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Fix rebasin

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AI-Casanova
2023-11-20 14:34:15 -06:00
parent 00b246c052
commit d077658524
1 changed files with 2 additions and 79 deletions
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modules/merging/merge_rebasin.py
+2 -79
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@@ -67,7 +67,7 @@ def sdunet_permutation_spec() -> PermutationSpec:
**conv(f"{name}.out_layers.3", f"P_{name}_inner4", p_out),
}
# Text Encoder blocks
# VAE blocks - Unused
easyblock2 = lambda name, p: { # pylint: disable=unnecessary-lambda-assignment
**norm(f"{name}.norm1", p),
**conv(f"{name}.conv1", p, f"P_{name}_inner"),
@@ -1510,83 +1510,6 @@ def sdunet_permutation_spec() -> PermutationSpec:
),
**norm("model.diffusion_model.out.0", "P_bg324"),
**conv("model.diffusion_model.out.2", "P_bg325", "P_bg326"),
# Text Encoder
# encoder down
**conv("first_stage_model.encoder.conv_in", "P_bg327", "P_bg328"),
**easyblock2("first_stage_model.encoder.down.0.block.0", "P_bg328"),
**easyblock2("first_stage_model.encoder.down.0.block.1", "P_bg328"),
**conv(
"first_stage_model.encoder.down.0.downsample.conv", "P_bg328", "P_bg329"
),
**shortcutblock(
"first_stage_model.encoder.down.1.block.0", "P_bg330", "P_bg331"
),
**easyblock2("first_stage_model.encoder.down.1.block.1", "P_bg331"),
**conv(
"first_stage_model.encoder.down.1.downsample.conv", "P_bg331", "P_bg332"
),
**shortcutblock(
"first_stage_model.encoder.down.2.block.0", "P_bg332", "P_bg333"
),
**easyblock2("first_stage_model.encoder.down.2.block.1", "P_bg333"),
**conv(
"first_stage_model.encoder.down.2.downsample.conv", "P_bg333", "P_bg334"
),
**easyblock2("first_stage_model.encoder.down.3.block.0", "P_bg334"),
**easyblock2("first_stage_model.encoder.down.3.block.1", "P_bg334"),
# encoder mid-block
**easyblock2("first_stage_model.encoder.mid.block_1", "P_bg334"),
**norm("first_stage_model.encoder.mid.attn_1.norm", "P_bg334"),
**conv("first_stage_model.encoder.mid.attn_1.q", "P_bg334", "P_bg335"),
**conv("first_stage_model.encoder.mid.attn_1.k", "P_bg334", "P_bg335"),
**conv("first_stage_model.encoder.mid.attn_1.v", "P_bg334", "P_bg335"),
**conv(
"first_stage_model.encoder.mid.attn_1.proj_out", "P_bg335", "P_bg336"
),
**easyblock2("first_stage_model.encoder.mid.block_2", "P_bg336"),
**norm("first_stage_model.encoder.norm_out", "P_bg337"),
**conv("first_stage_model.encoder.conv_out", "P_bg338", "P_bg339"),
**conv("first_stage_model.decoder.conv_in", "P_bg340", "P_bg341"),
# decoder mid-block
**easyblock2("first_stage_model.decoder.mid.block_1", "P_bg342"),
**norm("first_stage_model.decoder.mid.attn_1.norm", "P_bg342"),
**conv("first_stage_model.decoder.mid.attn_1.q", "P_bg342", "P_bg343"),
**conv("first_stage_model.decoder.mid.attn_1.k", "P_bg342", "P_bg343"),
**conv("first_stage_model.decoder.mid.attn_1.v", "P_bg342", "P_bg343"),
**conv(
"first_stage_model.decoder.mid.attn_1.proj_out", "P_bg343", "P_bg344"
),
**easyblock2("first_stage_model.decoder.mid.block_2", "P_bg345"),
# decoder up
**shortcutblock(
"first_stage_model.decoder.up.0.block.0", "P_bg346", "P_bg347"
),
**easyblock2("first_stage_model.decoder.up.0.block.1", "P_bg348"),
**easyblock2("first_stage_model.decoder.up.0.block.2", "P_bg349"),
**shortcutblock(
"first_stage_model.decoder.up.1.block.0", "P_bg350", "P_bg351"
),
**easyblock2("first_stage_model.decoder.up.1.block.1", "P_bg352"),
**easyblock2("first_stage_model.decoder.up.1.block.2", "P_bg353"),
**conv(
"first_stage_model.decoder.up.1.upsample.conv", "P_bg353", "P_bg354"
),
**easyblock2("first_stage_model.decoder.up.2.block.0", "P_bg355"),
**easyblock2("first_stage_model.decoder.up.2.block.1", "P_bg355"),
**easyblock2("first_stage_model.decoder.up.2.block.2", "P_bg355"),
**conv(
"first_stage_model.decoder.up.2.upsample.conv", "P_bg355", "P_bg356"
),
**easyblock2("first_stage_model.decoder.up.3.block.0", "P_bg356"),
**easyblock2("first_stage_model.decoder.up.3.block.1", "P_bg356"),
**easyblock2("first_stage_model.decoder.up.3.block.2", "P_bg356"),
**conv(
"first_stage_model.decoder.up.3.upsample.conv", "P_bg356", "P_bg357"
),
**norm("first_stage_model.decoder.norm_out", "P_bg358"),
**conv("first_stage_model.decoder.conv_out", "P_bg359", "P_bg360"),
**conv("first_stage_model.quant_conv", "P_bg361", "P_bg362"),
**conv("first_stage_model.post_quant_conv", "P_bg363", "P_bg364"),
**skip(
"cond_stage_model.transformer.text_model.embeddings.position_ids",
None,
@@ -2261,7 +2184,7 @@ def weight_matching(
linear_sum = 0
number = 0
special_layers = ["P_bg324", "P_bg358", "P_bg337"]
special_layers = ["P_bg324"]
for _i in range(max_iter):
progress = False
shuffle(special_layers)