Comments (3)
Okay, I understand. You also need to set use_tpu=False
in get_train_op
.
train_op = ddsp.training.train_util.get_train_op(loss,
learning_rate=learning_rate,
use_tpu=False)
I'll put in a PR to update the notebook to make this clear and set this to default as that's the more common option.
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Hi! Can you clarify, is this in colab, on cloud or locally? What command are you using to train?
from ddsp.
Hi! Can you clarify, is this in colab, on cloud or locally? What command are you using to train?
Hi!I wan to train ddsp in locally. To be more precise, I want to run 3_training.ipynb in my gpu server.
I have tried modifying the code
# Setup the session.
import os
assert "COLAB_TPU_ADDR" in os.environ, "ERROR: Not connected to a TPU runtime; please set the runtime type to 'TPU'."
TPU_ADDRESS = "grpc://" + os.environ["COLAB_TPU_ADDR"]
sess = tf.Session(TPU_ADDRESS)
to this
sess = tf.Session()
But I got some warnings and errors
WARNING:tensorflow:cross_replica_sum should be used within a tpu_shard_context, but got unset number_of_shards. Assuming 1.
InvalidArgumentError: No OpKernel was registered to support Op 'CrossReplicaSum' used by node training/CrossReplicaSum (defined at /root/anaconda3/envs/hw/lib/python3.6/site-packages/ddsp/training/train_util.py:101) with these attrs: [T=DT_FLOAT, _class=["loc:@train.../transpose"]]
Registered devices: [CPU, GPU, XLA_CPU, XLA_GPU]
Registered kernels:
<no registered kernels>
[[training/CrossReplicaSum]]
Errors may have originated from an input operation.
Input Source operations connected to node training/CrossReplicaSum:
training/clip_by_global_norm/training/clip_by_global_norm/_0 (defined at /root/anaconda3/envs/hw/lib/python3.6/site-packages/ddsp/training/train_util.py:35)
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