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Criteo Jax loss float64 cast #525

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Merged
merged 5 commits into from
Oct 16, 2023
Merged

Criteo Jax loss float64 cast #525

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4 changes: 3 additions & 1 deletion algorithmic_efficiency/workloads/criteo1tb/criteo1tb_jax/workload.py
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Original file line number Diff line number Diff line change
Expand Up @@ -6,6 +6,7 @@
from flax import jax_utils
import jax
import jax.numpy as jnp
import numpy as np

from algorithmic_efficiency import param_utils
from algorithmic_efficiency import spec
Expand Down Expand Up @@ -147,7 +148,8 @@ def _eval_batch(self,
batch: Dict[str, spec.Tensor]) -> spec.Tensor:
# We do NOT psum inside of _eval_batch_pmapped, so the returned tensor of
# shape (local_device_count,) will all be different values.
return self._eval_batch_pmapped(params, batch).sum()
return np.array(
self._eval_batch_pmapped(params, batch).sum(), dtype=np.float64)


class Criteo1TbDlrmSmallTestWorkload(Criteo1TbDlrmSmallWorkload):
Expand Down