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| author | Jean-Marc Valin <jmvalin@amazon.com> | 2023-11-15 12:08:50 +0300 |
|---|---|---|
| committer | Jean-Marc Valin <jmvalin@amazon.com> | 2023-11-15 12:08:50 +0300 |
| commit | b0620c0bf9864d9b18ead6b4bb6e0800542a931d (patch) | |
| tree | ea669c2226514d7f91989080fe2954623cbe83a8 /dnn/torch/lpcnet/utils | |
| parent | 58923f61c26ac0f5d8284d427344466e3bc2c674 (diff) | |
Using sparse GRUs in DRED decoder
Saves ~270 kB of weights in the decoder
Diffstat (limited to 'dnn/torch/lpcnet/utils')
| -rw-r--r-- | dnn/torch/lpcnet/utils/sparsification/common.py | 4 |
1 files changed, 2 insertions, 2 deletions
diff --git a/dnn/torch/lpcnet/utils/sparsification/common.py b/dnn/torch/lpcnet/utils/sparsification/common.py index 43fb28d4..2600cd01 100644 --- a/dnn/torch/lpcnet/utils/sparsification/common.py +++ b/dnn/torch/lpcnet/utils/sparsification/common.py @@ -29,7 +29,7 @@ import torch -def sparsify_matrix(matrix : torch.tensor, density : float, block_size : list[int, int], keep_diagonal : bool=False, return_mask : bool=False): +def sparsify_matrix(matrix : torch.tensor, density : float, block_size, keep_diagonal : bool=False, return_mask : bool=False): """ sparsifies matrix with specified block size Parameters: @@ -118,4 +118,4 @@ def calculate_gru_flops_per_step(gru, sparsification_dict=dict(), drop_input=Fal # activations estimated by 10 flops per activation flops += 30 * hidden_size - return flops
\ No newline at end of file + return flops |