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How to use a TF metric with a model?
The Next CEO of Stack Overflow2019 Community Moderator ElectionHow to use lists in Tensorflow?Is it possible to use grayscale images to existing model?How to speed-up trained Tensorflow model with FC layers for productionHow to Save TensorFlow model using estimator.export_savemodel()Custom conditional Keras metricCan I create pretrain model with tensorflow?Why is my Keras model not learning image segmentation?Tensorflow tf.divide how to useHow to run a saved TensorFlow Model? (Video Prediction Model)How to develop custom metric with one class priority Keras
$begingroup$
I am trying to compile a simple model and the following works just fine:
model.compile(optimizer=tf.train.AdamOptimizer(0.001),
loss='categorical_crossentropy',
metrics=['accuracy'])
However, I would like to use this metric: tf.metrics.precision_at_k and I am not sure how I can get it to work. It requires two arguments and that is causing an issue as I don't know how to pass predictions as an argument. I tried a
model.compile(optimizer=tf.train.AdamOptimizer(0.001),
loss='categorical_crossentropy',
metrics=[tf.metrics.precision_at_k])
And certain variations but did not help.
Minimal working code:
import tensorflow as tf
from tensorflow.keras import layers
model = tf.keras.Sequential([
tf.keras.layers.Conv2D(32, (3,3), padding='same', activation=tf.nn.relu, input_shape=(5, 5, 1)),
tf.keras.layers.MaxPooling2D((2, 2), strides=2),
tf.keras.layers.Flatten(),
tf.keras.layers.Dense(128, activation=tf.nn.relu),
tf.keras.layers.Dense(2, activation=tf.nn.softmax)
])
deep-learning tensorflow
asked Mar 22 at 17:12
ste_kwrste_kwr
1063
New contributor
ste_kwr is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
$endgroup$
add a comment |
$begingroup$
I am trying to compile a simple model and the following works just fine:
model.compile(optimizer=tf.train.AdamOptimizer(0.001),
loss='categorical_crossentropy',
metrics=['accuracy'])
However, I would like to use this metric: tf.metrics.precision_at_k and I am not sure how I can get it to work. It requires two arguments and that is causing an issue as I don't know how to pass predictions as an argument. I tried a
model.compile(optimizer=tf.train.AdamOptimizer(0.001),
loss='categorical_crossentropy',
metrics=[tf.metrics.precision_at_k])
And certain variations but did not help.
Minimal working code:
import tensorflow as tf
from tensorflow.keras import layers
model = tf.keras.Sequential([
tf.keras.layers.Conv2D(32, (3,3), padding='same', activation=tf.nn.relu, input_shape=(5, 5, 1)),
tf.keras.layers.MaxPooling2D((2, 2), strides=2),
tf.keras.layers.Flatten(),
tf.keras.layers.Dense(128, activation=tf.nn.relu),
tf.keras.layers.Dense(2, activation=tf.nn.softmax)
])
deep-learning tensorflow
asked Mar 22 at 17:12
ste_kwrste_kwr
1063
New contributor
ste_kwr is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
$endgroup$
add a comment |
$begingroup$
I am trying to compile a simple model and the following works just fine:
model.compile(optimizer=tf.train.AdamOptimizer(0.001),
loss='categorical_crossentropy',
metrics=['accuracy'])
However, I would like to use this metric: tf.metrics.precision_at_k and I am not sure how I can get it to work. It requires two arguments and that is causing an issue as I don't know how to pass predictions as an argument. I tried a
model.compile(optimizer=tf.train.AdamOptimizer(0.001),
loss='categorical_crossentropy',
metrics=[tf.metrics.precision_at_k])
And certain variations but did not help.
Minimal working code:
import tensorflow as tf
from tensorflow.keras import layers
model = tf.keras.Sequential([
tf.keras.layers.Conv2D(32, (3,3), padding='same', activation=tf.nn.relu, input_shape=(5, 5, 1)),
tf.keras.layers.MaxPooling2D((2, 2), strides=2),
tf.keras.layers.Flatten(),
tf.keras.layers.Dense(128, activation=tf.nn.relu),
tf.keras.layers.Dense(2, activation=tf.nn.softmax)
])
deep-learning tensorflow
asked Mar 22 at 17:12
ste_kwrste_kwr
1063
New contributor
ste_kwr is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
$endgroup$
I am trying to compile a simple model and the following works just fine:
model.compile(optimizer=tf.train.AdamOptimizer(0.001),
loss='categorical_crossentropy',
metrics=['accuracy'])
However, I would like to use this metric: tf.metrics.precision_at_k and I am not sure how I can get it to work. It requires two arguments and that is causing an issue as I don't know how to pass predictions as an argument. I tried a
model.compile(optimizer=tf.train.AdamOptimizer(0.001),
loss='categorical_crossentropy',
metrics=[tf.metrics.precision_at_k])
And certain variations but did not help.
Minimal working code:
import tensorflow as tf
from tensorflow.keras import layers
model = tf.keras.Sequential([
tf.keras.layers.Conv2D(32, (3,3), padding='same', activation=tf.nn.relu, input_shape=(5, 5, 1)),
tf.keras.layers.MaxPooling2D((2, 2), strides=2),
tf.keras.layers.Flatten(),
tf.keras.layers.Dense(128, activation=tf.nn.relu),
tf.keras.layers.Dense(2, activation=tf.nn.softmax)
])
deep-learning tensorflow
deep-learning tensorflow
asked Mar 22 at 17:12
ste_kwrste_kwr
1063
New contributor
ste_kwr is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
asked Mar 22 at 17:12
ste_kwrste_kwr
1063
New contributor
ste_kwr is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
edited Mar 22 at 19:39
ste_kwr
asked Mar 22 at 17:12
ste_kwrste_kwr
1063
New contributor
ste_kwr is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
asked Mar 22 at 17:12
ste_kwrste_kwr
1063
asked Mar 22 at 17:12
ste_kwrste_kwr
1063
1063
New contributor
ste_kwr is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
New contributor
ste_kwr is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
ste_kwr is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
add a comment |
add a comment |
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