TypeError: bad operand type for unary -: 'ReplicatedVariable', When i use tf.keras.layers.PReLU
Multi tool use
I'm converting an SRGAN keras model that will run on a GPU to run on a TPU.
The SRGAN uses a PReLU activation and when I use tf.keras.layers.PReLU in my functional API
x = layers.PReLU(alpha_initializer = 'zeros', alpha_regularizer = None, alpha_constraint = None, shared_axes=[1,2])(x)
I get the following TypeError when I Fit the model using the TPU
TypeError: bad operand type for unary -: 'ReplicatedVariable'
If I swap the PReLU layer with:
x = tf.Activations('relu')(x)
the error goes away.
Has anyone seen this problem? I think it might be related the call function of the PReLU class:
@tf_export('keras.layers.PReLU')
Class PReLU(layer):
...
def call(self, inputs, mask=None):
...
else:
neg = -self.alpha * K.relu(-inputs)
desktop-computer
asked Jan 23 at 23:33
user989129user989129
61
add a comment |
I'm converting an SRGAN keras model that will run on a GPU to run on a TPU.
The SRGAN uses a PReLU activation and when I use tf.keras.layers.PReLU in my functional API
x = layers.PReLU(alpha_initializer = 'zeros', alpha_regularizer = None, alpha_constraint = None, shared_axes=[1,2])(x)
I get the following TypeError when I Fit the model using the TPU
TypeError: bad operand type for unary -: 'ReplicatedVariable'
If I swap the PReLU layer with:
x = tf.Activations('relu')(x)
the error goes away.
Has anyone seen this problem? I think it might be related the call function of the PReLU class:
@tf_export('keras.layers.PReLU')
Class PReLU(layer):
...
def call(self, inputs, mask=None):
...
else:
neg = -self.alpha * K.relu(-inputs)
desktop-computer
asked Jan 23 at 23:33
user989129user989129
61
add a comment |
I'm converting an SRGAN keras model that will run on a GPU to run on a TPU.
The SRGAN uses a PReLU activation and when I use tf.keras.layers.PReLU in my functional API
x = layers.PReLU(alpha_initializer = 'zeros', alpha_regularizer = None, alpha_constraint = None, shared_axes=[1,2])(x)
I get the following TypeError when I Fit the model using the TPU
TypeError: bad operand type for unary -: 'ReplicatedVariable'
If I swap the PReLU layer with:
x = tf.Activations('relu')(x)
the error goes away.
Has anyone seen this problem? I think it might be related the call function of the PReLU class:
@tf_export('keras.layers.PReLU')
Class PReLU(layer):
...
def call(self, inputs, mask=None):
...
else:
neg = -self.alpha * K.relu(-inputs)
desktop-computer
asked Jan 23 at 23:33
user989129user989129
61
I'm converting an SRGAN keras model that will run on a GPU to run on a TPU.
The SRGAN uses a PReLU activation and when I use tf.keras.layers.PReLU in my functional API
x = layers.PReLU(alpha_initializer = 'zeros', alpha_regularizer = None, alpha_constraint = None, shared_axes=[1,2])(x)
I get the following TypeError when I Fit the model using the TPU
TypeError: bad operand type for unary -: 'ReplicatedVariable'
If I swap the PReLU layer with:
x = tf.Activations('relu')(x)
the error goes away.
Has anyone seen this problem? I think it might be related the call function of the PReLU class:
@tf_export('keras.layers.PReLU')
Class PReLU(layer):
...
def call(self, inputs, mask=None):
...
else:
neg = -self.alpha * K.relu(-inputs)
desktop-computer
desktop-computer
asked Jan 23 at 23:33
user989129user989129
61
asked Jan 23 at 23:33
user989129user989129
61
asked Jan 23 at 23:33
user989129user989129
61
asked Jan 23 at 23:33
user989129user989129
61
asked Jan 23 at 23:33
user989129user989129
61
61
add a comment |
add a comment |
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