patrickvonplaten
commited on
Commit
•
7a9344a
1
Parent(s):
f5c87bd
add model
Browse files- config.json +30 -0
- model/merges.txt +0 -0
- model/special_tokens_map.json +1 -0
- model/tokenizer_config.json +1 -0
- model/vocab.json +0 -0
- run.sh +1 -1
- run_model.py +32 -8
config.json
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{
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"activation_dropout": 0.0,
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"activation_function": "relu",
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"architectures": [
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"OPTModel"
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],
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"attention_dropout": 0.0,
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"bos_token_id": 0,
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"d_model": 4096,
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"decoder_layernorm": false,
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"decoder_start_token_id": 2,
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"dropout": 0.1,
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"eos_token_id": 2,
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"ffn_dim": 16384,
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"init_std": 0.02,
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"layerdrop": 0.0,
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"max_position_embeddings": 2048,
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"model_type": "opt",
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"num_attention_heads": 32,
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"num_hidden_layers": 32,
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"output_projection": true,
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"pad_token_id": 1,
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"scale_embedding": false,
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"share_input_output_embed": true,
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"torch_dtype": "float16",
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"transformers_version": "4.19.0.dev0",
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"use_cache": false,
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"vocab_size": 50272,
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"word_embed_proj_dim": 4096
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}
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model/merges.txt
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model/special_tokens_map.json
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{"bos_token": {"content": "<|endoftext|>", "single_word": false, "lstrip": false, "rstrip": false, "normalized": true}, "eos_token": {"content": "<|endoftext|>", "single_word": false, "lstrip": false, "rstrip": false, "normalized": true}, "unk_token": {"content": "<|endoftext|>", "single_word": false, "lstrip": false, "rstrip": false, "normalized": true}}
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model/tokenizer_config.json
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{"errors": "replace", "unk_token": {"content": "<|endoftext|>", "single_word": false, "lstrip": false, "rstrip": false, "normalized": true, "__type": "AddedToken"}, "bos_token": {"content": "<|endoftext|>", "single_word": false, "lstrip": false, "rstrip": false, "normalized": true, "__type": "AddedToken"}, "eos_token": {"content": "<|endoftext|>", "single_word": false, "lstrip": false, "rstrip": false, "normalized": true, "__type": "AddedToken"}, "add_prefix_space": false, "tokenizer_class": "GPT2Tokenizer"}
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model/vocab.json
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run.sh
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#!/usr/bin/env bash
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CUDA_VISIBLE_DEVICES="0" torchrun run_model.py --pipeline-model-parallel-size 1 --tensor-model-parallel-size 1
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#!/usr/bin/env bash
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CUDA_VISIBLE_DEVICES="0,3" torchrun run_model.py --pipeline-model-parallel-size 1 --tensor-model-parallel-size 1
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run_model.py
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#!/usr/bin/env python3
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#!/usr/bin/env python3
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import os
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from transformers import AutoTokenizer, GPT2Tokenizer
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from megatron.initialize import initialize_megatron
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from metaseq import checkpoint_utils
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import torch
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path = "./model"
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)
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model = checkpoint[0][0].eval()
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model = model.cuda
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# forward passes
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def single_batch_forward_logits(prompts):
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input_ids = tokenizer(prompts, return_tensors="pt").input_ids
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input_ids = torch.cat([torch.tensor([[0]]), input_ids], dim=-1)
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input_ids = input_ids.cuda
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with torch.no_grad():
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logits = model(input_ids)[0]
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return logits
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prompts = [
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-
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-
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]
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print("Next word generation")
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for prompt in prompts:
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print("-------------")
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print(f"Prompt: {prompt}...\n")
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-
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pred_next_token = torch.argmax(logits[0, -1], -1)
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next_token = tokenizer.convert_ids_to_tokens([pred_next_token])
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next_token = next_token[0].replace("Ġ", "")
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print(f"Next word: {next_token}")
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print("-------------")
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#!/usr/bin/env python3
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import os
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from transformers import AutoTokenizer, GPT2Tokenizer
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from megatron.initialize import initialize_megatron
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from metaseq import checkpoint_utils
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from transformers import OPTForCausalLM
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import torch
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path = "./model"
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)
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model = checkpoint[0][0].eval()
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model = model.to("cuda:0").half()
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hf_model = OPTForCausalLM.from_pretrained("../opt-6.7b").to("cuda:1").half()
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# forward passes
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def single_batch_forward_logits(prompts):
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input_ids = tokenizer(prompts, return_tensors="pt").input_ids
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input_ids = torch.cat([torch.tensor([[0]]), input_ids], dim=-1)
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input_ids = input_ids.to("cuda:0")
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with torch.no_grad():
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logits = model(input_ids)[0]
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return logits
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# forward hf
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def forward_hf(prompts):
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input_ids = tokenizer(prompts, return_tensors="pt").input_ids
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input_ids = torch.cat([torch.tensor([[0]]), input_ids], dim=-1)
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input_ids = input_ids.to("cuda:1")
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with torch.no_grad():
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logits = hf_model(input_ids)[0]
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return logits
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prompts = [
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"Today is a beautiful day and I want to",
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"In the city of",
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"Paris is the capital of France and",
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"Computers and mobile phones have taken",
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]
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prompts = [
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"Today is a beautiful day and I want to",
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]
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#import ipdb; ipdb.set_trace()
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print("Next word generation")
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for prompt in prompts:
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print("-------------")
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print(f"Prompt: {prompt}...\n")
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logits_fsq = single_batch_forward_logits(prompt)
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pred_next_token = torch.argmax(logits_fsq[0, -1], -1)
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next_token = tokenizer.convert_ids_to_tokens([pred_next_token])
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next_token = next_token[0].replace("Ġ", "")
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print(f"Next word: {next_token}")
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print("-------------")
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logits = forward_hf(prompt)
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pred_next_token = torch.argmax(logits[0, -1], -1)
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next_token = tokenizer.convert_ids_to_tokens([pred_next_token])
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next_token = next_token[0].replace("Ġ", "")
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print(f"Next word: {next_token}")
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print("-------------")
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torch.allclose(logits_fsq.cpu(), logits.cpu(), atol=1e-3)
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