ollama source for Momentry Core verification
This commit is contained in:
Accusys
318
convert/convert_gemma4_test.go
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318
convert/convert_gemma4_test.go
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@@ -0,0 +1,318 @@
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package convert
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import (
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"strings"
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"testing"
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)
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func TestGemma4AudioReplacements(t *testing.T) {
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p := gemma4Model{}
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r := strings.NewReplacer(p.Replacements()...)
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tests := []struct {
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name string
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in string
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want string
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}{
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// SSCP convolution blocks
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{
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"sscp conv0 weight",
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"model.audio_tower.subsample_conv_projection.conv_0.conv.weight",
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"a.conv1d.0.weight",
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},
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{
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"sscp conv0 norm",
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"model.audio_tower.subsample_conv_projection.conv_0.norm.weight",
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"a.conv1d.0.norm.weight",
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},
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{
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"sscp conv1 weight",
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"model.audio_tower.subsample_conv_projection.conv_1.conv.weight",
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"a.conv1d.1.weight",
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},
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{
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"sscp input proj weight",
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"model.audio_tower.subsample_conv_projection.input_proj_linear.weight",
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"a.pre_encode.out.weight",
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},
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{
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"sscp input proj bias",
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"model.audio_tower.subsample_conv_projection.input_proj_linear.bias",
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"a.pre_encode.out.bias",
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},
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{
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"sscp layer0 conv weight (new naming)",
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"model.audio_tower.subsample_conv_projection.layer0.conv.weight",
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"a.conv1d.0.weight",
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},
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{
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"sscp layer1 norm weight (new naming)",
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"model.audio_tower.subsample_conv_projection.layer1.norm.weight",
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"a.conv1d.1.norm.weight",
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},
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// Conformer attention
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{
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"attn q weight",
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"model.audio_tower.conformer.0.attention.attn.q_proj.linear.weight",
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"a.blk.0.attn_q.weight",
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},
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{
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"attn k weight",
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"model.audio_tower.conformer.5.attention.attn.k_proj.linear.weight",
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"a.blk.5.attn_k.weight",
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},
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{
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"attn v clamp input_min",
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"model.audio_tower.conformer.0.attention.attn.v_proj.input_min",
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"a.blk.0.attn_v.input_min",
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},
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{
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"attn out weight (ClippableLinear)",
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"model.audio_tower.conformer.0.attention.post.linear.weight",
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"a.blk.0.attn_out.weight",
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},
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{
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"attn out clamp output_max",
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"model.audio_tower.conformer.0.attention.post.output_max",
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"a.blk.0.attn_out.output_max",
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},
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{
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"attn pre norm",
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"model.audio_tower.conformer.0.attention.pre_attn_norm.weight",
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"a.blk.0.ln1.weight",
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},
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{
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"attn post norm",
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"model.audio_tower.conformer.0.attention.post_norm.weight",
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"a.blk.0.ln2.weight",
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},
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{
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"linear pos",
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"model.audio_tower.conformer.0.attention.attn.relative_position_embedding.pos_proj.weight",
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"a.blk.0.linear_pos.weight",
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},
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{
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"per dim scale",
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"model.audio_tower.conformer.0.attention.attn.per_dim_scale",
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"a.blk.0.per_dim_scale",
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},
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{
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"per dim key scale",
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"model.audio_tower.conformer.0.attention.attn.per_dim_key_scale",
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"a.blk.0.per_dim_k_scale",
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},
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{
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"attn relative k proj (new naming)",
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"model.audio_tower.layers.0.self_attn.relative_k_proj.weight",
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"a.blk.0.linear_pos.weight",
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},
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{
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"attn pre norm (new naming)",
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"model.audio_tower.layers.0.norm_pre_attn.weight",
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"a.blk.0.ln1.weight",
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},
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{
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"attn post norm (new naming)",
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"model.audio_tower.layers.0.norm_post_attn.weight",
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"a.blk.0.ln2.weight",
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},
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{
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"attn out clamp output_max (new naming)",
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"model.audio_tower.layers.0.self_attn.post.output_max",
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"a.blk.0.attn_out.output_max",
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},
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{
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"per dim scale (new naming)",
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"model.audio_tower.layers.0.self_attn.per_dim_scale",
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"a.blk.0.per_dim_scale",
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},
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// Conformer feedforward start
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{
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"ffn up weight",
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"model.audio_tower.conformer.0.ffw_layer_start.ffw_layer_1.linear.weight",
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"a.blk.0.ffn_up.weight",
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},
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{
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"ffn down weight",
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"model.audio_tower.conformer.0.ffw_layer_start.ffw_layer_2.linear.weight",
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"a.blk.0.ffn_down.weight",
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},
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{
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"ffn norm",
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"model.audio_tower.conformer.0.ffw_layer_start.pre_layer_norm.weight",
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"a.blk.0.ffn_norm.weight",
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},
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{
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"ffn post norm",
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"model.audio_tower.conformer.0.ffw_layer_start.post_layer_norm.weight",
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"a.blk.0.ffn_post_norm.weight",
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},
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// Conformer feedforward end
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{
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"ffn up 1 weight",
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"model.audio_tower.conformer.0.ffw_layer_end.ffw_layer_1.linear.weight",
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"a.blk.0.ffn_up_1.weight",
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},
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{
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"ffn down 1 weight",
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"model.audio_tower.conformer.0.ffw_layer_end.ffw_layer_2.linear.weight",
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"a.blk.0.ffn_down_1.weight",
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},
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{
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"ffn norm 1",
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"model.audio_tower.conformer.0.ffw_layer_end.pre_layer_norm.weight",
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"a.blk.0.ffn_norm_1.weight",
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},
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{
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"ffn post norm 1",
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"model.audio_tower.conformer.0.ffw_layer_end.post_layer_norm.weight",
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"a.blk.0.ffn_post_norm_1.weight",
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},
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{
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"ffn up output_max (new naming)",
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"model.audio_tower.layers.10.feed_forward1.ffw_layer_1.output_max",
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"a.blk.10.ffn_up.output_max",
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},
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{
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"ffn down output_min (new naming)",
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"model.audio_tower.layers.0.feed_forward1.ffw_layer_2.output_min",
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"a.blk.0.ffn_down.output_min",
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},
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{
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"ffn up 1 input_max (new naming)",
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"model.audio_tower.layers.0.feed_forward2.ffw_layer_1.input_max",
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"a.blk.0.ffn_up_1.input_max",
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},
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{
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"ffn norm 1 (new naming)",
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"model.audio_tower.layers.0.feed_forward2.pre_layer_norm.weight",
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"a.blk.0.ffn_norm_1.weight",
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},
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// Conformer lightweight conv1d
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{
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"conv dw weight",
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"model.audio_tower.conformer.0.lconv1d.depthwise_conv1d.weight",
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"a.blk.0.conv_dw.weight",
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},
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{
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"conv norm (pre_layer_norm)",
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"model.audio_tower.conformer.0.lconv1d.pre_layer_norm.weight",
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"a.blk.0.conv_norm.weight",
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},
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{
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"norm conv (conv_norm)",
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"model.audio_tower.conformer.0.lconv1d.conv_norm.weight",
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"a.blk.0.norm_conv.weight",
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},
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{
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"conv pw1 weight",
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"model.audio_tower.conformer.0.lconv1d.linear_start.linear.weight",
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"a.blk.0.conv_pw1.weight",
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},
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{
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"conv pw2 weight",
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"model.audio_tower.conformer.0.lconv1d.linear_end.linear.weight",
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"a.blk.0.conv_pw2.weight",
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},
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// Audio embedder
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{
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"audio embedder projection weight",
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"model.embed_audio.embedding_projection.linear.weight",
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"mm.a.input_projection.weight",
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},
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{
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"audio embedder projection bias",
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"model.embed_audio.embedding_projection.linear.bias",
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"mm.a.input_projection.bias",
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},
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// Audio output projection
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{
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"audio output proj weight",
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"model.audio_tower.output_proj.weight",
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"mm.a.fc.weight",
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},
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{
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"audio output proj bias",
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"model.audio_tower.output_proj.bias",
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"mm.a.fc.bias",
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},
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// Verify vision tensors still work
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{
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"vision q weight",
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"model.vision_tower.encoder.layers.0.self_attn.q_proj.linear.weight",
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"v.blk.0.attn_q.weight",
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},
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{
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"vision std bias",
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"model.vision_tower.std_bias",
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"v.std_bias",
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},
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{
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"vision std scale",
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"model.vision_tower.std_scale",
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"v.std_scale",
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},
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{
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"vision patch embd",
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"model.vision_tower.patch_embedder.input_proj.weight",
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"v.patch_embd.weight",
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},
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{
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"vision projector",
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"model.embed_vision.embedding_projection.linear.weight",
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"mm.input_projection.weight",
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},
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// Verify text tensors still work
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{
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"text attn q",
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"model.language_model.layers.0.self_attn.q_proj.weight",
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"blk.0.attn_q.weight",
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},
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{
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"text token embd",
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"model.language_model.embed_tokens.weight",
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"token_embd.weight",
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},
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{
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"text moe gate up fused",
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"model.language_model.layers.0.experts.gate_up_proj",
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"blk.0.ffn_gate_up_exps.weight",
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},
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{
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"text moe down",
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"model.language_model.layers.0.experts.down_proj",
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"blk.0.ffn_down_exps.weight",
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},
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{
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"text moe down with weight suffix",
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"model.language_model.layers.0.experts.down_proj.weight",
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"blk.0.ffn_down_exps.weight",
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},
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{
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"text moe per expert scale",
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"model.language_model.layers.0.router.per_expert_scale",
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"blk.0.ffn_down_exps.scale",
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},
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{
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"text moe per expert scale with weight suffix",
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"model.language_model.layers.0.router.per_expert_scale.weight",
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"blk.0.ffn_down_exps.scale",
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},
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}
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for _, tt := range tests {
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t.Run(tt.name, func(t *testing.T) {
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if got := r.Replace(tt.in); got != tt.want {
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t.Errorf("Replace(%q) = %q, want %q", tt.in, got, tt.want)
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}
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})
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}
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}
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