# all¶

paddle. all ( x, axis=None, keepdim=False, name=None ) [source]

Computes the `logical and` of tensor elements over the given dimension.

Parameters
• x (Tensor) – An N-D Tensor, the input data type should be bool.

• axis (int|list|tuple, optional) – The dimensions along which the `logical and` is compute. If `None`, and all elements of `x` and return a Tensor with a single element, otherwise must be in the range \([-rank(x), rank(x))\). If \(axis[i] < 0\), the dimension to reduce is \(rank + axis[i]\).

• keepdim (bool, optional) – Whether to reserve the reduced dimension in the output Tensor. The result Tensor will have one fewer dimension than the `x` unless `keepdim` is true, default value is False.

• name (str, optional) – Name for the operation (optional, default is None). For more information, please refer to Name.

Returns

Results the `logical and` on the specified axis of input Tensor x, it’s data type is bool.

Return type

Tensor

Examples

```import paddle

# x is a bool Tensor with following elements:
#    [[True, False]
#     [True, True]]
x = paddle.to_tensor([[1, 0], [1, 1]], dtype='int32')
print(x)

# out1 should be [False]
print(out1)

# out2 should be [True, False]
out2 = paddle.all(x, axis=0)  # [True, False]
print(out2)

# keepdim=False, out3 should be [False, True], out.shape should be (2,)
out3 = paddle.all(x, axis=-1)  # [False, True]
print(out3)

# keepdim=True, out4 should be [[False], [True]], out.shape should be (2,1)
out4 = paddle.all(x, axis=1, keepdim=True) # [[False], [True]]
print(out4)
```