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https://github.com/invoke-ai/InvokeAI
synced 2024-08-30 20:32:17 +00:00
blackify and rerun frontend build
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@ -265,7 +265,7 @@ class InvokeAICrossAttentionMixin:
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if q.shape[1] <= 4096: # (512x512) max q.shape[1]: 4096
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return self.einsum_lowest_level(q, k, v, None, None, None)
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else:
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slice_size = math.floor(2**30 / (q.shape[0] * q.shape[1]))
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slice_size = math.floor(2 ** 30 / (q.shape[0] * q.shape[1]))
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return self.einsum_op_slice_dim1(q, k, v, slice_size)
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def einsum_op_mps_v2(self, q, k, v):
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@ -215,10 +215,7 @@ class InvokeAIDiffuserComponent:
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dim=0,
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),
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}
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(
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encoder_hidden_states,
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encoder_attention_mask,
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) = self._concat_conditionings_for_batch(
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(encoder_hidden_states, encoder_attention_mask,) = self._concat_conditionings_for_batch(
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conditioning_data.unconditioned_embeddings.embeds,
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conditioning_data.text_embeddings.embeds,
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)
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@ -280,10 +277,7 @@ class InvokeAIDiffuserComponent:
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wants_cross_attention_control = len(cross_attention_control_types_to_do) > 0
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if wants_cross_attention_control:
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(
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unconditioned_next_x,
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conditioned_next_x,
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) = self._apply_cross_attention_controlled_conditioning(
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(unconditioned_next_x, conditioned_next_x,) = self._apply_cross_attention_controlled_conditioning(
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sample,
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timestep,
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conditioning_data,
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@ -291,10 +285,7 @@ class InvokeAIDiffuserComponent:
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**kwargs,
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)
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elif self.sequential_guidance:
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(
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unconditioned_next_x,
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conditioned_next_x,
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) = self._apply_standard_conditioning_sequentially(
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(unconditioned_next_x, conditioned_next_x,) = self._apply_standard_conditioning_sequentially(
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sample,
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timestep,
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conditioning_data,
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@ -302,10 +293,7 @@ class InvokeAIDiffuserComponent:
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)
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else:
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(
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unconditioned_next_x,
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conditioned_next_x,
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) = self._apply_standard_conditioning(
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(unconditioned_next_x, conditioned_next_x,) = self._apply_standard_conditioning(
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sample,
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timestep,
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conditioning_data,
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