本文整理汇总了Python中tensorflow.python.ops.control_flow_ops.Assert方法的典型用法代码示例。如果您正苦于以下问题:Python control_flow_ops.Assert方法的具体用法?Python control_flow_ops.Assert怎么用?Python control_flow_ops.Assert使用的例子?那么, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类tensorflow.python.ops.control_flow_ops
的用法示例。
在下文中一共展示了control_flow_ops.Assert方法的15个代码示例,这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞,您的评价将有助于系统推荐出更棒的Python代码示例。
示例1: _assert
# 需要导入模块: from tensorflow.python.ops import control_flow_ops [as 别名]
# 或者: from tensorflow.python.ops.control_flow_ops import Assert [as 别名]
def _assert(cond, ex_type, msg):
"""A polymorphic assert, works with tensors and boolean expressions.
If `cond` is not a tensor, behave like an ordinary assert statement, except
that a empty list is returned. If `cond` is a tensor, return a list
containing a single TensorFlow assert op.
Args:
cond: Something evaluates to a boolean value. May be a tensor.
ex_type: The exception class to use.
msg: The error message.
Returns:
A list, containing at most one assert op.
"""
if _is_tensor(cond):
return [control_flow_ops.Assert(cond, [msg])]
else:
if not cond:
raise ex_type(msg)
else:
return []
示例2: _assert
# 需要导入模块: from tensorflow.python.ops import control_flow_ops [as 别名]
# 或者: from tensorflow.python.ops.control_flow_ops import Assert [as 别名]
def _assert(cond, ex_type, msg):
"""A polymorphic assert, works with tensors and boolean expressions.
If `cond` is not a tensor, behave like an ordinary assert statement, except
that a empty list is returned. If `cond` is a tensor, return a list
containing a single TensorFlow assert op.
Args:
cond: Something evaluates to a boolean value. May be a tensor.
ex_type: The exception class to use.
msg: The error message.
Returns:
A list, containing at most one assert op.
"""
if _is_tensor(cond):
return [control_flow_ops.Assert(cond, [msg])]
else:
if not cond:
raise ex_type(msg)
else:
return []
示例3: assert_integer_form
# 需要导入模块: from tensorflow.python.ops import control_flow_ops [as 别名]
# 或者: from tensorflow.python.ops.control_flow_ops import Assert [as 别名]
def assert_integer_form(
x, data=None, summarize=None, message=None, name="assert_integer_form"):
"""Assert that x has integer components (or floats equal to integers).
Args:
x: Floating-point `Tensor`
data: The tensors to print out if the condition is `False`. Defaults to
error message and first few entries of `x` and `y`.
summarize: Print this many entries of each tensor.
message: A string to prefix to the default message.
name: A name for this operation (optional).
Returns:
Op raising `InvalidArgumentError` if round(x) != x.
"""
message = message or "x has non-integer components"
x = ops.convert_to_tensor(x, name="x")
casted_x = math_ops.to_int64(x)
return check_ops.assert_equal(
x, math_ops.cast(math_ops.round(casted_x), x.dtype),
data=data, summarize=summarize, message=message, name=name)
示例4: _assert_shape_op
# 需要导入模块: from tensorflow.python.ops import control_flow_ops [as 别名]
# 或者: from tensorflow.python.ops.control_flow_ops import Assert [as 别名]
def _assert_shape_op(expected_shape, actual_tensor):
"""Asserts actual_tensor's shape is expected_shape.
Args:
expected_shape: List of integers defining the expected shape, or tensor of
same.
actual_tensor: Tensor to test.
Returns:
New assert tensor.
"""
with ops.name_scope('assert_shape', values=[actual_tensor]) as scope:
actual_shape = array_ops.shape(actual_tensor, name='actual')
is_shape = _is_shape(expected_shape, actual_tensor, actual_shape)
return control_flow_ops.Assert(
is_shape, [
'Wrong shape for %s [expected] [actual].' % actual_tensor.name,
expected_shape,
actual_shape
], name=scope)
示例5: assert_scalar_int
# 需要导入模块: from tensorflow.python.ops import control_flow_ops [as 别名]
# 或者: from tensorflow.python.ops.control_flow_ops import Assert [as 别名]
def assert_scalar_int(tensor, name=None):
"""Assert `tensor` is 0-D, of type `tf.int32` or `tf.int64`.
Args:
tensor: `Tensor` to test.
name: Name of the op and of the new `Tensor` if one is created.
Returns:
`tensor`, for chaining.
Raises:
ValueError: if `tensor` is not 0-D, of integer type.
"""
with ops.name_scope(name, 'assert_scalar_int', [tensor]) as name_scope:
tensor = ops.convert_to_tensor(tensor)
data_type = tensor.dtype
if not data_type.base_dtype.is_integer:
raise ValueError('Expected integer type for %s, received type: %s.'
% (tensor.name, data_type))
return check_ops.assert_scalar(tensor, name=name_scope)
示例6: _CheckAtLeast3DImage
# 需要导入模块: from tensorflow.python.ops import control_flow_ops [as 别名]
# 或者: from tensorflow.python.ops.control_flow_ops import Assert [as 别名]
def _CheckAtLeast3DImage(image):
"""Assert that we are working with properly shaped image.
Args:
image: >= 3-D Tensor of size [*, height, width, depth]
Raises:
ValueError: if image.shape is not a [>= 3] vector.
"""
if not image.get_shape().is_fully_defined():
raise ValueError('\'image\' must be fully defined.')
if image.get_shape().ndims < 3:
raise ValueError('\'image\' must be at least three-dimensional.')
if not all(x > 0 for x in image.get_shape()):
raise ValueError('all dims of \'image.shape\' must be > 0: %s' %
image.get_shape())
示例7: __init__
# 需要导入模块: from tensorflow.python.ops import control_flow_ops [as 别名]
# 或者: from tensorflow.python.ops.control_flow_ops import Assert [as 别名]
def __init__(self, label_name, weight_column_name):
def loss_fn(logits, target):
check_shape_op = control_flow_ops.Assert(
math_ops.less_equal(array_ops.rank(target), 2),
["target's shape should be either [batch_size, 1] or [batch_size]"])
with ops.control_dependencies([check_shape_op]):
target = array_ops.reshape(
target, shape=[array_ops.shape(target)[0], 1])
return loss_ops.hinge_loss(logits, target)
super(_BinarySvmTargetColumn, self).__init__(
loss_fn=loss_fn,
n_classes=2,
label_name=label_name,
weight_column_name=weight_column_name)
示例8: assert_integer_form
# 需要导入模块: from tensorflow.python.ops import control_flow_ops [as 别名]
# 或者: from tensorflow.python.ops.control_flow_ops import Assert [as 别名]
def assert_integer_form(
x, data=None, summarize=None, message=None, name="assert_integer_form"):
"""Assert that x has integer components (or floats equal to integers).
Args:
x: Numeric `Tensor`
data: The tensors to print out if the condition is `False`. Defaults to
error message and first few entries of `x` and `y`.
summarize: Print this many entries of each tensor.
message: A string to prefix to the default message.
name: A name for this operation (optional).
Returns:
Op raising `InvalidArgumentError` if round(x) != x.
"""
message = message or "x has non-integer components"
x = ops.convert_to_tensor(x, name="x")
casted_x = math_ops.to_int64(x)
return check_ops.assert_equal(
x, math_ops.cast(math_ops.round(casted_x), x.dtype),
data=data, summarize=summarize, message=message, name=name)
示例9: assert_scalar_int
# 需要导入模块: from tensorflow.python.ops import control_flow_ops [as 别名]
# 或者: from tensorflow.python.ops.control_flow_ops import Assert [as 别名]
def assert_scalar_int(tensor, name=None):
"""Assert `tensor` is 0-D, of type `tf.int32` or `tf.int64`.
Args:
tensor: `Tensor` to test.
name: Name of the op and of the new `Tensor` if one is created.
Returns:
`tensor`, for chaining.
Raises:
ValueError: if `tensor` is not 0-D, of type `tf.int32` or `tf.int64`.
"""
with ops.name_scope(name, 'assert_scalar_int', [tensor]) as name_scope:
tensor = ops.convert_to_tensor(tensor)
data_type = tensor.dtype
if data_type.base_dtype not in [dtypes.int32, dtypes.int64]:
raise ValueError('Unexpected type %s for %s.' % (data_type, tensor.name))
return assert_scalar(tensor, name=name_scope)
示例10: _assert
# 需要导入模块: from tensorflow.python.ops import control_flow_ops [as 别名]
# 或者: from tensorflow.python.ops.control_flow_ops import Assert [as 别名]
def _assert(cond, ex_type, msg):
"""A polymorphic assert, works with tensors and boolean expressions.
If `cond` is not a tensor, behave like an ordinary assert statement, except
that a empty list is returned. If `cond` is a tensor, return a list
containing a single TensorFlow assert op.
Args:
cond: Something evaluates to a boolean value. May be a tensor.
ex_type: The exception class to use.
msg: The error message.
Returns:
A list, containing at most one assert op.
"""
if is_tensor(cond):
return [logging_ops.Assert(cond, [msg])]
else:
if not cond:
raise ex_type(msg)
else:
return []
示例11: _Check3DImage
# 需要导入模块: from tensorflow.python.ops import control_flow_ops [as 别名]
# 或者: from tensorflow.python.ops.control_flow_ops import Assert [as 别名]
def _Check3DImage(image, require_static=True):
"""Assert that we are working with properly shaped image.
Args:
image: 3-D Tensor of shape [height, width, channels]
require_static: If `True`, requires that all dimensions of `image` are
known and non-zero.
Raises:
ValueError: if `image.shape` is not a 3-vector.
Returns:
An empty list, if `image` has fully defined dimensions. Otherwise, a list
containing an assert op is returned.
"""
try:
image_shape = image.get_shape().with_rank(3)
except ValueError:
raise ValueError("'image' must be three-dimensional.")
if require_static and not image_shape.is_fully_defined():
raise ValueError("'image' must be fully defined.")
if any(x == 0 for x in image_shape):
raise ValueError("all dims of 'image.shape' must be > 0: %s" %
image_shape)
if not image_shape.is_fully_defined():
return [check_ops.assert_positive(array_ops.shape(image),
["all dims of 'image.shape' "
"must be > 0."])]
else:
return []
示例12: _Check3DImage
# 需要导入模块: from tensorflow.python.ops import control_flow_ops [as 别名]
# 或者: from tensorflow.python.ops.control_flow_ops import Assert [as 别名]
def _Check3DImage(image, require_static=True):
"""Assert that we are working with properly shaped image.
Args:
image: 3-D Tensor of shape [height, width, channels]
require_static: If `True`, requires that all dimensions of `image` are
known and non-zero.
Raises:
ValueError: if `image.shape` is not a 3-vector.
Returns:
An empty list, if `image` has fully defined dimensions. Otherwise, a list
containing an assert op is returned.
"""
try:
image_shape = image.get_shape().with_rank(3)
except ValueError:
raise ValueError("'image' (shape %s) must be three-dimensional." %
image.shape)
if require_static and not image_shape.is_fully_defined():
raise ValueError("'image' (shape %s) must be fully defined." %
image_shape)
if any(x == 0 for x in image_shape):
raise ValueError("all dims of 'image.shape' must be > 0: %s" %
image_shape)
if not image_shape.is_fully_defined():
return [check_ops.assert_positive(array_ops.shape(image),
["all dims of 'image.shape' "
"must be > 0."])]
else:
return []
示例13: _CheckAtLeast3DImage
# 需要导入模块: from tensorflow.python.ops import control_flow_ops [as 别名]
# 或者: from tensorflow.python.ops.control_flow_ops import Assert [as 别名]
def _CheckAtLeast3DImage(image, require_static=True):
"""Assert that we are working with properly shaped image.
Args:
image: >= 3-D Tensor of size [*, height, width, depth]
require_static: If `True`, requires that all dimensions of `image` are
known and non-zero.
Raises:
ValueError: if image.shape is not a [>= 3] vector.
Returns:
An empty list, if `image` has fully defined dimensions. Otherwise, a list
containing an assert op is returned.
"""
try:
if image.get_shape().ndims is None:
image_shape = image.get_shape().with_rank(3)
else:
image_shape = image.get_shape().with_rank_at_least(3)
except ValueError:
raise ValueError("'image' must be at least three-dimensional.")
if require_static and not image_shape.is_fully_defined():
raise ValueError('\'image\' must be fully defined.')
if any(x == 0 for x in image_shape):
raise ValueError('all dims of \'image.shape\' must be > 0: %s' %
image_shape)
if not image_shape.is_fully_defined():
return [check_ops.assert_positive(array_ops.shape(image),
["all dims of 'image.shape' "
"must be > 0."])]
else:
return []
示例14: assert_negative
# 需要导入模块: from tensorflow.python.ops import control_flow_ops [as 别名]
# 或者: from tensorflow.python.ops.control_flow_ops import Assert [as 别名]
def assert_negative(x, data=None, summarize=None, message=None, name=None):
"""Assert the condition `x < 0` holds element-wise.
Example of adding a dependency to an operation:
```python
with tf.control_dependencies([tf.assert_negative(x)]):
output = tf.reduce_sum(x)
```
Negative means, for every element `x[i]` of `x`, we have `x[i] < 0`.
If `x` is empty this is trivially satisfied.
Args:
x: Numeric `Tensor`.
data: The tensors to print out if the condition is False. Defaults to
error message and first few entries of `x`.
summarize: Print this many entries of each tensor.
message: A string to prefix to the default message.
name: A name for this operation (optional). Defaults to "assert_negative".
Returns:
Op raising `InvalidArgumentError` unless `x` is all negative.
"""
message = message or ''
with ops.name_scope(name, 'assert_negative', [x, data]):
x = ops.convert_to_tensor(x, name='x')
if data is None:
data = [
message,
'Condition x < 0 did not hold element-wise:',
'x (%s) = ' % x.name, x]
zero = ops.convert_to_tensor(0, dtype=x.dtype)
return assert_less(x, zero, data=data, summarize=summarize)
示例15: assert_positive
# 需要导入模块: from tensorflow.python.ops import control_flow_ops [as 别名]
# 或者: from tensorflow.python.ops.control_flow_ops import Assert [as 别名]
def assert_positive(x, data=None, summarize=None, message=None, name=None):
"""Assert the condition `x > 0` holds element-wise.
Example of adding a dependency to an operation:
```python
with tf.control_dependencies([tf.assert_positive(x)]):
output = tf.reduce_sum(x)
```
Positive means, for every element `x[i]` of `x`, we have `x[i] > 0`.
If `x` is empty this is trivially satisfied.
Args:
x: Numeric `Tensor`.
data: The tensors to print out if the condition is False. Defaults to
error message and first few entries of `x`.
summarize: Print this many entries of each tensor.
message: A string to prefix to the default message.
name: A name for this operation (optional). Defaults to "assert_positive".
Returns:
Op raising `InvalidArgumentError` unless `x` is all positive.
"""
message = message or ''
with ops.name_scope(name, 'assert_positive', [x, data]):
x = ops.convert_to_tensor(x, name='x')
if data is None:
data = [
message, 'Condition x > 0 did not hold element-wise:',
'x (%s) = ' % x.name, x]
zero = ops.convert_to_tensor(0, dtype=x.dtype)
return assert_less(zero, x, data=data, summarize=summarize)