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Replace # pytype: disable suppressions with # pyrefly: ignore #357

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Merged
copybara-service merged 1 commit into from
Oct 14, 2026
Merged

Replace # pytype: disable suppressions with # pyrefly: ignore #357

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2 changes: 1 addition & 1 deletion learned_optimization/tasks/parametric/image_mlp_ae.py
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Original file line number Diff line number Diff line change
Expand Up @@ -95,7 +95,7 @@ def init(self, key: PRNGKey) -> Params:
image = next(self.datasets.train)["image"] # pyrefly: ignore[missing-attribute]
return init_net(key, image)

def loss(self, params: Params, key: PRNGKey, data: Batch) -> jnp.ndarray: # pytype: disable=signature-mismatch # jax-ndarray
def loss(self, params: Params, key: PRNGKey, data: Batch) -> jnp.ndarray: # pyrefly: ignore[bad-override]
unused_init_net, apply_net = hk.without_apply_rng(
hk.transform(_forward))

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2 changes: 1 addition & 1 deletion learned_optimization/tasks/parametric/image_mlp_vae.py
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Expand Up @@ -126,7 +126,7 @@ def init(self, key: PRNGKey) -> Params:
image = next(self.datasets.train)["image"] # pyrefly: ignore[missing-attribute]
return hk.transform(_forward).init(key, image)

def loss(self, params: Params, key: PRNGKey, data: Batch) -> jnp.ndarray: # pytype: disable=signature-mismatch # jax-ndarray
def loss(self, params: Params, key: PRNGKey, data: Batch) -> jnp.ndarray: # pyrefly: ignore[bad-override]
image = data["image"]
center_fn = lambda img: 2 * (img - 0.5)
image = jax.lax.cond(task_params["center_data"], center_fn, lambda x: x,
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4 changes: 2 additions & 2 deletions learned_optimization/tasks/parametric/lm_rnn.py
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Expand Up @@ -85,7 +85,7 @@ def _forward(inp):
task_params.values["initializer"])

embed = hk.Embed(vocab_size, self.embed_size, w_init=w_init)(inp)
rnn_core = self.rnn_core_fn(self.rnn_size) # pytype: disable=wrong-arg-count # trace-all-classes
rnn_core = self.rnn_core_fn(self.rnn_size) # pyrefly: ignore[bad-argument-count]

# Make learnable initial states.
template_state = rnn_core.initial_state(1)
Expand Down Expand Up @@ -124,7 +124,7 @@ def init(self, rng: PRNGKey) -> Params:
seq = batch["obs"]
return init_net(rng, seq)

def loss(self, params: Params, rng: PRNGKey, data: Batch) -> jnp.ndarray: # pytype: disable=signature-mismatch # jax-ndarray
def loss(self, params: Params, rng: PRNGKey, data: Batch) -> jnp.ndarray:
net = hk.without_apply_rng(hk.transform(_forward))
obs = data["obs"]
target = data["target"]
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