colossalai.nn.layer.colossalai_layer

class colossalai.nn.layer.colossalai_layer.Linear(in_features, out_features, bias=True, dtype=None, weight_initializer=<function kaiming_uniform_.<locals>.initializer>, bias_initializer=<function xavier_uniform_.<locals>.initializer>, **kwargs)

Linear layer of colossalai

Parameters

  • in_features (int) – size of each input sample

  • out_features (int) – size of each output sample

  • bias (bool, optional) – If set to False, the layer will not learn an additive bias, defaults to True

  • dtype (torch.dtype, optional) – The dtype of parameters, defaults to None

  • weight_initializer (Callable, optional) – The intializer of weight, defaults to kaiming uniform initializer

  • bias_initializer (Callable, optional) – The intializer of bias, defaults to xavier uniform initializer

  • kwargs – Kwargs used for particular parallelisms

class colossalai.nn.layer.colossalai_layer.Classifier(in_features, num_classes, weight=None, bias=True, dtype=None, weight_initializer=<function kaiming_uniform_.<locals>.initializer>, bias_initializer=<function xavier_uniform_.<locals>.initializer>, vocab_parallel_limit=2048)

Classifier layer of colossalai

Parameters

  • in_features (int) – size of each input sample

  • num_classes (int) – number of total classes for the dataset

  • bias (bool, optional) – If set to False, the layer will not learn an additive bias, defaults to True

  • dtype (torch.dtype, optional) – The dtype of parameters, defaults to None

  • weight_initializer (Callable, optional) – The intializer of weight, defaults to kaiming uniform initializer

  • bias_initializer (Callable, optional) – The intializer of bias, defaults to xavier uniform initializer

class colossalai.nn.layer.colossalai_layer.Embedding(num_embeddings, embedding_dim, padding_idx=None, dtype=None, weight_initializer=<function normal_.<locals>.initializer>, vocab_parallel_limit=2048, *args, **kwargs)

Embedding for colossalai

Parameters

  • num_embeddings (int) – number of embeddings

  • embedding_dim (int) – dimension of embedding

  • padding_idx (int, optional) – index of padding, defaults to None

  • dtype (torch.dtype, optional) – The dtype of parameters, defaults to None

  • weight_initializer (Callable, optional) – The intializer of weight, defaults to normal initializer

  • args – Args used in F.embedding

  • kwargs – Kwargs used in F.embedding

class colossalai.nn.layer.colossalai_layer.PatchEmbedding(img_size, patch_size, in_chans, embed_size, dtype=None, flatten=True, weight_initializer=<function kaiming_uniform_.<locals>.initializer>, bias_initializer=<function xavier_uniform_.<locals>.initializer>, position_embed_initializer=<function zeros_.<locals>.initializer>)

2D Image to Patch Embedding

Parameters

  • img_size (int) – image size

  • patch_size (int) – patch size

  • in_chans (int) – number of channels of input image

  • embed_size (int) – size of embedding

  • dtype (torch.dtype, optional) – The dtype of parameters, defaults to None

  • flatten (bool, optional) – whether to flatten output tensor, defaults to True

  • weight_initializer (Callable, optional) – The intializer of weight, defaults to kaiming uniform initializer

  • bias_initializer (Callable, optional) – The intializer of bias, defaults to xavier uniform initializer

  • position_embed_initializer (Callable, optional) – The intializer of position embedding, defaults to zero

class colossalai.nn.layer.colossalai_layer.LayerNorm(normalized_shape, eps=1e-05, dtype=None)

Layer Normalization for colossalai

Parameters

  • normalized_shape (int) – input shape from an expected input of size. \([* \times \text{normalized_shape}[0] \times \text{normalized_shape}[1] \times \ldots \times \text{normalized_shape}[-1]]\) If a single integer is used, it is treated as a singleton list, and this module will normalize over the last dimension which is expected to be of that specific size.

  • eps (float, optional) – a value added to the denominator for numerical stability, defaults to 1e-05

  • dtype (torch.dtype, optional) – The dtype of parameters, defaults to None

class colossalai.nn.layer.colossalai_layer.Dropout(p=0.5, inplace=False)

Dropout layer of colossalai

Parameters

  • p (float, optional) – dropout rate, defaults to 0.5

  • inplace (bool, optional) – If set to True, will do this operation in-place, defaults tp False