d79992cfd669974296a34d861060c921a8b12d9f,tensorlayer/layers/convolution/expert_conv.py,Conv2dLayer,__init__,#Conv2dLayer#Any#Any#Any#Any#Any#Any#Any#Any#Any#Any#Any#Any#,176

Before Change

            )
        )

        with tf.variable_scope(name):
            W = tf.get_variable(
                name="W_conv2d", shape=shape, initializer=W_init, dtype=LayersConfig.tf_dtype, **self.W_init_args
            )

            self.outputs = tf.nn.conv2d(
                self.inputs, W, strides=strides, padding=padding, use_cudnn_on_gpu=use_cudnn_on_gpu,
                data_format=data_format
            )

            if b_init:
                b = tf.get_variable(
                    name="b_conv2d", shape=(shape[-1]), initializer=b_init, dtype=LayersConfig.tf_dtype,
                    **self.b_init_args
                )

                self.outputs = tf.nn.bias_add(self.outputs, b, name="bias_add")

            self.outputs = self._apply_activation(self.outputs)

        self._add_layers(self.outputs)

        if b_init:
            self._add_params([W, b])
        else:
            self._add_params(W)


class Conv3dLayer(Layer):
    

After Change

    ):
        // super(Conv2dLayer, self
        //      ).__init__(prev_layer=prev_layer, act=act, W_init_args=W_init_args, b_init_args=b_init_args, name=name)
        super().__init__(name)
        self.act = act,
        self.shape = shape
        self.stride = stride
        self.dilation_rate = dilation_rate

Instances