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Python Connector.tanh方法代码示例

本文整理汇总了Python中quagga.connector.Connector.tanh方法的典型用法代码示例。如果您正苦于以下问题:Python Connector.tanh方法的具体用法?Python Connector.tanh怎么用?Python Connector.tanh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quagga.connector.Connector的用法示例。


在下文中一共展示了Connector.tanh方法的1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: LstmBlock

# 需要导入模块: from quagga.connector import Connector [as 别名]
# 或者: from quagga.connector.Connector import tanh [as 别名]
class LstmBlock(object):
    """
    A long short-term memory (LSTM) block.

    Parameters
    ----------
    W
    R
    b
    grad_clipping
    x
    mask
    prev_c
    prev_h
    device_id : int
        Defines the device's id on which the computation will take place


    Returns
    -------
    """
    def __init__(self, W, R, b, grad_clipping, x, mask, prev_c, prev_h, device_id=None):
        self.f_context = Context(device_id)
        device_id = self.f_context.device_id
        if W.bpropagable:
            self.W, self.dL_dW = W.register_usage(device_id, device_id)
            self.W_b_context = Context(device_id)
        else:
            self.W = W.register_usage(device_id)
        if R.bpropagable:
            self.R, self.dL_dR = R.register_usage(device_id, device_id)
            self.R_b_context = Context(device_id)
        else:
            self.R = R.register_usage(device_id)
        if b.bpropagable:
            self.b, self.dL_db = b.register_usage(device_id, device_id)
            self.b_b_context = Context(device_id)
        else:
            self.b = b.register_usage(device_id)
        self.grad_clipping = grad_clipping
        if x.bpropagable:
            self.x, self.dL_dx = x.register_usage(device_id, device_id)
            self.x_b_context = Context(device_id)
        else:
            self.x = x.register_usage(device_id)
        if mask:
            self.mask = mask.register_usage(device_id)
        if prev_c.bpropagable:
            self.prev_c, self.dL_dprev_c = prev_c.register_usage(device_id, device_id)
            self.prev_c_b_context = Context(device_id)
        else:
            self.prev_c = prev_c.register_usage(device_id)
        if prev_h.bpropagable:
            self.prev_h, self.dL_dprev_h = prev_h.register_usage(device_id, device_id)
            self.prev_h_b_context = Context(device_id)
        else:
            self.prev_h = prev_h.register_usage(device_id)
        self.learning = W.bpropagable or R.bpropagable or x.bpropagable or \
                        prev_c.bpropagable or prev_h.bpropagable
        if self.learning:
            self.b_context = Context(device_id)

        dim = self.R.nrows
        batch_size = self.x.nrows

        self.zifo = Matrix.empty(batch_size, 4 * dim, device_id=device_id)
        self.z = self.zifo[:, 0*dim:1*dim]
        self.i = self.zifo[:, 1*dim:2*dim]
        self.f = self.zifo[:, 2*dim:3*dim]
        self.o = self.zifo[:, 3*dim:4*dim]
        self.c = Matrix.empty_like(self.prev_c, device_id)
        self.c = Connector(self.c, device_id if self.learning else None)
        self.tanh_c = Matrix.empty_like(self.c, device_id)
        self.h = Matrix.empty_like(self.c, device_id)
        self.h = Connector(self.h, device_id if self.learning else None)

        if self.learning:
            self._dzifo_dpre_zifo = Matrix.empty_like(self.zifo)
            self.dz_dpre_z = self._dzifo_dpre_zifo[:, 0*dim:1*dim]
            self.di_dpre_i = self._dzifo_dpre_zifo[:, 1*dim:2*dim]
            self.df_dpre_f = self._dzifo_dpre_zifo[:, 2*dim:3*dim]
            self.do_dpre_o = self._dzifo_dpre_zifo[:, 3*dim:4*dim]
            self.dL_dpre_zifo = self._dzifo_dpre_zifo
            self.dL_dpre_z = self.dz_dpre_z
            self.dL_dpre_i = self.di_dpre_i
            self.dL_dpre_f = self.df_dpre_f
            self.dL_dpre_o = self.do_dpre_o
            self._dtanh_c_dc = Matrix.empty_like(self.c)

    @property
    def dzifo_dpre_zifo(self):
        if self.learning:
            return self._dzifo_dpre_zifo

    @property
    def dtanh_c_dc(self):
        if self.learning:
            return self._dtanh_c_dc

    def fprop(self):
#.........这里部分代码省略.........
开发者ID:Sandy4321,项目名称:quagga,代码行数:103,代码来源:LstmBlock.py


注:本文中的quagga.connector.Connector.tanh方法示例由纯净天空整理自Github/MSDocs等开源代码及文档管理平台,相关代码片段筛选自各路编程大神贡献的开源项目,源码版权归原作者所有,传播和使用请参考对应项目的License;未经允许,请勿转载。