how to resolve tensors contains Nan or inf values error in tensorflow?
def ActivityNetV3(n_sensors, window_size): #inputs = Input(shape=(n_sensors, window_size, 1)) inputs = Input(shape=(n_sensors, window_size, 1)) print(“Inside the model”) print(inputs.shape) x = Conv2D( filters=1, kernel_size=(1, 1), weights=[np.array([[[[1.0]]]])], padding=’same’, activation=None, trainable=False, use_bias=False, )(inputs) x = BatchNormalization(center=False, scale=True,epsilon=1e-5)(x) x = ZeroPadding2D(padding=((0,0),(1,1)))(x) # (inputs) x = Conv2D( 32, kernel_size=(n_sensors, tconfig.KERNEL_SIZE), strides=1, padding=”valid”, use_bias=False, name=”Conv00″, )(x) x = BatchNormalization( name=”Conv00/BatchNorm” )(x) x […]
how to resolve tensors contains Nan or inf values error in tensorflow?
def ActivityNetV3(n_sensors, window_size): #inputs = Input(shape=(n_sensors, window_size, 1)) inputs = Input(shape=(n_sensors, window_size, 1)) print(“Inside the model”) print(inputs.shape) x = Conv2D( filters=1, kernel_size=(1, 1), weights=[np.array([[[[1.0]]]])], padding=’same’, activation=None, trainable=False, use_bias=False, )(inputs) x = BatchNormalization(center=False, scale=True,epsilon=1e-5)(x) x = ZeroPadding2D(padding=((0,0),(1,1)))(x) # (inputs) x = Conv2D( 32, kernel_size=(n_sensors, tconfig.KERNEL_SIZE), strides=1, padding=”valid”, use_bias=False, name=”Conv00″, )(x) x = BatchNormalization( name=”Conv00/BatchNorm” )(x) x […]