#Magic engine 1.13 key install#

Saving.load_weights_from_hdf5_group(f, self.layers)įile '/usr/local/lib/python3.6/dist-packages/tensorflow/python/keras/engine/saving.py', line 820, in load_weights_from_hdf5_groupįile '/usr/local/lib/python3.6/dist-packages/tensorflow/python/keras/backend.py', line 2880, in batch_set_value Self.op_builds.build_post(ops, self.signals, sess, rng)įile '/usr/local/lib/python3.6/dist-packages/nengo_dl/tensor_node.py', line 243, in build_postįile 'tensorflow-models.py', line 63, in post_buildįile '/usr/local/lib/python3.6/dist-packages/tensorflow/python/keras/engine/network.py', line 1516, in load_weights Self._wrapped_, self.instance, args, kwargs)įile '/usr/local/lib/python3.6/dist-packages/nengo_dl/tensor_graph.py', line 39, in with_selfįile '/usr/local/lib/python3.6/dist-packages/nengo_dl/tensor_graph.py', line 725, in build_postįile '/usr/local/lib/python3.6/dist-packages/nengo_dl/builder.py', line 135, in post_build Self.tensor_graph.build_post(ss, self.rng)įile '/usr/local/lib/python3.6/dist-packages/nengo/utils/magic.py', line 181, in _call_ With nengo_dl.Simulator(net, minibatch_size=minibatch_size) as sim:įile '/usr/local/lib/python3.6/dist-packages/nengo_dl/simulator.py', line 221, in _init_įile '/usr/local/lib/python3.6/dist-packages/nengo_dl/simulator.py', line 252, in reset ValueError: Tensor Tensor('SimTensorNodeBuilder_1/Placeholder:0', shape=(784, 128), dtype=float32) is not an element of this graph.ĭuring handling of the above exception, another exception occurred:įile 'tensorflow-models.py', line 87, in Raise ValueError('Tensor %s is not an element of this graph.' % obj) Return self._as_graph_element_locked(obj, allow_tensor, allow_operation)įile '/usr/local/lib/python3.6/dist-packages/tensorflow/python/framework/ops.py', line 3557, in _as_graph_element_locked Subfeed, allow_tensor=True, allow_operation=False)įile '/usr/local/lib/python3.6/dist-packages/tensorflow/python/framework/ops.py', line 3478, in as_graph_element Maybe someone has already made experiences with this stack and can help me.I’m attracted by the possibility to include Keras models as TensorNode in nengo_dl, but I am stacked with an error in all my attempts.Īt this point I tested the example given in nengo_dl package (tensorflow-models.ipynb), and I got exactly the same error: Traceback (most recent call last):įile '/usr/local/lib/python3.6/dist-packages/tensorflow/python/client/session.py', line 1092, in _run

'test:debug': 'node -inspect-brk -r tsconfig-paths/register -r ts-node/register node_modules/.bin/jest -runInBand', 'start:debug': 'nest start -debug -watch', 'start:prod': 'NODE_ENV=production node dist/main', 'start:release': 'NODE_ENV=release nest start -watch', 'start:stage': 'NODE_ENV=stage nest start -watch', 'start:dev': 'NODE_ENV=development nest start -watch',

'start': 'NODE_ENV=production node dist/main', pipe: atlassian/google-app-engine-deploy:1.0.0

#Magic engine 1.13 key install#

Name: Install Dependencies & Build Application Here's my bitbucket-pipelines.yaml: image: node:16.15.0 The problem is as follows and I am now at a loss as to what else to try:

Before I had the same setup with a simple Express.js backend which worked without problems. Unfortunately, I haven't gotten my NestJS backend up and running yet. In my current setup, I use Bitbucket Pipelines to deploy a Nest.js backend to Google App Engine.