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tensorflow.python.framework.errors_impl.InvalidArgumentError in python code

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0

I was trying to add tensorboard to a sentdex tutorial, and got the error tensorflow.python.framework.errors_impl.InvalidArgumentError. I'm rather new to tensorflow so I don't know what's wrong.

import tensorflow as tf
from tensorflow.keras.models import Sequential
from tensorflow.keras.layers import Dense, Dropout, LSTM
from tensorflow.keras.callbacks import TensorBoard
import time

NAME = f"MNIST-time.time"

mnist = tf.keras.datasets.mnist

tensorboard = TensorBoard(log_dir='logs/'.format(NAME))

(x_train, y_train), (x_test, y_test) = mnist.load_data()

x_train = x_train/255
x_test = x_test/255

model = Sequential()

model.add(LSTM(128, input_shape=(x_train.shape[1:]), activation='relu', return_sequences=True))
model.add(Dropout(0.2))

model.add(LSTM(128, activation='relu'))
model.add(Dropout(0.2))

model.add(Dense(32, activation='relu'))
model.add(Dropout(0.2))

model.add(Dense(10, activation='softmax'))

opt = tf.keras.optimizers.Adam(lr=1e-3, decay=1e-5)

model.compile(loss='sparse_categorical_crossentropy', optimizer=opt, metrics=['accuracy'])

tensorboard = TensorBoard(log_dir=f'logs/NAME')
model.fit(x_train, y_train, epochs=2, validation_data=(x_test, y_test), callbacks = [tensorboard])

model.save('MNIST')

python-3.x tensorflow tf.keras

share|improve this question

asked Mar 24 at 15:32

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add a comment | 

0

I was trying to add tensorboard to a sentdex tutorial, and got the error tensorflow.python.framework.errors_impl.InvalidArgumentError. I'm rather new to tensorflow so I don't know what's wrong.

import tensorflow as tf
from tensorflow.keras.models import Sequential
from tensorflow.keras.layers import Dense, Dropout, LSTM
from tensorflow.keras.callbacks import TensorBoard
import time

NAME = f"MNIST-time.time"

mnist = tf.keras.datasets.mnist

tensorboard = TensorBoard(log_dir='logs/'.format(NAME))

(x_train, y_train), (x_test, y_test) = mnist.load_data()

x_train = x_train/255
x_test = x_test/255

model = Sequential()

model.add(LSTM(128, input_shape=(x_train.shape[1:]), activation='relu', return_sequences=True))
model.add(Dropout(0.2))

model.add(LSTM(128, activation='relu'))
model.add(Dropout(0.2))

model.add(Dense(32, activation='relu'))
model.add(Dropout(0.2))

model.add(Dense(10, activation='softmax'))

opt = tf.keras.optimizers.Adam(lr=1e-3, decay=1e-5)

model.compile(loss='sparse_categorical_crossentropy', optimizer=opt, metrics=['accuracy'])

tensorboard = TensorBoard(log_dir=f'logs/NAME')
model.fit(x_train, y_train, epochs=2, validation_data=(x_test, y_test), callbacks = [tensorboard])

model.save('MNIST')

python-3.x tensorflow tf.keras

share|improve this question

asked Mar 24 at 15:32

hacker HDhacker HD

156

add a comment | 

I was trying to add tensorboard to a sentdex tutorial, and got the error tensorflow.python.framework.errors_impl.InvalidArgumentError. I'm rather new to tensorflow so I don't know what's wrong.

import tensorflow as tf
from tensorflow.keras.models import Sequential
from tensorflow.keras.layers import Dense, Dropout, LSTM
from tensorflow.keras.callbacks import TensorBoard
import time

NAME = f"MNIST-time.time"

mnist = tf.keras.datasets.mnist

tensorboard = TensorBoard(log_dir='logs/'.format(NAME))

(x_train, y_train), (x_test, y_test) = mnist.load_data()

x_train = x_train/255
x_test = x_test/255

model = Sequential()

model.add(LSTM(128, input_shape=(x_train.shape[1:]), activation='relu', return_sequences=True))
model.add(Dropout(0.2))

model.add(LSTM(128, activation='relu'))
model.add(Dropout(0.2))

model.add(Dense(32, activation='relu'))
model.add(Dropout(0.2))

model.add(Dense(10, activation='softmax'))

opt = tf.keras.optimizers.Adam(lr=1e-3, decay=1e-5)

model.compile(loss='sparse_categorical_crossentropy', optimizer=opt, metrics=['accuracy'])

tensorboard = TensorBoard(log_dir=f'logs/NAME')
model.fit(x_train, y_train, epochs=2, validation_data=(x_test, y_test), callbacks = [tensorboard])

model.save('MNIST')

python-3.x tensorflow tf.keras

share|improve this question

asked Mar 24 at 15:32

hacker HDhacker HD

156

import tensorflow as tf
from tensorflow.keras.models import Sequential
from tensorflow.keras.layers import Dense, Dropout, LSTM
from tensorflow.keras.callbacks import TensorBoard
import time

NAME = f"MNIST-time.time"

mnist = tf.keras.datasets.mnist

tensorboard = TensorBoard(log_dir='logs/'.format(NAME))

(x_train, y_train), (x_test, y_test) = mnist.load_data()

x_train = x_train/255
x_test = x_test/255

model = Sequential()

model.add(LSTM(128, input_shape=(x_train.shape[1:]), activation='relu', return_sequences=True))
model.add(Dropout(0.2))

model.add(LSTM(128, activation='relu'))
model.add(Dropout(0.2))

model.add(Dense(32, activation='relu'))
model.add(Dropout(0.2))

model.add(Dense(10, activation='softmax'))

opt = tf.keras.optimizers.Adam(lr=1e-3, decay=1e-5)

model.compile(loss='sparse_categorical_crossentropy', optimizer=opt, metrics=['accuracy'])

tensorboard = TensorBoard(log_dir=f'logs/NAME')
model.fit(x_train, y_train, epochs=2, validation_data=(x_test, y_test), callbacks = [tensorboard])

model.save('MNIST')

share|improve this question

asked Mar 24 at 15:32

hacker HDhacker HD

156

share|improve this question

asked Mar 24 at 15:32

hacker HDhacker HD

156

asked Mar 24 at 15:32

hacker HDhacker HD

156

asked Mar 24 at 15:32

hacker HDhacker HD

156

1 Answer
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The problem was the time.time code did not have ().

share|improve this answer

answered Mar 24 at 18:20

hacker HDhacker HD

156

add a comment | 

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0

The problem was the time.time code did not have ().

share|improve this answer

answered Mar 24 at 18:20

hacker HDhacker HD

156

add a comment | 

0

The problem was the time.time code did not have ().

share|improve this answer

answered Mar 24 at 18:20

hacker HDhacker HD

156

add a comment | 

The problem was the time.time code did not have ().

share|improve this answer

answered Mar 24 at 18:20

hacker HDhacker HD

156

share|improve this answer

answered Mar 24 at 18:20

hacker HDhacker HD

156

answered Mar 24 at 18:20

hacker HDhacker HD

156

answered Mar 24 at 18:20

hacker HDhacker HD

156