fix(asr): repair ConvSubsampling forward paths missed by the MaskedConvSequential refactor - #16225
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…nvSequential refactor The MaskedConvSequential refactor left three ConvSubsampling paths broken: 1. `subsampling_conv_chunking_factor=-1` (chunking disabled, documented in the class docstring) falls into `x, lengths = self.conv(x)`, which calls MaskedConvSequential.forward without the required `lengths` argument and raises TypeError for every conv2d stack (vggnet, striding, dw_striding). 2. The 1-D stacks (striding_conv1d, dw_striding_conv1d, conv2d_subsampling=False) always take that same branch regardless of the chunking factor, so both variants raise TypeError on every forward pass. 3. For vggnet, `_forward_torch` reads `layer.kernel_size[0]` / `layer.stride[0]`, but nn.MaxPool2d stores the int values passed in (kernel_size=2, stride=2), so every vggnet forward raises TypeError: 'int' object is not subscriptable. _layer_padding has the same problem with the int `padding`. Once the int access works, the length update must also honor MaxPool2d's ceil_mode=True, which calculate_conv_output_size's floor division ignores. Fixes: - ConvSubsampling.forward: pass `lengths` to the masked stack when chunking is disabled; run 1-D stacks as a plain sequential (MaskedConvSequential.forward accepts lengths=None for exactly this) and report the precomputed out_lengths. - _forward_torch: read kernel/stride/padding via a _pair_first helper that tolerates int attributes, and add the ceil-mode remainder frame when a pooling layer runs with ceil_mode=True. Adds CPU unit tests for all three paths; each fails with TypeError or wrong lengths on the unfixed code. The chunking=-1 path is asserted to match the default (chunked) path bit-for-bit, and conv1d/vggnet lengths are asserted against calc_length references. Signed-off-by: Manohar Paturi <186662190+ManoharPaturi@users.noreply.github.com>
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Fixes #16223.
Three repairs to paths the MaskedConvSequential refactor (#13827) missed:
MaskedConvSequential.forwardtakes optionallengths; 1-D stacks without length-aware layers just pass them throughConvSubsampling.forwardnow forwardslengthstoself.conv(...)in the non-chunked / conv1d branch (theelsethat previously calledself.conv(x))_layer_paddinghandlesnn.MaxPool2dstoring int kernel/stride/padding (via a_pair_firsthelper) and accounts for the extra frameceil_mode=Truecan addsubsampling_conv_chunking_factor=-1verified bit-identical to the default path for striding/dw_striding/vggnet at factors 4 and 8. 14 new CPU tests — all fail on main, pass here.