【发布时间】：2022-09-23 16:50:31
【问题描述】：
我正在尝试构建图像分类器 API。使用 Google Colab 构建模型，因为我没有 GPU。我正在使用 CPU 并将模型下载到 API 应用程序中。
但是当我尝试访问我的模型目录 Saved_Model 时出现此错误。 我知道这与 GPU 和 CUDA 设置有关，但我不知道什么是错误的，或者因为我使用 CPU 是如何排序的。
完全错误：
Elijah-A-W@DESKTOP-34M2E8U MINGW64 /d/myn/ML Prediction Project/New folder/Detection Potato Lite/Api
$ python main.py
2022-07-29 09:12:32.654485: W tensorflow/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library
\'cudart64_110.dll\'; dlerror: cudart64_110.dll not found
2022-07-29 09:12:32.670439: I tensorflow/stream_executor/cuda/cudart_stub.cc:29] Ignore above cudart dlerror if you do not
have a GPU set up on your machine.
2022-07-29 09:13:18.928444: W tensorflow/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library
\'nvcuda.dll\'; dlerror: nvcuda.dll not found
2022-07-29 09:13:18.928809: W tensorflow/stream_executor/cuda/cuda_driver.cc:269] failed call to cuInit: UNKNOWN ERROR (303)
2022-07-29 09:13:18.934497: I tensorflow/stream_executor/cuda/cuda_diagnostics.cc:169] retrieving CUDA diagnostic information for host: DESKTOP-34M2E8U
2022-07-29 09:13:18.935291: I tensorflow/stream_executor/cuda/cuda_diagnostics.cc:176] hostname: DESKTOP-34M2E8U
2022-07-29 09:13:19.068867: I tensorflow/core/platform/cpu_feature_guard.cc:193] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN) to use the following CPU instructions in performance-critical operations: AVX AVX2
To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.
Traceback (most recent call last):
File \"D:\\myn\\ML Prediction Project\\New folder\\Detection Potato Lite\\Api\\main.py\", line 10, in <module>
MODEL = tf.keras.models.load_model(\"../Saved_Model/1\")
File \"C:\\Users\\Elijah-A-W\\AppData\\Local\\Programs\\Python\\Python310\\lib\\site-packages\\keras\\utils\\traceback_utils.py\", line 67, in error_handler
raise e.with_traceback(filtered_tb) from None
File \"C:\\Users\\Elijah-A-W\\AppData\\Local\\Programs\\Python\\Python310\\lib\\site-packages\\tensorflow\\python\\saved_model\\load.py\", line 915, in load_partial
raise FileNotFoundError(
FileNotFoundError: Unsuccessful TensorSliceReader constructor: Failed to find any matching files for ../Saved_Model/1\\variables\\variables
You may be trying to load on a different device from the computational device. Consider setting the `experimental_io_device` option in `tf.saved_model.LoadOptions` to the io_device such as \'/job:localhost\'.
完整代码：
from fastapi import FastAPI, File, UploadFile
import uvicorn
import numpy as np
from io import BytesIO
from PIL import Image
import tensorflow as tf
app = FastAPI()
MODEL = tf.keras.models.load_model(\"../Saved_Model/1\")
CLASS_NAMES = [\"Early Blight\", \"Late Blight\", \"Healthy\"]
@app.get(\"/ping\")
async def ping():
return \"hello, I am alive\"
async def read_file_as_image(data) -> np.ndarray:
image = np.array(Image.open(BytesIO(data))) # reading an image as byte & converting into array
img_batch = np.expand_dims(image, 0) # adding extra dimesnion to the loaded img batch
prediction = MODEL.predict(img_batch) # calling the model predict the image batch
pass
@app.post(\"/predict\")
async def predict(file: UploadFile = File(...)):
image = read_file_as_image(await file.read())
return image
if __name__ == \"__main__\":
uvicorn.run(app, host=\'localhost\', port=5000)
这是项目目录的图像 [![在此处输入图像描述][1]][1]
标签： python gpu tensorflow2.0 fastapi