def __init__(self):
self.platform = sys.platform
self.tf_version = utils.get_tf_version()
self.opset = int(os.environ.get("TF2ONNX_TEST_OPSET", constants.PREFERRED_OPSET))
self.target = os.environ.get("TF2ONNX_TEST_TARGET", ",".join(constants.DEFAULT_TARGET)).split(',')
self.backend = os.environ.get("TF2ONNX_TEST_BACKEND", "onnxruntime")
self.backend_version = self._get_backend_version()
self.log_level = logging.WARNING
self.temp_dir = utils.get_temp_directory()
def __init__(self):
self.platform = sys.platform
self.tf_version = self._get_tf_version()
self.opset = int(os.environ.get("TF2ONNX_TEST_OPSET", 7))
self.target = os.environ.get("TF2ONNX_TEST_TARGET",
",".join(DEFAULT_TARGET)).split(',')
self.backend = os.environ.get("TF2ONNX_TEST_BACKEND", "onnxruntime")
self.backend_version = self._get_backend_version()
self.is_debug_mode = False
self.temp_dir = utils.get_temp_directory()
def __init__(self):
self.platform = sys.platform
self.tf_version = tf_utils.get_tf_version()
self.opset = int(os.environ.get("TF2ONNX_TEST_OPSET", constants.PREFERRED_OPSET))
self.target = os.environ.get("TF2ONNX_TEST_TARGET", ",".join(constants.DEFAULT_TARGET)).split(',')
self.backend = os.environ.get("TF2ONNX_TEST_BACKEND", "onnxruntime")
self.skip_tflite_tests = os.environ.get("TF2ONNX_SKIP_TFLITE_TESTS", "FALSE").upper() == "TRUE"
self.skip_tf_tests = os.environ.get("TF2ONNX_SKIP_TF_TESTS", "FALSE").upper() == "TRUE"
self.run_tfl_consistency_test = os.environ.get("TF2ONNX_RUN_TFL_CONSISTENCY_TEST", "FALSE").upper() == "TRUE"
self.backend_version = self._get_backend_version()
self.log_level = logging.WARNING
self.temp_dir = utils.get_temp_directory()
# contrib ops are registered only when the module is imported, the following import statement is needed,
# otherwise tf runtime error will show up when the tf model is restored from pb file because of un-registered ops.
try:
import tensorflow.contrib.rnn # pylint: disable=unused-import
except: # pylint: disable=bare-except
# not needed for tf-2.0
pass
from tf2onnx import tf_loader, logging, optimizer, utils, tf_utils
from tf2onnx.tfonnx import process_tf_graph
from tf2onnx.tf_loader import tf_session, tf_reset_default_graph
from tf2onnx.graph import ExternalTensorStorage
logger = logging.getLogger("run_pretrained")
TEMP_DIR = os.path.join(utils.get_temp_directory(), "run_pretrained")
PERFITER = 1000
def get_beach(shape):
"""Get beach image as input."""
resize_to = shape[1:3]
path = os.path.join(os.path.dirname(os.path.abspath(__file__)),
"beach.jpg")
img = PIL.Image.open(path)
img = img.resize(resize_to, PIL.Image.ANTIALIAS)
img_np = np.array(img).astype(np.float32)
img_np = np.stack([img_np] * shape[0], axis=0).reshape(shape)
return img_np / 255
