WARNING:tensorflow:`eval_fn` is not passed in. The `worker_fn` will be used if an "evaluator" task exists in the cluster.
WARNING:tensorflow:`eval_strategy` is not passed in. No distribution strategy will be used for evaluation.
WARNING:tensorflow:ModelCheckpoint callback is not provided. Workers will need to restart training if any fails.
WARNING:tensorflow:sample_weight modes were coerced from
  ...
    to  
  ['...']
WARNING:tensorflow:sample_weight modes were coerced from
  ...
    to  
  ['...']

Also looks like a small thing to fix:

Consider either turning off auto-sharding or switching the auto_shard_policy to DATA to shard this dataset. You can do this by creating a new `tf.data.Options()` object then setting `options.experimental_distribute.auto_shard_policy = AutoShardPolicy.DATA` before applying the options object to the dataset via `dataset.with_options(options)`.

Main problem: during fit(), in the first epoch after running for awhile, it dies with this:

Train for 121 steps, validate for 123 steps
Epoch 1/4
2020-01-18 18:55:17.738187: E tensorflow/core/common_runtime/ring_alg.cc:279] Aborting RingReduce with Invalid argument: Upper bound check fail for input 1 from node Mkl2Tf/_77 to node scoped_allocator_concat_1_1 input bounds = [0x7fa85486f880, 0x7fa85486ff40] backing_tensor bounds = [0x7fa5d84e1040, 0x7fa600ef9100]
         [[{{node scoped_allocator_concat_1_1}}]]
Additional GRPC error information:
{"created":"@1579398917.740498537","description":"Error received from peer","file":"external/grpc/src/core/lib/surface/call.cc","file_line":1039,"grpc_message":"Upper bound check fail for input 1 from node Mkl2Tf/_77 to node scoped_allocator_concat_1_1 input bounds = [0x7fa85486f880, 0x7fa85486ff40] backing_tensor bounds = [0x7fa5d84e1040, 0x7fa600ef9100]\n\t [[{{node scoped_allocator_concat_1_1}}]]","grpc_status":3}
...

It will correctly (afaict) distribute for Sequential() and model.compile but fails on model.fit. Some startup warnings to clean up: ``` WARNING:tensorflow:`eval_fn` is not passed in. The `worker_fn` will be used if an "evaluator" task exists in the cluster. WARNING:tensorflow:`eval_strategy` is not passed in. No distribution strategy will be used for evaluation. WARNING:tensorflow:ModelCheckpoint callback is not provided. Workers will need to restart training if any fails. WARNING:tensorflow:sample_weight modes were coerced from ... to ['...'] WARNING:tensorflow:sample_weight modes were coerced from ... to ['...'] ``` Also looks like a small thing to fix: ``` Consider either turning off auto-sharding or switching the auto_shard_policy to DATA to shard this dataset. You can do this by creating a new `tf.data.Options()` object then setting `options.experimental_distribute.auto_shard_policy = AutoShardPolicy.DATA` before applying the options object to the dataset via `dataset.with_options(options)`. ``` Main problem: during fit(), in the first epoch after running for awhile, it dies with this: ``` Train for 121 steps, validate for 123 steps Epoch 1/4 2020-01-18 18:55:17.738187: E tensorflow/core/common_runtime/ring_alg.cc:279] Aborting RingReduce with Invalid argument: Upper bound check fail for input 1 from node Mkl2Tf/_77 to node scoped_allocator_concat_1_1 input bounds = [0x7fa85486f880, 0x7fa85486ff40] backing_tensor bounds = [0x7fa5d84e1040, 0x7fa600ef9100] [[{{node scoped_allocator_concat_1_1}}]] Additional GRPC error information: {"created":"@1579398917.740498537","description":"Error received from peer","file":"external/grpc/src/core/lib/surface/call.cc","file_line":1039,"grpc_message":"Upper bound check fail for input 1 from node Mkl2Tf/_77 to node scoped_allocator_concat_1_1 input bounds = [0x7fa85486f880, 0x7fa85486ff40] backing_tensor bounds = [0x7fa5d84e1040, 0x7fa600ef9100]\n\t [[{{node scoped_allocator_concat_1_1}}]]","grpc_status":3} ... ```