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[Mosaic TPU] Add support for packing to 16-bit integers on TPUv4 #25824

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merged 1 commit into from
Jan 16, 2025
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[Mosaic TPU] Add support for packing to 16-bit integers on TPUv4 #25824

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26 changes: 15 additions & 11 deletions tests/pallas/ops_test.py
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Original file line number Diff line number Diff line change
Expand Up @@ -550,16 +550,16 @@ def test_cast(self, from_dtype, to_dtype, data):
self.skipTest("Unnecessary test")
if jtu.is_device_tpu(version=4):
if (from_dtype in {"int16", "int8", "uint16", "uint8"} or
to_dtype in {"int16", "int8", "uint16", "uint8"}):
self.skipTest(
"Not supported: TPU generation doesn't support this cast."
)
to_dtype in {"int8", "uint8"}):
self.skipTest("Not supported on this TPU generation")
if to_dtype in {"int16", "uint16"} and not jtu.if_cloud_tpu_at_least(2025, 1, 18):
self.skipTest("Test requires libtpu from 2025/1/18 or later")
if jtu.test_device_matches(["tpu"]) and jtu.get_tpu_version() < 4:
if (from_dtype in {"int32", "uint32", "float32", "bfloat16", "int16", "int8"} and
to_dtype in {"int16", "int8", "uint16", "uint8"}):
self.skipTest(
"Not supported: TPU generation doesn't support this cast."
)
# Currently only casts between 32-bit types and to bf16 are supported.
if (from_dtype not in {"int32", "uint32", "float32"} or
to_dtype not in {"int32", "uint32", "float32", "bfloat16"}):
self.skipTest("Not supported on this TPU generation")

from_int = np.issubdtype(np.dtype(from_dtype), np.integer)
to_int = np.issubdtype(np.dtype(to_dtype), np.integer)
if (
Expand All @@ -577,11 +577,15 @@ def test_cast(self, from_dtype, to_dtype, data):
if to_dtype == "bfloat16":
to_dtype = jnp.bfloat16

# XLA does not specify the float->int conversion result for NaNs.
elements = dict(allow_nan=not jnp.issubdtype(to_dtype, jnp.integer))
if from_dtype == jnp.bfloat16:
x = jnp.asarray(data.draw(hnp.arrays(jnp.float32, (8, 128))))
x = jnp.asarray(
data.draw(hnp.arrays(jnp.float32, (8, 128), elements=elements))
)
x = x.astype(jnp.bfloat16)
else:
x = data.draw(hnp.arrays(from_dtype, (8, 128)))
x = data.draw(hnp.arrays(from_dtype, (8, 128), elements=elements))
x = jnp.asarray(x)
if from_dtype == jnp.dtype("bool"):
x = x.astype(jnp.int32)
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