program(1.0) [buildInfo = dict, tensor>({{"coremlc-component-MIL", "3500.4.1"}, {"coremlc-version", "3500.6.1"}, {"coremltools-component-torch", "2.5.0"}, {"coremltools-source-dialect", "TorchScript"}, {"coremltools-version", "8.2"}, {"mldb_token", "mldb-lqgwek4g9p"}})] { func main(tensor input_feature_vector) [FlexibleShapeInformation = tuple, dict, tensor>>, tuple, dict, list, ?>>>>((("DefaultShapes", {{"input_feature_vector", [1, 17]}}), ("RangeDims", {{"input_feature_vector", [[1, 512], [17, 17]]}})))] { tensor var_21 = const()[name = tensor("op_21"), val = tensor(1)]; tensor var_25_begin_0 = const()[name = tensor("op_25_begin_0"), val = tensor([0, 0])]; tensor var_25_end_0 = const()[name = tensor("op_25_end_0"), val = tensor([0, 8])]; tensor var_25_end_mask_0 = const()[name = tensor("op_25_end_mask_0"), val = tensor([true, false])]; tensor input_feature_vector_to_fp16_dtype_0 = const()[name = tensor("input_feature_vector_to_fp16_dtype_0"), val = tensor("fp16")]; tensor input_feature_vector_to_fp16 = cast(dtype = input_feature_vector_to_fp16_dtype_0, x = input_feature_vector)[name = tensor("cast_32")]; tensor var_25_cast_fp16 = slice_by_index(begin = var_25_begin_0, end = var_25_end_0, end_mask = var_25_end_mask_0, x = input_feature_vector_to_fp16)[name = tensor("op_25_cast_fp16")]; tensor not_equal_0_cast_fp16 = not_equal(x = var_25_cast_fp16, y = var_25_cast_fp16)[name = tensor("not_equal_0_cast_fp16")]; tensor cast_0_dtype_0 = const()[name = tensor("cast_0_dtype_0"), val = tensor("int32")]; tensor cast_0 = cast(dtype = cast_0_dtype_0, x = not_equal_0_cast_fp16)[name = tensor("cast_31")]; tensor non_zero_0 = non_zero(x = cast_0)[name = tensor("non_zero_0")]; tensor shape_0 = shape(x = non_zero_0)[name = tensor("shape_0")]; tensor slice_by_index_0_begin_0 = const()[name = tensor("slice_by_index_0_begin_0"), val = tensor([0])]; tensor slice_by_index_0_end_0 = const()[name = tensor("slice_by_index_0_end_0"), val = tensor([0])]; tensor slice_by_index_0_squeeze_mask_0 = const()[name = tensor("slice_by_index_0_squeeze_mask_0"), val = tensor([true])]; tensor slice_by_index_0 = slice_by_index(begin = slice_by_index_0_begin_0, end = slice_by_index_0_end_0, squeeze_mask = slice_by_index_0_squeeze_mask_0, x = shape_0)[name = tensor("slice_by_index_0")]; tensor expand_dims_1_axes_0 = const()[name = tensor("expand_dims_1_axes_0"), val = tensor([0])]; tensor expand_dims_1 = expand_dims(axes = expand_dims_1_axes_0, x = slice_by_index_0)[name = tensor("expand_dims_1")]; tensor expand_dims_0_to_fp16 = const()[name = tensor("expand_dims_0_to_fp16"), val = tensor([0x0p+0])]; tensor tile_0_cast_fp16 = tile(reps = expand_dims_1, x = expand_dims_0_to_fp16)[name = tensor("tile_0_cast_fp16")]; tensor scatter_nd_0_mode_0 = const()[name = tensor("scatter_nd_0_mode_0"), val = tensor("update")]; tensor scatter_nd_0_cast_fp16 = scatter_nd(data = var_25_cast_fp16, indices = non_zero_0, mode = scatter_nd_0_mode_0, updates = tile_0_cast_fp16)[name = tensor("scatter_nd_0_cast_fp16")]; tensor mul_0_y_0_to_fp16 = const()[name = tensor("mul_0_y_0_to_fp16"), val = tensor(0x0p+0)]; tensor mul_0_cast_fp16 = mul(x = var_25_cast_fp16, y = mul_0_y_0_to_fp16)[name = tensor("mul_0_cast_fp16")]; tensor not_equal_1_cast_fp16 = not_equal(x = mul_0_cast_fp16, y = mul_0_cast_fp16)[name = tensor("not_equal_1_cast_fp16")]; tensor greater_0_y_0_to_fp16 = const()[name = tensor("greater_0_y_0_to_fp16"), val = tensor(0x0p+0)]; tensor greater_0_cast_fp16 = greater(x = var_25_cast_fp16, y = greater_0_y_0_to_fp16)[name = tensor("greater_0_cast_fp16")]; tensor logical_and_0 = logical_and(x = not_equal_1_cast_fp16, y = greater_0_cast_fp16)[name = tensor("logical_and_0")]; tensor less_0_y_0_to_fp16 = const()[name = tensor("less_0_y_0_to_fp16"), val = tensor(0x0p+0)]; tensor less_0_cast_fp16 = less(x = var_25_cast_fp16, y = less_0_y_0_to_fp16)[name = tensor("less_0_cast_fp16")]; tensor logical_and_1 = logical_and(x = not_equal_1_cast_fp16, y = less_0_cast_fp16)[name = tensor("logical_and_1")]; tensor cast_1_dtype_0 = const()[name = tensor("cast_1_dtype_0"), val = tensor("int32")]; tensor cast_1 = cast(dtype = cast_1_dtype_0, x = logical_and_0)[name = tensor("cast_30")]; tensor non_zero_1 = non_zero(x = cast_1)[name = tensor("non_zero_1")]; tensor shape_1 = shape(x = non_zero_1)[name = tensor("shape_1")]; tensor slice_by_index_1_begin_0 = const()[name = tensor("slice_by_index_1_begin_0"), val = tensor([0])]; tensor slice_by_index_1_end_0 = const()[name = tensor("slice_by_index_1_end_0"), val = tensor([0])]; tensor slice_by_index_1_squeeze_mask_0 = const()[name = tensor("slice_by_index_1_squeeze_mask_0"), val = tensor([true])]; tensor slice_by_index_1 = slice_by_index(begin = slice_by_index_1_begin_0, end = slice_by_index_1_end_0, squeeze_mask = slice_by_index_1_squeeze_mask_0, x = shape_1)[name = tensor("slice_by_index_1")]; tensor expand_dims_3_axes_0 = const()[name = tensor("expand_dims_3_axes_0"), val = tensor([0])]; tensor expand_dims_3 = expand_dims(axes = expand_dims_3_axes_0, x = slice_by_index_1)[name = tensor("expand_dims_3")]; tensor expand_dims_2_to_fp16 = const()[name = tensor("expand_dims_2_to_fp16"), val = tensor([inf])]; tensor tile_1_cast_fp16 = tile(reps = expand_dims_3, x = expand_dims_2_to_fp16)[name = tensor("tile_1_cast_fp16")]; tensor scatter_nd_1_mode_0 = const()[name = tensor("scatter_nd_1_mode_0"), val = tensor("update")]; tensor scatter_nd_1_cast_fp16 = scatter_nd(data = scatter_nd_0_cast_fp16, indices = non_zero_1, mode = scatter_nd_1_mode_0, updates = tile_1_cast_fp16)[name = tensor("scatter_nd_1_cast_fp16")]; tensor cast_2_dtype_0 = const()[name = tensor("cast_2_dtype_0"), val = tensor("int32")]; tensor cast_2 = cast(dtype = cast_2_dtype_0, x = logical_and_1)[name = tensor("cast_29")]; tensor non_zero_2 = non_zero(x = cast_2)[name = tensor("non_zero_2")]; tensor shape_2 = shape(x = non_zero_2)[name = tensor("shape_2")]; tensor slice_by_index_2_begin_0 = const()[name = tensor("slice_by_index_2_begin_0"), val = tensor([0])]; tensor slice_by_index_2_end_0 = const()[name = tensor("slice_by_index_2_end_0"), val = tensor([0])]; tensor slice_by_index_2_squeeze_mask_0 = const()[name = tensor("slice_by_index_2_squeeze_mask_0"), val = tensor([true])]; tensor slice_by_index_2 = slice_by_index(begin = slice_by_index_2_begin_0, end = slice_by_index_2_end_0, squeeze_mask = slice_by_index_2_squeeze_mask_0, x = shape_2)[name = tensor("slice_by_index_2")]; tensor expand_dims_5_axes_0 = const()[name = tensor("expand_dims_5_axes_0"), val = tensor([0])]; tensor expand_dims_5 = expand_dims(axes = expand_dims_5_axes_0, x = slice_by_index_2)[name = tensor("expand_dims_5")]; tensor expand_dims_4_to_fp16 = const()[name = tensor("expand_dims_4_to_fp16"), val = tensor([-inf])]; tensor tile_2_cast_fp16 = tile(reps = expand_dims_5, x = expand_dims_4_to_fp16)[name = tensor("tile_2_cast_fp16")]; tensor scatter_nd_2_mode_0 = const()[name = tensor("scatter_nd_2_mode_0"), val = tensor("update")]; tensor scatter_nd_2_cast_fp16 = scatter_nd(data = scatter_nd_1_cast_fp16, indices = non_zero_2, mode = scatter_nd_2_mode_0, updates = tile_2_cast_fp16)[name = tensor("scatter_nd_2_cast_fp16")]; tensor relu_features_cast_fp16 = relu(x = scatter_nd_2_cast_fp16)[name = tensor("relu_features_cast_fp16")]; tensor var_29_begin_0 = const()[name = tensor("op_29_begin_0"), val = tensor([0, 12])]; tensor var_29_end_0 = const()[name = tensor("op_29_end_0"), val = tensor([0, 13])]; tensor var_29_end_mask_0 = const()[name = tensor("op_29_end_mask_0"), val = tensor([true, false])]; tensor var_29_cast_fp16 = slice_by_index(begin = var_29_begin_0, end = var_29_end_0, end_mask = var_29_end_mask_0, x = input_feature_vector_to_fp16)[name = tensor("op_29_cast_fp16")]; tensor var_21_promoted_to_fp16 = const()[name = tensor("op_21_promoted_to_fp16"), val = tensor(0x1p+0)]; tensor sub_score_app_launched_in_coarse_time_pow_loc_launch_cast_fp16 = greater_equal(x = var_29_cast_fp16, y = var_21_promoted_to_fp16)[name = tensor("sub_score_app_launched_in_coarse_time_pow_loc_launch_cast_fp16")]; tensor app_category_begin_0 = const()[name = tensor("app_category_begin_0"), val = tensor([0, 13])]; tensor app_category_end_0 = const()[name = tensor("app_category_end_0"), val = tensor([0, 14])]; tensor app_category_end_mask_0 = const()[name = tensor("app_category_end_mask_0"), val = tensor([true, false])]; tensor app_category_cast_fp16 = slice_by_index(begin = app_category_begin_0, end = app_category_end_0, end_mask = app_category_end_mask_0, x = input_feature_vector_to_fp16)[name = tensor("app_category_cast_fp16")]; tensor var_15_promoted_to_fp16 = const()[name = tensor("op_15_promoted_to_fp16"), val = tensor(0x1.4p+3)]; tensor var_33_cast_fp16 = greater_equal(x = app_category_cast_fp16, y = var_15_promoted_to_fp16)[name = tensor("op_33_cast_fp16")]; tensor var_15_promoted_1_to_fp16 = const()[name = tensor("op_15_promoted_1_to_fp16"), val = tensor(0x1.4p+3)]; tensor var_34_cast_fp16 = less_equal(x = app_category_cast_fp16, y = var_15_promoted_1_to_fp16)[name = tensor("op_34_cast_fp16")]; tensor sub_score_tv_app_category = logical_and(x = var_33_cast_fp16, y = var_34_cast_fp16)[name = tensor("sub_score_tv_app_category")]; tensor app_intent_static_points_begin_0 = const()[name = tensor("app_intent_static_points_begin_0"), val = tensor([0, 14])]; tensor app_intent_static_points_end_0 = const()[name = tensor("app_intent_static_points_end_0"), val = tensor([0, 15])]; tensor app_intent_static_points_end_mask_0 = const()[name = tensor("app_intent_static_points_end_mask_0"), val = tensor([true, false])]; tensor app_intent_static_points_cast_fp16 = slice_by_index(begin = app_intent_static_points_begin_0, end = app_intent_static_points_end_0, end_mask = app_intent_static_points_end_mask_0, x = input_feature_vector_to_fp16)[name = tensor("app_intent_static_points_cast_fp16")]; tensor var_13_promoted_to_fp16 = const()[name = tensor("op_13_promoted_to_fp16"), val = tensor(-0x1.f4p+9)]; tensor var_38_cast_fp16 = greater_equal(x = app_intent_static_points_cast_fp16, y = var_13_promoted_to_fp16)[name = tensor("op_38_cast_fp16")]; tensor var_38_promoted_to_fp16_dtype_0 = const()[name = tensor("op_38_promoted_to_fp16_dtype_0"), val = tensor("fp16")]; tensor var_38_cast_fp16_to_fp16 = cast(dtype = var_38_promoted_to_fp16_dtype_0, x = var_38_cast_fp16)[name = tensor("cast_28")]; tensor sub_score_app_intent_static_points_cast_fp16 = mul(x = app_intent_static_points_cast_fp16, y = var_38_cast_fp16_to_fp16)[name = tensor("sub_score_app_intent_static_points_cast_fp16")]; tensor value_begin_0 = const()[name = tensor("value_begin_0"), val = tensor([0, 15])]; tensor value_end_0 = const()[name = tensor("value_end_0"), val = tensor([0, 16])]; tensor value_end_mask_0 = const()[name = tensor("value_end_mask_0"), val = tensor([true, false])]; tensor value_cast_fp16 = slice_by_index(begin = value_begin_0, end = value_end_0, end_mask = value_end_mask_0, x = input_feature_vector_to_fp16)[name = tensor("value_cast_fp16")]; tensor not_equal_2_cast_fp16 = not_equal(x = value_cast_fp16, y = value_cast_fp16)[name = tensor("not_equal_2_cast_fp16")]; tensor cast_3_dtype_0 = const()[name = tensor("cast_3_dtype_0"), val = tensor("int32")]; tensor cast_3 = cast(dtype = cast_3_dtype_0, x = not_equal_2_cast_fp16)[name = tensor("cast_27")]; tensor non_zero_3 = non_zero(x = cast_3)[name = tensor("non_zero_3")]; tensor expand_dims_6 = const()[name = tensor("expand_dims_6"), val = tensor([0x1.275p+21])]; tensor shape_3 = shape(x = non_zero_3)[name = tensor("shape_3")]; tensor slice_by_index_3_begin_0 = const()[name = tensor("slice_by_index_3_begin_0"), val = tensor([0])]; tensor slice_by_index_3_end_0 = const()[name = tensor("slice_by_index_3_end_0"), val = tensor([0])]; tensor slice_by_index_3_squeeze_mask_0 = const()[name = tensor("slice_by_index_3_squeeze_mask_0"), val = tensor([true])]; tensor slice_by_index_3 = slice_by_index(begin = slice_by_index_3_begin_0, end = slice_by_index_3_end_0, squeeze_mask = slice_by_index_3_squeeze_mask_0, x = shape_3)[name = tensor("slice_by_index_3")]; tensor expand_dims_7_axes_0 = const()[name = tensor("expand_dims_7_axes_0"), val = tensor([0])]; tensor expand_dims_7 = expand_dims(axes = expand_dims_7_axes_0, x = slice_by_index_3)[name = tensor("expand_dims_7")]; tensor tile_3 = tile(reps = expand_dims_7, x = expand_dims_6)[name = tensor("tile_3")]; tensor scatter_nd_3_mode_0 = const()[name = tensor("scatter_nd_3_mode_0"), val = tensor("update")]; tensor tile_3_to_fp16_dtype_0 = const()[name = tensor("tile_3_to_fp16_dtype_0"), val = tensor("fp16")]; tensor tile_3_to_fp16 = cast(dtype = tile_3_to_fp16_dtype_0, x = tile_3)[name = tensor("cast_26")]; tensor scatter_nd_3_cast_fp16 = scatter_nd(data = value_cast_fp16, indices = non_zero_3, mode = scatter_nd_3_mode_0, updates = tile_3_to_fp16)[name = tensor("scatter_nd_3_cast_fp16")]; tensor mul_1_y_0_to_fp16 = const()[name = tensor("mul_1_y_0_to_fp16"), val = tensor(0x0p+0)]; tensor mul_1_cast_fp16 = mul(x = value_cast_fp16, y = mul_1_y_0_to_fp16)[name = tensor("mul_1_cast_fp16")]; tensor not_equal_3_cast_fp16 = not_equal(x = mul_1_cast_fp16, y = mul_1_cast_fp16)[name = tensor("not_equal_3_cast_fp16")]; tensor greater_1_y_0_to_fp16 = const()[name = tensor("greater_1_y_0_to_fp16"), val = tensor(0x0p+0)]; tensor greater_1_cast_fp16 = greater(x = value_cast_fp16, y = greater_1_y_0_to_fp16)[name = tensor("greater_1_cast_fp16")]; tensor logical_and_2 = logical_and(x = not_equal_3_cast_fp16, y = greater_1_cast_fp16)[name = tensor("logical_and_2")]; tensor less_1_y_0_to_fp16 = const()[name = tensor("less_1_y_0_to_fp16"), val = tensor(0x0p+0)]; tensor less_1_cast_fp16 = less(x = value_cast_fp16, y = less_1_y_0_to_fp16)[name = tensor("less_1_cast_fp16")]; tensor logical_and_3 = logical_and(x = not_equal_3_cast_fp16, y = less_1_cast_fp16)[name = tensor("logical_and_3")]; tensor cast_4_dtype_0 = const()[name = tensor("cast_4_dtype_0"), val = tensor("int32")]; tensor cast_4 = cast(dtype = cast_4_dtype_0, x = logical_and_2)[name = tensor("cast_25")]; tensor non_zero_4 = non_zero(x = cast_4)[name = tensor("non_zero_4")]; tensor shape_4 = shape(x = non_zero_4)[name = tensor("shape_4")]; tensor slice_by_index_4_begin_0 = const()[name = tensor("slice_by_index_4_begin_0"), val = tensor([0])]; tensor slice_by_index_4_end_0 = const()[name = tensor("slice_by_index_4_end_0"), val = tensor([0])]; tensor slice_by_index_4_squeeze_mask_0 = const()[name = tensor("slice_by_index_4_squeeze_mask_0"), val = tensor([true])]; tensor slice_by_index_4 = slice_by_index(begin = slice_by_index_4_begin_0, end = slice_by_index_4_end_0, squeeze_mask = slice_by_index_4_squeeze_mask_0, x = shape_4)[name = tensor("slice_by_index_4")]; tensor expand_dims_9_axes_0 = const()[name = tensor("expand_dims_9_axes_0"), val = tensor([0])]; tensor expand_dims_9 = expand_dims(axes = expand_dims_9_axes_0, x = slice_by_index_4)[name = tensor("expand_dims_9")]; tensor expand_dims_8_to_fp16 = const()[name = tensor("expand_dims_8_to_fp16"), val = tensor([inf])]; tensor tile_4_cast_fp16 = tile(reps = expand_dims_9, x = expand_dims_8_to_fp16)[name = tensor("tile_4_cast_fp16")]; tensor scatter_nd_4_mode_0 = const()[name = tensor("scatter_nd_4_mode_0"), val = tensor("update")]; tensor scatter_nd_4_cast_fp16 = scatter_nd(data = scatter_nd_3_cast_fp16, indices = non_zero_4, mode = scatter_nd_4_mode_0, updates = tile_4_cast_fp16)[name = tensor("scatter_nd_4_cast_fp16")]; tensor cast_5_dtype_0 = const()[name = tensor("cast_5_dtype_0"), val = tensor("int32")]; tensor cast_5 = cast(dtype = cast_5_dtype_0, x = logical_and_3)[name = tensor("cast_24")]; tensor non_zero_5 = non_zero(x = cast_5)[name = tensor("non_zero_5")]; tensor shape_5 = shape(x = non_zero_5)[name = tensor("shape_5")]; tensor slice_by_index_5_begin_0 = const()[name = tensor("slice_by_index_5_begin_0"), val = tensor([0])]; tensor slice_by_index_5_end_0 = const()[name = tensor("slice_by_index_5_end_0"), val = tensor([0])]; tensor slice_by_index_5_squeeze_mask_0 = const()[name = tensor("slice_by_index_5_squeeze_mask_0"), val = tensor([true])]; tensor slice_by_index_5 = slice_by_index(begin = slice_by_index_5_begin_0, end = slice_by_index_5_end_0, squeeze_mask = slice_by_index_5_squeeze_mask_0, x = shape_5)[name = tensor("slice_by_index_5")]; tensor expand_dims_11_axes_0 = const()[name = tensor("expand_dims_11_axes_0"), val = tensor([0])]; tensor expand_dims_11 = expand_dims(axes = expand_dims_11_axes_0, x = slice_by_index_5)[name = tensor("expand_dims_11")]; tensor expand_dims_10_to_fp16 = const()[name = tensor("expand_dims_10_to_fp16"), val = tensor([-inf])]; tensor tile_5_cast_fp16 = tile(reps = expand_dims_11, x = expand_dims_10_to_fp16)[name = tensor("tile_5_cast_fp16")]; tensor scatter_nd_5_mode_0 = const()[name = tensor("scatter_nd_5_mode_0"), val = tensor("update")]; tensor scatter_nd_5_cast_fp16 = scatter_nd(data = scatter_nd_4_cast_fp16, indices = non_zero_5, mode = scatter_nd_5_mode_0, updates = tile_5_cast_fp16)[name = tensor("scatter_nd_5_cast_fp16")]; tensor scatter_nd_5_cast_fp16_to_fp32_dtype_0 = const()[name = tensor("scatter_nd_5_cast_fp16_to_fp32_dtype_0"), val = tensor("fp32")]; tensor var_10_promoted = const()[name = tensor("op_10_promoted"), val = tensor(0x1.518p+19)]; tensor scatter_nd_5_cast_fp16_to_fp32 = cast(dtype = scatter_nd_5_cast_fp16_to_fp32_dtype_0, x = scatter_nd_5_cast_fp16)[name = tensor("cast_23")]; tensor sub_score_filter_feature_not_performed_in_past_eight_days_filter = greater_equal(x = scatter_nd_5_cast_fp16_to_fp32, y = var_10_promoted)[name = tensor("sub_score_filter_feature_not_performed_in_past_eight_days_filter")]; tensor var_45_begin_0 = const()[name = tensor("op_45_begin_0"), val = tensor([0, 6])]; tensor var_45_end_0 = const()[name = tensor("op_45_end_0"), val = tensor([0, 7])]; tensor var_45_end_mask_0 = const()[name = tensor("op_45_end_mask_0"), val = tensor([true, false])]; tensor var_45_cast_fp16 = slice_by_index(begin = var_45_begin_0, end = var_45_end_0, end_mask = var_45_end_mask_0, x = input_feature_vector_to_fp16)[name = tensor("op_45_cast_fp16")]; tensor var_7_to_fp16 = const()[name = tensor("op_7_to_fp16"), val = tensor(0x1.064p-10)]; tensor sub_score_filter_feature_app_intent_not_popular_enough_cast_fp16 = less_equal(x = var_45_cast_fp16, y = var_7_to_fp16)[name = tensor("sub_score_filter_feature_app_intent_not_popular_enough_cast_fp16")]; tensor var_6_promoted_to_fp16 = const()[name = tensor("op_6_promoted_to_fp16"), val = tensor(-0x1.868p+14)]; tensor sub_score_static_points_blacklist_for_spotlight_cast_fp16 = less_equal(x = app_intent_static_points_cast_fp16, y = var_6_promoted_to_fp16)[name = tensor("sub_score_static_points_blacklist_for_spotlight_cast_fp16")]; tensor app_intent_day_zero_points_begin_0 = const()[name = tensor("app_intent_day_zero_points_begin_0"), val = tensor([0, 16])]; tensor app_intent_day_zero_points_end_0 = const()[name = tensor