testing Tora for I2V
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@@ -23,7 +23,7 @@ import numpy as np
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from einops import rearrange
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from diffusers.configuration_utils import ConfigMixin, register_to_config
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from diffusers.utils import is_torch_version, logging
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from diffusers.utils import logging
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from diffusers.utils.torch_utils import maybe_allow_in_graph
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from diffusers.models.attention import Attention, FeedForward
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from diffusers.models.attention_processor import AttentionProcessor
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@@ -37,11 +37,11 @@ logger = logging.get_logger(__name__) # pylint: disable=invalid-name
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try:
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from sageattention import sageattn
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SAGEATTN_IS_AVAVILABLE = True
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SAGEATTN_IS_AVAILABLE = True
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logger.info("Using sageattn")
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except:
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logger.info("sageattn not found, using sdpa")
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SAGEATTN_IS_AVAVILABLE = False
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SAGEATTN_IS_AVAILABLE = False
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class CogVideoXAttnProcessor2_0:
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r"""
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@@ -97,7 +97,7 @@ class CogVideoXAttnProcessor2_0:
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if not attn.is_cross_attention:
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key[:, :, text_seq_length:] = apply_rotary_emb(key[:, :, text_seq_length:], image_rotary_emb)
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if SAGEATTN_IS_AVAVILABLE:
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if SAGEATTN_IS_AVAILABLE:
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hidden_states = sageattn(query, key, value, is_causal=False)
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else:
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hidden_states = F.scaled_dot_product_attention(
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@@ -171,7 +171,7 @@ class FusedCogVideoXAttnProcessor2_0:
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if not attn.is_cross_attention:
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key[:, :, text_seq_length:] = apply_rotary_emb(key[:, :, text_seq_length:], image_rotary_emb)
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if SAGEATTN_IS_AVAVILABLE:
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if SAGEATTN_IS_AVAILABLE:
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hidden_states = sageattn(query, key, value, is_causal=False)
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else:
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hidden_states = F.scaled_dot_product_attention(
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