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Use jnp for metrics to make arrays addressable in multi-task setting. #834

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Use jnp for metrics to make arrays addressable in multi-task setting. #834

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8 changes: 4 additions & 4 deletions init2winit/model_lib/metrics.py
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Expand Up @@ -464,8 +464,8 @@ def average_ctc_loss():
@flax.struct.dataclass
class _Metric(metrics.Metric):
"""Applies `fun` and computes the average."""
total: np.float32
weight: np.float32
total: jnp.float32
weight: jnp.float32

@classmethod
def from_model_output(cls, normalized_loss, **_):
Expand All @@ -492,8 +492,8 @@ def compute_wer(decoded,
num_words = 0.0

if tokenizer_type == 'SPM':
decoded_lengths = np.sum(decoded_paddings == 0.0, axis=-1)
target_lengths = np.sum(target_paddings == 0.0, axis=-1)
decoded_lengths = jnp.sum(decoded_paddings == 0.0, axis=-1)
target_lengths = jnp.sum(target_paddings == 0.0, axis=-1)

batch_size = targets.shape[0]

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