Python tensorflow.python.ops.gen_math_ops._any() Examples
The following are 5
code examples of tensorflow.python.ops.gen_math_ops._any().
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Example #1
| Source File: math_ops.py From deep_image_model with Apache License 2.0 | 5 votes |
|
def reduce_any(input_tensor, reduction_indices=None, keep_dims=False,
name=None):
"""Computes the "logical or" of elements across dimensions of a tensor.
Reduces `input_tensor` along the dimensions given in `reduction_indices`.
Unless `keep_dims` is true, the rank of the tensor is reduced by 1 for each
entry in `reduction_indices`. If `keep_dims` is true, the reduced dimensions
are retained with length 1.
If `reduction_indices` has no entries, all dimensions are reduced, and a
tensor with a single element is returned.
For example:
```python
# 'x' is [[True, True]
# [False, False]]
tf.reduce_any(x) ==> True
tf.reduce_any(x, 0) ==> [True, True]
tf.reduce_any(x, 1) ==> [True, False]
```
Args:
input_tensor: The boolean tensor to reduce.
reduction_indices: The dimensions to reduce. If `None` (the default),
reduces all dimensions.
keep_dims: If true, retains reduced dimensions with length 1.
name: A name for the operation (optional).
Returns:
The reduced tensor.
"""
return gen_math_ops._any(input_tensor, _ReductionDims(input_tensor,
reduction_indices),
keep_dims, name=name)
Example #2
| Source File: math_ops.py From lambda-packs with MIT License | 4 votes |
|
def reduce_any(input_tensor,
axis=None,
keep_dims=False,
name=None,
reduction_indices=None):
"""Computes the "logical or" of elements across dimensions of a tensor.
Reduces `input_tensor` along the dimensions given in `axis`.
Unless `keep_dims` is true, the rank of the tensor is reduced by 1 for each
entry in `axis`. If `keep_dims` is true, the reduced dimensions
are retained with length 1.
If `axis` has no entries, all dimensions are reduced, and a
tensor with a single element is returned.
For example:
```python
# 'x' is [[True, True]
# [False, False]]
tf.reduce_any(x) ==> True
tf.reduce_any(x, 0) ==> [True, True]
tf.reduce_any(x, 1) ==> [True, False]
```
Args:
input_tensor: The boolean tensor to reduce.
axis: The dimensions to reduce. If `None` (the default),
reduces all dimensions.
keep_dims: If true, retains reduced dimensions with length 1.
name: A name for the operation (optional).
reduction_indices: The old (deprecated) name for axis.
Returns:
The reduced tensor.
@compatibility(numpy)
Equivalent to np.any
@end_compatibility
"""
return gen_math_ops._any(
input_tensor,
_ReductionDims(input_tensor, axis, reduction_indices),
keep_dims,
name=name)
Example #3
| Source File: math_ops.py From auto-alt-text-lambda-api with MIT License | 4 votes |
|
def reduce_any(input_tensor,
axis=None,
keep_dims=False,
name=None,
reduction_indices=None):
"""Computes the "logical or" of elements across dimensions of a tensor.
Reduces `input_tensor` along the dimensions given in `axis`.
Unless `keep_dims` is true, the rank of the tensor is reduced by 1 for each
entry in `axis`. If `keep_dims` is true, the reduced dimensions
are retained with length 1.
If `axis` has no entries, all dimensions are reduced, and a
tensor with a single element is returned.
For example:
```python
# 'x' is [[True, True]
# [False, False]]
tf.reduce_any(x) ==> True
tf.reduce_any(x, 0) ==> [True, True]
tf.reduce_any(x, 1) ==> [True, False]
```
Args:
input_tensor: The boolean tensor to reduce.
axis: The dimensions to reduce. If `None` (the default),
reduces all dimensions.
keep_dims: If true, retains reduced dimensions with length 1.
name: A name for the operation (optional).
reduction_indices: The old (deprecated) name for axis.
Returns:
The reduced tensor.
@compatibility(numpy)
Equivalent to np.any
@end_compatibility
"""
return gen_math_ops._any(
input_tensor,
_ReductionDims(input_tensor, axis, reduction_indices),
keep_dims,
name=name)
Example #4
| Source File: math_ops.py From Serverless-Deep-Learning-with-TensorFlow-and-AWS-Lambda with MIT License | 4 votes |
|
def reduce_any(input_tensor,
axis=None,
keep_dims=False,
name=None,
reduction_indices=None):
"""Computes the "logical or" of elements across dimensions of a tensor.
Reduces `input_tensor` along the dimensions given in `axis`.
Unless `keep_dims` is true, the rank of the tensor is reduced by 1 for each
entry in `axis`. If `keep_dims` is true, the reduced dimensions
are retained with length 1.
If `axis` has no entries, all dimensions are reduced, and a
tensor with a single element is returned.
For example:
```python
x = tf.constant([[True, True], [False, False]])
tf.reduce_any(x) # True
tf.reduce_any(x, 0) # [True, True]
tf.reduce_any(x, 1) # [True, False]
```
Args:
input_tensor: The boolean tensor to reduce.
axis: The dimensions to reduce. If `None` (the default),
reduces all dimensions. Must be in the range
`[-rank(input_tensor), rank(input_tensor))`.
keep_dims: If true, retains reduced dimensions with length 1.
name: A name for the operation (optional).
reduction_indices: The old (deprecated) name for axis.
Returns:
The reduced tensor.
@compatibility(numpy)
Equivalent to np.any
@end_compatibility
"""
return gen_math_ops._any(
input_tensor,
_ReductionDims(input_tensor, axis, reduction_indices),
keep_dims,
name=name)
Example #5
| Source File: math_ops.py From keras-lambda with MIT License | 4 votes |
|
def reduce_any(input_tensor,
axis=None,
keep_dims=False,
name=None,
reduction_indices=None):
"""Computes the "logical or" of elements across dimensions of a tensor.
Reduces `input_tensor` along the dimensions given in `axis`.
Unless `keep_dims` is true, the rank of the tensor is reduced by 1 for each
entry in `axis`. If `keep_dims` is true, the reduced dimensions
are retained with length 1.
If `axis` has no entries, all dimensions are reduced, and a
tensor with a single element is returned.
For example:
```python
# 'x' is [[True, True]
# [False, False]]
tf.reduce_any(x) ==> True
tf.reduce_any(x, 0) ==> [True, True]
tf.reduce_any(x, 1) ==> [True, False]
```
Args:
input_tensor: The boolean tensor to reduce.
axis: The dimensions to reduce. If `None` (the default),
reduces all dimensions.
keep_dims: If true, retains reduced dimensions with length 1.
name: A name for the operation (optional).
reduction_indices: The old (deprecated) name for axis.
Returns:
The reduced tensor.
@compatibility(numpy)
Equivalent to np.any
@end_compatibility
"""
return gen_math_ops._any(
input_tensor,
_ReductionDims(input_tensor, axis, reduction_indices),
keep_dims,
name=name)
