Could not load library cudnn_cnn_infer64_8.dll. Error code 126
Please make sure cudnn_cnn_infer64_8.dll is in your library path!
I keep getting this error when I try to use TensorFlow with GPU, I've installed CUDA, cuDNN, and all the drivers multiple times according to the instructions. But nothing seems to work. If I use notebook then TensorFlow uses the CPU, with VS code notebook extension i can use the gpu but it stops the session at 1st epoch, when I tried to run it as a normal python file. the above error occurred.
Complete terminal output:
Found 14630 validated image filenames belonging to 3 classes.
Found 1500 validated image filenames belonging to 3 classes.
2021-11-08 11:03:58.000354: I tensorflow/core/platform/cpu_feature_guard.cc:151] 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.
2021-11-08 11:03:58.603592: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1525] Created device /job:localhost/replica:0/task:0/device:GPU:0 with 2775 MB memory: -> device: 0, name: NVIDIA GeForce GTX 1050 Ti, pci bus id: 0000:01:00.0, compute capability: 6.1
Epoch 1/10
2021-11-08 11:04:07.306011: I tensorflow/stream_executor/cuda/cuda_dnn.cc:366] Loaded cuDNN version 8300
Could not load library cudnn_cnn_infer64_8.dll. Error code 126
Please make sure cudnn_cnn_infer64_8.dll is in your library path!
E:\MyWorkSpace\animal_detect>
The code snippet:
import tensorflow as tf
from tensorflow.keras.preprocessing.image import ImageDataGenerator
from tensorflow.keras import layers
from tensorflow.keras import Model
from tensorflow.keras.preprocessing.image import ImageDataGenerator
from tensorflow.keras.applications.vgg16 import VGG16
import pandas as pd
import numpy as np
train_df = pd.read_csv('train.csv')
test_df = pd.read_csv('test.csv')
train_gen = ImageDataGenerator(rescale = 1./255.,rotation_range = 40, width_shift_range = 0.2, height_shift_range = 0.2, shear_range = 0.2, zoom_range = 0.2, horizontal_flip = True)
test_gen = ImageDataGenerator( rescale = 1.0/255. )
train_set = train_gen.flow_from_dataframe(train_df,x_col='loc',y_col='label',batch_size=20,target_size=(224,224))
test_set = train_gen.flow_from_dataframe(test_df,x_col='loc',y_col='label',batch_size=20,target_size=(224,224))
base_model = VGG16(input_shape = (224, 224, 3),
include_top = False,
weights = 'imagenet')
for layer in base_model.layers:
layer.trainable = False
x = layers.Flatten()(base_model.output)
x = layers.Dense(512, activation='relu')(x)
x = layers.Dropout(0.5)(x)
x = layers.Dense(3, activation='sigmoid')(x)
model = tf.keras.models.Model(base_model.input, x)
model.compile(optimizer = tf.keras.optimizers.RMSprop(learning_rate=0.0001), loss = 'categorical_crossentropy',metrics = ['acc'])
vgghist = model.fit(train_set, validation_data = test_set, steps_per_epoch = 100, epochs = 10)
the same code has been used for Jupyter-notebook, VS code notebook extension and as a normal python file
Device specifications:
processor: Intel i5 gpu: Nvidia Geforce 1050ti
Cuda version: 11.5 cuDNN version: 8.3
The error is not specific to a Gen application. In general, reason code 126 "Failed to load DLL <module>" means "The specified module could not be found": https://docs.microsoft.com/en-us/windows/win32/debug/system-error-codes--0-499-
For those still having this issue, please make sure you also have completed this step:
Download, unzip and add zlibwapi.dll
to your system path.
I wasted half an hour with this so you don't have to do it too. Good luck!
The same "errors" as me. Even though I have re-compiled the tensorflow-gpu 2.6.0 with "Cuda version: 11.5 cuDNN version: 8.3". The "errors" disappeared when I changed cudnn version to 8.2 but kept cuda version as 11.5. (Re-compiled is als needed) So I think this error must on "cuDNN".
Please See androidu's answer. It worked perfectly.
If you love us? You can donate to us via Paypal or buy me a coffee so we can maintain and grow! Thank you!
Donate Us With