# reduce_mean¶

dragon.vm.tensorflow.math.reduce_mean(
input_tensor,
axis=None,
keepdims=False,
name=None
)[source]

Compute the mean value of elements along the given axis.

The argument axis could be negative or None:

x = tf.constant([[1, 2, 3], [4, 5, 6]])

# A negative axis is the last-k axis
print(tf.math.reduce_mean(x, 1))
print(tf.math.reduce_mean(x, -1))  # Equivalent

# If axis is None, the vector-style reduction
# will be applied to return a scalar result
print(tf.math.reduce_mean(x))  # Result is 3

# Also, axis could be a sequence of integers
print(tf.math.reduce_mean(x, [0, 1]))  # Result is 3

Parameters:
• input_tensor (dragon.Tensor) – The input tensor.
• axis (Union[int, Sequence[int]], optional) – The axis to reduce.
• keepdims (bool, optional, default=False) – Keep the reduced dimensions or not.
• name (str, optional) – A optional name for the operation.
Returns:

dragon.Tensor – The output tensor.