# model
model = Model()
sparseData = Input("sparseData", "TENSOR_FLOAT32", "{4}")
traversalOrder = Parameter("traversalOrder", "TENSOR_INT32", "{4}", [0, 1, 2, 3])
blockMap = Parameter("blockMap", "TENSOR_INT32", "{2}", [0, 1])
dimFormat = Parameter("dimFormat", "TENSOR_INT32", "{4}", [0, 0, 1, 1])
dimensions = Parameter("dimensions", "TENSOR_INT32", "{4}", [2, 3, 5, 7])
d0ArrSegments = Parameter("d0ArrSegments", "TENSOR_INT32", "{0}", [])
d0ArrIndices = Parameter("d0ArrIndices", "TENSOR_INT32", "{0}", [])
d1ArrSegments = Parameter("d1ArrSegments", "TENSOR_INT32", "{0}", [])
d1ArrIndices = Parameter("d1ArrIndices", "TENSOR_INT32", "{0}", [])
d2ArrSegments = Parameter("d2ArrSegments", "TENSOR_INT32", "{7}", [0, 1, 2, 3, 4, 4, 4])
d2ArrIndices = Parameter("d2ArrIndices", "TENSOR_INT32", "{4}", [1, 2, 3, 1])
d3ArrSegments = Parameter("d3ArrSegments", "TENSOR_INT32", "{5}", [0, 1, 2, 3, 4])
d3ArrIndices = Parameter("d3ArrIndices", "TENSOR_INT32", "{4}", [1, 2, 3, 3])
denseOut = Output("denseOut", "TENSOR_FLOAT32", "{10, 21}")
model = model.Operation("DENSIFY", sparseData, traversalOrder, blockMap,
                        dimFormat, dimensions, d0ArrSegments, d0ArrIndices, d1ArrSegments,
                        d1ArrIndices, d2ArrSegments, d2ArrIndices, d3ArrSegments,
                        d3ArrIndices).To(denseOut)

# Example 1. Input in operand 0,
input0 = {sparseData: # input 0
          [11.0, 13.0, 17.0, 19.0]}

outputData = [0.0] * 210
outputData[22] = 11.0
outputData[51] = 13.0
outputData[80] = 17.0
outputData[129] = 19.0
output0 = {denseOut: # output 0
           outputData}

quant8_symm = DataTypeConverter().Identify({
    sparseData: ("TENSOR_QUANT8_SYMM", 3.0),
    denseOut: ("TENSOR_QUANT8_SYMM", 3.0)
})

quant8_asymm = DataTypeConverter().Identify({
    sparseData: ("TENSOR_QUANT8_ASYMM", 2.25, 3),
    denseOut: ("TENSOR_QUANT8_ASYMM", 2.25, 3)
})

quant8_asymm_signed = DataTypeConverter().Identify({
    sparseData: ("TENSOR_QUANT8_ASYMM_SIGNED", 2.875, -4),
    denseOut: ("TENSOR_QUANT8_ASYMM_SIGNED", 2.875, -4)
})

quant16_symm = DataTypeConverter().Identify({
    sparseData: ("TENSOR_QUANT16_SYMM", 3.25),
    denseOut: ("TENSOR_QUANT16_SYMM", 3.25)
})

quant16_asymm = DataTypeConverter().Identify({
    sparseData: ("TENSOR_QUANT16_ASYMM", 6.0, 14),
    denseOut: ("TENSOR_QUANT16_ASYMM", 6.0, 14)
})

# Instantiate an example
Example((input0, output0)).AddVariations("relaxed", "float16", "int32", quant8_symm,
                                        quant8_asymm, quant8_asymm_signed, quant16_symm,
                                        quant16_asymm)