{ "handwrite/__line6/choice": { "_type": "choice", "_value": [ "foo", "bar" ] }, "handwrite/conv_size/choice": { "_type": "choice", "_value": [ 2, 3, 5, 7 ] }, "handwrite/abc/choice": { "_type": "choice", "_value": [ "2", 3, "(5 * 6)", 7 ] }, "handwrite/__line9/function_choice": { "_type": "choice", "_value": [ "max_pool", "h_conv1", "avg_pool" ] }, "handwrite/max_pool/function_choice": { "_type": "choice", "_value": [ "max_pool(h_conv1)", "avg_pool(h_conv2, h_conv3)" ] }, "handwrite/max_poo/function_choice": { "_type": "choice", "_value": [ "max_poo(h_conv1)", "(2 * 3 + 4)", "(lambda x: 1 + x)" ] }, "handwrite/__line19/qlognormal": { "_type": "qlognormal", "_value": [ 1.2, 3, 4.5 ] }, "mnist/self.conv_size/choice": { "_type": "choice", "_value": [ 2, 3, 5, 7 ] }, "mnist/self.hidden_size/choice": { "_type": "choice", "_value": [ 124, 512, 1024 ] }, "mnist/self.learning_rate/randint": { "_type": "randint", "_value": [ 2, 3, 5 ] }, "mnist/tf.nn.relu/function_choice": { "_type": "choice", "_value": [ "tf.nn.relu(conv2d(x_image, W_conv1) + b_conv1)", "tf.nn.sigmoid(conv2d(x_image, W_conv1) + b_conv1)", "tf.nn.tanh(conv2d(x_image, W_conv1) + b_conv1)" ] }, "mnist/max_pool/function_choice": { "_type": "choice", "_value": [ "max_pool(h_conv1, self.pool_size)", "avg_pool(h_conv1, self.pool_size)" ] }, "mnist/batch_size/choice": { "_type": "choice", "_value": [ 50, 250, 500 ] }, "mnist/dropout_rate/choice": { "_type": "choice", "_value": [ 1, 5 ] }, "dir.simple/conv_size/choice": { "_type": "choice", "_value": [ 2, 3, 5, 7 ] }, "dir.simple/abc/choice": { "_type": "choice", "_value": [ "2", 3, "(5 * 6)", "{(1): 2, '3': 4}", "[1, 2, 3]" ] }, "dir.simple/max_pool/function_choice": { "_type": "choice", "_value": [ "max_pool(h_conv1)", "avg_pool(h_conv2, h_conv3)" ] }, "dir.simple/max_poo/function_choice": { "_type": "choice", "_value": [ "max_poo(h_conv1)", "(2 * 3 + 4)", "(lambda x: 1 + x)" ] } }