rankprofile[0].name "mnist_softmax"
rankprofile[0].fef.property[0].name "rankingExpression(default.add).rankingScript"
rankprofile[0].fef.property[0].value "join(reduce(join(rename(Placeholder, (d0, d1), (d0, d2)), constant(mnist_softmax_Variable), f(a,b)(a * b)), sum, d2), constant(mnist_softmax_Variable_1), f(a,b)(a + b))"
rankprofile[0].fef.property[1].name "rankingExpression(default.add).Placeholder.type"
rankprofile[0].fef.property[1].value "tensor(d0[],d1[784])"
rankprofile[1].name "xgboost_2_2"
rankprofile[1].fef.property[0].name "rankingExpression(xgboost_2_2).rankingScript"
rankprofile[1].fef.property[0].value "if (f29 < -0.1234567, if (f56 < -0.242398, 1.71218, -1.70044), if (f109 < 0.8723473, -1.94071, 1.85965)) + if (f60 < -0.482947, if (f29 < -4.2387498, 0.784718, -0.96853), -6.23624)"
rankprofile[2].name "mnist_softmax_saved"
rankprofile[2].fef.property[0].name "rankingExpression(serving_default.y).rankingScript"
rankprofile[2].fef.property[0].value "join(reduce(join(rename(Placeholder, (d0, d1), (d0, d2)), constant(mnist_softmax_saved_layer_Variable_read), f(a,b)(a * b)), sum, d2), constant(mnist_softmax_saved_layer_Variable_1_read), f(a,b)(a + b))"
rankprofile[2].fef.property[1].name "rankingExpression(serving_default.y).x.type"
rankprofile[2].fef.property[1].value "tensor(d0[],d1[784])"
rankprofile[3].name "mnist_saved"
rankprofile[3].fef.property[0].name "rankingExpression(imported_ml_function_mnist_saved_dnn_hidden1_add).rankingScript"
rankprofile[3].fef.property[0].value "join(reduce(join(rename(input, (d0, d1), (d0, d4)), constant(mnist_saved_dnn_hidden1_weights_read), f(a,b)(a * b)), sum, d4), constant(mnist_saved_dnn_hidden1_bias_read), f(a,b)(a + b))"
rankprofile[3].fef.property[1].name "rankingExpression(imported_ml_function_mnist_saved_dnn_hidden1_add).type"
rankprofile[3].fef.property[1].value "tensor(d3[300])"
rankprofile[3].fef.property[2].name "rankingExpression(serving_default.y).rankingScript"
rankprofile[3].fef.property[2].value "join(reduce(join(map(join(reduce(join(join(join(rankingExpression(imported_ml_function_mnist_saved_dnn_hidden1_add), 0.009999999776482582, f(a,b)(a * b)), rankingExpression(imported_ml_function_mnist_saved_dnn_hidden1_add), f(a,b)(max(a,b))), constant(mnist_saved_dnn_hidden2_weights_read), f(a,b)(a * b)), sum, d3), constant(mnist_saved_dnn_hidden2_bias_read), f(a,b)(a + b)), f(a)(1.050701 * if (a >= 0, a, 1.673263 * (exp(a) - 1)))), constant(mnist_saved_dnn_outputs_weights_read), f(a,b)(a * b)), sum, d2), constant(mnist_saved_dnn_outputs_bias_read), f(a,b)(a + b))"
rankprofile[3].fef.property[3].name "rankingExpression(serving_default.y).x.type"
rankprofile[3].fef.property[3].value "tensor(d0[],d1[784])"