benthomasson

{
    "templates": [
        {
            "template_id": 2,
            "name": "template_name_0",
            "run_count": 1338,
            "failed_run_count": 420,
            "successful_run_count": 442,
            "elapsed_sum": 7858.074,
            "failed_elapsed_sum": 2466.66,

benthomasson

##VGG19 model for Keras

This is the Keras model of the 19-layer network used by the VGG team in the ILSVRC-2014 competition.

It has been obtained by directly converting the Caffe model provived by the authors.

Details about the network architecture can be found in the following arXiv paper:

Very Deep Convolutional Networks for Large-Scale Image Recognition

K. Simonyan, A. Zisserman

benthomasson

from __future__ import print_function
from nanomsg import Socket, REQ, REP, PUB, SUB, DONTWAIT, \
                    NanoMsgAPIError, EAGAIN, SUB_SUBSCRIBE
import time
from gevent import monkey
import gevent

monkey.patch_all()

benthomasson

diff --git a/tastypie/fields.py b/tastypie/fields.py
index ae3f291..568788c 100644
--- a/tastypie/fields.py
+++ b/tastypie/fields.py
@@ -644,7 +644,7 @@ class RelatedField(ApiField):
         Accepts either a URI, a data dictionary (or dictionary-like structure)
         or an object with a ``pk``.
         """
-        self.fk_resource = self.to_class()
+        self.fk_resource = self.to_class(api_name=self.api_name)