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[CLAP] Replace hard-coded batch size to enable dynamic ONNX export (#27790)

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* [CLAP] Replace hard-coded batch size to enable dynamic ONNX export

* Add back docstring
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Joshua Lochner 2023-12-09 11:39:39 +02:00 committed by GitHub
parent 80377eb018
commit ffd426eef8
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1 changed files with 5 additions and 5 deletions
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src/transformers/models/clap/modeling_clap.py
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@ -92,6 +92,7 @@ def window_partition(hidden_states, window_size):
# Adapted from https://github.com/LAION-AI/CLAP/blob/6ad05a971ba0622f6acee8c41993e0d02bbed639/src/open_clip/htsat.py#L263
def window_reverse(windows, window_size, height, width):
"""
Merges windows to produce higher resolution features.
Args:
windows (`torch.FloatTensor` of shape `(num_windows * batch_size, window_size, window_size, num_channels)`):
Input windows
@ -102,11 +103,10 @@ def window_reverse(windows, window_size, height, width):
width (`int`):
Width of the resized audio
"""
batch_size = int(windows.shape[0] / (height * width / window_size / window_size))
hidden_states = windows.view(batch_size, height // window_size, width // window_size, window_size, window_size, -1)
hidden_states = hidden_states.permute(0, 1, 3, 2, 4, 5).contiguous().view(batch_size, height, width, -1)
return hidden_states
num_channels = windows.shape[-1]
windows = windows.view(-1, height // window_size, width // window_size, window_size, window_size, num_channels)
windows = windows.permute(0, 1, 3, 2, 4, 5).contiguous().view(-1, height, width, num_channels)
return windows
# Copied from transformers.models.roberta.modeling_roberta.create_position_ids_from_input_ids