Commit
•
49422ae
1
Parent(s):
64cf789
added support for text-generation pipeline
Browse files- config.json +2 -1
- modeling_decilm.py +9 -10
- version_check.py +3 -3
config.json
CHANGED
@@ -25,5 +25,6 @@
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"use_bfloat16": true,
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"transformers_version": "4.35.2",
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"use_cache": true,
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-
"vocab_size": 32000
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}
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"use_bfloat16": true,
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"transformers_version": "4.35.2",
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"use_cache": true,
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"vocab_size": 32000,
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"tokenizer_class": "LlamaTokenizer"
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}
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modeling_decilm.py
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@@ -1,5 +1,5 @@
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# coding=utf-8
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# Copyright and license
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""" PyTorch DeciLM model."""
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from .version_check import check_transformers_version
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@@ -11,18 +11,18 @@ import torch
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import torch.nn.functional as F
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import torch.utils.checkpoint
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from torch import nn
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from .transformers_v4_35_2__modeling_llama import LlamaMLP, LlamaRMSNorm, LlamaAttention, apply_rotary_pos_emb, \
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repeat_kv, LlamaPreTrainedModel, LLAMA_START_DOCSTRING, LlamaDecoderLayer, LlamaForCausalLM, LlamaModel, \
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BaseModelOutputWithPast, LLAMA_INPUTS_DOCSTRING
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from .transformers_v4_35_2__modeling_attn_mask_utils import _prepare_4d_causal_attention_mask
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from transformers.utils import add_start_docstrings, add_start_docstrings_to_model_forward, logging
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from .configuration_decilm import DeciLMConfig
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logger = logging.get_logger(__name__)
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_CONFIG_FOR_DOC = "DeciLMConfig"
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class DeciLMAttention(LlamaAttention):
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@@ -61,7 +61,7 @@ class DeciLMAttention(LlamaAttention):
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past_key_value: Optional[Tuple[torch.Tensor]] = None,
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output_attentions: bool = False,
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use_cache: bool = False,
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) -> Tuple[torch.Tensor, Optional[torch.Tensor], Optional[Tuple[torch.Tensor]]]:
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bsz, q_len, _ = hidden_states.size()
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is_decode = past_key_value is not None
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@@ -135,8 +135,7 @@ class DeciLMAttention(LlamaAttention):
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else:
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attn_output = self.o_proj(attn_output)
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attn_weights = None
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return attn_output, attn_weights, past_key_value
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# coding=utf-8
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# Copyright and license in the repo.
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""" PyTorch DeciLM model."""
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from .version_check import check_transformers_version
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import torch.nn.functional as F
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import torch.utils.checkpoint
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from torch import nn
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from transformers.models.auto.modeling_auto import MODEL_FOR_CAUSAL_LM_MAPPING_NAMES
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from transformers.utils import add_start_docstrings, add_start_docstrings_to_model_forward, logging
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from .configuration_decilm import DeciLMConfig
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from .transformers_v4_35_2__modeling_attn_mask_utils import _prepare_4d_causal_attention_mask
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from .transformers_v4_35_2__modeling_llama import LlamaMLP, LlamaRMSNorm, LlamaAttention, apply_rotary_pos_emb, \
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repeat_kv, LlamaPreTrainedModel, LLAMA_START_DOCSTRING, LlamaDecoderLayer, LlamaForCausalLM, LlamaModel, \
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BaseModelOutputWithPast, LLAMA_INPUTS_DOCSTRING
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MODEL_FOR_CAUSAL_LM_MAPPING_NAMES["deci"] = "DeciLMForCausalLM"
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_CONFIG_FOR_DOC = "DeciLMConfig"
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logger = logging.get_logger(__name__)
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class DeciLMAttention(LlamaAttention):
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past_key_value: Optional[Tuple[torch.Tensor]] = None,
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output_attentions: bool = False,
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use_cache: bool = False,
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**kwargs,
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) -> Tuple[torch.Tensor, Optional[torch.Tensor], Optional[Tuple[torch.Tensor]]]:
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bsz, q_len, _ = hidden_states.size()
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is_decode = past_key_value is not None
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else:
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attn_output = self.o_proj(attn_output)
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attn_weights = None
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return attn_output, attn_weights, past_key_value
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version_check.py
CHANGED
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import transformers
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from packaging import version
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def check_transformers_version():
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if version.parse(transformers.__version__) < version.parse(
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raise ImportError(
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f"You are using transformers=={transformers.__version__}, but transformers>={
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)
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import transformers
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from packaging import version
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MIN_VERSION = "4.35.2"
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def check_transformers_version():
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if version.parse(transformers.__version__) < version.parse(MIN_VERSION):
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raise ImportError(
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f"You are using transformers=={transformers.__version__}, but transformers>={MIN_VERSION} is required to use DeciLM. Please upgrade transformers."
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)
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