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# Copyright (c) Facebook, Inc. and its affiliates.
# -*- coding: utf-8 -*-
import copy
import os
import tempfile
import unittest
import torch
from detectron2 import model_zoo
from detectron2.utils.logger import setup_logger
from detectron2.utils.testing import get_sample_coco_image
@unittest.skipIf(os.environ.get("CI"), "Require COCO data and model zoo.")
class TestCaffe2Export(unittest.TestCase):
def setUp(self):
setup_logger()
def _test_model(self, config_path, device="cpu"):
# requires extra dependencies
from detectron2.export import Caffe2Model, add_export_config, Caffe2Tracer
cfg = model_zoo.get_config(config_path)
add_export_config(cfg)
cfg.MODEL.DEVICE = device
model = model_zoo.get(config_path, trained=True, device=device)
inputs = [{"image": get_sample_coco_image()}]
tracer = Caffe2Tracer(cfg, model, copy.deepcopy(inputs))
c2_model = tracer.export_caffe2()
with tempfile.TemporaryDirectory(prefix="detectron2_unittest") as d:
c2_model.save_protobuf(d)
c2_model.save_graph(os.path.join(d, "test.svg"), inputs=copy.deepcopy(inputs))
c2_model = Caffe2Model.load_protobuf(d)
c2_model(inputs)[0]["instances"]
ts_model = tracer.export_torchscript()
ts_model.save(os.path.join(d, "model.ts"))
def testMaskRCNN(self):
# TODO: this test requires manifold access, see: T88318502
self._test_model("COCO-InstanceSegmentation/mask_rcnn_R_50_FPN_3x.yaml")
@unittest.skipIf(not torch.cuda.is_available(), "CUDA not available")
def testMaskRCNNGPU(self):
# TODO: this test requires manifold access, see: T88318502
self._test_model("COCO-InstanceSegmentation/mask_rcnn_R_50_FPN_3x.yaml", device="cuda")
def testRetinaNet(self):
# TODO: this test requires manifold access, see: T88318502
self._test_model("COCO-Detection/retinanet_R_50_FPN_3x.yaml")
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