Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Fix grpc tensor convert for python2 #317

Merged
merged 1 commit into from
Nov 29, 2018
Merged

Fix grpc tensor convert for python2 #317

Changes from all commits
Commits
Show all changes
1 commit
Select commit
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
17 changes: 10 additions & 7 deletions wrappers/python/microservice.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -9,6 +9,7 @@
import json
import time
import logging
import sys
import multiprocessing as mp
logging.basicConfig(level=logging.INFO)
logger = logging.getLogger(__name__)
Expand Down Expand Up @@ -117,13 +118,15 @@ def array_to_rest_datadef(array,names,original_datadef):
def grpc_datadef_to_array(datadef):
data_type = datadef.WhichOneof("data_oneof")
if data_type == "tensor":
sz = np.prod(datadef.tensor.shape) # get number of float64 entries
c = datadef.tensor.SerializeToString() # get bytes
# create array from packed entries which are at end of bytes - assumes same endianness
features = np.frombuffer(memoryview(c[-(sz*8):]), dtype=np.float64, count=sz, offset=0)
features = features.reshape(datadef.tensor.shape)
# Previous method which is slower
# features = np.array(datadef.tensor.values).reshape(datadef.tensor.shape)
if (sys.version_info >= (3, 0)):
sz = np.prod(datadef.tensor.shape) # get number of float64 entries
c = datadef.tensor.SerializeToString() # get bytes
# create array from packed entries which are at end of bytes - assumes same endianness
features = np.frombuffer(memoryview(c[-(sz*8):]), dtype=np.float64, count=sz, offset=0)
features = features.reshape(datadef.tensor.shape)
else:
# Python 2 version which is slower
features = np.array(datadef.tensor.values).reshape(datadef.tensor.shape)
elif data_type == "ndarray":
features = np.array(datadef.ndarray)
else:
Expand Down