Qwen35.Config(
                channels_in=16,
                channels_out=32,
                num_layers=2,
                proj_in=Embedding.Config(
                        channels_in=32,
                        channels_out=16,
                        padding_idx=None,
                        device=None,
                        dtype=None,
                        shard=None,
                        depth_index=(),
                        init_weight=functools.partial(<function torch.nn.init.normal_ at 0xdefacedeface>, std=0.02)
                ),
                block=[
                │       TransformerBlock.Config(
                │               channels_in=16,
                │               channels_out=16,
                │               attn=Qwen35GatedDeltaNet.Config(
                │                       channels_in=16,
                │                       channels_out=16,
                │                       num_heads_k=1,
                │                       num_heads_v=2,
                │                       channels_k_head=4,
                │                       channels_v_head=4,
                │                       conv_kernel_size=4,
                │                       norm=Qwen35RMSNormGated.Config(
                │                               channels_in=4,
                │                               eps=1e-06
                │                       ),
                │                       init_weight=functools.partial(<function torch.nn.init.normal_ at 0xdefacedeface>, std=0.02),
                │                       init_conv_weight=<function priml.model.init.kaiming_uniform at 0xdefacedeface>,
                │                       init_decay=<function priml.model.attention.qwen3_5_delta._init_decay at 0xdefacedeface>,
                │                       depth_index=((0, 2),)
                │               ),
                │               ffn=SwiGLU.Config(
                │                       channels_in=16,
                │                       channels_out=16,
                │                       channels_hidden=24,
                │                       expansion=2.6666666666666665,
                │                       round_to=256,
                │                       gate=True,
                │                       bias=False,
                │                       split_gate_projection=False,
                │                       norm=None,
                │                       act=<function priml.model.swiglu.silu at 0xdefacedeface>,
                │                       depth_index=((0, 2),),
                │                       init_weight=functools.partial(<function torch.nn.init.normal_ at 0xdefacedeface>, std=0.02),
                │                       init_weight_out=functools.partial(<function torch.nn.init.normal_ at 0xdefacedeface>, std=0.02),
                │                       shard='colwise'
                │               ),
                │               norm1=CenteredRMSNorm.Config(
                │                       channels_in=16,
                │                       channels_out=16,
                │                       eps=1e-06
                │               ),
                │               norm2=CenteredRMSNorm.Config(
                │                       channels_in=16,
                │                       channels_out=16,
                │                       eps=1e-06
                │               ),
                │               prenorm=True,
                │               checkpoint=False,
                │               depth_index=((0, 2),)
                │       ),
                │       TransformerBlock.Config(
                │               channels_in=16,
                │               channels_out=16,
                │               attn=GatedAttention.Config(
                │                       channels_in=16,
                │                       channels_out=16,
                │                       num_heads=2,
                │                       num_heads_kv=1,
                │                       channels_head=8,
                │                       bias=False,
                │                       dropout=0.0,
                │                       norm_qk=CenteredRMSNorm.Config(
                │                               channels_in=8,
                │                               channels_out=8,
                │                               eps=1e-06
                │                       ),
                │                       rope=RoPE.Config(
                │                               channels_head=4,
                │                               reduction_mode='cat',
                │                               frequencies=HuggingFaceFrequencies.Config(
                │                                       base=10000.0
                │                               ),
                │                               dtype=torch.float32
                │                       ),
                │                       attn_kernel=SdpaNaive.Config(),
                │                       init_weight=functools.partial(<function torch.nn.init.normal_ at 0xdefacedeface>, std=0.02),
                │                       depth_index=((1, 2),)
                │               ),
                │               ffn=SwiGLU.Config(
                │                       channels_in=16,
                │                       channels_out=16,
                │                       channels_hidden=24,
                │                       expansion=2.6666666666666665,
                │                       round_to=256,
                │                       gate=True,
                │                       bias=False,
                │                       split_gate_projection=False,
                │                       norm=None,
                │                       act=<function priml.model.swiglu.silu at 0xdefacedeface>,
                │                       depth_index=((1, 2),),
                │                       init_weight=functools.partial(<function torch.nn.init.normal_ at 0xdefacedeface>, std=0.02),
                │                       init_weight_out=functools.partial(<function torch.nn.init.normal_ at 0xdefacedeface>, std=0.02),
                │                       shard='colwise'
                │               ),
                │               norm1=CenteredRMSNorm.Config(
                │                       channels_in=16,
                │                       channels_out=16,
                │                       eps=1e-06
                │               ),
                │               norm2=CenteredRMSNorm.Config(
                │                       channels_in=16,
                │                       channels_out=16,
                │                       eps=1e-06
                │               ),
                │               prenorm=True,
                │               checkpoint=False,
                │               depth_index=((1, 2),)
                │       )
                ],
                proj_out=Linear.Config(
                        channels_in=16,
                        channels_out=32,
                        bias=False,
                        depth_index=(),
                        device=None,
                        dtype=None,
                        init_weight=functools.partial(<function torch.nn.init.normal_ at 0xdefacedeface>, std=0.02),
                        init_bias=<function torch.nn.init.zeros_ at 0xdefacedeface>,
                        shard=None
                ),
                norm=CenteredRMSNorm.Config(
                        channels_in=16,
                        channels_out=16,
                        eps=1e-06
                )
        )
