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run.py
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# Copyright 2024 Google LLC
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
import argparse
import contextlib
import random
import numpy as np
import torch
from gemma import config
from gemma import model as gemma_model
@contextlib.contextmanager
def _set_default_tensor_type(dtype: torch.dtype):
"""Sets the default torch dtype to the given dtype."""
torch.set_default_dtype(dtype)
yield
torch.set_default_dtype(torch.float)
def main(args):
# Construct the model config.
model_config = config.get_model_config(args.variant)
model_config.dtype = "float32" if args.device == "cpu" else "float16"
model_config.quant = args.quant
# Seed random.
random.seed(args.seed)
np.random.seed(args.seed)
torch.manual_seed(args.seed)
# Create the model and load the weights.
device = torch.device(args.device)
with _set_default_tensor_type(model_config.get_dtype()):
model = gemma_model.GemmaForCausalLM(model_config)
model.load_weights(args.ckpt)
model = model.to(device).eval()
print("Model loading done")
# Generate the response.
result = model.generate(args.prompt, device)
# Print the prompts and results.
print('======================================')
print(f'PROMPT: {args.prompt}')
print(f'RESULT: {result}')
print('======================================')
if __name__ == "__main__":
parser = argparse.ArgumentParser()
parser.add_argument("--ckpt", type=str, required=True)
parser.add_argument("--variant",
type=str,
default="2b",
choices=["2b", "7b"])
parser.add_argument("--device",
type=str,
default="cpu",
choices=["cpu", "cuda"])
parser.add_argument("--output_len", type=int, default=4)
parser.add_argument("--seed", type=int, default=12345)
parser.add_argument("--quant", action='store_true')
parser.add_argument("--prompt", type=str, default="The meaning of life is")
args = parser.parse_args()
main(args)