tensorflow_tutorials/deep_mnist/deep_mnist.py
def connected_layer(cls, weight_shape, bias_shape, pool_shape, inputs):
        """Return a new connected layer."""
        weights = cls.weight_variable(weight_shape)
        bias = cls.bias_variable(bias_shape)
        pool = tf.reshape(inputs, pool_shape)

        return tf.nn.relu(tf.matmul(pool, weights) + bias)
Return a new connected layer.
Return a new connected layer.
Return a new connected layer .
def connected_layer(cls, weight_shape, bias_shape, pool_shape, inputs):
        weights = cls.weight_variable(weight_shape)
        bias = cls.bias_variable(bias_shape)
        pool = tf.reshape(inputs, pool_shape)
        return tf.nn.relu(tf.matmul(pool, weights) + bias)
def connected_layer ( cls , weight_shape , bias_shape , pool_shape , inputs ) : weights = cls . weight_variable ( weight_shape ) bias = cls . bias_variable ( bias_shape ) pool = tf . reshape ( inputs , pool_shape ) return tf . nn . relu ( tf . matmul ( pool , weights ) + bias )
Return a new connected layer.
Return a new connected layer .
"""Return a new connected layer."""
cls
weight_shape
bias_shape
pool_shape
inputs