 0.0, 1.0] } } },
      "outputs": { "y": { "dtype": "float32", "shape": [3], "tolerance": 0.00001 } }
    },
    {
      "name": "vec4_f16_lanes",
      "inputs": {
        "x": {
          "dtype": "float16",
          "shape": [16],
          "data": {
            "kind": "values",
            "values": [-6.0, -4.0, -3.0, -2.0, -1.5, -1.0, -0.5, -0.25, 0.0, 0.25, 0.5, 1.0, 1.5, 2.0, 4.0, 6.0]
          }
        }
      },
      "outputs": { "y": { "dtype": "float16", "shape": [16], "tolerance": 0.001, "relTolerance": 0.002 } }
    },
    {
      "name": "vec4_f32_extremes",
      "inputs": {
        "x": {
          "dtype": "float32",
          "shape": [8],
          "data": {
            "kind": "values",
            "values": [-1.0, 0.0, 1.0, 100.0, -100.0, 3.4028234663852886e+38, -3.4028234663852886e+38, "Infinity"]
          }
        }
      },
      "outputs": { "y": { "dtype": "float32", "shape": [8], "tolerance": 0.000001 } }
    },
    {
      "name": "empty_input_zero_dim",
      "inputs": { "x": { "dtype": "float32", "shape": [0], "data": { "kind": "values", "values": [] } } },
      "outputs": { "y": { "dtype": "float32", "shape": [0], "tolerance": 0 } }
    },
    {
      "name": "f16_nan_preserved_vec4",
      "inputs": {
        "x": {
          "dtype": "float16",
          "shape": [8],
          "data": { "kind": "values", "values": ["NaN", -2.0, -1.0, 0.0, 1.0, 2.0, "NaN", -0.5] }
        }
      },
      "outputs": { "y": { "dtype": "float16", "shape": [8], "tolerance": 0.001, "allowNaN": true } }
    },
    {
      "name": "f16_empty_zero_dim",
      "inputs": { "x": { "dtype": "float16", "shape": [0], "data": { "kind": "values", "values": [] } } },
      "outputs": { "y": { "dtype": "float16", "shape": [0], "tolerance": 0 } }
    },
    {
      "name": "f32_large_dispatch_fold_boundary",
      "inputs": {
        "x": {
          "dtype": "float32",
          "shape": [65537, 256],
          "data": { "kind": "fillFloat32", "sinStep": 0.1, "cosStep": 0.07 }
        }
      },
      "outputs": { "y": { "dtype": "float32", "shape": [65537, 256], "tolerance": 0.000001 } }
    }
  ]
}