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fix multi-gpu with static cache #32543

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Merged
ArthurZucker merged 1 commit into from
Aug 16, 2024
Merged

fix multi-gpu with static cache #32543

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4 changes: 2 additions & 2 deletions src/transformers/cache_utils.py
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Original file line number Diff line number Diff line change
Expand Up @@ -1069,6 +1069,8 @@ def update(
A tuple containing the updated key and value states.
"""
cache_position = cache_kwargs.get("cache_position")
self.key_cache[layer_idx] = self.key_cache[layer_idx].to(device=key_states.device)
self.value_cache[layer_idx] = self.value_cache[layer_idx].to(device=value_states.device)
Comment on lines +1072 to +1073
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@SunMarc SunMarc Aug 8, 2024

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Same as what we have in hybrid cache class

k_out = self.key_cache[layer_idx]
v_out = self.value_cache[layer_idx]

Expand All @@ -1080,8 +1082,6 @@ def update(
# `tensor[:, :, index] = tensor`, but the first one is compile-friendly and it does explicitly an in-place
# operation, that avoids copies and uses less memory.
try:
# If using several devices (e.g.: multiple GPUs), we need to ensure everything is on the same one
cache_position.to(device=k_out.device)
k_out.index_copy_(2, cache_position, key_states)
v_out.index_copy_(2, cache_position, value_states)
except NotImplementedError:
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