本文整理匯總了Python中tensorflow.python.ops.nn_ops.top_k方法的典型用法代碼示例。如果您正苦於以下問題：Python nn_ops.top_k方法的具體用法？Python nn_ops.top_k怎麽用？Python nn_ops.top_k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tensorflow.python.ops.nn_ops的用法示例。
在下文中一共展示了nn_ops.top_k方法的3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: _sort_tensor
# 需要導入模塊: from tensorflow.python.ops import nn_ops [as 別名]
# 或者: from tensorflow.python.ops.nn_ops import top_k [as 別名]
def _sort_tensor(tensor):
"""Use `top_k` to sort a `Tensor` along the last dimension."""
sorted_, _ = nn_ops.top_k(tensor, k=array_ops.shape(tensor)[-1])
return sorted_ 示例2: get_best
# 需要導入模塊: from tensorflow.python.ops import nn_ops [as 別名]
# 或者: from tensorflow.python.ops.nn_ops import top_k [as 別名]
def get_best(self, n):
"""Return the indices and values of the n highest scores in the TopN."""
def refresh_shortlist():
"""Update the shortlist with the highest scores in id_to_score."""
new_scores, new_ids = nn_ops.top_k(self.id_to_score, self.shortlist_size)
smallest_new_score = math_ops.reduce_min(new_scores)
new_length = math_ops.reduce_sum(
math_ops.to_int32(math_ops.greater(new_scores, dtypes.float32.min)))
u1 = self.sl_ids.assign(
math_ops.to_int64(array_ops.concat([[new_length], new_ids], 0)))
u2 = self.sl_scores.assign(
array_ops.concat([[smallest_new_score], new_scores], 0))
self.last_ops = [u1, u2]
return control_flow_ops.group(u1, u2)
# We only need to refresh the shortlist if n is greater than the
# current shortlist size (which is stored in sl_ids[0]).
with ops.control_dependencies(self.last_ops):
cond_op = control_flow_ops.cond(n > self.sl_ids[0], refresh_shortlist,
control_flow_ops.no_op)
with ops.control_dependencies([cond_op]):
topk_values, topk_indices = nn_ops.top_k(
self.sl_scores,
math_ops.minimum(n, math_ops.to_int32(self.sl_ids[0])))
# topk_indices are the indices into the shortlist, we want to return
# the indices into id_to_score
gathered_indices = array_ops.gather(self.sl_ids, topk_indices)
return gathered_indices, topk_values 示例3: _test_topk
# 需要導入模塊: from tensorflow.python.ops import nn_ops [as 別名]
# 或者: from tensorflow.python.ops.nn_ops import top_k [as 別名]
def _test_topk(in_shape, k=1):
""" One iteration of TOPK """
data = np.random.uniform(size=in_shape).astype('float32')
with tf.Graph().as_default():
in_data = array_ops.placeholder(shape=data.shape, dtype=data.dtype)
out = nn_ops.top_k(in_data, k, name='TopK')
compare_tflite_with_tvm(data, 'Placeholder:0', [in_data], [out[0]])