# model model = Model() sparseData = Input("sparseData", "TENSOR_FLOAT32", "{12}") traversalOrder = Parameter("traversalOrder", "TENSOR_INT32", "{2}", [0, 1]) blockMap = Parameter("blockMap", "TENSOR_INT32", "{0}", []) dimFormat = Parameter("dimFormat", "TENSOR_INT32", "{2}", [0, 0]) dimensions = Parameter("dimensions", "TENSOR_INT32", "{2}", [3, 4]) d0ArrSegments = Parameter("d0ArrSegments", "TENSOR_INT32", "{0}", []) d0ArrIndices = Parameter("d0ArrIndices", "TENSOR_INT32", "{0}", []) d1ArrSegments = Parameter("d1ArrSegments", "TENSOR_INT32", "{0}", []) d1ArrIndices = Parameter("d1ArrIndices", "TENSOR_INT32", "{0}", []) denseOut = Output("denseOut", "TENSOR_FLOAT32", "{3, 4}") model = model.Operation("DENSIFY", sparseData, traversalOrder, blockMap, dimFormat, dimensions, d0ArrSegments, d0ArrIndices, d1ArrSegments, d1ArrIndices).To(denseOut) # Example 1. Input in operand 0, input0 = {sparseData: # input 0 [6.0, 0.0, 9.0, 8.0, 0.0, 0.0, 0.0, 0.0, 5.0, 0.0, 0.0, 7.0]} output0 = {denseOut: # output 0 [6.0, 0.0, 9.0, 8.0, 0.0, 0.0, 0.0, 0.0, 5.0, 0.0, 0.0, 7.0]} quant8_symm = DataTypeConverter().Identify({ sparseData: ("TENSOR_QUANT8_SYMM", 2.0), denseOut: ("TENSOR_QUANT8_SYMM", 2.0) }) quant8_asymm = DataTypeConverter().Identify({ sparseData: ("TENSOR_QUANT8_ASYMM", 0.5, 4), denseOut: ("TENSOR_QUANT8_ASYMM", 0.5, 4) }) quant8_asymm_signed = DataTypeConverter().Identify({ sparseData: ("TENSOR_QUANT8_ASYMM_SIGNED", 2.5, -9), denseOut: ("TENSOR_QUANT8_ASYMM_SIGNED", 2.5, -9) }) quant16_symm = DataTypeConverter().Identify({ sparseData: ("TENSOR_QUANT16_SYMM", 3.0), denseOut: ("TENSOR_QUANT16_SYMM", 3.0) }) quant16_asymm = DataTypeConverter().Identify({ sparseData: ("TENSOR_QUANT16_ASYMM", 2.0, 4), denseOut: ("TENSOR_QUANT16_ASYMM", 2.0, 4) }) # Instantiate an example Example((input0, output0)).AddVariations("relaxed", "float16", "int32", quant8_symm, quant8_asymm, quant8_asymm_signed, quant16_symm, quant16_asymm)