def __call__(self, x):
h1 = F.max_pooling_2d(F.relu(self.conv1(x)), ksize=2, stride=2)
h2 = F.max_pooling_2d(F.relu(self.conv2(h1)), ksize=2, stride=2)
h3 = F.max_pooling_2d(F.relu(self.conv3(h2)), ksize=2, stride=2)
h4 = F.tanh(self.l4(h3)) # -1〜+1に納める
return distribution.ContinuousDeterministicDistribution(
h4) #連続値（6次元のベクトル）を返す
def __call__(self, x):
# Model
if self.model_call is not None:
h = self.model_call(self.model, x)
else:
h = self.model(x)
# Action filter
if self.action_filter is not None:
h = self.action_filter(h)
# Wrap by Distribution
return distribution.ContinuousDeterministicDistribution(h)
def setUp(self):
self.x = np.random.rand(self.batch_size, self.ndim).astype(np.float32)
self.distrib = distribution.ContinuousDeterministicDistribution(self.x)