def __init__(self, net, input_nodes):
self._op_shape_inference = {
MaceOp.Conv2D.name: self.infer_shape_conv_pool_shape,
MaceOp.Deconv2D.name: self.infer_shape_deconv,
MaceOp.DepthwiseConv2d.name: self.infer_shape_conv_pool_shape,
MaceOp.DepthwiseDeconv2d.name: self.infer_shape_deconv,
MaceOp.Eltwise.name: self.infer_shape_general,
MaceOp.BatchNorm.name: self.infer_shape_general,
MaceOp.AddN.name: self.infer_shape_general,
MaceOp.Activation.name: self.infer_shape_general,
MaceOp.Pooling.name: self.infer_shape_conv_pool_shape,
MaceOp.Concat.name: self.infer_shape_concat,
MaceOp.Split.name: self.infer_shape_slice,
MaceOp.Softmax.name: self.infer_shape_general,
MaceOp.FullyConnected.name: self.infer_shape_fully_connected,
MaceOp.Crop.name: self.infer_shape_crop,
MaceOp.BiasAdd.name: self.infer_shape_general,
MaceOp.ChannelShuffle.name: self.infer_shape_channel_shuffle,
MaceOp.Transpose.name: self.infer_shape_permute,
MaceOp.PriorBox.name: self.infer_shape_prior_box,
MaceOp.Reshape.name: self.infer_shape_reshape,
MaceOp.ResizeBilinear.name: self.infer_shape_resize_bilinear,
}
self._net = net
self._output_shape_cache = {}
for input_node in input_nodes:
input_shape = input_node.shape[:]
# transpose input from NCHW to NHWC
Transformer.transpose_shape(input_shape, [0, 3, 1, 2])
self._output_shape_cache[input_node.name] = input_shape
for tensor in net.tensors:
self._output_shape_cache[tensor.name] = list(tensor.dims)
def init_output_shape_cache(self):
self._output_shape_cache = {}
for input_node in self._option.input_nodes.values():
# input_shape is assigned in .yml file
input_shape = input_node.shape[:]
# transpose input from NHWC to NCHW
if len(input_shape) == 4 and \
input_node.data_format == DataFormat.NHWC:
Transformer.transpose_shape(input_shape, [0, 3, 1, 2])
self._output_shape_cache[input_node.name] = input_shape
def update_data(self):
"""
Update City list from database.
"""
CityListView.hotels_data = Transformer.transform_hotels((scrapper.get_hotels_from_city(CityListView.city)))
self.data = [{'text': name} for name
in CityListView.hotels_data.keys()]
def transform_thread(self):
"""worker "transform" thread function.
"""
self.transform_result = Transformer.transform_all(self.extract_list, SelectableLabel.selected_hotel, self.hotel_address)
def convert_data_to_table_format():
logger.info("transform")
transformer = Transformer()
data = FileStorage(SCRAPPED_FILE).read_data()
transformer.transform(data)
default="out.dat",
help="raw dump of transformed rows in python-ish syntax")
parser.add_argument("--spec-file",
default="spec.py",
help="file containing transformation spec")
args = parser.parse_args()
out_file = open(args.output_file, "w")
def dump_row(row):
out_file.write(str(row))
out_file.write("\n")
data = read_spec_file(args.spec_file)
transformer = Transformer(data["column_names"], data["transformations"])
transformer.transform_columns()
with open(args.data_file, "rb") as fh:
reader = csv.reader(fh)
for row in reader:
try:
transformed = transformer.transform_row(row)
dump_row(transformer.get(transformed, data["output_columns"]))
except Exception as e:
print "Could not transform row={} reason='{}'".format(
str(row), str(e))
out_file.close()