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| author | Jan Buethe <jbuethe@amazon.de> | 2023-12-07 22:40:22 +0300 |
|---|---|---|
| committer | Jean-Marc Valin <jmvalin@amazon.com> | 2023-12-20 07:01:22 +0300 |
| commit | e21026d90967c2958e16182cbca5aa58ff770095 (patch) | |
| tree | 2d8022dec0c5cc2e1bc9f85e0a64f63293e674a9 | |
| parent | f16640a205eb863a1f5af638138db6d00efd38dd (diff) | |
removed debug prints
| -rw-r--r-- | dnn/torch/weight-exchange/wexchange/torch/torch.py | 2 |
1 files changed, 0 insertions, 2 deletions
diff --git a/dnn/torch/weight-exchange/wexchange/torch/torch.py b/dnn/torch/weight-exchange/wexchange/torch/torch.py index a3c3fbdc..00a1a4bb 100644 --- a/dnn/torch/weight-exchange/wexchange/torch/torch.py +++ b/dnn/torch/weight-exchange/wexchange/torch/torch.py @@ -63,12 +63,10 @@ def dump_torch_adaptive_conv1d_weights(where, adaconv, name='adaconv', scale=1/1 if quantize and kernel_size % 8: kernel_padding = 8 - (kernel_size % 8) - print(f"{w_kernel.shape=}") w_kernel = np.concatenate( (np.zeros((out_channels, in_channels, kernel_padding, feature_dim)), w_kernel.reshape(out_channels, in_channels, kernel_size, feature_dim)), dtype=w_kernel.dtype, axis=2).reshape(-1, feature_dim) - print(f"{w_kernel.shape=}") b_kernel = np.concatenate( (np.zeros((out_channels, in_channels, kernel_padding)), b_kernel.reshape(out_channels, in_channels, kernel_size)), dtype=b_kernel.dtype, |