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Donate model's memory buffer to jit/pmap functions. #226

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merged 1 commit into from
Mar 23, 2022
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Donate model's memory buffer to jit/pmap functions. #226

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13 changes: 9 additions & 4 deletions elegy/model/model_core.py
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Original file line number Diff line number Diff line change
Expand Up @@ -124,17 +124,18 @@ def train_step_fn(self, model: M) -> TrainStep[M]:

@dataclass(unsafe_hash=True)
class JIT(DistributedStrategy):
# donate 'model' memory buffer since we return an updated model
def init_step_fn(self, model: M) -> InitStep[M]:
return jax.jit(model.__class__._static_init_step)
return jax.jit(model.__class__._static_init_step, donate_argnums=0)

def pred_step_fn(self, model: M) -> PredStep[M]:
return jax.jit(model.__class__._static_pred_step)
return jax.jit(model.__class__._static_pred_step, donate_argnums=0)

def test_step_fn(self, model: M) -> TestStep[M]:
return jax.jit(model.__class__._static_test_step)
return jax.jit(model.__class__._static_test_step, donate_argnums=0)

def train_step_fn(self, model: M) -> TrainStep[M]:
return jax.jit(model.__class__._static_train_step)
return jax.jit(model.__class__._static_train_step, donate_argnums=0)


@dataclass(unsafe_hash=True)
Expand Down Expand Up @@ -204,26 +205,30 @@ def init_step_fn(self, model: M) -> InitStep[M]:
return jax.pmap(
model.__class__._static_init_step,
axis_name="device",
donate_argnums=0,
)

def pred_step_fn(self, model: M) -> PredStep[M]:
return jax.pmap(
model.__class__._static_pred_step,
axis_name="device",
donate_argnums=0,
)

def test_step_fn(self, model: M) -> TestStep[M]:
return jax.pmap(
model.__class__._static_test_step,
axis_name="device",
out_axes=(0, None, 0), # None = logs not replicated
donate_argnums=0,
)

def train_step_fn(self, model: M) -> TrainStep[M]:
return jax.pmap(
model.__class__._static_train_step,
axis_name="device",
out_axes=(None, 0), # None = logs not replicated
donate_argnums=0,
)


Expand Down