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Fix NumPy Deprecation Warning for np.bool Usage in attention.py #50

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Fix NumPy Deprecation Warning for np.bool Usage in attention.py #50

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e889ae9
Update attention.py
conorKotwasinski Mar 8, 2024
3c11871
Update attention.py
conorKotwasinski Mar 8, 2024
7ad3ca2
Update attention.py
conorKotwasinski Mar 8, 2024
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18 changes: 9 additions & 9 deletions glide_text2im/clip/attention.py
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Original file line number Diff line number Diff line change
Expand Up @@ -39,13 +39,13 @@ def __attrs_post_init__(self) -> None:

def _make_global_layout(self) -> None:
if not self.is_head_specific:
m = np.ones([self.n_query_block, self.n_key_block], dtype=np.bool)
m = np.ones([self.n_query_block, self.n_key_block], dtype=np.bool_)
r = product(*[range(n) for n in m.shape])

for qb, kb in r:
m[qb, kb] = np.any(self.block_layout(None, 0, qb, kb, 0))
else:
m = np.ones([self.n_head, self.n_query_block, self.n_key_block], dtype=np.bool)
m = np.ones([self.n_head, self.n_query_block, self.n_key_block], dtype=np.bool_)
r = product(*[range(n) for n in m.shape])

for h, qb, kb in r:
Expand All @@ -66,7 +66,7 @@ def block_layout(
`query_idx`, `key_idx` are block-level, zero-based indices.
"""

m = np.ones([self.block_size, self.block_size], dtype=np.bool)
m = np.ones([self.block_size, self.block_size], dtype=np.bool_)

if query_idx >= self.first_pad_query_block_idx:
n_pad = min(
Expand All @@ -91,7 +91,7 @@ class DenseAttentionMask(AttentionMask):
def __attrs_post_init__(self) -> None:
super().__attrs_post_init__()

self.global_layout = np.ones([self.n_query_block, self.n_key_block], dtype=np.bool)
self.global_layout = np.ones([self.n_query_block, self.n_key_block], dtype=np.bool_)
n_zero_query_blocks = self.n_query_pad // self.block_size
n_zero_key_blocks = self.n_key_pad // self.block_size
self.global_layout[self.n_query_block - n_zero_query_blocks :] = False
Expand All @@ -100,15 +100,15 @@ def __attrs_post_init__(self) -> None:
def _block_layout(
self, blk_shape: Any, head_idx: int, query_idx: int, key_idx: int, blk_idx: int
) -> np.ndarray:
return np.ones([self.block_size, self.block_size], dtype=np.bool)
return np.ones([self.block_size, self.block_size], dtype=np.bool_)


@attr.s
class DenseCausalAttentionMask(AttentionMask):
def __attrs_post_init__(self) -> None:
super().__attrs_post_init__()

self.global_layout = np.tril(np.ones([self.n_query_block, self.n_key_block], dtype=np.bool))
self.global_layout = np.tril(np.ones([self.n_query_block, self.n_key_block], dtype=np.bool_))
n_zero_query_blocks = self.n_query_pad // self.block_size
n_zero_key_blocks = self.n_key_pad // self.block_size
self.global_layout[self.n_query_block - n_zero_query_blocks :] = False
Expand All @@ -118,11 +118,11 @@ def _block_layout(
self, blk_shape: Any, head_idx: int, query_idx: int, key_idx: int, blk_idx: int
) -> np.ndarray:
if query_idx > key_idx:
return np.ones(2 * [self.block_size], dtype=np.bool)
return np.ones(2 * [self.block_size], dtype=np.bool_)
elif query_idx < key_idx:
return np.zeros(2 * [self.block_size], dtype=np.bool)
return np.zeros(2 * [self.block_size], dtype=np.bool_)
else:
return np.tril(np.ones(2 * [self.block_size], dtype=np.bool))
return np.tril(np.ones(2 * [self.block_size], dtype=np.bool_))


@attr.s(eq=False, repr=False)
Expand Down