本文整理匯總了Python中cntk.one_hot方法的典型用法代碼示例。如果您正苦於以下問題：Python cntk.one_hot方法的具體用法？Python cntk.one_hot怎麽用？Python cntk.one_hot使用的例子？那麽, 這裏精選的方法代碼示例或許可以為您提供幫助。您也可以進一步了解該方法所在類cntk的用法示例。
在下文中一共展示了cntk.one_hot方法的6個代碼示例，這些例子默認根據受歡迎程度排序。您可以為喜歡或者感覺有用的代碼點讚，您的評價將有助於係統推薦出更棒的Python代碼示例。
示例1: gather
# 需要導入模塊: import cntk [as 別名]
# 或者: from cntk import one_hot [as 別名]
def gather(reference, indices):
# There is a bug in cntk gather op which may cause crash.
# We have made a fix but not catched in CNTK 2.1 release.
# Will update with gather op in next release
if _get_cntk_version() >= 2.2:
return C.ops.gather(reference, indices)
else:
num_classes = reference.shape[0]
one_hot_matrix = C.ops.one_hot(indices, num_classes)
return C.times(one_hot_matrix, reference, output_rank=len(reference.shape) - 1) 示例2: sparse_categorical_crossentropy
# 需要導入模塊: import cntk [as 別名]
# 或者: from cntk import one_hot [as 別名]
def sparse_categorical_crossentropy(target, output, from_logits=False, axis=-1):
# Here, unlike other backends, the tensors lack a batch dimension:
axis_without_batch = -1 if axis == -1 else axis - 1
output_dimensions = list(range(len(output.shape)))
if axis_without_batch != -1 and axis_without_batch not in output_dimensions:
raise ValueError(
'{}{}{}'.format(
'Unexpected channels axis {}. '.format(axis_without_batch),
'Expected to be -1 or one of the axes of `output`, ',
'which has {} dimensions.'.format(len(output.shape))))
target = C.one_hot(target, output.shape[axis_without_batch],
axis=axis_without_batch)
target = C.reshape(target, output.shape)
return categorical_crossentropy(target, output, from_logits, axis=axis) 示例3: one_hot
# 需要導入模塊: import cntk [as 別名]
# 或者: from cntk import one_hot [as 別名]
def one_hot(indices, num_classes):
return C.one_hot(indices, num_classes) 示例4: in_top_k
# 需要導入模塊: import cntk [as 別名]
# 或者: from cntk import one_hot [as 別名]
def in_top_k(predictions, targets, k):
_targets = C.one_hot(targets, predictions.shape[-1])
result = C.classification_error(predictions, _targets, topN=k)
return 1 - C.reshape(result, shape=()) 示例5: emit_Embedding
# 需要導入模塊: import cntk [as 別名]
# 或者: from cntk import one_hot [as 別名]
def emit_Embedding(self, IR_node):
codes = list()
codes.append("{}_P = cntk.one_hot({}, __weights_dict['{}']['weights'].shape[0])".format(
IR_node.variable_name,
self.parent_variable_name(IR_node),
IR_node.name))
codes.append("{:<15} = layers.Embedding(weights=__weights_dict['{}']['weights'])({}_P)".format(
IR_node.variable_name,
# IR_node.get_attr('output_dim'),
IR_node.name,
IR_node.variable_name))
return codes 示例6: sparse_categorical_crossentropy
# 需要導入模塊: import cntk [as 別名]
# 或者: from cntk import one_hot [as 別名]
def sparse_categorical_crossentropy(target, output, from_logits=False):
target = C.one_hot(target, output.shape[-1])
target = C.reshape(target, output.shape)
return categorical_crossentropy(target, output, from_logits)