Dev (#148)

* Create publish-docker-images.yaml

* Add copilot_proxy publishing

* Add model_converter publishing

* Use dockerhub version

* Do not login for PRs

* Overwrite some of labels value

* Move ignore files to the root of `context`

* Add comments & fix some issue

* Fix typos

* Remove the target of the master branch

* Delete .dockerignore

* Delete .dockerignore

* Add Flake8

* Add Flake8 and format code accordingly

* Iterate on the PR template, fix the token for the contributor action

* Remove converter image build

* Update Dockerfile of proxy

* Comment out proxy image in compose

Co-authored-by: Fred de Gier <freddegier@me.com>

* Fix build action

---------

Co-authored-by: Rowe Wilson Frederisk Holme <frederisk@outlook.com>

.github/PULL_REQUEST_TEMPLATE.md

@@ -1,18 +1,12 @@
 ---
-# [Template] PR Description
-
-In general, the github system duplicates your commit message automatically for your convenience.
-After composing your own PR description using this template, please remove any unneeded portions.
-```bash
 ## 1. General Description
-The commit title must begin with one of the eleven given options.
-Build, chore, CI, documentation, task, fix, performance, refactor, revert, style, and test are some examples. 
-or more details, please see [HERE](https://www.conventionalcommits.org/en/v1.0.0/).
-Summarize changes in no more than 50 characters ASAP for readability and maintenance.
+<!-- Describe what this PR intents to do -->
+
 
 ## 2. Changes proposed in this PR:
- - Bulleted lists are also acceptable. 
- - Typically, a hyphen or asterisk before the bullet, followed by a single space.
+<!-- Bulleted lists are also acceptable. Typically, a hyphen or asterisk before the bullet, followed by a single space.-->
+1.
+1.
 
 Resolves: #{GitHub-Issue-Number}
 See also: #{GitHub-Issue-Number}
@@ -20,8 +14,9 @@ See also: #{GitHub-Issue-Number}
 
 ## 3. How to evaluate:
 1. Describe how to evaluate such that it may be reproduced by the reviewer (s).
-2. Self assessment:**
- - Build test: [ ]Passed [ ]Failed [*]Skipped
- - Run test: [ ]Passed [ ]Failed [* ]Skipped
-```
-
+    1.
+    1.
+    1.
+1. Self assessment:
+ - [ ] Successfully build locally `docker-compose build`:
+ - [ ] Successfully tested the full solution locally

.github/workflows/lint.yml

@@ -0,0 +1,17 @@
+name: flake8 Lint
+
+on: [push, pull_request]
+
+jobs:
+  flake8-lint:
+    runs-on: ubuntu-latest
+    name: Lint
+    steps:
+      - name: Check out source repository
+        uses: actions/checkout@v3
+      - name: Set up Python environment
+        uses: actions/setup-python@v4
+        with:
+          python-version: "3.10"
+      - name: flake8 Lint
+        uses: py-actions/flake8@v2

.github/workflows/publish-docker-images.yaml

@@ -0,0 +1,94 @@
+name: Publish Docker Images
+
+on:
+  # `push` will build and public the image with a tag corresponding to the branch name (such as `main`, `master`).
+  # `push tag` will build and public the image with a tag has the same name as git tag (such as `v1.2.3`, `v0.0.1-alpha.1`) and a tag named `latest`.
+  push:
+    branches: [main]
+  # `pull request` will only build to test the image, not publish.
+  pull_request:
+    # The branches below must be a subset of the branches above.
+    branches: [main]
+  # `release publish` is almost the same as `push tag`.
+  release:
+    types: [published]
+
+jobs:
+  publish_copilot_proxy:
+    name: Publish copilot_proxy
+    # The `-latest` runner images are the latest **stable** images that GitHub provides.
+    # Here it is equivalent to `ubuntu-20.04`.
+    runs-on: ubuntu-latest
+
+    steps:
+      - name: Checkout repository
+        uses: actions/checkout@v3
+
+      - name: Extract Docker metadata
+        uses: docker/metadata-action@v4
+        with:
+          # Define image name
+          images: moyix/copilot_proxy
+          # Overwrite labels
+          labels: |
+            org.opencontainers.image.title=CopilotProxy
+            org.opencontainers.image.description=A simple proxy that enables triton to send back copilot compatible communication content.
+            org.opencontainers.image.url=https://github.com/moyix/fauxpilot/tree/main/copilot_proxy
+            org.opencontainers.image.source=https://github.com/moyix/fauxpilot/tree/main/copilot_proxy
+
+      - name: Login to Docker Hub
+        # Do not login for PRs
+        if: github.event_name != 'pull_request'
+        uses: docker/login-action@v2
+        with:
+          username: ${{ secrets.DOCKERHUB_USERNAME }}
+          password: ${{ secrets.DOCKERHUB_TOKEN }}
+
+      - name: Build and push images
+        uses: docker/build-push-action@v3
+        with:
+          # For PRs, just build and not push.
+          push: ${{ github.event_name != 'pull_request' }}
+          context: .
+          file: proxy.Dockerfile
+          tags: ${{ steps.meta.outputs.tags }}
+          labels: ${{ steps.meta.outputs.labels }}
+
+  # publish_model_converter:
+  #   name: Publish model_converter
+  #   # The `-latest` runner images are the latest **stable** images that GitHub provides.
+  #   # Here it is equivalent to `ubuntu-20.04`.
+  #   runs-on: ubuntu-latest
+
+  #   steps:
+  #     - name: Checkout repository
+  #       uses: actions/checkout@v3
+
+  #     - name: Extract Docker metadata
+  #       uses: docker/metadata-action@v4
+  #       with:
+  #         # Define image name
+  #         images: moyix/model_converter
+  #         # Overwrite labels
+  #         labels: |
+  #           org.opencontainers.image.title=ModelConverter
+  #           org.opencontainers.image.description=Convert the model to GPT-J to adapt the FasterTransformer Backend.
+  #           org.opencontainers.image.url=https://github.com/moyix/fauxpilot/tree/main/converter
+  #           org.opencontainers.image.source=https://github.com/moyix/fauxpilot/tree/main/converter
+
+  #     - name: Login to Docker Hub
+  #       # Do not login for PRs.
+  #       if: github.event_name != 'pull_request'
+  #       uses: docker/login-action@v2
+  #       with:
+  #         username: ${{ secrets.DOCKERHUB_USERNAME }}
+  #         password: ${{ secrets.DOCKERHUB_TOKEN }}
+
+  #     - name: Build and push images
+  #       uses: docker/build-push-action@v3
+  #       with:
+  #         # For PRs, just build and not push.
+  #         push: ${{ github.event_name != 'pull_request' }}
+  #         context: ./converter
+  #         tags: ${{ steps.meta.outputs.tags }}
+  #         labels: ${{ steps.meta.outputs.labels }}

.github/workflows/welcome-new-contributor.yml

@@ -13,7 +13,7 @@ jobs:
       - name: 'Greet the contributor'
         uses: garg3133/welcome-new-contributors@v1.2
         with:
-          token: ${{ secrets.BOT_ACCESS_TOKEN }}
+          token: ${{ secrets.GITHUB_TOKEN }}
           is-oauth-token: true
           issue-message: 'Hello there, thanks for opening your first issue. We
 welcome you to the FauxPilot community!'

converter/codegen_gptj_convert.py

@@ -4,14 +4,14 @@ import argparse
 import torch
 from transformers import GPTJForCausalLM, GPTJConfig
 # Note: these need the git version of Transformers as of 7/22/2022
-from transformers import CodeGenTokenizer, CodeGenForCausalLM
+from transformers import CodeGenTokenizer, CodeGenForCausalLM  # noqa: F401
 from transformers import CODEGEN_PRETRAINED_MODEL_ARCHIVE_LIST
 
 parser = argparse.ArgumentParser('Convert SalesForce CodeGen model to GPT-J')
 parser.add_argument('--code_model',
                     choices=CODEGEN_PRETRAINED_MODEL_ARCHIVE_LIST, default='Salesforce/codegen-350M-multi',
                     help='which SalesForce model to convert'
-)
+                    )
 parser.add_argument('output_dir', help='where to store the converted model')
 args = parser.parse_args()
 
@@ -47,13 +47,16 @@ config.tokenizer_class = 'CodeGenTokenizer'
 gptj_model = GPTJForCausalLM(config).half()
 embed_dim = config.n_embd
 
-def replace(model, weights, name):
-    model.state_dict()[name].copy_(weights.detach())
+
+def replace(model, weights, model_name):
+    model.state_dict()[model_name].copy_(weights.detach())
+
 
 def replace_by_name(dest_model, src_model, old_name, new_name):
     assert old_name in src_model.state_dict()
     assert new_name in dest_model.state_dict()
-    replace(dest_model, src_model.state_dict()[old_name], new_name)
+    replace(model=dest_model, weights=src_model.state_dict()[old_name], model_name=new_name)
+
 
 print('Converting...')
 # Copy weights from CodeGen model
@@ -72,9 +75,9 @@ with torch.no_grad():
             # After a great deal of pain, I figured out that this permutation on
             # the weights of the qkv_proj fixes it.
             base_permutation = [0, 3, 6, 9, 1, 4, 7, 10, 2, 5, 8, 11]
-            permutation = torch.cat([torch.arange(i*local_dim, (i+1)*local_dim) for i in base_permutation])
+            permutation = torch.cat([torch.arange(i * local_dim, (i + 1) * local_dim) for i in base_permutation])
             # NB: we permute the *rows* here because the computation is xA.T
-            new_qkv_proj = qkv_proj[permutation,:]
+            new_qkv_proj = qkv_proj[permutation, :]
             # NB: the name QKV is misleading here; they are actually stored in
             #     the order QVK
             query, value, key = torch.split(new_qkv_proj, embed_dim, dim=0)
@@ -82,7 +85,7 @@ with torch.no_grad():
             replace(gptj_model, key, name.replace('qkv_proj', 'k_proj'))
             replace(gptj_model, value, name.replace('qkv_proj', 'v_proj'))
         else:
-            replace_by_name(gptj_model, cg_model, name, name)
+            replace_by_name(dest_model=gptj_model, src_model=cg_model, old_name=name, new_name=name)
 
     print('Conversion complete.')
     print(f"Saving model to {args.output_dir}...")

converter/huggingface_gptj_convert.py

@@ -23,10 +23,12 @@ import torch
 import os
 import sys
 from transformers import GPTJForCausalLM
+
 dir_path = os.path.dirname(os.path.realpath(__file__))
 sys.path.append(dir_path + "/../../../..")
 sys.path.append(dir_path)
 
+
 def get_weight_data_type(data_type):
     if data_type == "fp32":
         return np.float32
@@ -35,8 +37,8 @@ def get_weight_data_type(data_type):
     else:
         assert False, f"Invalid weight data type {data_type}"
 
-def split_and_convert_process(i, saved_dir,factor,key,args, val):
 
+def split_and_convert_process(i, saved_dir, factor, key, val):
     if key.find("input_layernorm.weight") != -1 or key.find("input_layernorm.bias") != -1 or \
             key.find("attention.dense.bias") != -1 or key.find("post_attention_layernorm.weight") != -1 or \
             key.find("post_attention_layernorm.bias") != -1 or key.find("mlp.dense_4h_to_h.bias") != -1 or \
@@ -70,16 +72,16 @@ def split_and_convert_process(i, saved_dir,factor,key,args, val):
     else:
         print("[ERROR] cannot find key '{}'".format(key))
 
+
 def split_and_convert(args):
     saved_dir = args.saved_dir + "/%d-gpu/" % args.infer_gpu_num
 
-    if(os.path.exists(saved_dir) == False):
+    if os.path.exists(saved_dir) is False:
         os.makedirs(saved_dir)
-    ckpt_name = args.in_file
 
     t_gpu_num = args.trained_gpu_num
     i_gpu_num = args.infer_gpu_num
-    assert(i_gpu_num % t_gpu_num == 0)
+    assert (i_gpu_num % t_gpu_num == 0)
 
     factor = (int)(i_gpu_num / t_gpu_num)
 
@@ -93,10 +95,10 @@ def split_and_convert(args):
         for k, v in vars(model.config).items():
             config["gpt"][k] = f"{v}"
         config["gpt"]["weight_data_type"] = args.weight_data_type
-        with open((Path(saved_dir) / f"config.ini").as_posix(), 'w') as configfile:
+        with open((Path(saved_dir) / "config.ini").as_posix(), 'w') as configfile:
             config.write(configfile)
-    except:
-        print(f"Fail to save the config in config.ini.")
+    except Exception:
+        print("Fail to save the config in config.ini.")
     np_weight_data_type = get_weight_data_type(args.weight_data_type)
 
     huggingface_model_name_pattern = [
@@ -130,9 +132,11 @@ def split_and_convert(args):
         if name == 'transformer.wte.weight':
             param.detach().cpu().numpy().astype(np_weight_data_type).tofile(saved_dir + "model.wte.bin")
         elif name == 'transformer.ln_f.bias':
-            param.detach().cpu().numpy().astype(np_weight_data_type).tofile(saved_dir + "model.final_layernorm.bias.bin")
+            param.detach().cpu().numpy().astype(np_weight_data_type).tofile(
+                saved_dir + "model.final_layernorm.bias.bin")
         elif name == 'transformer.ln_f.weight':
-            param.detach().cpu().numpy().astype(np_weight_data_type).tofile(saved_dir + "model.final_layernorm.weight.bin")
+            param.detach().cpu().numpy().astype(np_weight_data_type).tofile(
+                saved_dir + "model.final_layernorm.weight.bin")
         elif name == 'lm_head.weight':
             param.detach().cpu().numpy().astype(np_weight_data_type).tofile(saved_dir + "model.lm_head.weight.bin")
         elif name == 'lm_head.bias':
@@ -156,12 +160,12 @@ def split_and_convert(args):
                         weights = param.detach().cpu().numpy().astype(np_weight_data_type)
 
                     # Some weights need to be transposed
-                    if name.find("mlp.fc_in.weight") != -1 or \
-                        name.find("mlp.fc_out.weight") != -1 or \
+                    if name.find("mlp.fc_in.weight") != -1 or name.find("mlp.fc_out.weight") != -1 or \
                             name.find("attn.out_proj.weight") != -1:
                         weights = weights.T
 
-                    new_name = name.replace("transformer.h.", "layers.").replace(huggingface_model_name_pattern[i], ft_model_name_pattern[i])
+                    new_name = name.replace("transformer.h.", "layers.").replace(huggingface_model_name_pattern[i],
+                                                                                 ft_model_name_pattern[i])
 
                     pool.starmap(split_and_convert_process,
                                  [(0, saved_dir, factor, new_name, args,
@@ -170,14 +174,17 @@ def split_and_convert(args):
     pool.close()
     pool.join()
 
+
 if __name__ == "__main__":
     parser = argparse.ArgumentParser(formatter_class=argparse.RawTextHelpFormatter)
     parser.add_argument('-saved_dir', '-o', type=str, help='file name of output file', required=True)
     parser.add_argument('-in_file', '-i', type=str, help='HF model name or directory', required=True)
     parser.add_argument('-trained_gpu_num', '-t_g', type=int, help='How many gpus for training', default=1)
     parser.add_argument('-infer_gpu_num', '-i_g', type=int, help='How many gpus for inference', required=True)
-    parser.add_argument("-processes", "-p", type=int, help="How many processes to spawn for conversion (default: 4)", default=4)
-    parser.add_argument("-weight_data_type", type=str, default="fp32", choices=["fp32", "fp16"], help="output weight data type")
+    parser.add_argument("-processes", "-p", type=int, help="How many processes to spawn for conversion (default: 4)",
+                        default=4)
+    parser.add_argument("-weight_data_type", type=str, default="fp32", choices=["fp32", "fp16"],
+                        help="output weight data type")
 
     args = parser.parse_args()
     print("\n=============== Argument ===============")

converter/triton_config_gen.py

@@ -6,10 +6,12 @@ from string import Template
 from transformers import GPTJConfig, AutoTokenizer
 import torch
 
+
 def round_up(x, multiple):
     remainder = x % multiple
     return x if remainder == 0 else x + multiple - remainder
 
+
 SCRIPT_DIR = os.path.dirname(os.path.realpath(__file__))
 CONFIG_TEMPLATE_PATH = os.path.join(SCRIPT_DIR, 'config_template.pbtxt')
 

copilot_proxy/app.py

@@ -27,6 +27,7 @@ app = FastAPI(
     swagger_ui_parameters={"defaultModelsExpandDepth": -1}
 )
 
+
 @app.exception_handler(FauxPilotException)
 async def fauxpilot_handler(request: Request, exc: FauxPilotException):
     return JSONResponse(
@@ -34,6 +35,7 @@ async def fauxpilot_handler(request: Request, exc: FauxPilotException):
         content=exc.json()
     )
 
+
 # Used to support copilot.vim
 @app.get("/copilot_internal/v2/token")
 def get_copilot_token():
@@ -43,6 +45,7 @@ def get_copilot_token():
         content=content
     )
 
+
 @app.post("/v1/engines/codegen/completions")
 # Used to support copilot.vim
 @app.post("/v1/engines/copilot-codex/completions")

copilot_proxy/models.py

@@ -2,9 +2,11 @@ from typing import Optional, Union
 
 from pydantic import BaseModel, constr
 
+ModelType = constr(regex="^(fastertransformer|py-model)$")
+
 
 class OpenAIinput(BaseModel):
-    model: constr(regex="^(fastertransformer|py-model)$") = "fastertransformer"
+    model: ModelType = "fastertransformer"
     prompt: Optional[str]
     suffix: Optional[str]
     max_tokens: Optional[int] = 16
@@ -20,4 +22,3 @@ class OpenAIinput(BaseModel):
     best_of: Optional[int] = 1
     logit_bias: Optional[dict]
     user: Optional[str]
-

copilot_proxy/utils/errors.py

@@ -1,10 +1,12 @@
-from typing import *
+from typing import Optional
+
 
 class FauxPilotException(Exception):
-    def __init__(self, message: str, type: Optional[str] = None, param: Optional[str] = None, code: Optional[int] = None):
+    def __init__(self, message: str, error_type: Optional[str] = None, param: Optional[str] = None,
+                 code: Optional[int] = None):
         super().__init__(message)
         self.message = message
-        self.type = type
+        self.error_type = error_type
         self.param = param
         self.code = code
 
@@ -12,7 +14,7 @@ class FauxPilotException(Exception):
         return {
             'error': {
                 'message': self.message,
-                'type': self.type,
+                'type': self.error_type,
                 'param': self.param,
                 'code': self.code
             }

docker-compose.yaml

@@ -23,7 +23,6 @@ services:
   copilot_proxy:
     # For dockerhub version
     # image: moyix/copilot_proxy:latest
-    # command: python3 -m flask run --host=0.0.0.0 --port=5000
     # For local build
     build:
       context: .

setup.cfg

@@ -0,0 +1,3 @@
+[flake8]
+max-line-length = 120
+exclude = venv

tests/python_backend/test_setup.py

@@ -27,6 +27,7 @@ def setup_module():
     if root.joinpath(".env").exists():
         shutil.move(str(root.joinpath(".env")), str(root.joinpath(".env.bak")))
 
+
 def teardown_module():
     """
     Teardown steps for tests in this module
@@ -43,6 +44,7 @@ def teardown_module():
             f"Exception: {exc}"
         )
 
+
 def enter_input(proc: pexpect.spawn, expect: str, input_s: str, timeout: int = 5) -> str:
     """
     Helper function to enter input for a given prompt. Returns consumed output.
@@ -61,6 +63,7 @@ def enter_input(proc: pexpect.spawn, expect: str, input_s: str, timeout: int = 5
     proc.sendline(input_s)
     return after
 
+
 def run_common_setup_steps(n_gpus: int = 0) -> pexpect.spawn:
     """
     Helper function to run common setup steps.
@@ -78,6 +81,7 @@ def run_common_setup_steps(n_gpus: int = 0) -> pexpect.spawn:
 
     return proc
 
+
 def load_test_env():
     """
     Load test env vars
@@ -90,6 +94,7 @@ def load_test_env():
             env[key] = val
     return env
 
+
 def run_inference(
     prompt: str, model: str = "py-model", port: int = 5000, return_all: bool = False,
     **kwargs