137 lines
4.3 KiB
Python
137 lines
4.3 KiB
Python
import subprocess
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import argparse
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import ast
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TEMPLATE = """
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# Supported Models and Hardware
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Text Generation Inference enables serving optimized models on specific hardware for the highest performance. The following sections list which models are hardware are supported.
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## Supported Models
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SUPPORTED_MODELS
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If the above list lacks the model you would like to serve, depending on the model's pipeline type, you can try to initialize and serve the model anyways to see how well it performs, but performance isn't guaranteed for non-optimized models:
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```python
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# for causal LMs/text-generation models
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AutoModelForCausalLM.from_pretrained(<model>, device_map="auto")`
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# or, for text-to-text generation models
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AutoModelForSeq2SeqLM.from_pretrained(<model>, device_map="auto")
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```
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If you wish to serve a supported model that already exists on a local folder, just point to the local folder.
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```bash
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text-generation-launcher --model-id <PATH-TO-LOCAL-BLOOM>
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```
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"""
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def check_cli(check: bool):
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output = subprocess.check_output(["text-generation-launcher", "--help"]).decode(
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"utf-8"
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)
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wrap_code_blocks_flag = "<!-- WRAP CODE BLOCKS -->"
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final_doc = f"# Text-generation-launcher arguments\n\n{wrap_code_blocks_flag}\n\n"
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lines = output.split("\n")
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header = ""
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block = []
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for line in lines:
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if line.startswith(" -") or line.startswith(" -"):
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rendered_block = "\n".join(block)
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if header:
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final_doc += f"## {header}\n```shell\n{rendered_block}\n```\n"
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else:
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final_doc += f"```shell\n{rendered_block}\n```\n"
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block = []
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tokens = line.split("<")
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if len(tokens) > 1:
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header = tokens[-1][:-1]
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else:
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header = line.split("--")[-1]
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header = header.upper().replace("-", "_")
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block.append(line)
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rendered_block = "\n".join(block)
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final_doc += f"## {header}\n```shell\n{rendered_block}\n```\n"
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block = []
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filename = "docs/source/basic_tutorials/launcher.md"
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if check:
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with open(filename, "r") as f:
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doc = f.read()
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if doc != final_doc:
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tmp = "launcher.md"
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with open(tmp, "w") as g:
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g.write(final_doc)
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diff = subprocess.run(
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["diff", tmp, filename], capture_output=True
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).stdout.decode("utf-8")
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print(diff)
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raise Exception(
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"Cli arguments Doc is not up-to-date, run `python update_doc.py` in order to update it"
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)
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else:
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with open(filename, "w") as f:
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f.write(final_doc)
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def check_supported_models(check: bool):
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filename = "server/text_generation_server/models/__init__.py"
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with open(filename, "r") as f:
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tree = ast.parse(f.read())
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enum_def = [
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x for x in tree.body if isinstance(x, ast.ClassDef) and x.name == "ModelType"
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][0]
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_locals = {}
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_globals = {}
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exec(f"import enum\n{ast.unparse(enum_def)}", _globals, _locals)
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ModelType = _locals["ModelType"]
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list_string = ""
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for data in ModelType:
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list_string += f"- [{data.value['name']}]({data.value['url']})"
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if data.value.get("multimodal", None):
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list_string += " (Multimodal)"
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list_string += "\n"
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final_doc = TEMPLATE.replace("SUPPORTED_MODELS", list_string)
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filename = "docs/source/supported_models.md"
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if check:
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with open(filename, "r") as f:
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doc = f.read()
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if doc != final_doc:
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tmp = "supported.md"
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with open(tmp, "w") as g:
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g.write(final_doc)
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diff = subprocess.run(
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["diff", tmp, filename], capture_output=True
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).stdout.decode("utf-8")
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print(diff)
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raise Exception(
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"Supported models is not up-to-date, run `python update_doc.py` in order to update it"
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)
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else:
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with open(filename, "w") as f:
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f.write(final_doc)
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def main():
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parser = argparse.ArgumentParser()
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parser.add_argument("--check", action="store_true")
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args = parser.parse_args()
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check_cli(args.check)
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check_supported_models(args.check)
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if __name__ == "__main__":
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main()
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