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Create mapping for FP8 torch dtypes #9573

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Merged
merged 1 commit into from
Aug 22, 2025
Merged

Create mapping for FP8 torch dtypes #9573

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16 changes: 12 additions & 4 deletions torchax/torchax/ops/mappings.py
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Original file line number Diff line number Diff line change
Expand Up @@ -6,6 +6,14 @@
import torch.utils.dlpack as torchdl
import torch.utils._mode_utils as mode_utils

NUMPY_UNSUPPORTED_DTYPES = {
torch.bfloat16: jnp.bfloat16,
torch.float8_e4m3fn: jnp.float8_e4m3fn,
torch.float8_e4m3fnuz: jnp.float8_e4m3fnuz,
torch.float8_e5m2: jnp.float8_e5m2,
torch.float8_e5m2fnuz: jnp.float8_e5m2fnuz,
}


def t2j(t, use_dlpack=True):
is_bool = False
Expand All @@ -28,14 +36,14 @@ def t2j(t, use_dlpack=True):
if res is None:
# https://github.com/google/jax/issues/7657
# https://github.com/google/jax/issues/17784
if t.dtype == torch.bfloat16:
if t.dtype in NUMPY_UNSUPPORTED_DTYPES:
nparray = (t.cpu().detach().to(torch.float32).numpy()
) # numpy don't support bfloat16
) # handle dtypes not supported by numpy
else:
nparray = t.cpu().detach().numpy()
res = jnp.asarray(nparray)
if t.dtype == torch.bfloat16:
res = res.astype(jnp.bfloat16)
if t.dtype in NUMPY_UNSUPPORTED_DTYPES:
res = res.astype(NUMPY_UNSUPPORTED_DTYPES[t.dtype])

if is_bool:
res = res.astype(jnp.bool_)
Expand Down