Add contributing guideline and mypy config (#122)
This commit is contained in:
@@ -168,8 +168,8 @@ class GPT2Model(nn.Module):
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def forward(
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self,
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input_ids: torch.LongTensor,
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position_ids: torch.LongTensor,
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input_ids: torch.Tensor,
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position_ids: torch.Tensor,
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kv_caches: List[KVCache],
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input_metadata: InputMetadata,
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cache_events: Optional[List[torch.cuda.Event]],
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@@ -204,8 +204,8 @@ class GPT2LMHeadModel(nn.Module):
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def forward(
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self,
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input_ids: torch.LongTensor,
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positions: torch.LongTensor,
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input_ids: torch.Tensor,
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positions: torch.Tensor,
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kv_caches: List[KVCache],
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input_metadata: InputMetadata,
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cache_events: Optional[List[torch.cuda.Event]],
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@@ -67,7 +67,7 @@ class GPTNeoXAttention(nn.Module):
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def forward(
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self,
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position_ids: torch.LongTensor,
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position_ids: torch.Tensor,
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hidden_states: torch.Tensor,
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kv_cache: KVCache,
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input_metadata: InputMetadata,
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@@ -118,7 +118,7 @@ class GPTNeoXLayer(nn.Module):
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def forward(
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self,
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position_ids: torch.LongTensor,
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position_ids: torch.Tensor,
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hidden_states: torch.Tensor,
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kv_cache: KVCache,
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input_metadata: InputMetadata,
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@@ -162,8 +162,8 @@ class GPTNeoXModel(nn.Module):
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def forward(
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self,
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input_ids: torch.LongTensor,
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position_ids: torch.LongTensor,
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input_ids: torch.Tensor,
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position_ids: torch.Tensor,
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kv_caches: List[KVCache],
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input_metadata: InputMetadata,
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cache_events: Optional[List[torch.cuda.Event]],
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@@ -199,8 +199,8 @@ class GPTNeoXForCausalLM(nn.Module):
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def forward(
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self,
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input_ids: torch.LongTensor,
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positions: torch.LongTensor,
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input_ids: torch.Tensor,
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positions: torch.Tensor,
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kv_caches: List[KVCache],
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input_metadata: InputMetadata,
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cache_events: Optional[List[torch.cuda.Event]],
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@@ -109,7 +109,7 @@ class LlamaAttention(nn.Module):
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def forward(
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self,
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positions: torch.LongTensor,
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positions: torch.Tensor,
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hidden_states: torch.Tensor,
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kv_cache: KVCache,
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input_metadata: InputMetadata,
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@@ -143,7 +143,7 @@ class LlamaDecoderLayer(nn.Module):
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def forward(
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self,
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positions: torch.LongTensor,
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positions: torch.Tensor,
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hidden_states: torch.Tensor,
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kv_cache: KVCache,
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input_metadata: InputMetadata,
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@@ -184,8 +184,8 @@ class LlamaModel(nn.Module):
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def forward(
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self,
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input_ids: torch.LongTensor,
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positions: torch.LongTensor,
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input_ids: torch.Tensor,
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positions: torch.Tensor,
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kv_caches: List[KVCache],
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input_metadata: InputMetadata,
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cache_events: Optional[List[torch.cuda.Event]],
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@@ -222,8 +222,8 @@ class LlamaForCausalLM(nn.Module):
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def forward(
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self,
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input_ids: torch.LongTensor,
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positions: torch.LongTensor,
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input_ids: torch.Tensor,
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positions: torch.Tensor,
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kv_caches: List[KVCache],
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input_metadata: InputMetadata,
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cache_events: Optional[List[torch.cuda.Event]],
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@@ -47,7 +47,7 @@ class OPTLearnedPositionalEmbedding(nn.Embedding):
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self.offset = 2
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super().__init__(num_embeddings + self.offset, embedding_dim)
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def forward(self, positions: torch.LongTensor):
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def forward(self, positions: torch.Tensor):
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return super().forward(positions + self.offset)
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@@ -199,8 +199,8 @@ class OPTDecoder(nn.Module):
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def forward(
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self,
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input_ids: torch.LongTensor,
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positions: torch.LongTensor,
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input_ids: torch.Tensor,
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positions: torch.Tensor,
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kv_caches: List[KVCache],
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input_metadata: InputMetadata,
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cache_events: Optional[List[torch.cuda.Event]],
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@@ -235,8 +235,8 @@ class OPTModel(nn.Module):
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def forward(
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self,
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input_ids: torch.LongTensor,
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positions: torch.LongTensor,
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input_ids: torch.Tensor,
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positions: torch.Tensor,
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kv_caches: List[KVCache],
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input_metadata: InputMetadata,
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cache_events: Optional[List[torch.cuda.Event]],
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@@ -258,8 +258,8 @@ class OPTForCausalLM(nn.Module):
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def forward(
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self,
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input_ids: torch.LongTensor,
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positions: torch.LongTensor,
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input_ids: torch.Tensor,
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positions: torch.Tensor,
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kv_caches: List[KVCache],
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input_metadata: InputMetadata,
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cache_events: Optional[List[torch.cuda.Event]],
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