本文整理汇总了Python中tensorflow.python.ops.standard_ops.matmul方法的典型用法代码示例。如果您正苦于以下问题：Python standard_ops.matmul方法的具体用法？Python standard_ops.matmul怎么用？Python standard_ops.matmul使用的例子？那么恭喜您, 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.standard_ops的用法示例。
在下文中一共展示了standard_ops.matmul方法的3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: call
# 需要导入模块: from tensorflow.python.ops import standard_ops [as 别名]
# 或者: from tensorflow.python.ops.standard_ops import matmul [as 别名]
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
# 需要导入模块: from tensorflow.python.ops import standard_ops [as 别名]
# 或者: from tensorflow.python.ops.standard_ops import matmul [as 别名]
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
# 需要导入模块: from tensorflow.python.ops import standard_ops [as 别名]
# 或者: from tensorflow.python.ops.standard_ops import matmul [as 别名]
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 开发者ID:PacktPublishing，项目名称:Serverless-Deep-Learning-with-TensorFlow-and-AWS-Lambda，代码行数:20，代码来源:core.py