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Fix docstring of CLIP model #523

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Fix docstring of CLIP model #523

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3 changes: 2 additions & 1 deletion torchmultimodal/models/clip/image_encoder.py
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Expand Up @@ -235,7 +235,8 @@ class ResNetForCLIP(nn.Module):
- The final pooling layer is a QKV attention instead of an average pool.
Args:
layers (Tuple[int]):
layers (Tuple[int]): number of residual blocks in each stage.
of the ResNet architecture
output_dim (int): dimension of output tensor
heads (int): number of heads in the attention pooling layer
input_resolution (int): resolution of image input to encoder
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2 changes: 1 addition & 1 deletion torchmultimodal/models/clip/text_encoder.py
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Expand Up @@ -21,7 +21,7 @@ class CLIPTextEncoder(nn.Module):
Args:
embedding_dim (int): Embedding dimension for text and image encoders projections.
context_length (int): Maximum sequence length for Transforer.
context_length (int): Maximum sequence length for Transformer.
vocab_size (int): Vocab size.
width (int): Embedding dimension for Transformer encoder.
dim_feedforward (int): Dimension of the feedfoward networks.
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