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fix librispeech ctc_loss incompatibility with jit #926

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fix librispeech ctc_loss incompatibility with jit #926

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12 changes: 9 additions & 3 deletions algoperf/workloads/librispeech_conformer/librispeech_jax/workload.py
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Original file line number Diff line number Diff line change
Expand Up @@ -325,7 +325,14 @@ def greedy_decode(
jax_sharding_utils.get_replicate_sharding(), # model_state
jax_sharding_utils.get_replicate_sharding(), # rng
),
out_shardings=jax_sharding_utils.get_batch_dim_sharding(),
out_shardings={
'loss_per_example': jax_sharding_utils.get_batch_dim_sharding(),
'decoded': jax_sharding_utils.get_batch_dim_sharding(),
'decoded_paddings': jax_sharding_utils.get_batch_dim_sharding(),
'targets': jax_sharding_utils.get_batch_dim_sharding(),
'target_paddings': jax_sharding_utils.get_batch_dim_sharding(),
'n_valid_examples': jax_sharding_utils.get_replicate_sharding(),
},
static_argnums=(0,),
)
def _eval_step(
Expand Down Expand Up @@ -354,8 +361,7 @@ def _eval_step(
'decoded_paddings': decoded_paddings,
'targets': targets,
'target_paddings': target_paddings,
'n_valid_examples': jnp.zeros((len(jax.devices()), 1))
+ loss['n_valid_examples'],
'n_valid_examples': loss['n_valid_examples'],
}
return metrics_dict

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