For the complete documentation index, see llms.txt. Markdown versions of all pages are available by appending .md to any URL (e.g. /max/get-started.md).

Mojo function

causal_conv1d_channel_last_fwd_cpu

causal_conv1d_channel_last_fwd_cpu[x_dtype: DType, weight_dtype: DType, output_dtype: DType, bias_dtype: DType](batch: Int, dim: Int, seqlen: Int, width: Int, x: TileTensor[x_dtype, address_space=x.address_space, linear_idx_type=x.linear_idx_type, element_size=x.element_size], weight: TileTensor[weight_dtype, address_space=weight.address_space, linear_idx_type=weight.linear_idx_type, element_size=weight.element_size], output: TileTensor[output_dtype, address_space=output.address_space, linear_idx_type=output.linear_idx_type, element_size=output.element_size], bias: TileTensor[bias_dtype, address_space=bias.address_space, linear_idx_type=bias.linear_idx_type, element_size=bias.element_size], x_batch_stride: UInt32, x_c_stride: UInt32, x_l_stride: UInt32, weight_c_stride: UInt32, weight_width_stride: UInt32, out_batch_stride: UInt32, out_c_stride: UInt32, out_l_stride: UInt32, silu_activation: Bool)

Optimized CPU implementation of causal conv1d for channel-last layout with bias.

Structured for potential SIMD optimizations. Currently similar to naive but organized for future vectorization improvements.

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