Use other MPS optimization for large q.shape[0] * q.shape[1]
Check if q.shape[0] * q.shape[1] is 2**18 or larger and use the lower memory usage MPS optimization if it is. This should prevent most crashes that were occurring at certain resolutions (e.g. 1024x1024, 2048x512, 512x2048). Also included is a change to check slice_size and prevent it from being divisible by 4096 which also results in a crash. Otherwise a crash can occur at 1024x512 or 512x1024 resolution.
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@ -127,7 +127,7 @@ def check_for_psutil():
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invokeAI_mps_available = check_for_psutil()
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# -- Taken from https://github.com/invoke-ai/InvokeAI --
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# -- Taken from https://github.com/invoke-ai/InvokeAI and modified --
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if invokeAI_mps_available:
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import psutil
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mem_total_gb = psutil.virtual_memory().total // (1 << 30)
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@ -152,14 +152,16 @@ def einsum_op_slice_1(q, k, v, slice_size):
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return r
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def einsum_op_mps_v1(q, k, v):
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if q.shape[1] <= 4096: # (512x512) max q.shape[1]: 4096
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if q.shape[0] * q.shape[1] <= 2**16: # (512x512) max q.shape[1]: 4096
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return einsum_op_compvis(q, k, v)
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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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if slice_size % 4096 == 0:
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slice_size -= 1
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return einsum_op_slice_1(q, k, v, slice_size)
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def einsum_op_mps_v2(q, k, v):
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if mem_total_gb > 8 and q.shape[1] <= 4096:
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if mem_total_gb > 8 and q.shape[0] * q.shape[1] <= 2**16:
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return einsum_op_compvis(q, k, v)
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else:
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return einsum_op_slice_0(q, k, v, 1)
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@ -188,7 +190,7 @@ def einsum_op(q, k, v):
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return einsum_op_cuda(q, k, v)
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if q.device.type == 'mps':
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if mem_total_gb >= 32:
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if mem_total_gb >= 32 and q.shape[0] % 32 != 0 and q.shape[0] * q.shape[1] < 2**18:
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return einsum_op_mps_v1(q, k, v)
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return einsum_op_mps_v2(q, k, v)
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