本文整理匯總了Python中tensorflow.python.ops.standard_ops.matmul方法的典型用法代碼示例。如果您正苦於以下問題：Python standard_ops.matmul方法的具體用法？Python standard_ops.matmul怎麽用？Python standard_ops.matmul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.standard_ops的用法示例。
在下文中一共展示了standard_ops.matmul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: call
# 需要導入模塊: from tensorflow.python.ops import standard_ops [as 別名]
# 或者: from tensorflow.python.ops.standard_ops import matmul [as 別名]
def call(self, inputs):
inputs = ops.convert_to_tensor(inputs, dtype=self.dtype)
shape = inputs.get_shape().as_list()
output_shape = shape[:-1] + [self.units]
if len(output_shape) > 2:
# Broadcasting is required for the inputs.
outputs = standard_ops.tensordot(inputs, self.kernel, [[len(shape) - 1],
[0]])
# Reshape the output back to the original ndim of the input.
outputs.set_shape(output_shape)
else:
outputs = standard_ops.matmul(inputs, self.kernel)
if self.use_bias:
outputs = nn.bias_add(outputs, self.bias)
if self.activation is not None:
return self.activation(outputs) # pylint: disable=not-callable
return outputs 示例2: call
# 需要導入模塊: from tensorflow.python.ops import standard_ops [as 別名]
# 或者: from tensorflow.python.ops.standard_ops import matmul [as 別名]
def call(self, inputs):
shape = inputs.get_shape().as_list()
input_dim = shape[-1]
output_shape = shape[:-1] + [self.units]
if len(output_shape) > 2:
# Reshape the input to 2D.
output_shape_tensors = array_ops.unstack(array_ops.shape(inputs))
output_shape_tensors[-1] = self.units
output_shape_tensor = array_ops.stack(output_shape_tensors)
inputs = array_ops.reshape(inputs, [-1, input_dim])
outputs = standard_ops.matmul(inputs, self.kernel)
if self.use_bias:
outputs = nn.bias_add(outputs, self.bias)
if len(output_shape) > 2:
# Reshape the output back to the original ndim of the input.
outputs = array_ops.reshape(outputs, output_shape_tensor)
outputs.set_shape(output_shape)
if self.activation is not None:
return self.activation(outputs) # pylint: disable=not-callable
return outputs 示例3: call
# 需要導入模塊: from tensorflow.python.ops import standard_ops [as 別名]
# 或者: from tensorflow.python.ops.standard_ops import matmul [as 別名]
def call(self, inputs):
inputs = ops.convert_to_tensor(inputs, dtype=self.dtype)
shape = inputs.get_shape().as_list()
if len(shape) > 2:
# Broadcasting is required for the inputs.
outputs = standard_ops.tensordot(inputs, self.kernel, [[len(shape) - 1],
[0]])
# Reshape the output back to the original ndim of the input.
if context.in_graph_mode():
output_shape = shape[:-1] + [self.units]
outputs.set_shape(output_shape)
else:
outputs = standard_ops.matmul(inputs, self.kernel)
if self.use_bias:
outputs = nn.bias_add(outputs, self.bias)
if self.activation is not None:
return self.activation(outputs) # pylint: disable=not-callable
return outputs 開發者ID:PacktPublishing，項目名稱:Serverless-Deep-Learning-with-TensorFlow-and-AWS-Lambda，代碼行數:20，代碼來源:core.py