I’ve been training an Image Classifier that can detect Oil and Pencil Paintings. While doing so I encountered a value error. I searched the web throughly unfortunately, I didn’t find any satisfactory answer as there was not much discussion about it.
Code:
import tensorflow as tf
import os
import matplotlib.pyplot as plt
gpus = tf.config.experimental.list_physical_devices('GPU')
for gpu in gpus:
tf.config.experimental.set_memory_growth(gpu, True)
len(gpus)
# Data Generator
IMAGE_SHAPE = (224, 224)
TRAINING_DATA = '/content/drive/MyDrive/Datasets/train'
VALID_DATA = '/content/drive/MyDrive/Datasets/test'
datagen = tf.keras.preprocessing.image.ImageDataGenerator(
rescale=1./225
)
train_generator = datagen.flow_from_directory(
TRAINING_DATA,
shuffle=True,
target_size=IMAGE_SHAPE,
)
valid_generator = datagen.flow_from_directory(
VALID_DATA,
shuffle=False,
target_size = IMAGE_SHAPE,
)
def build_model(num_classes):
model = tf.keras.Sequential([
tf.keras.layers.Conv2D(filters=8, kernel_size=(3,3), activation='relu',
input_shape=(224, 224, 3)),
tf.keras.layers.MaxPooling2D(pool_size=(2,2), strides=2),
tf.keras.layers.Conv2D(filters=16, kernel_size=(3,3), activation='relu'),
tf.keras.layers.MaxPooling2D(pool_size=(2, 2), strides=2),
tf.keras.layers.Conv2D(filters=32, kernel_size=(3, 3), activation='relu'),
tf.keras.layers.MaxPooling2D(pool_size=(2, 2), strides=2),
tf.keras.layers.Flatten(),
tf.keras.layers.Dense(64, activation='relu'),
tf.keras.layers.Dense(num_classes, activation='softmax')
])
return model
model = build_model(num_classes=2)
model.compile(
optimizer=tf.keras.optimizers.Adam(lr=0.0001),
loss=tf.keras.losses.CategoricalCrossentropy(from_logits=True),
metrics=['accuracy']
)
print(model.summary())
Error Code:
EPOCHS = 20
BATCH_SIZE = 32
history = model.fit(train_generator,
steps_per_epoch=train_generator.samples // BATCH_SIZE,
epochs=EPOCHS,
validation_data=valid_generator,
validation_steps=valid_generator.samples // BATCH_SIZE,
verbose=1
)
1393 logs = tf_utils.sync_to_numpy_or_python_type(logs)
1394 if logs is None:
-> 1395 raise ValueError('Unexpected result of `train_function` '
1396 '(Empty logs). Please use '
1397 '`Model.compile(..., run_eagerly=True)`, or '
ValueError: Unexpected result of `train_function` (Empty logs). Please use `Model.compile(..., run_eagerly=True)`, or `tf.config.run_functions_eagerly(True)` for more information of where went wrong, or file a issue/bug to `tf.keras`.
Can someone help to solve this problem? 