def parse_param_file(param_file, return_shape=True):
from paddle.fluid.proto.framework_pb2 import VarType
f = open(param_file, 'rb')
version = np.fromstring(f.read(4), dtype='int32')
lod_level = np.fromstring(f.read(8), dtype='int64')
for i in range(int(lod_level)):
_size = np.fromstring(f.read(8), dtype='int64')
_ = f.read(_size)
version = np.fromstring(f.read(4), dtype='int32')
tensor_desc = VarType.TensorDesc()
tensor_desc_size = np.fromstring(f.read(4), dtype='int32')
tensor_desc.ParseFromString(f.read(int(tensor_desc_size)))
tensor_shape = tuple(tensor_desc.dims)
if return_shape:
f.close()
return tuple(tensor_desc.dims)
if tensor_desc.data_type != 5:
raise Exception(
"Unexpected data type while parse {}".format(param_file))
data_size = 4
for i in range(len(tensor_shape)):
data_size *= tensor_shape[i]
weight = np.fromstring(f.read(data_size), dtype='float32')
f.close()
return np.reshape(weight, tensor_shape)
def parse_shape_from_file(filename):
with open(filename, "rb") as file:
version = file.read(4)
lod_level = to_int(file.read(8), dest="Q")
for i in range(lod_level):
_size = to_int(file.read(8), dest="Q")
_ = file.read(_size)
version = file.read(4)
tensor_desc_size = to_int(file.read(4))
tensor_desc = VarType.TensorDesc()
tensor_desc.ParseFromString(file.read(tensor_desc_size))
return tuple(tensor_desc.dims)
