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Change constant torch.tensor to torch.full #20061

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Merged
sgugger merged 1 commit into from
Nov 4, 2022
Merged

Change constant torch.tensor to torch.full #20061

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6 changes: 3 additions & 3 deletions src/transformers/models/decision_transformer/modeling_decision_transformer.py
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Original file line number Diff line number Diff line change
Expand Up @@ -170,8 +170,8 @@ def _attn(self, query, key, value, attention_mask=None, head_mask=None):
attn_weights = torch.matmul(query, key.transpose(-1, -2))

if self.scale_attn_weights:
attn_weights = attn_weights / torch.tensor(
value.size(-1) ** 0.5, dtype=attn_weights.dtype, device=attn_weights.device
attn_weights = attn_weights / torch.full(
[], value.size(-1) ** 0.5, dtype=attn_weights.dtype, device=attn_weights.device
)

# Layer-wise attention scaling
Expand All @@ -185,7 +185,7 @@ def _attn(self, query, key, value, attention_mask=None, head_mask=None):
mask_value = torch.finfo(attn_weights.dtype).min
# Need to be a tensor, otherwise we get error: `RuntimeError: expected scalar type float but found double`.
# Need to be on the same device, otherwise `RuntimeError: ..., x and y to be on the same device`
mask_value = torch.tensor(mask_value, dtype=attn_weights.dtype).to(attn_weights.device)
mask_value = torch.full([], mask_value, dtype=attn_weights.dtype).to(attn_weights.device)
attn_weights = torch.where(causal_mask, attn_weights, mask_value)

if attention_mask is not None:
Expand Down
6 changes: 3 additions & 3 deletions src/transformers/models/gpt2/modeling_gpt2.py
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Original file line number Diff line number Diff line change
Expand Up @@ -182,8 +182,8 @@ def _attn(self, query, key, value, attention_mask=None, head_mask=None):
attn_weights = torch.matmul(query, key.transpose(-1, -2))

if self.scale_attn_weights:
attn_weights = attn_weights / torch.tensor(
value.size(-1) ** 0.5, dtype=attn_weights.dtype, device=attn_weights.device
attn_weights = attn_weights / torch.full(
[], value.size(-1) ** 0.5, dtype=attn_weights.dtype, device=attn_weights.device
)

# Layer-wise attention scaling
Expand All @@ -197,7 +197,7 @@ def _attn(self, query, key, value, attention_mask=None, head_mask=None):
mask_value = torch.finfo(attn_weights.dtype).min
# Need to be a tensor, otherwise we get error: `RuntimeError: expected scalar type float but found double`.
# Need to be on the same device, otherwise `RuntimeError: ..., x and y to be on the same device`
mask_value = torch.tensor(mask_value, dtype=attn_weights.dtype).to(attn_weights.device)
mask_value = torch.full([], mask_value, dtype=attn_weights.dtype).to(attn_weights.device)
attn_weights = torch.where(causal_mask, attn_weights, mask_value)

if attention_mask is not None:
Expand Down